Impact of Respiratory Infections on Hospitalized Congestive Heart Failure Patients: A Retrospective Analysis of NIS Database (2019–2022)

Impact of Respiratory Infections on Hospitalized Congestive Heart Failure Patients: A Retrospective Analysis of NIS Database (2019–2022) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Impact of Respiratory Infections on Hospitalized Congestive Heart Failure Patients: A Retrospective Analysis of NIS Database (2019–2022) Yuyan Ma, Jiaqian Liu, Jerry Zhou, Haoling Wang, Manling Zhang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8575946/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background Congestive heart failure (CHF) is a leading cause of hospitalization and mortality in the elderly, with patients particularly vulnerable to adverse outcomes when exposed to infections. The evolving impact of COVID-19 on in-hospital outcomes among patients with CHF remains insufficiently understood. This study examines the temporal variations in mortality and in-hospital outcomes among CHF patients with and without COVID-19 using National Inpatient Sample (NIS) data from 2019 to 2022, with 2019 as a pre-pandemic reference year. Methods We conducted a retrospective observational study on NIS data 2019–2022. Patients aged 18–90 with CHF, identified using ICD-10-CM I50.x diagnosis codes, were included. The primary outcome was mortality, with secondary outcomes including vasopressor use, sudden cardiac arrest, acute kidney injury, pulmonary embolism, mechanical ventilation, and time to in-hospital death. The main covariate of interest is the presence or absence of a COVID-19 diagnosis. Multivariate logistic regression and Cox proportional hazards models were applied to estimate adjusted odds ratios (aORs) or hazard ratios (aHRs) controlling for demographic and comorbidities based on the Elixhauser Comorbidity Index. Results The in-hospital mortality rate of CHF patients with a COVID-19 diagnosis was significantly higher than those without COVID-19 in 2020 to 2022, although the difference narrowed in 2022. aORs (95% CI) were 6.12 (5.95–6.31), 5.71 (5.57–5.86), and 2.53 (2.46–2.60) in 2020, 2021, and 2022, respectively. By 2022, the impact of COVID-19 on mortality among CHF patients had declined to a level comparable to that of non-COVID pneumonia (aOR 2.50, 95% CI 2.45–2.56 in 2022). Among secondary outcomes, the time to in-hospital death followed a similar pattern to overall mortality, with significantly elevated risks early in the pandemic and showed a clear reduction by 2022. Other outcomes, such as mechanical ventilation and pulmonary embolism, showed an initial increase in risk followed by a decline over the same period. Conclusions Using NIS data 2019–2022, this analysis demonstrates that while COVID-19 was associated with substantially higher in-hospital mortality and adverse outcomes among CHF patients early in the pandemic, its impact progressively declined by 2022, converging to levels comparable with non-COVID respiratory infections. Congestive heart failure HFpEF HFrEF In-hospital outcomes National Inpatient Sample Respiratory infection Survival analysis 1. Background Congestive heart failure (CHF) is a chronic, progressive condition characterized by impaired cardiac function and remains a leading cause of hospitalization and in-hospital mortality, particularly in older adults. Patients with CHF often have multiple coexisting conditions and are especially vulnerable to acute clinical deterioration when exposed to physiological stressors such as infection. CHF encompasses a heterogeneous group of patients, commonly categorized into heart failure with reduced ejection fraction (HFrEF) and heart failure with preserved ejection fraction (HFpEF), which differ in pathophysiology, clinical characteristics, and treatment response [ 1 ]. Since its emergence in late 2019, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19) [ 2 ], has had a profound impact on global health systems. COVID-19 commonly presents with clinical manifestations such as fever and respiratory distress, and is frequently associated with pulmonary conditions, including pneumonia and other respiratory tract infections. Beyond the respiratory system, it has been linked to systemic complications and the exacerbation of chronic comorbidities. Heart disease and hypertension, as well as diabetes and chronic kidney disease, are known to increase the risk of severe outcomes in patients with COVID-19 [ 3 , 4 ]. CHF, in particular, has drawn attention as a key comorbidity during the pandemic. As a high-risk cardiovascular condition, CHF not only increases the risk of severe outcomes after SARS-CoV-2 infection but may also be directly affected by the infection through inflammatory and cardiovascular pathways [ 11 ]. Moreover, as the virus has evolved into variants with differing transmissibility and severity, the impact of COVID-19 on patients with CHF has likely shifted over time [ 5 ]. However, most prior studies have focused on early pandemic data [ 4 , 6 – 8 ], leaving these temporal changes largely unexplored. We analyzed National Inpatient Sample (NIS) data from 2019 to 2022 to evaluate in-hospital outcomes among CHF patients with and without COVID-19. This retrospective analysis included over 3.4 million CHF hospitalizations in the United States over these four years, representing the largest cohort to date for such comparisons. By capturing data across the early, peak, and post-pandemic phases, we aimed to assess temporal variations in the clinical impact of COVID-19, specifically regarding in-hospital mortality, time (from hospitalization) to in-hospital death, and other adverse outcomes. We also explored differences between CHF subtype HFrEF and HFpEF, to better characterize COVID-19’s evolving influence on this high-risk population. 2. Methods 2.1 Data Source We conducted a retrospective observational study using the Agency for Healthcare Research and Quality NIS dataset, which contains discharge-level data from a 20% stratified sample of U.S. community hospital discharges [ 9 ]. Our study analyzed data from January 1, 2019, to December 31, 2022. Patients aged 18 to 90 years admitted with a CHF diagnosis (primary or secondary) were included. The included patients were further stratified based on the presence or absence of a concurrent COVID-19 diagnosis. Data from 2019 served as a pre-pandemic reference cohort. The number of CHF patients included per year was as follows: 873,278 in 2019, 812,412 in 2020 (with 653,209 from March to December, after COVID-19 was identified and spread in the U.S.), 860,110 in 2021, and 910,364 in 2022. The NIS dataset applies the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) for diagnoses and ICD-10 procedure codes for interventions. Data extraction was based on these codes, with a detailed summary provided in Supporting Information S1. 2.2 Study Outcomes and Covariates The primary outcome of this study was in-hospital mortality. Secondary outcomes included vasopressor use, mechanical ventilation, mechanical circulatory support, sudden cardiac arrest, acute kidney injury, pulmonary embolism, and cardiogenic shock. We also analyzed the survival outcome, which is defined as the time to in-hospital death. Potential confounders adjusted for included: (1) demographic factors such as age, sex, race, insurance status, injury condition, and elective admission, (2) hospital characteristics such as division, bed size, teaching status, and ownership of hospital, (3) patient comorbidities assessed using the Elixhauser Comorbidity Index (ECI). 2.3 Statistical Methods In the descriptive analysis, continuous variables were compared using Student’s t-test, and categorical variables were compared using the chi-square test between the COVID-19 and non-COVID-19 groups. Univariable logistic regression was used to estimate unadjusted odds ratios (ORs) for the primary (death) and secondary outcomes (e.g., sudden cardiac arrest, acute kidney injury, pulmonary embolism, cardiogenic shock, vasopressor use, mechanical ventilation, and mechanical circulatory Support). Variables with a p-value ≤ 0.001 in the univariable analysis were included in the multivariable logistic regression to adjust for potential confounders. Adjusted odds ratios (aORs) with 95% confidence intervals (CIs) were reported. The Cox proportional hazards model was used to evaluate the association between COVID-19 diagnosis and time to in-hospital death (from hospitalization) among patients with CHF. Time to in-hospital death, or length of stay, was defined as the number of days from hospital admission to either death or discharge, with patients discharged alive treated as right-censored observations. Univariable Cox regression was first performed to estimate unadjusted hazard ratios (HRs) with 95% confidence intervals (CIs). Variables with a p-value ≤ 0.001 in the univariable Cox regression were subsequently included in the multivariable Cox model to adjust for potential confounders. Adjusted hazard ratios (aHRs) with 95% CIs were reported. All statistical analyses were performed using R software (version 4.4.1; R Foundation for Statistical Computing, Vienna, Austria). 3. Results 3.1. Demographics, Baseline Comorbidities and Hospital Characteristics This study analyzed four years of data on patients with CHF from the NIS database. In 2019, 873,278 patients were included. In 2020 (March to December, post COVID-19 identification and spread in the U.S.), 653,209 patients were included, of whom 39,276 (6.0%) had a concurrent diagnosis of COVID-19. In 2021, 860,110 patients were included, with 53,613 (6.2%) diagnosed with COVID-19. In 2022, 910,364 patients were included, and 69,635 (7.6%) had a COVID-19 diagnosis. Table 1 presents patient demographics for the two groups. In both 2020 and 2022, CHF patients with COVID-19 were significantly older. In 2020, 74.9% of patients in the COVID-19 group were over 65, compared to 70.4% in the non-COVID group (p < 0.001). In 2022, 75.9% of patients in the COVID-19 group were over 65, compared to 71.6% in the non-COVID group (p < 0.001). However, in 2021, there was no statistically significant difference in age distribution between the two groups (p = 0.078). Between 2020 and 2022, the age distribution of CHF patients without COVID-19 was generally comparable to that of the 2019 cohort. In addition to age, several other variables differed between the COVID-19 and non-COVID-19 groups. Compared with patients without COVID-19, those with CHF and COVID-19 were more likely to be male (2020: 54.1% vs. 53.0%; 2021: 54.7% vs. 52.7%; p < 0.001), had fewer elective admissions (2020: 2.8% vs. 8.4%; 2021: 2.5% vs. 8.4%; 2022: 2.6% vs. 8.4%; p < 0.001), and experienced a longer mean of length of hospital stay, regardless of whether they were discharged alive or died in the hospital (2020: 10.0 vs. 6.6 days; 2021: 10.6 vs. 6.7 days; 2022: 9.6 vs. 6.9 days; p < 0.001). For the non-COVID-19 group, these characteristics are similar to those observed in the 2019 cohort. Several hospital characteristics also differed between the COVID-19 and non-COVID-19 groups. Compared with those without COVID-19, patients with CHF and COVID-19 were less often admitted to large hospitals (2020: 49.1% vs. 50.7%; 2021: 48.0% vs. 50.3%; 2022: 47.4% vs. 48.9%; p < 0.001). They were also more likely to be treated in rural hospitals (2021: 10.0% vs. 8.2%; 2022: 9.0% vs. 8.5%; p < 0.001). Modest but significant regional variations were observed across hospital divisions, with differences most notable in the New England and Pacific regions. Overall, hospital characteristics in the non-COVID-19 group are consistent with patterns observed in 2019. Table 1 Patient and Hospital Characteristics Characteristics 2019 2020 CHF Without COVID-19 2020 CHF With COVID-19 P-Value 2021 CHF Without COVID-19 2021 CHF With COVID-19 P-Value 2022 CHF Without COVID-19 2022 CHF With COVID-19 P-Value N = 873,278 N = 653,209 N = 860,110 N = 910, 364 n 0 = 613,933 (94.0%) n 1 = 39,276 (6.0%) n 0 = 806,497 (93.8%) n 1 = 53,613 (6.2%) n 0 = 840,729 (92.4%) n 1 = 69,635 (7.6%) Age Mean (SD) 71.7 (13.5) 71.0 (13.5) 72.5 (13.1) < 0.001 71.2 (13.6) 71.0 (13.5) 0.003 71.3 (13.5) 73.0 (13.2) < 0.001 Median [Min, Max] 73.0 [18.0, 90.0] 72.0 [18.0, 90.0] 74.0 [18.0, 90.0] 73.0 [18.0, 90.0] 73.0 [18.0, 90.0] 73.0 [18.0, 90.0] 75.0 [18.0, 90.0] < 65 245,462 (28.1%) 181,893 (29.6%) 9,853 (25.1%) = 65 627,816 (71.9%) 432,040 (70.4%) 29,423 (74.9%) 572,847 (71.0%) 37,889 (70.7%) 602,369 (71.6%) 52,842 (75.9%) Race White 609,065 (69.7%) 428,391 (69.8%) 23,568 (60.0%) < 0.001 560,154 (69.5%) 35,502 (66.2%) < 0.001 580,872 (69.1%) 47,607 (68.4%) < 0.001 Black 157,117 (18.0%) 111,023 (18.1%) 8,652 (22.0%) 144,625 (17.9%) 10,328 (19.3%) 150,100 (17.9%) 12,227 (17.6%) Hispanic 64,284 (7.4%) 44,857 (7.3%) 4,776 (12.2%) 62,728 (7.8%) 5,111 (9.5%) 67,722 (8.1%) 5,955 (8.6%) Asian or Pacific Islander 18,653 (2.1%) 12,622 (2.1%) 856 (2.2%) 17,515 (2.2%) 1,127 (2.1%) 18,929 (2.3%) 1,781 (2.6%) Native American 4,837 (0.6%) 3,395 (0.6%) 316 (0.8%) 4,485 (0.6%) 350 (0.7%) 4,710 (0.6%) 400 (0.6%) Other 19,322 (2.2%) 13,645 (2.2%) 1,108 (2.8%) 16,990 (2.1%) 1,195 (2.2%) 18,396 (2.2%) 1,665 (2.4%) Sex Male 451,777 (51.7%) 325,608 (53.0%) 2,1267 (54.1%) < 0.001 425,169 (52.7%) 29,350 (54.7%) < 0.001 442,426 (52.6%) 36,968 (53.1%) 0.021 Female 421,501 (48.3%) 288,325 (47.0%) 1,8009 (45.9%) 381,328 (47.3%) 24,263 (45.3%) 398,303 (47.4%) 32,667 (46.9%) Elective Non-elective admission (0) 801,871 (91.8%) 562,090 (91.6%) 38,166 (97.2%) < 0.001 738,449 (91.6%) 52,265 (97.5%) < 0.001 769,967 (91.6%) 67,815 (97.4%) < 0.001 Elective admission (1) 71,407 (8.2%) 51,843 (8.4%) 1,110 (2.8%) 68,048 (8.4%) 1,348 (2.5%) 70,762 (8.4%) 1,820 (2.6%) Median Household Income [1] 0-25th percentile 280,405 (32.1%) 197,699 (32.2%) 13,700 (34.9%) < 0.001 256,361 (31.8%) 18,305 (34.1%) < 0.001 263,088 (31.3%) 21,488 (30.9%) 0.012 26–50th percentile 225,187 (25.8%) 170,742 (27.8%) 10,895 (27.7%) 208,331 (25.8%) 14,694 (27.4%) 221,316 (26.3%) 18,204 (26.1%) 51–75th percentile 208,769 (23.9%) 138,061 (22.5%) 8,616 (21.9%) 189,908 (23.5%) 12,533 (23.4%) 200,295 (23.8%) 16,897 (24.3%) 76–100th percentile 158,917 (18.2%) 107,431 (17.5%) 6,065 (15.4%) 151,897 (18.8%) 8,081 (15.1%) 156,030 (18.6%) 13,046 (18.7%) Insurance Medicare 655,760 (75.1%) 448,437 (73.0%) 29,366 (74.8%) < 0.001 586,889 (72.8%) 38,519 (71.8%) < 0.001 610,004 (72.6%) 52,769 (75.8%) < 0.001 Medicaid 81,344 (9.3%) 61,739 (10.1%) 3,429 (8.7%) 83,200 (10.3%) 5,378 (10.0%) 87,296 (10.4%) 6,546 (9.4%) Private insurance 99,220 (11.4%) 74,654 (12.2%) 4,801 (12.2%) 97,125 (12.0%) 7,137 (13.3%) 102,536 (12.2%) 7,444 (10.7%) Self-pay 19,441 (2.2%) 14,138 (2.3%) 589 (1.5%) 18,375 (2.3%) 911 (1.7%) 18,100 (2.2%) 1,037 (1.5%) No charge 1,317 (0.2%) 998 (0.2%) 50 (0.1%) 1,204 (0.1%) 76 (0.1%) 1,091 (0.1%) 82 (0.1%) Other 16,196 (1.9%) 13,967 (2.3%) 1,041 (2.7%) 19,704 (2.4%) 1,592 (3.0%) 21,702 (2.6%) 1,757 (2.5%) Injury Diagnosis Reported No injury 808,624 (92.6%) 564,633 (92.0%) 37,376 (95.2%) < 0.001 743,385 (92.2%) 50886 (94.9%) < 0.001 774,469 (92.1%) 64,641 (92.8%) < 0.001 Injury in first listed diagnosis 26,392 (3.0%) 21,109 (3.4%) 415 (1.1%) 27,106 (3.4%) 627 (1.2%) 28,077 (3.3%) 1,457 (2.1%) Injury not in first listed diagnosis 38,262 (4.4%) 28191 (4.6%) 1485 (3.8%) 36,006 (4.5%) 2100 (3.9%) 38,183 (4.5%) 3,537 (5.1%) Length of Stay Mean (SD) 6.4 (7.3) 6.5 (7.6) 10.0 (10.2) < 0.001 6.6 (7.9) 10.5 (12.1) < 0.001 6.8 (8.3) 9.5 (12.6) < 0.001 Median [Min, Max] 4.0 [0, 364] 4.0 [0, 350] 7.0 [0, 277] 5.0 [0, 364] 7.0 [0, 340] 5.0 [0, 364] 6.0 [0, 356] Hospital Division New England 45,377 (5.2%) 31,366 (5.1%) 1,854 (4.7%) < 0.001 42,397 (5.3%) 2,185 (4.1%) < 0.001 42,310 (5.0%) 3,791 (5.4%) < 0.001 Middle Atlantic 122,226 (14.0%) 81,606 (13.3%) 5,617 (14.3%) 110,695 (13.7%) 7,656 (14.3%) 112,294 (13.4%) 10,745 (15.4%) East North Central 158,463 (18.1%) 109,578 (17.8%) 7,959 (20.3%) 143,636 (17.8%) 9,359 (17.5%) 148,775 (17.7%) 11,962 (17.2%) West North Central 55,904 (6.4%) 39,453 (6.4%) 2,731 (7.0%) 51,459 (6.4%) 2,950 (5.5%) 53,032 (6.3%) 3,874 (5.6%) South Atlantic 184,029 (21.1%) 134,506 (21.9%) 7,678 (19.5%) 176,461 (21.9%) 12,704 (23.7%) 185,008 (22.0%) 15,260 (21.9%) East South Central 63,040 (7.2%) 45,206 (7.4%) 2,773 (7.1%) 58,270 (7.2%) 3,877 (7.2%) 60,741 (7.2%) 4,568 (6.6%) West South Central 96,589 (11.1%) 68,066 (11.1%) 4,888 (12.4%) 88,360 (11.0%) 6,408 (12.0%) 96,260 (11.4%) 7,188 (10.3%) Mountain 39,409 (4.5%) 28,501 (4.6%) 1,975 (5.0%) 35,523 (4.4%) 2,624 (4.9%) 38,485 (4.6%) 3,123 (4.5%) Pacific 108,241 (12.4%) 75,651 (12.3%) 3,801 (9.7%) 99,696 (12.4%) 5,850 (10.9%) 103,824 (12.3%) 9,124 (13.1%) Control/ownership of hospital Government, nonfederal 86,562 (9.9%) 62220 (10.1%) 4,082 (10.4%) 0.054 79,307 (9.8%) 5,326 (9.9%) 0.612 81,703 (9.7%) 6,642 (9.5%) < 0.001 Private, not-profit 678,915 (77.7%) 473,688 (77.2%) 30,336 (77.2%) 631,091 (78.3%) 41,955 (78.3%) 656,822 (78.1%) 55,557 (79.8%) Private, invest-own 107,801 (12.3%) 78,025 (12.7%) 4,858 (12.4%) 96,099 (11.9%) 6,332 (11.8%) 102,204 (12.2%) 7,436 (10.7%) Hospital Bed Size Small 184,076 (21.1%) 131,442 (21.4%) 8926 (22.7%) < 0.001 176,415 (21.9%) 12,314 (23.0%) < 0.001 187,775 (22.3%) 15,923 (22.9%) < 0.001 Medium 253,889 (29.1%) 171,433 (27.9%) 11,065 (28.2%) 224,681 (27.9%) 15,556 (29.0%) 241,887 (28.8%) 20,677 (29.7%) Large 435,313 (49.8%) 311,058 (50.7%) 19,285 (49.1%) 405,401 (50.3%) 25,743 (48.0%) 411,067 (48.9%) 33,035 (47.4%) Hospital Teaching Status Status Rural 74,810 (8.6%) 52,671 (8.6%) 3,491 (8.9%) 0.065 66,364 (8.2%) 5,351 (10.0%) < 0.001 71,675 (8.5%) 6,267 (9.0%) < 0.001 Urban nonteaching 154,544 (17.7%) 105,922 (17.3%) 6,678 (17.0%) 137,301 (17.0%) 9,820 (18.3%) 134,742 (16.0%) 11,482 (16.5%) Urban teaching 643,924 (73.7%) 455,340 (74.2%) 29,107 (74.1%) 602,832 (74.7%) 38,442 (71.7%) 634,312 (75.4%) 51,886 (74.5%) [ 1 ]: Median household income quartiles are defined separately for each year based on year-specific ZIP code–level income distributions. Beyond patient characteristics, several comorbidity conditions were included as covariates in the model. variables with < 3% occurrence were excluded. As presented in Table 2 , most comorbidities showed significant differences in distribution between the COVID-19 and non-COVID groups. Patients without COVID-19 had a higher prevalence (p < 0.001) of cardiovascular comorbidities, including coronary artery disease, atrial fibrillation, history of coronary artery bypass grafting (CABG), and previous myocardial infarction (MI). They also exhibited a greater incidence (p < 0.001) of adverse health behaviors such as alcohol abuse, drug abuse, and smoking. In contrast, patients with COVID-19 were more likely (p < 0.001) to have comorbid conditions such as diabetes with complications, hypertension with complications, and dementia. Table 2 Patient Comorbidity Conditions Characteristics 2019 2020 CHF Without COVID-19 2020 CHF With COVID-19 P-Value 2021 CHF Without COVID-19 2021 CHF With COVID-19 P-Value 2022 CHF Without COVID-19 2022 CHF With COVID-19 P-Value N = 873, 278 N = 653,209 N = 860,110 N = 910,364 n 0 = 613,933 (94.0%) n 1 = 39,276 (6.0%) n 0 = 806,497 (93.8%) n 1 = 53,613 (6.2%) n 0 = 840,729 (92.4%) n 1 = 69,635 (7.6%) Hypertension Followed Up with Complications 575,427 (65.9%) 410,498 (66.9%) 33,671 (85.7%) < 0.001 533,766 (66.2%) 44,761 (83.5%) < 0.001 564,236 (67.1%) 56,125 (80.6%) < 0.001 Atrial Fibrillation 404,051 (46.3%) 282,620 (46.0%) 16,965 (43.2%) < 0.001 375,336 (46.5%) 22,883 (42.7%) < 0.001 391,709 (46.6%) 31,836 (45.7%) < 0.001 Pulmonary Circulation Disorder 155,234 (17.8%) 109,525 (17.8%) 5,223 (13.3%) < 0.001 147,087 (18.2%) 8,026 (15.0%) < 0.001 152,823 (18.2%) 11,243 (16.1%) < 0.001 History of CABG 105,531 (12.1%) 65,657 (10.7%) 3,830 (9.8%) < 0.001 81,281 (10.1%) 4,725 (8.8%) < 0.001 76,039 (9.0%) 5,892 (8.5%) < 0.001 Previous MI 132,021 (15.1%) 89,985 (14.7%) 4,604 (11.7%) < 0.001 113,956 (14.1%) 6,437 (12.0%) < 0.001 110,739 (13.2%) 8,253 (11.9%) < 0.001 Peripheral Vascular Disease 102,975 (11.8%) 71,508 (11.6%) 3,156 (8.0%) < 0.001 94,954 (11.8%) 4,397 (8.2%) < 0.001 99,071 (11.8%) 7,242 (10.4%) < 0.001 Pneumonia, Except COVID-19 Related 143,237 (16.4%) 94,424 (15.4%) 1,206 (3.1%) < 0.001 112,211 (13.9%) 1,203 (2.2%) < 0.001 130,427 (15.5%) 3,244 (4.7%) < 0.001 Coronary Artery Disease 457,269 (52.4%) 317,805 (51.8%) 18,010 (45.9%) < 0.001 412,152 (51.1%) 23,864 (44.5%) < 0.001 422,480 (50.3%) 32,533 (46.7%) < 0.001 Chronic Lung Diseases 331,830 (38.0%) 224,298 (36.5%) 14,173 (36.1%) 0.074 286,691 (35.5%) 19,454 (36.3%) < 0.001 298,789 (35.5%) 26,204 (37.6%) < 0.001 Asthma 251,226 (28.8%) 167,945 (27.4%) 10,201 (26.0%) < 0.001 213,717 (26.5%) 13,370 (24.9%) < 0.001 214,507 (25.5%) 16,914 (24.3%) < 0.001 Obstructive Sleep Apnea 141,680 (16.2%) 96,572 (15.7%) 5,811 (14.8%) < 0.001 129,297 (16.0%) 8,141 (15.2%) < 0.001 132,661 (15.8%) 9,582 (13.8%) < 0.001 Chronic Kidney Disease 414,946 (47.5%) 292,036 (47.6%) 19,102 (48.6%) < 0.001 376,632 (46.7%) 24,222 (45.2%) < 0.001 389,314 (46.3%) 33,309 (47.8%) < 0.001 Diabetes Followed Up with Complications 327,723 (37.5%) 238,203 (38.8%) 17,331 (44.1%) < 0.001 310,647 (38.5%) 22,483 (41.9%) < 0.001 321,798 (38.3%) 27,874 (40.0%) < 0.001 Diabetes With No Complications 87,179 (10.0%) 58,201 (9.5%) 3,815 (9.7%) 0.128 75,390 (9.3%) 5,058 (9.4%) 0.511 79,326 (9.4%) 5,911 (8.5%) < 0.001 Obesity 222,256 (25.5%) 168,146 (27.4%) 11,386 (29.0%) < 0.001 225,215 (27.9%) 16,657 (31.1%) < 0.001 234,733 (27.9%) 17,960 (25.8%) < 0.001 Hypothyroidism 164,103 (18.8%) 114,631 (18.7%) 7,008 (17.8%) < 0.001 149,640 (18.6%) 9,044 (16.9%) < 0.001 157,979 (18.8%) 13,014 (18.7%) 0.512 Autoimmune Conditions 26,618 (4.3%) 1,546 (3.9%) < 0.001 35,098 (4.4%) 2,367 (4.4%) 0.495 36,503 (4.3%) 3,303 (4.7%) < 0.001 Dementia 84,467 (9.7%) 57,723 (9.4%) 6,300 (16.0%) < 0.001 72,729 (9.0%) 5,697 (10.6%) < 0.001 74,059 (8.8%) 8,520 (12.2%) < 0.001 Depression 118,315 (13.5%) 85,137 (13.9%) 5,106 (13.0%) < 0.001 111,471 (13.8%) 6,415 (12.0%) < 0.001 112,360 (13.4%) 8,659 (12.4%) < 0.001 Smoking 361,918 (41.4%) 251,072 (40.9%) 12,413 (31.6%) < 0.001 322,802 (40.0%) 17,750 (33.1%) < 0.001 327,857 (39.0%) 24,266 (34.8%) < 0.001 Alcohol Abuse 32,193 (3.7%) 26,161 (4.3%) 830 (2.1%) < 0.001 34,139 (4.2%) 1,318 (2.5%) < 0.001 34,769 (4.1%) 2,047 (2.9%) < 0.001 Drug Abuse 32,006 (3.7%) 25,602 (4.2%) 905 (2.3%) < 0.001 34,683 (4.3%) 1,684 (3.1%) < 0.001 36,436 (4.3%) 2,374 (3.4%) < 0.001 3.2. In-Hospital Mortality and Complications CHF patients with a concurrent diagnosis of COVID-19 had significantly higher in-hospital mortality compared to those without COVID-19 (Table 3 ). In January and February 2020, prior to the pandemic, the overall in-hospital mortality rate among CHF patients was 4.6% (7,513 of 159,203), similar to the 2019 rate of 4.4%. However, from March 2020 onward, the mortality rate among CHF patients with COVID-19 increased sharply: reaching 22.0% in 2020, 20.6% in 2021, and then decreasing to 11.1% in 2022. In contrast, the mortality rate among CHF patients without COVID-19 remained relatively stable at approximately 5.0% across all three years. These trends indicate that while COVID-19 substantially increased mortality risk in CHF patients early in the pandemic, its impact declined by 2022. Table 3 In-Hospital Mortality for CHF Patients by COVID-19 Diagnosis Mortality 2019 2020 (Mar to Dec) 2021 2022 p-value Without COVID-19 With COVID-19 p-value Without COVID-19 With COVID-19 p-value Without COVID-19 With COVID-19 N (sample size) 873,278 613,933 (94.0%) 39,276 (6.0%) 806,497 (93.8%) 53,613 (6.2%) 840,729 (92.4%) 69,635 (7.6%) Did not die 834,931 (95.6%) 583,924 (95.1%) 30,623 (78.0%) < 0.001 766,421 (95.0%) 42,560 (79.4%) < 0.001 798,558 (95.0%) 61,900 (88.9%) < 0.001 Died 38,347 (4.4%) 30,009 (4.9%) 8,653 (22.0%) 40,076 (5.0%) 11,053 (20.6%) 42,171 (5.0%) 7,735 (11.1%) As shown in Table 4 , after adjustment for potential confounders, CHF patients with a concurrent COVID-19 diagnosis exhibited higher rates of adverse in-hospital outcomes, including mortality, compared with those without COVID-19. Unlike the pattern observed for in-hospital mortality (aOR: 6.124 in 2020; 5.712 in 2021; 2.529 in 2022; p < 0.001), other adverse outcomes exhibited a modest increase in 2021, followed by a decline in 2022. Specifically, the aORs for pulmonary embolism were 2.216 in 2020, 2.743 in 2021, and 1.897 in 2022; for acute kidney injury, 1.397, 1.450, and 1.236; and for mechanical ventilation, 2.571, 2.725, and 1.735, respectively. Cardiogenic shock showed varying effects across years, but the aORs consistently remained close to 1. Additionally, across 2020–2022, COVID-19 infection was associated with higher total hospital charges, with adjusted increases of USD 34,671 (2020), 44,831 (2021), and 24,827 (2022) compared to patients without COVID-19. The mean total hospital charges for CHF patients with COVID-19 were consistently higher than those for patients without COVID-19 across all three years. Specifically, the mean total charges for COVID-19 versus non–COVID-19 patients were USD 114,929 vs 88,643 in 2020, USD 128,288 vs 92,141 in 2021, and USD 114,019 vs 97,854 in 2022. Table 4 Comparison of COVID-19 vs non-COVID-19 Groups in Mortality and Complications among CHF Patients. Outcomes Sample Size [2] R 2 Adjusted OR or Regression Coefficient [1] P-Value 2020 (Mar to Dec) N = 622,426 Mortality 36,596 (5.9%) 0.091 6.124 (5.946, 6.307) < 0.001 Sudden Cardiac Arrest 17,167 (2.8%) 0.039 1.836 (1.739, 1.938) < 0.001 Acute Kidney Injury 231,230 (37.1%) 0.070 1.397 (1.366, 1.429) < 0.001 Pulmonary Embolism 10,234 (1.6%) 0.405 2.216 (2.048, 2.397) < 0.001 Cardiogenic Shock 18,380 (3.0%) 0.068 0.879 (0.817, 0.946) < 0.001 Vasopressor Use 15,129 (2.4%) 0.065 2.102 (1.988, 2.223) < 0.001 Mechanical Ventilation 86,519 (13.9%) 0.076 2.571 (2.504, 2.640) < 0.001 Mechanical Circulatory Support 5,605 (0.9%) 0.128 0.482 (0.405, 0.575) < 0.001 Total Hospitalization Charge (USD) 114,929 (194,612) 60,019 [31,464, 123,490] 0.091 34671.3 (33103.0, 36239.7) < 0.001 2021 N = 818,248 Mortality 48,064 (5.9%) 0.089 5.712 (5.567, 5.860) < 0.001 Sudden Cardiac Arrest 24,514 (3.0%) 0.042 1.774 (1.695, 1.856) < 0.001 Acute Kidney Injury 301,334 (36.8%) 0.070 1.450 (1.422, 1.478) < 0.001 Pulmonary Embolism 14,805 (1.8%) 0.409 2.743 (2.584, 2.911) < 0.001 Cardiogenic Shock 24,542 (3.0%) 0.066 1.058 (0.999, 1.120) 0.057 Vasopressor Use 20,583 (2.5%) 0.067 2.127 (2.030, 2.229) < 0.001 Mechanical Ventilation 113,769 (13.9%) 0.073 2.725 (2.666, 2.786) < 0.001 Mechanical Circulatory Support 7,444 (0.9%) 0.125 0.617 (0.541, 0.704) < 0.001 Total Hospitalization Charge (USD) 128,288 (220,925) 66,556 [35,301, 137,779] 0.092 44830.6 (43425.9, 46235.2) < 0.001 2022 N = 866,595 Mortality 47,021 (5.4%) 0.064 2.529 (2.461, 2.600) < 0.001 Sudden Cardiac Arrest 24,307 (2.8%) 0.041 1.330 (1.271, 1.393) < 0.001 Acute Kidney Injury 315,295 (36.4%) 0.070 1.236 (1.216, 1.258) < 0.001 Pulmonary Embolism 14,909 (1.7%) 0.400 1.891 (1.786, 2.001) < 0.001 Cardiogenic Shock 27,191 (3.1%) 0.066 1.091 (1.040, 1.145) < 0.001 Vasopressor Use 24,231 (2.8%) 0.061 1.577 (1.511, 1.646) < 0.001 Mechanical Ventilation 120,032 (13.9%) 0.070 1.735 (1.698, 1.773) < 0.001 Mechanical Circulatory Support 7,828 (0.9%) 0.118 0.750 (0.675, 0.834) < 0.001 Total Hospitalization Charge (USD) 114,019 (194,612) 61,584 [33,799, 120,363] 0.090 24826.6 (23530.9, 26122.3) < 0.001 [ 1 ] Adjusted for age, sex, race, insurance, and whether it is an elective admission, income, injury diagnosis reported, Elixhauser co-morbidities, hospital division, ownership, teaching status, and bed size. [ 2 ] The total sample size (N) is smaller due to the exclusion of patients whose insurance status was classified as Self-pay or Other . For binary outcomes, the value represents the number of patients who experienced the outcome, whereas for the continuous outcome total charge, the numbers are reported as mean (SD) and median [IQR] for patients who had COVID-19. 3.3 Time-to-Event Analysis Cox proportional hazards regression models were applied to analyze time to in-hospital death for each year. In 2019, the analysis included 826,933 patients. In 2020 (March to December), the analysis included 37,257 CHF patients with COVID-19 (6.1% of the cohort) and 577,684 without COVID-19 (93.9%). The adjusted hazard ratio (aHR) associated with COVID-19 was 2.912 (95% CI: 2.835–2.992). In 2021, 50,587 patients (6.3%) had COVID-19 and 757,582 (93.7%) did not; the aHR slightly declined to 2.606 (95% CI: 2.545–2.668). In 2022, 66,155 patients (7.7%) were in the COVID-19 group and 788,865 (92.3%) were in the non-COVID group, and the aHR further decreased to 1.558 (95% CI: 1.518–1.599). The descriptive statistics of the length of stay are presented in Supporting Information S3. Regression results for other covariates are presented in Supporting Information S5. These findings indicate a progressive reduction in the hazard of in-hospital death among COVID-19 patients compared with non-COVID-19 patients over time, paralleling the trends observed in the multivariable logistic regression, where survival differences between COVID and non-COVID groups narrowed substantially by 2022. Table 5 Time to In-hospital Death Analysis Result for COVID-19 and Non-COVID-related Pneumonia Variables 2019 (N = 826,933) 2020 (Mar - Dec) (N = 614,941) 2021 (N = 808,169) 2022 (N = 855,020) Variable aHR 95% CI P-value aHR 95% CI P-value aHR 95% CI P-value aHR 95% CI P-value COVID-19 (Yes vs. No) 2.912 (2.835, 2.992) < 0.001 2.606 (2.545, 2.668) < 0.001 1.558 (1.518, 1.599) < 0.001 Non-COVID-related Pneumonia (Yes vs. No) 1.505 (1.471, 1.541) < 0.001 1.556 (1.517, 1.596) < 0.001 1.567 (1.532, 1.603) < 0.001 1.550 (1.517, 1.583) < 0.001 [ 1 ] Adjusted for age, sex, race, insurance, and whether it is an elective admission, income, injury diagnosis reported, Elixhauser co-morbidities, hospital division, teaching status, and bed size (see Supporting Information S5). 3.4. Comparison with Non-COVID Pneumonia To contextualize the COVID-19 findings, we evaluated non-COVID pneumonia among CHF patients, excluding records coded with COVID-19. In 2019–2022, the proportion of CHF admissions with non-COVID pneumonia was 16.4% (2019), 20.1% (2020 January and February), 14.6% (2020 March to December), 13.2% (2021), and 14.7% (2022), respectively. The high non-COVID pneumonia rate in the two winter months (January and February in 2020) is as expected. Moreover, compared to the effect of COVID-19, the mortality rate among CHF patients with pneumonia remained around 10.5% throughout the three years without significant fluctuation. Note that the mortality rate for patients with non-COVID pneumonia in 2022 was similar to that of patients with COVID-19 (10.5% vs. 11.1%). This further supports the observation that the effect of COVID-19 on CHF mortality lessened in 2022 and approached the level seen with other respiratory infections. Table 6 In-Hospital Mortality for CHF Patients by non-COVID Pneumonia Diagnosis Actual Mortality 2019 2020 (Jan to Feb) 2020 (Mar to Dec) 2021 2022 Without Pneumonia With Pneumonia Without Pneumonia With Pneumonia Without Pneumonia With Pneumonia Without Pneumonia With Pneumonia Without Pneumonia With Pneumonia P-value < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 N (sample size) 730,041 (83.6%) 143,237 (16.4%) 127,174 (79.9%) 32,029 (20.1%) 557,579 (85.4%) 95,630 (14.6%) 746,696 (86.8%) 113,414 (13.2%) 783,546 (85.3%) 134,887 (14.7%) Did not die 703,834 (96.4%) 131,097 (91.5%) 122,394 (96.2%) 29,456 (92.0%) 528,814 (94.8%) 85,733 (89.7%) 707,919 (94.8%) 101,062 (89.1%) 747,324 (95.4%) 120,761 (89.5%) Died 26,207 (3.6%) 12,140 (8.5%) 4,780 (3.8%) 2,573 (8.0%) 28,765 (5.2%) 9,897 (10.3%) 38,777 (5.2%) 12,352 (10.9%) 36,222 (4.6%) 14,126 (10.5%) Using multivariable logistic regression and Cox proportional hazards models, the association between non-COVID pneumonia and mortality among CHF patients remained remarkably stable from 2019 to 2022. The aOR were 2.407 (95% CI: 2.351–2.465) in 2019, 2.559 (95% CI: 2.492–2.627) in 2020, 2.628 (95% CI: 2.567–2.691) in 2021, and 2.502 (95% CI: 2.447–2.558) in 2022 (Supporting Information S2). Other adverse outcomes for patients with non-COVID pneumonia also remained stable across the four years; for example, in contrast to the temporal variation observed among COVID-19 patients (Table 4 ), the aOR for cardiogenic shock in non-COVID pneumonia patients was consistently around 1.7–1.9. Consistent results were observed in the Cox model analysis: the aHR for the association of non-COVID pneumonia with mortality among CHF patients were 1.505 (95% CI: 1.471–1.541), 1.556 (95% CI: 1.517–1.596), 1.567 (95% CI: 1.532–1.603), and 1.550 (95% CI: 1.517–1.583), respectively, as shown in Table 5 . This stability is consistent with a COVID-specific temporal change in mortality risk among CHF patients, rather than a uniform improvement across all respiratory infections. Nevertheless, this comparison is intended to be supportive rather than definitive, given that pathogen mix, coding practices, and care pathways may have evolved differently for pneumonia and COVID-19. 3.5 Subgroup Analysis of HFrEF and HFpEF patients Since CHF comprises two main subtypes, HFrEF and HFpEF, we further examined the impact of COVID-19 on these two subgroups separately. HFrEF patients had a higher mortality rate compared with HFpEF patients among both the COVID-19 and non-COVID-19 groups across all three years (COVID-19 group: 22.6% vs 21.5% in 2020, 21.0% vs 20.3% in 2021, 12.1% vs 10.2% in 2022; non-COVID-19 group: 5.6% vs 4.2% in 2020, 5.6% vs 4.3% in 2021, 5.6% vs 4.4% in 2022). Among patients with COVID-19, both HFrEF and HFpEF subgroups experienced a significant decline in mortality in 2022 (around 10–11%) compared to the previous two years (over 20%), consistent with the trend observed in the overall cohort. In the non-COVID-19 group, mortality rates for both HFrEF and HFpEF are slightly higher than in 2019. Table 7 In-Hospital Mortality for HFrEF or HFpEF Patients by COVID-19 Diagnosis HFrEF Patients Mortality 2019 2020 (Mar to Dec) 2021 2022 p-value Without COVID-19 With COVID-19 p-value Without COVID-19 With COVID-19 P-value Without COVID-19 With COVID-19 N (sample size) 435,822 309,371 18,250 403,141 25,627 421,001 34,247 Did not die 413,881 (95.0%) 292,188 (94.4%) 14,120 (77.4%) < 0.001 380,540 (94.4%) 20,242 (79.0%) < 0.001 397,333 (94.4%) 30,114 (87.9%) < 0.001 Died 21,941 (5.0%) 17,183 (5.6%) 4,130 (22.6%) 22,601 (5.6%) 5,385 (21.0%) 23,668 (5.6%) 4,133 (12.1%) HFpEF Patients Mortality 2019 2020 (Mar to Dec) 2021 2022 p-value Without COVID-19 With COVID-19 p-value Without COVID-19 With COVID-19 P-value Without COVID-19 With COVID-19 N (sample size) 437,456 304,562 21,026 403,356 27,986 419,728 35388 Did not die 421,050 (96.2%) 291,736 (95.8%) 16,503 (78.5%) < 0.001 385,881 (95.7%) 22,318 (79.7%) < 0.001 401,225 (95.6%) 31,786 (89.8%) < 0.001 Died 16,406 (3.8%) 12,826 (4.2%) 4,523 (21.5%) 17,475 (4.3%) 5,668 (20.3%) 18,503 (4.4%) 3,602 (10.2%) Further analysis of in-hospital outcomes showed that HFpEF patients had higher aORs for multiple adverse events, including mortality, compared to both HFrEF patients and the overall CHF population across all three years. For instance, the aORs of COVID-19 on mortality in HFpEF patients were 7.207 (95% CI: 6.912–7.515) in 2020, 6.756 (95% CI: 6.514–7.007) in 2021, and 2.685 (95% CI: 2.579–2.795) in 2022, while they were 5.324 (95% CI: 5.106–5.553) in 2020, 4.906 (95% CI: 4.731–5.087) in 2021, and 2.390 (95% CI: 2.302–2.482) in 2022 for HFrEF patients. A complete set of results is provided in Supporting Information S6. 3.6 Result Summary CHF patients with concurrent COVID-19 infection had significantly higher odds of in-hospital mortality and other major adverse outcomes compared to those without COVID-19. COVID-19-positive CHF patients experienced shorter in-hospital survival times. The difference in outcomes between COVID-19-positive and COVID-19-negative patients progressively narrowed over the three years, as reflected by decreasing gaps in both odds ratios and hazard ratios. Among patients infected with COVID-19, those with HFpEF had a higher adjusted odds of mortality and complications compared to those with HFrEF. 4. Discussion Possible mechanism for higher mortality in patients with respiratory infections Our findings are consistent with prior studies. A nationwide analysis using the NIS data reported that, in 2020, CHF patients with COVID-19 had markedly higher in-hospital mortality, longer hospital stays, and increased complications compared to those without COVID-19 [ 8 ]. Similarly, a meta-analysis demonstrated that pre-existing heart failure is associated with a significantly higher risk of hospitalization and death from COVID-19 [ 10 ]. Several mechanisms may explain the increased vulnerability of CHF patients to COVID-19. Impaired cardiac reserve in heart failure limits the ability to tolerate the hemodynamic stress and hypoxia caused by systemic infection. SARS-CoV-2 infection also induces substantial release of pro-inflammatory cytokines, including IL-1 and IL-6, which may directly or indirectly damage the myocardium [ 11 – 13 ]. Moreover, the widespread inflammatory response and cytokine activation seen in severe COVID-19 may further destabilize cardiac function in patients with pre-existing heart failure. These overlapping processes offer a coherent explanation for the elevated mortality and complication rates identified in this population [ 14 , 15 ]. Additionally, although many patients with chronic heart failure receive long-term angiotensin-converting enzyme inhibitors (ACEI) and angiotensin receptor blockers (ARB), such treatment has been associated with reduced COVID-19 mortality in observational studies [ 16 ]. Their protective effect may not fully counterbalance the heightened inflammatory burden in this high-risk group. Other variables associated with mortality and in-hospital adverse outcomes In addition to COVID-19 infection, we identified several independent variables associated with in-hospital mortality among patients hospitalized with CHF. Increasing age and non-elective admission were both strongly associated with higher odds of mortality, consistent with previous studies highlighting age and acute presentation as critical risk factors for poor outcomes. Several comorbidity-related variables, including pulmonary circulation disease and uncomplicated hypertension, were also independently associated with increased mortality risk. Several co-existing conditions, including smoking, sleep apnea, depression, diabetes, and previous myocardial infarction, traditionally associated with adverse outcomes, were paradoxically linked to lower in-hospital mortality among patients with CHF. These counterintuitive findings are unlikely to represent true protective effects and may instead reflect residual confounding, such as incomplete adjustment for disease severity, misclassification of diagnoses, or unmeasured clinical and socioeconomic factors. For instance, patients with well-managed chronic conditions might have more frequent healthcare interactions, leading to earlier diagnosis, better outpatient management, and potentially improved resilience during hospitalization. In the case of previous myocardial infarction, the lower observed mortality may also partly reflect higher use of ACEI/ARB, which has been associated with reduced mortality risk [ 16 ]. Alternatively, some of these conditions may be undercoded or selectively recorded among sicker patients, potentially skewing the observed associations. HFpEF vs HFrEF Our study observed that COVID-19 infection was associated with a higher adjusted odds ratio for in-hospital mortality in patients with HFpEF compared to those with HFrEF. This observation contrasts with previous expectations and observations that patients with HFrEF, given their significantly reduced cardiac function and poorer baseline health, experience higher mortality when infected with COVID-19 [ 7 , 17 , 18 ]. However, some recent studies have reported findings similar to ours [ 19 ]. Patients with HFpEF typically are older and often have multiple metabolic and inflammatory comorbidities such as hypertension, diabetes, and obesity, potentially placing them at greater risk for severe complications from COVID-19 [ 20 ]. Furthermore, viral-induced myocardial injury and systemic inflammation can lead to a HFpEF-like syndrome or exacerbate existing HFpEF conditions [ 21 , 22 ]. Additionally, one study noted that during COVID-19 hospitalization, patients with HFpEF experienced longer delays in diagnosis compared to those with HFrEF [ 6 ]. These studies highlight the critical need for improved risk assessment and more timely, personalized treatment strategies for HFpEF patients during outbreaks such as COVID-19. Limitations Several limitations should be considered when interpreting our findings. First, this analysis relied on administrative data and ICD-10 codes from the NIS database, which may introduce misclassification. Clinical variables such as laboratory results and echocardiographic measurements were unavailable. Second, because the NIS captures discharge-level data rather than patient-level trajectories, we could not distinguish between initial and recurrent hospitalizations or assess post-discharge outcomes. In other words, the database does not permit ascertainment of whether a given hospitalization represented an index admission or a subsequent readmission. Third, although we adjusted for multiple confounders, unmeasured factors such as vaccination status, healthcare system burden at different times [ 23 ], SARS-CoV-2 variant type, and outpatient management strategies may have influenced the results. Vaccination status is of particular concern, as research has shown that vaccination can reduce hospitalization and mortality in heart failure patients [ 24 ]. Although an ICD code for COVID-19 under immunization (Z28.3) has been available since 2021, very few patients had records of this code (only 246 [0.03%] in 2021 and 10,504 [1.1%] in 2022 with code Z28.3 available). In contrast, population-level surveillance data until 2021 indicated that vaccination coverage among adults aged ≥ 18 years had reached 58.8% [ 25 ]. The substantial discrepancy between population surveillance data and hospital administrative coding suggests severe underreporting of vaccination status in records and warrants further investigation. Given this data limitation, we were unable to reliably assess the independent effect of COVID-19 vaccination on in-hospital outcomes in this study. The effect of COVID vaccination on in-hospital outcomes of CHF patients still needs further exploration. Also, as the NIS captures only hospitalized patients, our findings may not generalize to the broader CHF population treated in outpatient settings. Despite these limitations, the use of a large, nationally representative cohort provides robust evidence regarding the evolving impact of COVID-19 on hospitalized patients with congestive heart failure. 5. Conclusion In summary, this study analyzed more than 3.4 million hospitalized CHF patients from 2019 to 2022 using the NIS database. COVID-19 infection was associated with a markedly increased risk of in-hospital mortality as well as other adverse outcomes. However, the excess risk declined over time, with differences in mortality and complications converging by 2022 to levels comparable with those observed for non-COVID respiratory infections such as pneumonia. These observations likely reflect multiple factors, including evolving viral variants, improved clinical management, availability of vaccines and effective treatments, and heightened awareness of cardiovascular risk in this vulnerable population. Our findings also highlight the disproportionate impact of COVID-19 on patients with CHF and underscore the importance of continued monitoring, tailored surveillance strategies, and optimal management of comorbidities in this high-risk group. Abbreviations SARS-CoV-2 Severe Acute Respiratory Syndrome Coronavirus 2 COVID-19 coronavirus disease 19 CHF congestive heart failure HFrEF heart failure with reduced ejection fraction HFpEF heart failure with preserved ejection fraction NIS the National Inpatient Sample ICD-10-CM the tenth revision of the International Classification of Diseases OR odds ratio aOR adjusted odds ratio CI confidence interval HR hazard ratio aHR adjusted hazard ratio CABG coronary artery bypass grafting MI myocardial infarction Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Funding This research received no external funding. YD used internal research funding to support the purchase of the NIS datasets and the student researcher stipend. Author Contribution Conceptualization: YD, JZ, and MZData curation: YD, YM, JL, JZ, and HWFormal analysis: YM, JL, and JZMethodology: YD, YM, JL, JZ, and HWProject administration: YDSupervision: YDVisualization: YM and JLWriting – original draft: YM, JL, and JZWriting – review & editing: YD, JL, HW, and MZ Acknowledgements The authors gratefully acknowledge the Healthcare Cost and Utilization Project (HCUP) for providing access to the National Inpatient Sample (NIS) datasets used in this analysis. Data Availability The data that support the findings of this study are openly available for access (with fees) in the National Inpatient Sample (NIS) at [https://hcup-us.ahrq.gov/nisoverview.jsp](https:/hcup-us.ahrq.gov/nisoverview.jsp) . References Heidenreich PA, Bozkurt B, Aguilar D, Allen LA, Byun JJ, Colvin MM, et al. 2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2022;145(18):e895–1032. 10.1161/CIR.0000000000001063 . Epub 20220401. Ram-Mohan N, Kim D, Zudock EJ, Hashemi MM, Tjandra KC, Rogers AJ, et al. SARS-CoV-2 RNAemia Predicts Clinical Deterioration and Extrapulmonary Complications from COVID-19. Clin Infect Dis. 2022;74(2):218–26. 10.1093/cid/ciab394 . Williamson EJ, Walker AJ, Bhaskaran K, Bacon S, Bates C, Morton CE, et al. Factors associated with COVID-19-related death using OpenSAFELY. Nature. 2020;584(7821):430–6. 10.1038/s41586-020-2521-4 . Epub 20200708. Petrilli CM, Jones SA, Yang J, Rajagopalan H, O'Donnell L, Chernyak Y et al. Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study. BMJ. 2020;369:m1966. Epub 20200522. 10.1136/bmj.m 1966. Ward IL, Bermingham C, Ayoubkhani D, Gethings OJ, Pouwels KB, Yates T, et al. Risk of covid-19 related deaths for SARS-CoV-2 omicron (B.1.1.529) compared with delta (B.1.617.2): retrospective cohort study. BMJ. 2022;378:e070695. 10.1136/bmj-2022-070695 . Epub 20220802. Alharbi A, Alfatlawi H, Mohamed A, Mhanna M, Mahmoud M, Elsheik R, et al. Outcomes of Heart Failure Related Hospitalizations During the COVID-19 Pandemic. Cureus. 2023;15(3):e36935. 10.7759/cureus.36935 . Epub 20230330. Nasrullah A, Gangu K, Cannon HR, Khan UA, Shumway NB, Bobba A, et al. COVID-19 and Heart Failure with Preserved and Reduced Ejection Fraction Clinical Outcomes among Hospitalized Patients in the United States. Viruses. 2023;15(3). 10.3390/v15030600 . Epub 20230222. Fatuyi M, Amoah J, Egbuchiem H, Antia A, Akinti S, Mararenko A, et al. Impact of COVID-19 Infection on Clinical Outcomes Among Patients With Acute Decompensated Heart Failure: A Nationwide Analysis. Curr Probl Cardiol. 2023;48(11):101908. 10.1016/j.cpcardiol.2023.101908 . Epub 20230701. HCUP National Inpatient Sample (NIS) [Internet]. 2012 [cited 21 Jan 2025]. Available from: Yonas E, Alwi I, Pranata R, Huang I, Lim MA, Gutierrez EJ, et al. Effect of heart failure on the outcome of COVID-19 - A meta analysis and systematic review. Am J Emerg Med. 2021;46:204–11. 10.1016/j.ajem.2020.07.009 . Epub 20200709. Unudurthi SD, Luthra P, Bose RJC, McCarthy JR, Kontaridis MI. Cardiac inflammation in COVID-19: Lessons from heart failure. Life Sci. 2020;260:118482. 10.1016/j.lfs.2020.118482 . Epub 20200921. Peng X, Wang Y, Xi X, Jia Y, Tian J, Yu B, Tian J. Promising Therapy for Heart Failure in Patients with Severe COVID-19: Calming the Cytokine Storm. Cardiovasc Drugs Ther. 2021;35(2):231–47. 10.1007/s10557-020-07120-8 . Epub 20210106. Zanza C, Romenskaya T, Manetti AC, Franceschi F, La Russa R, Bertozzi G et al. Cytokine Storm in COVID-19: Immunopathogenesis and Therapy. Medicina (Kaunas). 2022;58(2). Epub 20220118. 10.3390/medicina58020144 Tomasoni D, Inciardi RM, Lombardi CM, Tedino C, Agostoni P, Ameri P, et al. Impact of heart failure on the clinical course and outcomes of patients hospitalized for COVID-19. Results of the Cardio-COVID-Italy multicentre study. Eur J Heart Fail. 2020;22(12):2238–47. 10.1002/ejhf.2052 . Epub 20201127. Mir T, Almas T, Kaur J, Faisaluddin M, Song D, Ullah W, et al. Coronavirus disease 2019 (COVID-19): Multisystem review of pathophysiology. Ann Med Surg (Lond). 2021;69:102745. 10.1016/j.amsu.2021.102745 . Epub 20210823. Zhang P, Zhu L, Cai J, Lei F, Qin JJ, Xie J, et al. Association of Inpatient Use of Angiotensin-Converting Enzyme Inhibitors and Angiotensin II Receptor Blockers With Mortality Among Patients With Hypertension Hospitalized With COVID-19. Circ Res. 2020;126(12):1671–81. 10.1161/CIRCRESAHA.120.317134 . Epub 20200417. Alvarez-Garcia J, Lee S, Gupta A, Cagliostro M, Joshi AA, Rivas-Lasarte M, et al. Prognostic Impact of Prior Heart Failure in Patients Hospitalized With COVID-19. J Am Coll Cardiol. 2020;76(20):2334–48. 10.1016/j.jacc.2020.09.549 . Epub 20201028. Freaney PM, Shah SJ, Khan SS. COVID-19 and Heart Failure With Preserved Ejection Fraction. JAMA. 2020;324(15):1499–500. 10.1001/jama.2020.17445 . Panagides V, Vincent F, Weizman O, Jonveaux M, Trimaille A, Pommier T, et al. History of heart failure in patients with coronavirus disease 2019: Insights from a French registry. Arch Cardiovasc Dis. 2021;114(5):415–25. 10.1016/j.acvd.2021.04.003 . Epub 20210524. DeBerge M, Shah SJ, Wilsbacher L, Thorp EB. Macrophages in Heart Failure with Reduced versus Preserved Ejection Fraction. Trends Mol Med. 2019;25(4):328–40. 10.1016/j.molmed.2019.01.002 . Epub 20190205. Akhmerov A, Marban E. COVID-19 and the Heart. Circ Res. 2020;126(10):1443–55. 10.1161/CIRCRESAHA.120.317055 . Epub 20200407. Hadzibegovic S, Lena A, Churchill TW, Ho JE, Potthoff S, Denecke C, et al. Heart failure with preserved ejection fraction according to the HFA-PEFF score in COVID-19 patients: clinical correlates and echocardiographic findings. Eur J Heart Fail. 2021;23(11):1891–902. 10.1002/ejhf.2210 . Epub 20210712. Miller IF, Becker AD, Grenfell BT, Metcalf CJE. Disease and healthcare burden of COVID-19 in the United States. Nat Med. 2020;26(8):1212–7. 10.1038/s41591-020-0952-y . Epub 20200616. Johnson KW, Patel S, Thapi S, Jaladanki SK, Rao A, Nirenberg S, Lala A. Association of Reduced Hospitalizations and Mortality Rates Among COVID-19-Vaccinated Patients With Heart Failure. J Card Fail. 2022;28(9):1475–9. 10.1016/j.cardfail.2022.05.008 . Epub 20220609. Suthar AB, Wang J, Seffren V, Wiegand RE, Griffing S, Zell E. Public health impact of covid-19 vaccines in the US: observational study. BMJ. 2022;377:e069317. 10.1136/bmj-2021-069317 . Epub 20220427. Additional Declarations No competing interests reported. Supplementary Files Supportinginformation.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 17 Feb, 2026 Reviewers agreed at journal 12 Feb, 2026 Reviewers agreed at journal 10 Feb, 2026 Reviewers agreed at journal 04 Feb, 2026 Reviewers invited by journal 04 Feb, 2026 Editor invited by journal 13 Jan, 2026 Editor assigned by journal 13 Jan, 2026 Submission checks completed at journal 13 Jan, 2026 First submitted to journal 11 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8575946","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":585870993,"identity":"58b8f2ff-28d2-45ac-ad6c-f3b1981d81bb","order_by":0,"name":"Yuyan Ma","email":"","orcid":"","institution":"University of Pittsburgh","correspondingAuthor":false,"prefix":"","firstName":"Yuyan","middleName":"","lastName":"Ma","suffix":""},{"id":585871002,"identity":"55ca143e-8a6a-4c90-bfa3-fafa07811223","order_by":1,"name":"Jiaqian Liu","email":"","orcid":"","institution":"University of Pittsburgh","correspondingAuthor":false,"prefix":"","firstName":"Jiaqian","middleName":"","lastName":"Liu","suffix":""},{"id":585871007,"identity":"cd07df95-6427-4f9f-85f1-1cb8e4e8bb24","order_by":2,"name":"Jerry Zhou","email":"","orcid":"","institution":"University of Pittsburgh","correspondingAuthor":false,"prefix":"","firstName":"Jerry","middleName":"","lastName":"Zhou","suffix":""},{"id":585871012,"identity":"43e10ed3-9680-44d6-8205-30f4629ad45f","order_by":3,"name":"Haoling Wang","email":"","orcid":"","institution":"University of Pittsburgh","correspondingAuthor":false,"prefix":"","firstName":"Haoling","middleName":"","lastName":"Wang","suffix":""},{"id":585871013,"identity":"3f910563-625d-48ec-b650-6432f36266b4","order_by":4,"name":"Manling Zhang","email":"","orcid":"","institution":"University of Pittsburgh","correspondingAuthor":false,"prefix":"","firstName":"Manling","middleName":"","lastName":"Zhang","suffix":""},{"id":585871016,"identity":"2faa5eab-0958-4e68-9f47-bdaea5b6b6cc","order_by":5,"name":"Ying Ding","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0UlEQVRIiWNgGAWjYDACZiDmMWBg4GdgbADxISRRWiQbGBsbDhClBQR4gNjgAFA1UVoMjvMefvGm4I7d5tvN7Y8/MNjIbjhASMthvjTLOQbPkrfdOQhyWJoxEVp4zIx5DA4nm91IBGk5nEi8FuMZYC3/idJi/Bioxc5AAqzlAGEtkkBbGOcYHE6QAPplxhmDZOOZhLTwnT9j/OHNn8P2/LPbH3yoqLCT7SOkReEAA5sEkE5skAC7k4ByEJBvYGD+AKTtGSSIUD0KRsEoGAUjEwAABmdN3uKfbQwAAAAASUVORK5CYII=","orcid":"","institution":"University of Pittsburgh","correspondingAuthor":true,"prefix":"","firstName":"Ying","middleName":"","lastName":"Ding","suffix":""}],"badges":[],"createdAt":"2026-01-11 22:38:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8575946/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8575946/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102296246,"identity":"64fc5a9b-e511-4a88-9515-7ddf4f3b5b42","added_by":"auto","created_at":"2026-02-10 10:18:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2665595,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8575946/v1/4f3e1282-079d-445a-84de-3cdbb7e30aa4.pdf"},{"id":102069787,"identity":"107f3918-d2fc-40ea-9cae-d4e302eb3e45","added_by":"auto","created_at":"2026-02-06 19:11:55","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":72163,"visible":true,"origin":"","legend":"","description":"","filename":"Supportinginformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-8575946/v1/4275f834cae8ba3c30c76014.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of Respiratory Infections on Hospitalized Congestive Heart Failure Patients: A Retrospective Analysis of NIS Database (2019–2022)","fulltext":[{"header":"1. Background","content":"\u003cp\u003eCongestive heart failure (CHF) is a chronic, progressive condition characterized by impaired cardiac function and remains a leading cause of hospitalization and in-hospital mortality, particularly in older adults. Patients with CHF often have multiple coexisting conditions and are especially vulnerable to acute clinical deterioration when exposed to physiological stressors such as infection. CHF encompasses a heterogeneous group of patients, commonly categorized into heart failure with reduced ejection fraction (HFrEF) and heart failure with preserved ejection fraction (HFpEF), which differ in pathophysiology, clinical characteristics, and treatment response [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSince its emergence in late 2019, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], has had a profound impact on global health systems. COVID-19 commonly presents with clinical manifestations such as fever and respiratory distress, and is frequently associated with pulmonary conditions, including pneumonia and other respiratory tract infections. Beyond the respiratory system, it has been linked to systemic complications and the exacerbation of chronic comorbidities. Heart disease and hypertension, as well as diabetes and chronic kidney disease, are known to increase the risk of severe outcomes in patients with COVID-19 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. CHF, in particular, has drawn attention as a key comorbidity during the pandemic.\u003c/p\u003e \u003cp\u003eAs a high-risk cardiovascular condition, CHF not only increases the risk of severe outcomes after SARS-CoV-2 infection but may also be directly affected by the infection through inflammatory and cardiovascular pathways [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Moreover, as the virus has evolved into variants with differing transmissibility and severity, the impact of COVID-19 on patients with CHF has likely shifted over time [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, most prior studies have focused on early pandemic data [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], leaving these temporal changes largely unexplored.\u003c/p\u003e \u003cp\u003eWe analyzed National Inpatient Sample (NIS) data from 2019 to 2022 to evaluate in-hospital outcomes among CHF patients with and without COVID-19. This retrospective analysis included over 3.4\u0026nbsp;million CHF hospitalizations in the United States over these four years, representing the largest cohort to date for such comparisons. By capturing data across the early, peak, and post-pandemic phases, we aimed to assess temporal variations in the clinical impact of COVID-19, specifically regarding in-hospital mortality, time (from hospitalization) to in-hospital death, and other adverse outcomes. We also explored differences between CHF subtype HFrEF and HFpEF, to better characterize COVID-19\u0026rsquo;s evolving influence on this high-risk population.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Data Source\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective observational study using the Agency for Healthcare Research and Quality NIS dataset, which contains discharge-level data from a 20% stratified sample of U.S. community hospital discharges [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur study analyzed data from January 1, 2019, to December 31, 2022. Patients aged 18 to 90 years admitted with a CHF diagnosis (primary or secondary) were included. The included patients were further stratified based on the presence or absence of a concurrent COVID-19 diagnosis. Data from 2019 served as a pre-pandemic reference cohort. The number of CHF patients included per year was as follows: 873,278 in 2019, 812,412 in 2020 (with 653,209 from March to December, after COVID-19 was identified and spread in the U.S.), 860,110 in 2021, and 910,364 in 2022.\u003c/p\u003e \u003cp\u003eThe NIS dataset applies the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) for diagnoses and ICD-10 procedure codes for interventions. Data extraction was based on these codes, with a detailed summary provided in Supporting Information S1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Study Outcomes and Covariates\u003c/h2\u003e \u003cp\u003eThe primary outcome of this study was in-hospital mortality. Secondary outcomes included vasopressor use, mechanical ventilation, mechanical circulatory support, sudden cardiac arrest, acute kidney injury, pulmonary embolism, and cardiogenic shock. We also analyzed the survival outcome, which is defined as the time to in-hospital death.\u003c/p\u003e \u003cp\u003ePotential confounders adjusted for included: (1) demographic factors such as age, sex, race, insurance status, injury condition, and elective admission, (2) hospital characteristics such as division, bed size, teaching status, and ownership of hospital, (3) patient comorbidities assessed using the Elixhauser Comorbidity Index (ECI).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Statistical Methods\u003c/h2\u003e \u003cp\u003eIn the descriptive analysis, continuous variables were compared using Student\u0026rsquo;s t-test, and categorical variables were compared using the chi-square test between the COVID-19 and non-COVID-19 groups.\u003c/p\u003e \u003cp\u003eUnivariable logistic regression was used to estimate unadjusted odds ratios (ORs) for the primary (death) and secondary outcomes (e.g., sudden cardiac arrest, acute kidney injury, pulmonary embolism, cardiogenic shock, vasopressor use, mechanical ventilation, and mechanical circulatory Support). Variables with a p-value\u0026thinsp;\u0026le;\u0026thinsp;0.001 in the univariable analysis were included in the multivariable logistic regression to adjust for potential confounders. Adjusted odds ratios (aORs) with 95% confidence intervals (CIs) were reported.\u003c/p\u003e \u003cp\u003eThe Cox proportional hazards model was used to evaluate the association between COVID-19 diagnosis and time to in-hospital death (from hospitalization) among patients with CHF. Time to in-hospital death, or length of stay, was defined as the number of days from hospital admission to either death or discharge, with patients discharged alive treated as right-censored observations. Univariable Cox regression was first performed to estimate unadjusted hazard ratios (HRs) with 95% confidence intervals (CIs). Variables with a p-value\u0026thinsp;\u0026le;\u0026thinsp;0.001 in the univariable Cox regression were subsequently included in the multivariable Cox model to adjust for potential confounders. Adjusted hazard ratios (aHRs) with 95% CIs were reported.\u003c/p\u003e \u003cp\u003eAll statistical analyses were performed using R software (version 4.4.1; R Foundation for Statistical Computing, Vienna, Austria).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Demographics, Baseline Comorbidities and Hospital Characteristics\u003c/h2\u003e \u003cp\u003eThis study analyzed four years of data on patients with CHF from the NIS database. In 2019, 873,278 patients were included. In 2020 (March to December, post COVID-19 identification and spread in the U.S.), 653,209 patients were included, of whom 39,276 (6.0%) had a concurrent diagnosis of COVID-19. In 2021, 860,110 patients were included, with 53,613 (6.2%) diagnosed with COVID-19. In 2022, 910,364 patients were included, and 69,635 (7.6%) had a COVID-19 diagnosis.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents patient demographics for the two groups. In both 2020 and 2022, CHF patients with COVID-19 were significantly older. In 2020, 74.9% of patients in the COVID-19 group were over 65, compared to 70.4% in the non-COVID group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In 2022, 75.9% of patients in the COVID-19 group were over 65, compared to 71.6% in the non-COVID group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). However, in 2021, there was no statistically significant difference in age distribution between the two groups (p\u0026thinsp;=\u0026thinsp;0.078). Between 2020 and 2022, the age distribution of CHF patients without COVID-19 was generally comparable to that of the 2019 cohort.\u003c/p\u003e \u003cp\u003eIn addition to age, several other variables differed between the COVID-19 and non-COVID-19 groups. Compared with patients without COVID-19, those with CHF and COVID-19 were more likely to be male (2020: 54.1% vs. 53.0%; 2021: 54.7% vs. 52.7%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), had fewer elective admissions (2020: 2.8% vs. 8.4%; 2021: 2.5% vs. 8.4%; 2022: 2.6% vs. 8.4%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and experienced a longer mean of length of hospital stay, regardless of whether they were discharged alive or died in the hospital (2020: 10.0 vs. 6.6 days; 2021: 10.6 vs. 6.7 days; 2022: 9.6 vs. 6.9 days; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). For the non-COVID-19 group, these characteristics are similar to those observed in the 2019 cohort.\u003c/p\u003e \u003cp\u003eSeveral hospital characteristics also differed between the COVID-19 and non-COVID-19 groups. Compared with those without COVID-19, patients with CHF and COVID-19 were less often admitted to large hospitals (2020: 49.1% vs. 50.7%; 2021: 48.0% vs. 50.3%; 2022: 47.4% vs. 48.9%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). They were also more likely to be treated in rural hospitals (2021: 10.0% vs. 8.2%; 2022: 9.0% vs. 8.5%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Modest but significant regional variations were observed across hospital divisions, with differences most notable in the New England and Pacific regions. Overall, hospital characteristics in the non-COVID-19 group are consistent with patterns observed in 2019.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient and Hospital Characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003cp\u003eCHF Without\u003c/p\u003e \u003cp\u003eCOVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003cp\u003eCHF With\u003c/p\u003e \u003cp\u003eCOVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003cp\u003eCHF Without\u003c/p\u003e \u003cp\u003eCOVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003cp\u003eCHF With\u003c/p\u003e \u003cp\u003eCOVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003cp\u003eCHF Without\u003c/p\u003e \u003cp\u003eCOVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003cp\u003eCHF With\u003c/p\u003e \u003cp\u003eCOVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;873,278\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;653,209\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;860,110\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;910, 364\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;613,933 \u003c/p\u003e \u003cp\u003e(94.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;39,276 \u003c/p\u003e \u003cp\u003e(6.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;806,497 \u003c/p\u003e \u003cp\u003e(93.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;53,613 \u003c/p\u003e \u003cp\u003e(6.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003en\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;840,729 \u003c/p\u003e \u003cp\u003e(92.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003en\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;69,635 \u003c/p\u003e \u003cp\u003e(7.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71.7 \u003c/p\u003e \u003cp\u003e(13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.0 \u003c/p\u003e \u003cp\u003e(13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72.5 \u003c/p\u003e \u003cp\u003e(13.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e71.2\u003c/p\u003e \u003cp\u003e(13.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e71.0\u003c/p\u003e \u003cp\u003e(13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e71.3\u003c/p\u003e \u003cp\u003e(13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e73.0\u003c/p\u003e \u003cp\u003e(13.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian [Min, Max]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73.0\u003c/p\u003e \u003cp\u003e[18.0, 90.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.0\u003c/p\u003e \u003cp\u003e[18.0, 90.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74.0\u003c/p\u003e \u003cp\u003e[18.0, 90.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e73.0\u003c/p\u003e \u003cp\u003e[18.0, 90.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e73.0\u003c/p\u003e \u003cp\u003e[18.0, 90.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e73.0\u003c/p\u003e \u003cp\u003e[18.0, 90.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e75.0\u003c/p\u003e \u003cp\u003e[18.0, 90.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e245,462\u003c/p\u003e \u003cp\u003e(28.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e181,893\u003c/p\u003e \u003cp\u003e(29.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9,853 \u003c/p\u003e \u003cp\u003e(25.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e233,650\u003c/p\u003e \u003cp\u003e(29.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15,724\u003c/p\u003e \u003cp\u003e(29.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e238,360\u003c/p\u003e \u003cp\u003e(28.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e16,793\u003c/p\u003e \u003cp\u003e(24.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;= 65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e627,816\u003c/p\u003e \u003cp\u003e(71.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e432,040\u003c/p\u003e \u003cp\u003e(70.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29,423 \u003c/p\u003e \u003cp\u003e(74.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e572,847\u003c/p\u003e \u003cp\u003e(71.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37,889\u003c/p\u003e \u003cp\u003e(70.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e602,369\u003c/p\u003e \u003cp\u003e(71.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e52,842\u003c/p\u003e \u003cp\u003e(75.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e609,065\u003c/p\u003e \u003cp\u003e(69.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e428,391\u003c/p\u003e \u003cp\u003e(69.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23,568 \u003c/p\u003e \u003cp\u003e(60.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e560,154\u003c/p\u003e \u003cp\u003e(69.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35,502\u003c/p\u003e \u003cp\u003e(66.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e580,872\u003c/p\u003e \u003cp\u003e(69.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e47,607\u003c/p\u003e \u003cp\u003e(68.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e157,117\u003c/p\u003e \u003cp\u003e(18.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e111,023\u003c/p\u003e \u003cp\u003e(18.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8,652\u003c/p\u003e \u003cp\u003e(22.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e144,625\u003c/p\u003e \u003cp\u003e(17.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10,328\u003c/p\u003e \u003cp\u003e(19.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e150,100\u003c/p\u003e \u003cp\u003e(17.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e12,227\u003c/p\u003e \u003cp\u003e(17.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64,284\u003c/p\u003e \u003cp\u003e(7.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44,857\u003c/p\u003e \u003cp\u003e(7.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,776\u003c/p\u003e \u003cp\u003e(12.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e62,728\u003c/p\u003e \u003cp\u003e(7.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5,111\u003c/p\u003e \u003cp\u003e(9.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e67,722\u003c/p\u003e \u003cp\u003e(8.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5,955\u003c/p\u003e \u003cp\u003e(8.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian or Pacific Islander\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18,653\u003c/p\u003e \u003cp\u003e(2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12,622\u003c/p\u003e \u003cp\u003e(2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e856\u003c/p\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17,515\u003c/p\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,127\u003c/p\u003e \u003cp\u003e(2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18,929\u003c/p\u003e \u003cp\u003e(2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1,781\u003c/p\u003e \u003cp\u003e(2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNative American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,837\u003c/p\u003e \u003cp\u003e(0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,395\u003c/p\u003e \u003cp\u003e(0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e316\u003c/p\u003e \u003cp\u003e(0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,485\u003c/p\u003e \u003cp\u003e(0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e350\u003c/p\u003e \u003cp\u003e(0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4,710\u003c/p\u003e \u003cp\u003e(0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e400\u003c/p\u003e \u003cp\u003e(0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19,322\u003c/p\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13,645\u003c/p\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,108\u003c/p\u003e \u003cp\u003e(2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16,990\u003c/p\u003e \u003cp\u003e(2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,195\u003c/p\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18,396\u003c/p\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1,665\u003c/p\u003e \u003cp\u003e(2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e451,777\u003c/p\u003e \u003cp\u003e(51.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e325,608\u003c/p\u003e \u003cp\u003e(53.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,1267\u003c/p\u003e \u003cp\u003e(54.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e425,169\u003c/p\u003e \u003cp\u003e(52.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e29,350\u003c/p\u003e \u003cp\u003e(54.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e442,426\u003c/p\u003e \u003cp\u003e(52.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e36,968\u003c/p\u003e \u003cp\u003e(53.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e421,501\u003c/p\u003e \u003cp\u003e(48.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e288,325\u003c/p\u003e \u003cp\u003e(47.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,8009\u003c/p\u003e \u003cp\u003e(45.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e381,328\u003c/p\u003e \u003cp\u003e(47.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24,263\u003c/p\u003e \u003cp\u003e(45.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e398,303\u003c/p\u003e \u003cp\u003e(47.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e32,667\u003c/p\u003e \u003cp\u003e(46.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eElective\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-elective admission (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e801,871\u003c/p\u003e \u003cp\u003e(91.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e562,090\u003c/p\u003e \u003cp\u003e(91.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38,166\u003c/p\u003e \u003cp\u003e(97.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e738,449\u003c/p\u003e \u003cp\u003e(91.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e52,265\u003c/p\u003e \u003cp\u003e(97.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e769,967\u003c/p\u003e \u003cp\u003e(91.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e67,815\u003c/p\u003e \u003cp\u003e(97.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElective admission (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71,407\u003c/p\u003e \u003cp\u003e(8.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51,843\u003c/p\u003e \u003cp\u003e(8.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,110\u003c/p\u003e \u003cp\u003e(2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e68,048\u003c/p\u003e \u003cp\u003e(8.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,348\u003c/p\u003e \u003cp\u003e(2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e70,762\u003c/p\u003e \u003cp\u003e(8.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1,820\u003c/p\u003e \u003cp\u003e(2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedian Household Income\u003c/b\u003e \u003csup\u003e\u003cb\u003e[1]\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0-25th percentile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e280,405\u003c/p\u003e \u003cp\u003e(32.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e197,699\u003c/p\u003e \u003cp\u003e(32.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13,700\u003c/p\u003e \u003cp\u003e(34.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e256,361\u003c/p\u003e \u003cp\u003e(31.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18,305\u003c/p\u003e \u003cp\u003e(34.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e263,088\u003c/p\u003e \u003cp\u003e(31.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e21,488\u003c/p\u003e \u003cp\u003e(30.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u0026ndash;50th percentile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e225,187\u003c/p\u003e \u003cp\u003e(25.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e170,742\u003c/p\u003e \u003cp\u003e(27.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10,895\u003c/p\u003e \u003cp\u003e(27.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e208,331\u003c/p\u003e \u003cp\u003e(25.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14,694\u003c/p\u003e \u003cp\u003e(27.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e221,316\u003c/p\u003e \u003cp\u003e(26.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e18,204\u003c/p\u003e \u003cp\u003e(26.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e51\u0026ndash;75th percentile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e208,769\u003c/p\u003e \u003cp\u003e(23.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e138,061\u003c/p\u003e \u003cp\u003e(22.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8,616\u003c/p\u003e \u003cp\u003e(21.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e189,908\u003c/p\u003e \u003cp\u003e(23.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12,533\u003c/p\u003e \u003cp\u003e(23.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e200,295\u003c/p\u003e \u003cp\u003e(23.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e16,897\u003c/p\u003e \u003cp\u003e(24.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e76\u0026ndash;100th percentile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e158,917\u003c/p\u003e \u003cp\u003e(18.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e107,431\u003c/p\u003e \u003cp\u003e(17.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6,065\u003c/p\u003e \u003cp\u003e(15.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e151,897\u003c/p\u003e \u003cp\u003e(18.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8,081\u003c/p\u003e \u003cp\u003e(15.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e156,030\u003c/p\u003e \u003cp\u003e(18.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e13,046\u003c/p\u003e \u003cp\u003e(18.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInsurance\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedicare\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e655,760\u003c/p\u003e \u003cp\u003e(75.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e448,437\u003c/p\u003e \u003cp\u003e(73.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29,366\u003c/p\u003e \u003cp\u003e(74.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e586,889\u003c/p\u003e \u003cp\u003e(72.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e38,519\u003c/p\u003e \u003cp\u003e(71.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e610,004\u003c/p\u003e \u003cp\u003e(72.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e52,769\u003c/p\u003e \u003cp\u003e(75.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedicaid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81,344\u003c/p\u003e \u003cp\u003e(9.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61,739\u003c/p\u003e \u003cp\u003e(10.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,429\u003c/p\u003e \u003cp\u003e(8.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83,200\u003c/p\u003e \u003cp\u003e(10.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5,378\u003c/p\u003e \u003cp\u003e(10.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e87,296\u003c/p\u003e \u003cp\u003e(10.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6,546\u003c/p\u003e \u003cp\u003e(9.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99,220\u003c/p\u003e \u003cp\u003e(11.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74,654\u003c/p\u003e \u003cp\u003e(12.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,801\u003c/p\u003e \u003cp\u003e(12.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97,125\u003c/p\u003e \u003cp\u003e(12.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7,137\u003c/p\u003e \u003cp\u003e(13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e102,536\u003c/p\u003e \u003cp\u003e(12.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7,444\u003c/p\u003e \u003cp\u003e(10.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-pay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19,441\u003c/p\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14,138\u003c/p\u003e \u003cp\u003e(2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e589\u003c/p\u003e \u003cp\u003e(1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18,375\u003c/p\u003e \u003cp\u003e(2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e911\u003c/p\u003e \u003cp\u003e(1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18,100\u003c/p\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1,037\u003c/p\u003e \u003cp\u003e(1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo charge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,317\u003c/p\u003e \u003cp\u003e(0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e998\u003c/p\u003e \u003cp\u003e(0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003cp\u003e(0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,204\u003c/p\u003e \u003cp\u003e(0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e76\u003c/p\u003e \u003cp\u003e(0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1,091\u003c/p\u003e \u003cp\u003e(0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e82\u003c/p\u003e \u003cp\u003e(0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16,196\u003c/p\u003e \u003cp\u003e(1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13,967\u003c/p\u003e \u003cp\u003e(2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,041\u003c/p\u003e \u003cp\u003e(2.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19,704\u003c/p\u003e \u003cp\u003e(2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,592\u003c/p\u003e \u003cp\u003e(3.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e21,702\u003c/p\u003e \u003cp\u003e(2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1,757\u003c/p\u003e \u003cp\u003e(2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInjury Diagnosis Reported\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo injury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e808,624\u003c/p\u003e \u003cp\u003e(92.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e564,633\u003c/p\u003e \u003cp\u003e(92.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37,376\u003c/p\u003e \u003cp\u003e(95.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e743,385\u003c/p\u003e \u003cp\u003e(92.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50886\u003c/p\u003e \u003cp\u003e(94.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e774,469\u003c/p\u003e \u003cp\u003e(92.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e64,641\u003c/p\u003e \u003cp\u003e(92.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInjury in first listed diagnosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26,392\u003c/p\u003e \u003cp\u003e(3.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21,109\u003c/p\u003e \u003cp\u003e(3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e415\u003c/p\u003e \u003cp\u003e(1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27,106\u003c/p\u003e \u003cp\u003e(3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e627\u003c/p\u003e \u003cp\u003e(1.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e28,077\u003c/p\u003e \u003cp\u003e(3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1,457\u003c/p\u003e \u003cp\u003e(2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInjury not in first listed diagnosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38,262\u003c/p\u003e \u003cp\u003e(4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28191\u003c/p\u003e \u003cp\u003e(4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1485\u003c/p\u003e \u003cp\u003e(3.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36,006\u003c/p\u003e \u003cp\u003e(4.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2100\u003c/p\u003e \u003cp\u003e(3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e38,183\u003c/p\u003e \u003cp\u003e(4.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3,537\u003c/p\u003e \u003cp\u003e(5.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLength of Stay\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003cp\u003e(7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003cp\u003e(7.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003cp\u003e(10.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003cp\u003e(7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003cp\u003e(12.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003cp\u003e(8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003cp\u003e(12.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian [Min, Max]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.0 [0, 364]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.0 [0, 350]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.0 [0, 277]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.0 [0, 364]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.0 [0, 340]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.0 [0, 364]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6.0 [0, 356]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHospital Division\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNew England\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45,377\u003c/p\u003e \u003cp\u003e(5.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31,366\u003c/p\u003e \u003cp\u003e(5.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,854\u003c/p\u003e \u003cp\u003e(4.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42,397\u003c/p\u003e \u003cp\u003e(5.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2,185\u003c/p\u003e \u003cp\u003e(4.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e42,310\u003c/p\u003e \u003cp\u003e(5.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3,791\u003c/p\u003e \u003cp\u003e(5.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle Atlantic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e122,226\u003c/p\u003e \u003cp\u003e(14.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81,606\u003c/p\u003e \u003cp\u003e(13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,617\u003c/p\u003e \u003cp\u003e(14.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e110,695\u003c/p\u003e \u003cp\u003e(13.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7,656\u003c/p\u003e \u003cp\u003e(14.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e112,294\u003c/p\u003e \u003cp\u003e(13.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e10,745\u003c/p\u003e \u003cp\u003e(15.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEast North Central\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e158,463\u003c/p\u003e \u003cp\u003e(18.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e109,578\u003c/p\u003e \u003cp\u003e(17.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7,959\u003c/p\u003e \u003cp\u003e(20.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e143,636\u003c/p\u003e \u003cp\u003e(17.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9,359\u003c/p\u003e \u003cp\u003e(17.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e148,775\u003c/p\u003e \u003cp\u003e(17.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e11,962\u003c/p\u003e \u003cp\u003e(17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWest North Central\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55,904\u003c/p\u003e \u003cp\u003e(6.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39,453\u003c/p\u003e \u003cp\u003e(6.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,731\u003c/p\u003e \u003cp\u003e(7.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51,459\u003c/p\u003e \u003cp\u003e(6.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2,950\u003c/p\u003e \u003cp\u003e(5.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e53,032\u003c/p\u003e \u003cp\u003e(6.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3,874\u003c/p\u003e \u003cp\u003e(5.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth Atlantic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e184,029\u003c/p\u003e \u003cp\u003e(21.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e134,506\u003c/p\u003e \u003cp\u003e(21.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7,678\u003c/p\u003e \u003cp\u003e(19.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e176,461\u003c/p\u003e \u003cp\u003e(21.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12,704\u003c/p\u003e \u003cp\u003e(23.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e185,008\u003c/p\u003e \u003cp\u003e(22.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e15,260\u003c/p\u003e \u003cp\u003e(21.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEast South Central\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63,040\u003c/p\u003e \u003cp\u003e(7.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45,206\u003c/p\u003e \u003cp\u003e(7.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,773\u003c/p\u003e \u003cp\u003e(7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58,270\u003c/p\u003e \u003cp\u003e(7.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3,877\u003c/p\u003e \u003cp\u003e(7.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e60,741\u003c/p\u003e \u003cp\u003e(7.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4,568\u003c/p\u003e \u003cp\u003e(6.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWest South Central\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96,589\u003c/p\u003e \u003cp\u003e(11.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68,066\u003c/p\u003e \u003cp\u003e(11.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,888\u003c/p\u003e \u003cp\u003e(12.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e88,360\u003c/p\u003e \u003cp\u003e(11.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6,408\u003c/p\u003e \u003cp\u003e(12.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e96,260\u003c/p\u003e \u003cp\u003e(11.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7,188\u003c/p\u003e \u003cp\u003e(10.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMountain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39,409\u003c/p\u003e \u003cp\u003e(4.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28,501\u003c/p\u003e \u003cp\u003e(4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,975\u003c/p\u003e \u003cp\u003e(5.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35,523\u003c/p\u003e \u003cp\u003e(4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2,624\u003c/p\u003e \u003cp\u003e(4.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e38,485\u003c/p\u003e \u003cp\u003e(4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3,123\u003c/p\u003e \u003cp\u003e(4.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePacific\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e108,241\u003c/p\u003e \u003cp\u003e(12.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75,651\u003c/p\u003e \u003cp\u003e(12.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,801\u003c/p\u003e \u003cp\u003e(9.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e99,696\u003c/p\u003e \u003cp\u003e(12.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5,850\u003c/p\u003e \u003cp\u003e(10.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e103,824\u003c/p\u003e \u003cp\u003e(12.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9,124\u003c/p\u003e \u003cp\u003e(13.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eControl/ownership of hospital\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGovernment, nonfederal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86,562\u003c/p\u003e \u003cp\u003e(9.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62220\u003c/p\u003e \u003cp\u003e(10.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,082\u003c/p\u003e \u003cp\u003e(10.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e79,307\u003c/p\u003e \u003cp\u003e(9.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5,326\u003c/p\u003e \u003cp\u003e(9.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e81,703\u003c/p\u003e \u003cp\u003e(9.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6,642\u003c/p\u003e \u003cp\u003e(9.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate, not-profit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e678,915\u003c/p\u003e \u003cp\u003e(77.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e473,688\u003c/p\u003e \u003cp\u003e(77.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30,336\u003c/p\u003e \u003cp\u003e(77.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e631,091\u003c/p\u003e \u003cp\u003e(78.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41,955\u003c/p\u003e \u003cp\u003e(78.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e656,822\u003c/p\u003e \u003cp\u003e(78.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e55,557\u003c/p\u003e \u003cp\u003e(79.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate, invest-own\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e107,801\u003c/p\u003e \u003cp\u003e(12.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78,025\u003c/p\u003e \u003cp\u003e(12.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,858\u003c/p\u003e \u003cp\u003e(12.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96,099\u003c/p\u003e \u003cp\u003e(11.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6,332\u003c/p\u003e \u003cp\u003e(11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e102,204\u003c/p\u003e \u003cp\u003e(12.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7,436\u003c/p\u003e \u003cp\u003e(10.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHospital Bed Size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e184,076\u003c/p\u003e \u003cp\u003e(21.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e131,442\u003c/p\u003e \u003cp\u003e(21.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8926\u003c/p\u003e \u003cp\u003e(22.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e176,415\u003c/p\u003e \u003cp\u003e(21.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12,314\u003c/p\u003e \u003cp\u003e(23.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e187,775\u003c/p\u003e \u003cp\u003e(22.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e15,923\u003c/p\u003e \u003cp\u003e(22.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e253,889\u003c/p\u003e \u003cp\u003e(29.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e171,433\u003c/p\u003e \u003cp\u003e(27.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11,065\u003c/p\u003e \u003cp\u003e(28.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e224,681\u003c/p\u003e \u003cp\u003e(27.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15,556\u003c/p\u003e \u003cp\u003e(29.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e241,887\u003c/p\u003e \u003cp\u003e(28.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e20,677\u003c/p\u003e \u003cp\u003e(29.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLarge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e435,313\u003c/p\u003e \u003cp\u003e(49.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e311,058\u003c/p\u003e \u003cp\u003e(50.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19,285\u003c/p\u003e \u003cp\u003e(49.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e405,401\u003c/p\u003e \u003cp\u003e(50.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25,743\u003c/p\u003e \u003cp\u003e(48.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e411,067\u003c/p\u003e \u003cp\u003e(48.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e33,035\u003c/p\u003e \u003cp\u003e(47.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHospital Teaching \u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eStatus\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eStatus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74,810\u003c/p\u003e \u003cp\u003e(8.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52,671\u003c/p\u003e \u003cp\u003e(8.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,491\u003c/p\u003e \u003cp\u003e(8.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e66,364\u003c/p\u003e \u003cp\u003e(8.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5,351\u003c/p\u003e \u003cp\u003e(10.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e71,675\u003c/p\u003e \u003cp\u003e(8.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6,267\u003c/p\u003e \u003cp\u003e(9.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban nonteaching\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e154,544\u003c/p\u003e \u003cp\u003e(17.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105,922\u003c/p\u003e \u003cp\u003e(17.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6,678\u003c/p\u003e \u003cp\u003e(17.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e137,301\u003c/p\u003e \u003cp\u003e(17.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9,820\u003c/p\u003e \u003cp\u003e(18.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e134,742\u003c/p\u003e \u003cp\u003e(16.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e11,482\u003c/p\u003e \u003cp\u003e(16.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban teaching\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e643,924\u003c/p\u003e \u003cp\u003e(73.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e455,340\u003c/p\u003e \u003cp\u003e(74.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29,107\u003c/p\u003e \u003cp\u003e(74.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e602,832\u003c/p\u003e \u003cp\u003e(74.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e38,442\u003c/p\u003e \u003cp\u003e(71.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e634,312\u003c/p\u003e \u003cp\u003e(75.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e51,886\u003c/p\u003e \u003cp\u003e(74.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]: Median household income quartiles are defined separately for each year based on year-specific ZIP code\u0026ndash;level income distributions.\u003c/p\u003e \u003cp\u003eBeyond patient characteristics, several comorbidity conditions were included as covariates in the model. variables with \u0026lt;\u0026thinsp;3% occurrence were excluded. As presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, most comorbidities showed significant differences in distribution between the COVID-19 and non-COVID groups. Patients without COVID-19 had a higher prevalence (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) of cardiovascular comorbidities, including coronary artery disease, atrial fibrillation, history of coronary artery bypass grafting (CABG), and previous myocardial infarction (MI). They also exhibited a greater incidence (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) of adverse health behaviors such as alcohol abuse, drug abuse, and smoking.\u003c/p\u003e \u003cp\u003eIn contrast, patients with COVID-19 were more likely (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) to have comorbid conditions such as diabetes with complications, hypertension with complications, and dementia.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient Comorbidity Conditions\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003cp\u003eCHF Without COVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003cp\u003eCHF With COVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003cp\u003eCHF Without COVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003cp\u003eCHF With COVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003cp\u003eCHF Without COVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003cp\u003eCHF With COVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;873, 278\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;653,209\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;860,110\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;910,364\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;613,933\u003c/p\u003e \u003cp\u003e(94.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;39,276\u003c/p\u003e \u003cp\u003e(6.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;806,497\u003c/p\u003e \u003cp\u003e(93.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;53,613\u003c/p\u003e \u003cp\u003e(6.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003en\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;840,729\u003c/p\u003e \u003cp\u003e(92.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003en\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;69,635\u003c/p\u003e \u003cp\u003e(7.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHypertension Followed Up with Complications\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e575,427\u003c/p\u003e \u003cp\u003e(65.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e410,498\u003c/p\u003e \u003cp\u003e(66.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33,671\u003c/p\u003e \u003cp\u003e(85.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e533,766\u003c/p\u003e \u003cp\u003e(66.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e44,761\u003c/p\u003e \u003cp\u003e(83.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e564,236\u003c/p\u003e \u003cp\u003e(67.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e56,125\u003c/p\u003e \u003cp\u003e(80.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAtrial Fibrillation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e404,051\u003c/p\u003e \u003cp\u003e(46.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e282,620\u003c/p\u003e \u003cp\u003e(46.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16,965\u003c/p\u003e \u003cp\u003e(43.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e375,336\u003c/p\u003e \u003cp\u003e(46.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22,883\u003c/p\u003e \u003cp\u003e(42.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e391,709\u003c/p\u003e \u003cp\u003e(46.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e31,836\u003c/p\u003e \u003cp\u003e(45.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePulmonary Circulation Disorder\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e155,234\u003c/p\u003e \u003cp\u003e(17.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e109,525\u003c/p\u003e \u003cp\u003e(17.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,223\u003c/p\u003e \u003cp\u003e(13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e147,087\u003c/p\u003e \u003cp\u003e(18.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8,026\u003c/p\u003e \u003cp\u003e(15.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e152,823\u003c/p\u003e \u003cp\u003e(18.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e11,243\u003c/p\u003e \u003cp\u003e(16.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHistory of CABG\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105,531\u003c/p\u003e \u003cp\u003e(12.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65,657\u003c/p\u003e \u003cp\u003e(10.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,830\u003c/p\u003e \u003cp\u003e(9.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e81,281\u003c/p\u003e \u003cp\u003e(10.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4,725\u003c/p\u003e \u003cp\u003e(8.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e76,039\u003c/p\u003e \u003cp\u003e(9.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5,892\u003c/p\u003e \u003cp\u003e(8.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrevious MI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e132,021\u003c/p\u003e \u003cp\u003e(15.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89,985\u003c/p\u003e \u003cp\u003e(14.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,604\u003c/p\u003e \u003cp\u003e(11.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e113,956\u003c/p\u003e \u003cp\u003e(14.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6,437\u003c/p\u003e \u003cp\u003e(12.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e110,739\u003c/p\u003e \u003cp\u003e(13.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8,253\u003c/p\u003e \u003cp\u003e(11.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePeripheral Vascular Disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e102,975\u003c/p\u003e \u003cp\u003e(11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71,508\u003c/p\u003e \u003cp\u003e(11.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,156\u003c/p\u003e \u003cp\u003e(8.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e94,954\u003c/p\u003e \u003cp\u003e(11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4,397\u003c/p\u003e \u003cp\u003e(8.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e99,071\u003c/p\u003e \u003cp\u003e(11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7,242\u003c/p\u003e \u003cp\u003e(10.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePneumonia, Except COVID-19 Related\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e143,237\u003c/p\u003e \u003cp\u003e(16.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94,424\u003c/p\u003e \u003cp\u003e(15.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,206\u003c/p\u003e \u003cp\u003e(3.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e112,211\u003c/p\u003e \u003cp\u003e(13.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,203\u003c/p\u003e \u003cp\u003e(2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e130,427\u003c/p\u003e \u003cp\u003e(15.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3,244\u003c/p\u003e \u003cp\u003e(4.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCoronary Artery Disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e457,269\u003c/p\u003e \u003cp\u003e(52.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e317,805\u003c/p\u003e \u003cp\u003e(51.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18,010\u003c/p\u003e \u003cp\u003e(45.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e412,152\u003c/p\u003e \u003cp\u003e(51.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23,864\u003c/p\u003e \u003cp\u003e(44.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e422,480\u003c/p\u003e \u003cp\u003e(50.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e32,533\u003c/p\u003e \u003cp\u003e(46.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChronic Lung Diseases\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e331,830\u003c/p\u003e \u003cp\u003e(38.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e224,298\u003c/p\u003e \u003cp\u003e(36.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14,173\u003c/p\u003e \u003cp\u003e(36.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e286,691\u003c/p\u003e \u003cp\u003e(35.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19,454\u003c/p\u003e \u003cp\u003e(36.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e298,789\u003c/p\u003e \u003cp\u003e(35.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e26,204\u003c/p\u003e \u003cp\u003e(37.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAsthma\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e251,226\u003c/p\u003e \u003cp\u003e(28.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e167,945\u003c/p\u003e \u003cp\u003e(27.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10,201\u003c/p\u003e \u003cp\u003e(26.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e213,717\u003c/p\u003e \u003cp\u003e(26.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13,370\u003c/p\u003e \u003cp\u003e(24.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e214,507\u003c/p\u003e \u003cp\u003e(25.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e16,914\u003c/p\u003e \u003cp\u003e(24.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eObstructive Sleep Apnea\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e141,680\u003c/p\u003e \u003cp\u003e(16.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96,572\u003c/p\u003e \u003cp\u003e(15.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,811\u003c/p\u003e \u003cp\u003e(14.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e129,297\u003c/p\u003e \u003cp\u003e(16.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8,141\u003c/p\u003e \u003cp\u003e(15.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e132,661\u003c/p\u003e \u003cp\u003e(15.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9,582\u003c/p\u003e \u003cp\u003e(13.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChronic Kidney Disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e414,946\u003c/p\u003e \u003cp\u003e(47.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e292,036\u003c/p\u003e \u003cp\u003e(47.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19,102\u003c/p\u003e \u003cp\u003e(48.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e376,632\u003c/p\u003e \u003cp\u003e(46.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24,222\u003c/p\u003e \u003cp\u003e(45.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e389,314\u003c/p\u003e \u003cp\u003e(46.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e33,309\u003c/p\u003e \u003cp\u003e(47.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes Followed Up with Complications\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e327,723\u003c/p\u003e \u003cp\u003e(37.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e238,203\u003c/p\u003e \u003cp\u003e(38.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17,331\u003c/p\u003e \u003cp\u003e(44.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e310,647\u003c/p\u003e \u003cp\u003e(38.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22,483\u003c/p\u003e \u003cp\u003e(41.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e321,798\u003c/p\u003e \u003cp\u003e(38.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e27,874\u003c/p\u003e \u003cp\u003e(40.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes With No Complications\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87,179\u003c/p\u003e \u003cp\u003e(10.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58,201\u003c/p\u003e \u003cp\u003e(9.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,815\u003c/p\u003e \u003cp\u003e(9.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e75,390\u003c/p\u003e \u003cp\u003e(9.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5,058\u003c/p\u003e \u003cp\u003e(9.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.511\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e79,326\u003c/p\u003e \u003cp\u003e(9.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5,911\u003c/p\u003e \u003cp\u003e(8.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eObesity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e222,256\u003c/p\u003e \u003cp\u003e(25.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e168,146\u003c/p\u003e \u003cp\u003e(27.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11,386\u003c/p\u003e \u003cp\u003e(29.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e225,215\u003c/p\u003e \u003cp\u003e(27.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16,657\u003c/p\u003e \u003cp\u003e(31.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e234,733\u003c/p\u003e \u003cp\u003e(27.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e17,960\u003c/p\u003e \u003cp\u003e(25.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHypothyroidism\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e164,103\u003c/p\u003e \u003cp\u003e(18.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e114,631\u003c/p\u003e \u003cp\u003e(18.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7,008\u003c/p\u003e \u003cp\u003e(17.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e149,640\u003c/p\u003e \u003cp\u003e(18.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9,044\u003c/p\u003e \u003cp\u003e(16.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e157,979\u003c/p\u003e \u003cp\u003e(18.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e13,014\u003c/p\u003e \u003cp\u003e(18.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.512\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAutoimmune Conditions\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26,618\u003c/p\u003e \u003cp\u003e(4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,546\u003c/p\u003e \u003cp\u003e(3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35,098\u003c/p\u003e \u003cp\u003e(4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2,367\u003c/p\u003e \u003cp\u003e(4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e36,503\u003c/p\u003e \u003cp\u003e(4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3,303\u003c/p\u003e \u003cp\u003e(4.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDementia\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84,467\u003c/p\u003e \u003cp\u003e(9.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57,723\u003c/p\u003e \u003cp\u003e(9.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6,300\u003c/p\u003e \u003cp\u003e(16.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e72,729\u003c/p\u003e \u003cp\u003e(9.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5,697\u003c/p\u003e \u003cp\u003e(10.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e74,059\u003c/p\u003e \u003cp\u003e(8.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8,520\u003c/p\u003e \u003cp\u003e(12.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDepression\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e118,315\u003c/p\u003e \u003cp\u003e(13.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85,137\u003c/p\u003e \u003cp\u003e(13.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,106\u003c/p\u003e \u003cp\u003e(13.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e111,471\u003c/p\u003e \u003cp\u003e(13.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6,415\u003c/p\u003e \u003cp\u003e(12.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e112,360\u003c/p\u003e \u003cp\u003e(13.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8,659\u003c/p\u003e \u003cp\u003e(12.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e361,918\u003c/p\u003e \u003cp\u003e(41.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e251,072\u003c/p\u003e \u003cp\u003e(40.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12,413\u003c/p\u003e \u003cp\u003e(31.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e322,802\u003c/p\u003e \u003cp\u003e(40.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17,750\u003c/p\u003e \u003cp\u003e(33.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e327,857\u003c/p\u003e \u003cp\u003e(39.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e24,266\u003c/p\u003e \u003cp\u003e(34.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlcohol Abuse\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32,193\u003c/p\u003e \u003cp\u003e(3.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26,161\u003c/p\u003e \u003cp\u003e(4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e830\u003c/p\u003e \u003cp\u003e(2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34,139\u003c/p\u003e \u003cp\u003e(4.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,318\u003c/p\u003e \u003cp\u003e(2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e34,769\u003c/p\u003e \u003cp\u003e(4.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2,047\u003c/p\u003e \u003cp\u003e(2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDrug Abuse\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32,006\u003c/p\u003e \u003cp\u003e(3.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25,602\u003c/p\u003e \u003cp\u003e(4.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e905\u003c/p\u003e \u003cp\u003e(2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34,683\u003c/p\u003e \u003cp\u003e(4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,684\u003c/p\u003e \u003cp\u003e(3.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e36,436\u003c/p\u003e \u003cp\u003e(4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2,374\u003c/p\u003e \u003cp\u003e(3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2. In-Hospital Mortality and Complications\u003c/h2\u003e \u003cp\u003eCHF patients with a concurrent diagnosis of COVID-19 had significantly higher in-hospital mortality compared to those without COVID-19 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In January and February 2020, prior to the pandemic, the overall in-hospital mortality rate among CHF patients was 4.6% (7,513 of 159,203), similar to the 2019 rate of 4.4%. However, from March 2020 onward, the mortality rate among CHF patients with COVID-19 increased sharply: reaching 22.0% in 2020, 20.6% in 2021, and then decreasing to 11.1% in 2022. In contrast, the mortality rate among CHF patients without COVID-19 remained relatively stable at approximately 5.0% across all three years. These trends indicate that while COVID-19 substantially increased mortality risk in CHF patients early in the pandemic, its impact declined by 2022.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIn-Hospital Mortality for CHF Patients by COVID-19 Diagnosis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMortality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e2020 (Mar to Dec)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWithout COVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWith COVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWithout COVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eWith\u003c/p\u003e \u003cp\u003eCOVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eWithout COVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eWith COVID-19\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003cp\u003e(sample size)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e873,278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e613,933\u003c/p\u003e \u003cp\u003e(94.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39,276\u003c/p\u003e \u003cp\u003e(6.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e806,497\u003c/p\u003e \u003cp\u003e(93.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e53,613\u003c/p\u003e \u003cp\u003e(6.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e840,729\u003c/p\u003e \u003cp\u003e(92.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e69,635\u003c/p\u003e \u003cp\u003e(7.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDid not die\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e834,931 (95.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e583,924 (95.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30,623 (78.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e766,421\u003c/p\u003e \u003cp\u003e(95.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e42,560 (79.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e798,558 (95.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e61,900 (88.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38,347 (4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30,009 (4.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8,653 (22.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e40,076\u003c/p\u003e \u003cp\u003e(5.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e11,053 (20.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e42,171 (5.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e7,735 (11.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, after adjustment for potential confounders, CHF patients with a concurrent COVID-19 diagnosis exhibited higher rates of adverse in-hospital outcomes, including mortality, compared with those without COVID-19. Unlike the pattern observed for in-hospital mortality (aOR: 6.124 in 2020; 5.712 in 2021; 2.529 in 2022; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), other adverse outcomes exhibited a modest increase in 2021, followed by a decline in 2022. Specifically, the aORs for pulmonary embolism were 2.216 in 2020, 2.743 in 2021, and 1.897 in 2022; for acute kidney injury, 1.397, 1.450, and 1.236; and for mechanical ventilation, 2.571, 2.725, and 1.735, respectively. Cardiogenic shock showed varying effects across years, but the aORs consistently remained close to 1. Additionally, across 2020\u0026ndash;2022, COVID-19 infection was associated with higher total hospital charges, with adjusted increases of USD 34,671 (2020), 44,831 (2021), and 24,827 (2022) compared to patients without COVID-19. The mean total hospital charges for CHF patients with COVID-19 were consistently higher than those for patients without COVID-19 across all three years. Specifically, the mean total charges for COVID-19 versus non\u0026ndash;COVID-19 patients were USD 114,929 vs 88,643 in 2020, USD 128,288 vs 92,141 in 2021, and USD 114,019 vs 97,854 in 2022.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of COVID-19 vs non-COVID-19 Groups in Mortality and Complications among CHF Patients.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcomes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSample Size\u003csup\u003e[2]\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjusted OR\u003c/p\u003e \u003cp\u003eor Regression Coefficient\u003csup\u003e[1]\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2020 (Mar to Dec)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;622,426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMortality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e36,596 (5.9%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.091\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e6.124 (5.946, 6.307)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSudden Cardiac Arrest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17,167 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.836 (1.739, 1.938)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute Kidney Injury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e231,230 (37.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.397 (1.366, 1.429)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulmonary Embolism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10,234 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.216 (2.048, 2.397)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiogenic Shock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18,380 (3.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.879 (0.817, 0.946)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVasopressor Use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15,129 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.102 (1.988, 2.223)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanical Ventilation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86,519 (13.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.571 (2.504, 2.640)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanical Circulatory Support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,605 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.482 (0.405, 0.575)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Hospitalization Charge (USD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e114,929 (194,612)\u003c/p\u003e \u003cp\u003e60,019 [31,464, 123,490]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34671.3\u003c/p\u003e \u003cp\u003e(33103.0, 36239.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2021\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;818,248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMortality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e48,064 (5.9%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.089\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e5.712 (5.567, 5.860)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSudden Cardiac Arrest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24,514 (3.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.774 (1.695, 1.856)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute Kidney Injury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e301,334 (36.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.450 (1.422, 1.478)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulmonary Embolism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14,805 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.743 (2.584, 2.911)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiogenic Shock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24,542 (3.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.058 (0.999, 1.120)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVasopressor Use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20,583 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.127 (2.030, 2.229)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanical Ventilation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113,769 (13.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.725 (2.666, 2.786)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanical Circulatory Support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,444 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.617 (0.541, 0.704)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Hospitalization Charge (USD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e128,288 (220,925)\u003c/p\u003e \u003cp\u003e66,556 [35,301, 137,779]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44830.6\u003c/p\u003e \u003cp\u003e(43425.9, 46235.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2022\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;866,595\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMortality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e47,021 (5.4%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.064\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.529 (2.461, 2.600)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSudden Cardiac Arrest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24,307 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.330 (1.271, 1.393)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute Kidney Injury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e315,295 (36.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.236 (1.216, 1.258)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulmonary Embolism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14,909 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.891 (1.786, 2.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiogenic Shock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27,191 (3.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.091 (1.040, 1.145)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVasopressor Use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24,231 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.577 (1.511, 1.646)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanical Ventilation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e120,032 (13.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.735 (1.698, 1.773)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanical Circulatory Support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,828 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.750 (0.675, 0.834)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Hospitalization Charge (USD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e114,019 (194,612)\u003c/p\u003e \u003cp\u003e61,584 [33,799, 120,363]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24826.6\u003c/p\u003e \u003cp\u003e(23530.9, 26122.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] Adjusted for age, sex, race, insurance, and whether it is an elective admission, income, injury diagnosis reported, Elixhauser co-morbidities, hospital division, ownership, teaching status, and bed size.\u003c/p\u003e \u003cp\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] The total sample size (N) is smaller due to the exclusion of patients whose insurance status was classified as \u003cem\u003eSelf-pay\u003c/em\u003e or \u003cem\u003eOther\u003c/em\u003e. For binary outcomes, the value represents the number of patients who experienced the outcome, whereas for the continuous outcome total charge, the numbers are reported as mean (SD) and median [IQR] for patients who had COVID-19.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Time-to-Event Analysis\u003c/h2\u003e \u003cp\u003eCox proportional hazards regression models were applied to analyze time to in-hospital death for each year. In 2019, the analysis included 826,933 patients. In 2020 (March to December), the analysis included 37,257 CHF patients with COVID-19 (6.1% of the cohort) and 577,684 without COVID-19 (93.9%). The adjusted hazard ratio (aHR) associated with COVID-19 was 2.912 (95% CI: 2.835\u0026ndash;2.992). In 2021, 50,587 patients (6.3%) had COVID-19 and 757,582 (93.7%) did not; the aHR slightly declined to 2.606 (95% CI: 2.545\u0026ndash;2.668). In 2022, 66,155 patients (7.7%) were in the COVID-19 group and 788,865 (92.3%) were in the non-COVID group, and the aHR further decreased to 1.558 (95% CI: 1.518\u0026ndash;1.599). The descriptive statistics of the length of stay are presented in Supporting Information S3. Regression results for other covariates are presented in Supporting Information S5. These findings indicate a progressive reduction in the hazard of in-hospital death among COVID-19 patients compared with non-COVID-19 patients over time, paralleling the trends observed in the multivariable logistic regression, where survival differences between COVID and non-COVID groups narrowed substantially by 2022.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTime to In-hospital Death Analysis Result for COVID-19 and Non-COVID-related Pneumonia Variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"16\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;826,933)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e2020 (Mar - Dec)\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;614,941)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;808,169)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c16\" namest=\"c14\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;855,020)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eaHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eaHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eaHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eaHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOVID-19 (Yes vs. No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(2.835, 2.992)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e(2.545, 2.668)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e1.558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e(1.518, 1.599)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-COVID-related Pneumonia\u003c/p\u003e \u003cp\u003e(Yes vs. No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.505\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(1.471, 1.541)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e(1.517, 1.596)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e(1.532, 1.603)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e1.550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e(1.517, 1.583)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] Adjusted for age, sex, race, insurance, and whether it is an elective admission, income, injury diagnosis reported, Elixhauser co-morbidities, hospital division, teaching status, and bed size (see Supporting Information S5).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Comparison with Non-COVID Pneumonia\u003c/h2\u003e \u003cp\u003eTo contextualize the COVID-19 findings, we evaluated non-COVID pneumonia among CHF patients, excluding records coded with COVID-19. In 2019\u0026ndash;2022, the proportion of CHF admissions with non-COVID pneumonia was 16.4% (2019), 20.1% (2020 January and February), 14.6% (2020 March to December), 13.2% (2021), and 14.7% (2022), respectively. The high non-COVID pneumonia rate in the two winter months (January and February in 2020) is as expected.\u003c/p\u003e \u003cp\u003eMoreover, compared to the effect of COVID-19, the mortality rate among CHF patients with pneumonia remained around 10.5% throughout the three years without significant fluctuation. Note that the mortality rate for patients with non-COVID pneumonia in 2022 was similar to that of patients with COVID-19 (10.5% vs. 11.1%). This further supports the observation that the effect of COVID-19 on CHF mortality lessened in 2022 and approached the level seen with other respiratory infections.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIn-Hospital Mortality for CHF Patients by non-COVID Pneumonia Diagnosis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"15\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eActual Mortality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e2020 (Jan to Feb)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e2020 (Mar to Dec)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWithout Pneumonia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWith Pneumonia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWithout Pneumonia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWith Pneumonia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eWithout Pneumonia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWith Pneumonia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eWithout Pneumonia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eWith\u003c/p\u003e \u003cp\u003ePneumonia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eWithout Pneumonia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003eWith Pneumonia\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003cp\u003e(sample size)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e730,041\u003c/p\u003e \u003cp\u003e(83.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e143,237\u003c/p\u003e \u003cp\u003e(16.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e127,174\u003c/p\u003e \u003cp\u003e(79.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32,029\u003c/p\u003e \u003cp\u003e(20.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e557,579\u003c/p\u003e \u003cp\u003e(85.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e95,630\u003c/p\u003e \u003cp\u003e(14.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e746,696\u003c/p\u003e \u003cp\u003e(86.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e113,414\u003c/p\u003e \u003cp\u003e(13.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e783,546\u003c/p\u003e \u003cp\u003e(85.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e134,887\u003c/p\u003e \u003cp\u003e(14.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDid not die\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e703,834\u003c/p\u003e \u003cp\u003e(96.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e131,097\u003c/p\u003e \u003cp\u003e(91.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e122,394\u003c/p\u003e \u003cp\u003e(96.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29,456\u003c/p\u003e \u003cp\u003e(92.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e528,814\u003c/p\u003e \u003cp\u003e(94.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e85,733\u003c/p\u003e \u003cp\u003e(89.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e707,919\u003c/p\u003e \u003cp\u003e(94.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e101,062\u003c/p\u003e \u003cp\u003e(89.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e747,324\u003c/p\u003e \u003cp\u003e(95.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e120,761\u003c/p\u003e \u003cp\u003e(89.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26,207\u003c/p\u003e \u003cp\u003e(3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12,140\u003c/p\u003e \u003cp\u003e(8.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4,780\u003c/p\u003e \u003cp\u003e(3.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,573\u003c/p\u003e \u003cp\u003e(8.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28,765\u003c/p\u003e \u003cp\u003e(5.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9,897\u003c/p\u003e \u003cp\u003e(10.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e38,777\u003c/p\u003e \u003cp\u003e(5.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e12,352\u003c/p\u003e \u003cp\u003e(10.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e36,222\u003c/p\u003e \u003cp\u003e(4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e14,126\u003c/p\u003e \u003cp\u003e(10.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eUsing multivariable logistic regression and Cox proportional hazards models, the association between non-COVID pneumonia and mortality among CHF patients remained remarkably stable from 2019 to 2022. The aOR were 2.407 (95% CI: 2.351\u0026ndash;2.465) in 2019, 2.559 (95% CI: 2.492\u0026ndash;2.627) in 2020, 2.628 (95% CI: 2.567\u0026ndash;2.691) in 2021, and 2.502 (95% CI: 2.447\u0026ndash;2.558) in 2022 (Supporting Information S2). Other adverse outcomes for patients with non-COVID pneumonia also remained stable across the four years; for example, in contrast to the temporal variation observed among COVID-19 patients (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), the aOR for cardiogenic shock in non-COVID pneumonia patients was consistently around 1.7\u0026ndash;1.9. Consistent results were observed in the Cox model analysis: the aHR for the association of non-COVID pneumonia with mortality among CHF patients were 1.505 (95% CI: 1.471\u0026ndash;1.541), 1.556 (95% CI: 1.517\u0026ndash;1.596), 1.567 (95% CI: 1.532\u0026ndash;1.603), and 1.550 (95% CI: 1.517\u0026ndash;1.583), respectively, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. This stability is consistent with a COVID-specific temporal change in mortality risk among CHF patients, rather than a uniform improvement across all respiratory infections. Nevertheless, this comparison is intended to be supportive rather than definitive, given that pathogen mix, coding practices, and care pathways may have evolved differently for pneumonia and COVID-19.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Subgroup Analysis of HFrEF and HFpEF patients\u003c/h2\u003e \u003cp\u003eSince CHF comprises two main subtypes, HFrEF and HFpEF, we further examined the impact of COVID-19 on these two subgroups separately.\u003c/p\u003e \u003cp\u003eHFrEF patients had a higher mortality rate compared with HFpEF patients among both the COVID-19 and non-COVID-19 groups across all three years (COVID-19 group: 22.6% vs 21.5% in 2020, 21.0% vs 20.3% in 2021, 12.1% vs 10.2% in 2022; non-COVID-19 group: 5.6% vs 4.2% in 2020, 5.6% vs 4.3% in 2021, 5.6% vs 4.4% in 2022). Among patients with COVID-19, both HFrEF and HFpEF subgroups experienced a significant decline in mortality in 2022 (around 10\u0026ndash;11%) compared to the previous two years (over 20%), consistent with the trend observed in the overall cohort. In the non-COVID-19 group, mortality rates for both HFrEF and HFpEF are slightly higher than in 2019.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIn-Hospital Mortality for HFrEF or HFpEF Patients by COVID-19 Diagnosis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eHFrEF Patients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMortality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e2020 (Mar to Dec)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWithout COVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWith COVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWithout COVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eWith\u003c/p\u003e \u003cp\u003eCOVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eWithout COVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eWith COVID-19\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003cp\u003e(sample size)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e435,822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e309,371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18,250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e403,141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25,627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e421,001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e34,247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDid not die\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e413,881\u003c/p\u003e \u003cp\u003e(95.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e292,188\u003c/p\u003e \u003cp\u003e(94.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14,120\u003c/p\u003e \u003cp\u003e(77.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e380,540\u003c/p\u003e \u003cp\u003e(94.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20,242\u003c/p\u003e \u003cp\u003e(79.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e397,333\u003c/p\u003e \u003cp\u003e(94.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e30,114\u003c/p\u003e \u003cp\u003e(87.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21,941\u003c/p\u003e \u003cp\u003e(5.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17,183\u003c/p\u003e \u003cp\u003e(5.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4,130\u003c/p\u003e \u003cp\u003e(22.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22,601\u003c/p\u003e \u003cp\u003e(5.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5,385\u003c/p\u003e \u003cp\u003e(21.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e23,668\u003c/p\u003e \u003cp\u003e(5.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4,133\u003c/p\u003e \u003cp\u003e(12.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003eHFpEF Patients\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMortality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2019\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2020 (Mar to Dec)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003e2021\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e\u003cb\u003e2022\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eWithout COVID-19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eWith COVID-19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eWithout COVID-19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eWith\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eCOVID-19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eP-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eWithout COVID-19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003eWith COVID-19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003cp\u003e(sample size)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e437,456\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e304,562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21,026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e403,356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27,986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e419,728\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e35388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDid not die\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e421,050\u003c/p\u003e \u003cp\u003e(96.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e291,736\u003c/p\u003e \u003cp\u003e(95.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16,503\u003c/p\u003e \u003cp\u003e(78.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e385,881\u003c/p\u003e \u003cp\u003e(95.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22,318\u003c/p\u003e \u003cp\u003e(79.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e401,225\u003c/p\u003e \u003cp\u003e(95.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e31,786\u003c/p\u003e \u003cp\u003e(89.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16,406\u003c/p\u003e \u003cp\u003e(3.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12,826\u003c/p\u003e \u003cp\u003e(4.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4,523\u003c/p\u003e \u003cp\u003e(21.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17,475\u003c/p\u003e \u003cp\u003e(4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5,668\u003c/p\u003e \u003cp\u003e(20.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e18,503\u003c/p\u003e \u003cp\u003e(4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3,602\u003c/p\u003e \u003cp\u003e(10.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFurther analysis of in-hospital outcomes showed that HFpEF patients had higher aORs for multiple adverse events, including mortality, compared to both HFrEF patients and the overall CHF population across all three years. For instance, the aORs of COVID-19 on mortality in HFpEF patients were 7.207 (95% CI: 6.912\u0026ndash;7.515) in 2020, 6.756 (95% CI: 6.514\u0026ndash;7.007) in 2021, and 2.685 (95% CI: 2.579\u0026ndash;2.795) in 2022, while they were 5.324 (95% CI: 5.106\u0026ndash;5.553) in 2020, 4.906 (95% CI: 4.731\u0026ndash;5.087) in 2021, and 2.390 (95% CI: 2.302\u0026ndash;2.482) in 2022 for HFrEF patients. A complete set of results is provided in Supporting Information S6.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Result Summary\u003c/h2\u003e \u003cp\u003eCHF patients with concurrent COVID-19 infection had significantly higher odds of in-hospital mortality and other major adverse outcomes compared to those without COVID-19. COVID-19-positive CHF patients experienced shorter in-hospital survival times. The difference in outcomes between COVID-19-positive and COVID-19-negative patients progressively narrowed over the three years, as reflected by decreasing gaps in both odds ratios and hazard ratios. Among patients infected with COVID-19, those with HFpEF had a higher adjusted odds of mortality and complications compared to those with HFrEF.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003ePossible mechanism for higher mortality in patients with respiratory infections\u003c/span\u003e \u003c/p\u003e \u003cp\u003eOur findings are consistent with prior studies. A nationwide analysis using the NIS data reported that, in 2020, CHF patients with COVID-19 had markedly higher in-hospital mortality, longer hospital stays, and increased complications compared to those without COVID-19 [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Similarly, a meta-analysis demonstrated that pre-existing heart failure is associated with a significantly higher risk of hospitalization and death from COVID-19 [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Several mechanisms may explain the increased vulnerability of CHF patients to COVID-19. Impaired cardiac reserve in heart failure limits the ability to tolerate the hemodynamic stress and hypoxia caused by systemic infection. SARS-CoV-2 infection also induces substantial release of pro-inflammatory cytokines, including IL-1 and IL-6, which may directly or indirectly damage the myocardium [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Moreover, the widespread inflammatory response and cytokine activation seen in severe COVID-19 may further destabilize cardiac function in patients with pre-existing heart failure. These overlapping processes offer a coherent explanation for the elevated mortality and complication rates identified in this population [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Additionally, although many patients with chronic heart failure receive long-term angiotensin-converting enzyme inhibitors (ACEI) and angiotensin receptor blockers (ARB), such treatment has been associated with reduced COVID-19 mortality in observational studies [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Their protective effect may not fully counterbalance the heightened inflammatory burden in this high-risk group.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eOther variables associated with mortality and in-hospital adverse outcomes\u003c/span\u003e \u003c/p\u003e \u003cp\u003eIn addition to COVID-19 infection, we identified several independent variables associated with in-hospital mortality among patients hospitalized with CHF. Increasing age and non-elective admission were both strongly associated with higher odds of mortality, consistent with previous studies highlighting age and acute presentation as critical risk factors for poor outcomes. Several comorbidity-related variables, including pulmonary circulation disease and uncomplicated hypertension, were also independently associated with increased mortality risk.\u003c/p\u003e \u003cp\u003eSeveral co-existing conditions, including smoking, sleep apnea, depression, diabetes, and previous myocardial infarction, traditionally associated with adverse outcomes, were paradoxically linked to lower in-hospital mortality among patients with CHF. These counterintuitive findings are unlikely to represent true protective effects and may instead reflect residual confounding, such as incomplete adjustment for disease severity, misclassification of diagnoses, or unmeasured clinical and socioeconomic factors. For instance, patients with well-managed chronic conditions might have more frequent healthcare interactions, leading to earlier diagnosis, better outpatient management, and potentially improved resilience during hospitalization. In the case of previous myocardial infarction, the lower observed mortality may also partly reflect higher use of ACEI/ARB, which has been associated with reduced mortality risk [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Alternatively, some of these conditions may be undercoded or selectively recorded among sicker patients, potentially skewing the observed associations.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eHFpEF vs HFrEF\u003c/span\u003e \u003c/p\u003e \u003cp\u003eOur study observed that COVID-19 infection was associated with a higher adjusted odds ratio for in-hospital mortality in patients with HFpEF compared to those with HFrEF. This observation contrasts with previous expectations and observations that patients with HFrEF, given their significantly reduced cardiac function and poorer baseline health, experience higher mortality when infected with COVID-19 [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, some recent studies have reported findings similar to ours [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Patients with HFpEF typically are older and often have multiple metabolic and inflammatory comorbidities such as hypertension, diabetes, and obesity, potentially placing them at greater risk for severe complications from COVID-19 [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Furthermore, viral-induced myocardial injury and systemic inflammation can lead to a HFpEF-like syndrome or exacerbate existing HFpEF conditions [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Additionally, one study noted that during COVID-19 hospitalization, patients with HFpEF experienced longer delays in diagnosis compared to those with HFrEF [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These studies highlight the critical need for improved risk assessment and more timely, personalized treatment strategies for HFpEF patients during outbreaks such as COVID-19.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eLimitations\u003c/span\u003e \u003c/p\u003e \u003cp\u003eSeveral limitations should be considered when interpreting our findings. First, this analysis relied on administrative data and ICD-10 codes from the NIS database, which may introduce misclassification. Clinical variables such as laboratory results and echocardiographic measurements were unavailable. Second, because the NIS captures discharge-level data rather than patient-level trajectories, we could not distinguish between initial and recurrent hospitalizations or assess post-discharge outcomes. In other words, the database does not permit ascertainment of whether a given hospitalization represented an index admission or a subsequent readmission. Third, although we adjusted for multiple confounders, unmeasured factors such as vaccination status, healthcare system burden at different times [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], SARS-CoV-2 variant type, and outpatient management strategies may have influenced the results. Vaccination status is of particular concern, as research has shown that vaccination can reduce hospitalization and mortality in heart failure patients [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Although an ICD code for COVID-19 under immunization (Z28.3) has been available since 2021, very few patients had records of this code (only 246 [0.03%] in 2021 and 10,504 [1.1%] in 2022 with code Z28.3 available). In contrast, population-level surveillance data until 2021 indicated that vaccination coverage among adults aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years had reached 58.8% [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The substantial discrepancy between population surveillance data and hospital administrative coding suggests severe underreporting of vaccination status in records and warrants further investigation. Given this data limitation, we were unable to reliably assess the independent effect of COVID-19 vaccination on in-hospital outcomes in this study. The effect of COVID vaccination on in-hospital outcomes of CHF patients still needs further exploration. Also, as the NIS captures only hospitalized patients, our findings may not generalize to the broader CHF population treated in outpatient settings. Despite these limitations, the use of a large, nationally representative cohort provides robust evidence regarding the evolving impact of COVID-19 on hospitalized patients with congestive heart failure.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn summary, this study analyzed more than 3.4\u0026nbsp;million hospitalized CHF patients from 2019 to 2022 using the NIS database. COVID-19 infection was associated with a markedly increased risk of in-hospital mortality as well as other adverse outcomes. However, the excess risk declined over time, with differences in mortality and complications converging by 2022 to levels comparable with those observed for non-COVID respiratory infections such as pneumonia. These observations likely reflect multiple factors, including evolving viral variants, improved clinical management, availability of vaccines and effective treatments, and heightened awareness of cardiovascular risk in this vulnerable population. Our findings also highlight the disproportionate impact of COVID-19 on patients with CHF and underscore the importance of continued monitoring, tailored surveillance strategies, and optimal management of comorbidities in this high-risk group.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSARS-CoV-2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSevere Acute Respiratory Syndrome Coronavirus 2\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCOVID-19\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecoronavirus disease 19\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCHF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econgestive heart failure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHFrEF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eheart failure with reduced ejection fraction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHFpEF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eheart failure with preserved ejection fraction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNIS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ethe National Inpatient Sample\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICD-10-CM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ethe tenth revision of the International Classification of Diseases\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eodds ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eaOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eadjusted odds ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehazard ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eaHR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eadjusted hazard ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCABG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecoronary artery bypass grafting\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emyocardial infarction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research received no external funding. YD used internal research funding to support the purchase of the NIS datasets and the student researcher stipend.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization: YD, JZ, and MZData curation: YD, YM, JL, JZ, and HWFormal analysis: YM, JL, and JZMethodology: YD, YM, JL, JZ, and HWProject administration: YDSupervision: YDVisualization: YM and JLWriting \u0026ndash; original draft: YM, JL, and JZWriting \u0026ndash; review \u0026amp; editing: YD, JL, HW, and MZ\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThe authors gratefully acknowledge the Healthcare Cost and Utilization Project (HCUP) for providing access to the National Inpatient Sample (NIS) datasets used in this analysis.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are openly available for access (with fees) in the National Inpatient Sample (NIS) at [https://hcup-us.ahrq.gov/nisoverview.jsp](https:/hcup-us.ahrq.gov/nisoverview.jsp) .\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHeidenreich PA, Bozkurt B, Aguilar D, Allen LA, Byun JJ, Colvin MM, et al. 2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2022;145(18):e895\u0026ndash;1032. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1161/CIR.0000000000001063\u003c/span\u003e\u003cspan address=\"10.1161/CIR.0000000000001063\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 20220401.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRam-Mohan N, Kim D, Zudock EJ, Hashemi MM, Tjandra KC, Rogers AJ, et al. SARS-CoV-2 RNAemia Predicts Clinical Deterioration and Extrapulmonary Complications from COVID-19. Clin Infect Dis. 2022;74(2):218\u0026ndash;26. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/cid/ciab394\u003c/span\u003e\u003cspan address=\"10.1093/cid/ciab394\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilliamson EJ, Walker AJ, Bhaskaran K, Bacon S, Bates C, Morton CE, et al. Factors associated with COVID-19-related death using OpenSAFELY. Nature. 2020;584(7821):430\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41586-020-2521-4\u003c/span\u003e\u003cspan address=\"10.1038/s41586-020-2521-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 20200708.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePetrilli CM, Jones SA, Yang J, Rajagopalan H, O'Donnell L, Chernyak Y et al. Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study. BMJ. 2020;369:m1966. Epub 20200522. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmj.m\u003c/span\u003e\u003cspan address=\"10.1136/bmj.m\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e1966.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWard IL, Bermingham C, Ayoubkhani D, Gethings OJ, Pouwels KB, Yates T, et al. Risk of covid-19 related deaths for SARS-CoV-2 omicron (B.1.1.529) compared with delta (B.1.617.2): retrospective cohort study. BMJ. 2022;378:e070695. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmj-2022-070695\u003c/span\u003e\u003cspan address=\"10.1136/bmj-2022-070695\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 20220802.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlharbi A, Alfatlawi H, Mohamed A, Mhanna M, Mahmoud M, Elsheik R, et al. Outcomes of Heart Failure Related Hospitalizations During the COVID-19 Pandemic. Cureus. 2023;15(3):e36935. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.7759/cureus.36935\u003c/span\u003e\u003cspan address=\"10.7759/cureus.36935\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 20230330.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNasrullah A, Gangu K, Cannon HR, Khan UA, Shumway NB, Bobba A, et al. COVID-19 and Heart Failure with Preserved and Reduced Ejection Fraction Clinical Outcomes among Hospitalized Patients in the United States. Viruses. 2023;15(3). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/v15030600\u003c/span\u003e\u003cspan address=\"10.3390/v15030600\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 20230222.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFatuyi M, Amoah J, Egbuchiem H, Antia A, Akinti S, Mararenko A, et al. Impact of COVID-19 Infection on Clinical Outcomes Among Patients With Acute Decompensated Heart Failure: A Nationwide Analysis. Curr Probl Cardiol. 2023;48(11):101908. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.cpcardiol.2023.101908\u003c/span\u003e\u003cspan address=\"10.1016/j.cpcardiol.2023.101908\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 20230701.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHCUP National Inpatient Sample (NIS) [Internet]. 2012 [cited 21 Jan 2025]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003c/span\u003e\u003cspan address=\"http://www.hcup-us.ahrq.gov/nisoverview.jsp\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYonas E, Alwi I, Pranata R, Huang I, Lim MA, Gutierrez EJ, et al. Effect of heart failure on the outcome of COVID-19 - A meta analysis and systematic review. Am J Emerg Med. 2021;46:204\u0026ndash;11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ajem.2020.07.009\u003c/span\u003e\u003cspan address=\"10.1016/j.ajem.2020.07.009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 20200709.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUnudurthi SD, Luthra P, Bose RJC, McCarthy JR, Kontaridis MI. Cardiac inflammation in COVID-19: Lessons from heart failure. Life Sci. 2020;260:118482. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.lfs.2020.118482\u003c/span\u003e\u003cspan address=\"10.1016/j.lfs.2020.118482\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 20200921.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePeng X, Wang Y, Xi X, Jia Y, Tian J, Yu B, Tian J. Promising Therapy for Heart Failure in Patients with Severe COVID-19: Calming the Cytokine Storm. Cardiovasc Drugs Ther. 2021;35(2):231\u0026ndash;47. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10557-020-07120-8\u003c/span\u003e\u003cspan address=\"10.1007/s10557-020-07120-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 20210106.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZanza C, Romenskaya T, Manetti AC, Franceschi F, La Russa R, Bertozzi G et al. Cytokine Storm in COVID-19: Immunopathogenesis and Therapy. Medicina (Kaunas). 2022;58(2). Epub 20220118. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/medicina58020144\u003c/span\u003e\u003cspan address=\"10.3390/medicina58020144\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTomasoni D, Inciardi RM, Lombardi CM, Tedino C, Agostoni P, Ameri P, et al. Impact of heart failure on the clinical course and outcomes of patients hospitalized for COVID-19. Results of the Cardio-COVID-Italy multicentre study. Eur J Heart Fail. 2020;22(12):2238\u0026ndash;47. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/ejhf.2052\u003c/span\u003e\u003cspan address=\"10.1002/ejhf.2052\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 20201127.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMir T, Almas T, Kaur J, Faisaluddin M, Song D, Ullah W, et al. Coronavirus disease 2019 (COVID-19): Multisystem review of pathophysiology. Ann Med Surg (Lond). 2021;69:102745. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.amsu.2021.102745\u003c/span\u003e\u003cspan address=\"10.1016/j.amsu.2021.102745\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 20210823.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang P, Zhu L, Cai J, Lei F, Qin JJ, Xie J, et al. Association of Inpatient Use of Angiotensin-Converting Enzyme Inhibitors and Angiotensin II Receptor Blockers With Mortality Among Patients With Hypertension Hospitalized With COVID-19. Circ Res. 2020;126(12):1671\u0026ndash;81. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1161/CIRCRESAHA.120.317134\u003c/span\u003e\u003cspan address=\"10.1161/CIRCRESAHA.120.317134\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 20200417.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlvarez-Garcia J, Lee S, Gupta A, Cagliostro M, Joshi AA, Rivas-Lasarte M, et al. Prognostic Impact of Prior Heart Failure in Patients Hospitalized With COVID-19. J Am Coll Cardiol. 2020;76(20):2334\u0026ndash;48. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jacc.2020.09.549\u003c/span\u003e\u003cspan address=\"10.1016/j.jacc.2020.09.549\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 20201028.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFreaney PM, Shah SJ, Khan SS. COVID-19 and Heart Failure With Preserved Ejection Fraction. JAMA. 2020;324(15):1499\u0026ndash;500. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jama.2020.17445\u003c/span\u003e\u003cspan address=\"10.1001/jama.2020.17445\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePanagides V, Vincent F, Weizman O, Jonveaux M, Trimaille A, Pommier T, et al. History of heart failure in patients with coronavirus disease 2019: Insights from a French registry. Arch Cardiovasc Dis. 2021;114(5):415\u0026ndash;25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.acvd.2021.04.003\u003c/span\u003e\u003cspan address=\"10.1016/j.acvd.2021.04.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 20210524.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDeBerge M, Shah SJ, Wilsbacher L, Thorp EB. Macrophages in Heart Failure with Reduced versus Preserved Ejection Fraction. Trends Mol Med. 2019;25(4):328\u0026ndash;40. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.molmed.2019.01.002\u003c/span\u003e\u003cspan address=\"10.1016/j.molmed.2019.01.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 20190205.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkhmerov A, Marban E. COVID-19 and the Heart. Circ Res. 2020;126(10):1443\u0026ndash;55. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1161/CIRCRESAHA.120.317055\u003c/span\u003e\u003cspan address=\"10.1161/CIRCRESAHA.120.317055\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 20200407.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHadzibegovic S, Lena A, Churchill TW, Ho JE, Potthoff S, Denecke C, et al. Heart failure with preserved ejection fraction according to the HFA-PEFF score in COVID-19 patients: clinical correlates and echocardiographic findings. Eur J Heart Fail. 2021;23(11):1891\u0026ndash;902. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/ejhf.2210\u003c/span\u003e\u003cspan address=\"10.1002/ejhf.2210\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 20210712.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller IF, Becker AD, Grenfell BT, Metcalf CJE. Disease and healthcare burden of COVID-19 in the United States. Nat Med. 2020;26(8):1212\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41591-020-0952-y\u003c/span\u003e\u003cspan address=\"10.1038/s41591-020-0952-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 20200616.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohnson KW, Patel S, Thapi S, Jaladanki SK, Rao A, Nirenberg S, Lala A. Association of Reduced Hospitalizations and Mortality Rates Among COVID-19-Vaccinated Patients With Heart Failure. J Card Fail. 2022;28(9):1475\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.cardfail.2022.05.008\u003c/span\u003e\u003cspan address=\"10.1016/j.cardfail.2022.05.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 20220609.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSuthar AB, Wang J, Seffren V, Wiegand RE, Griffing S, Zell E. Public health impact of covid-19 vaccines in the US: observational study. BMJ. 2022;377:e069317. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmj-2021-069317\u003c/span\u003e\u003cspan address=\"10.1136/bmj-2021-069317\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 20220427.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Congestive heart failure, HFpEF, HFrEF, In-hospital outcomes, National Inpatient Sample, Respiratory infection, Survival analysis","lastPublishedDoi":"10.21203/rs.3.rs-8575946/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8575946/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eCongestive heart failure (CHF) is a leading cause of hospitalization and mortality in the elderly, with patients particularly vulnerable to adverse outcomes when exposed to infections. The evolving impact of COVID-19 on in-hospital outcomes among patients with CHF remains insufficiently understood. This study examines the temporal variations in mortality and in-hospital outcomes among CHF patients with and without COVID-19 using National Inpatient Sample (NIS) data from 2019 to 2022, with 2019 as a pre-pandemic reference year.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective observational study on NIS data 2019\u0026ndash;2022. Patients aged 18\u0026ndash;90 with CHF, identified using ICD-10-CM I50.x diagnosis codes, were included. The primary outcome was mortality, with secondary outcomes including vasopressor use, sudden cardiac arrest, acute kidney injury, pulmonary embolism, mechanical ventilation, and time to in-hospital death. The main covariate of interest is the presence or absence of a COVID-19 diagnosis. Multivariate logistic regression and Cox proportional hazards models were applied to estimate adjusted odds ratios (aORs) or hazard ratios (aHRs) controlling for demographic and comorbidities based on the Elixhauser Comorbidity Index.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe in-hospital mortality rate of CHF patients with a COVID-19 diagnosis was significantly higher than those without COVID-19 in 2020 to 2022, although the difference narrowed in 2022. aORs (95% CI) were 6.12 (5.95\u0026ndash;6.31), 5.71 (5.57\u0026ndash;5.86), and 2.53 (2.46\u0026ndash;2.60) in 2020, 2021, and 2022, respectively. By 2022, the impact of COVID-19 on mortality among CHF patients had declined to a level comparable to that of non-COVID pneumonia (aOR 2.50, 95% CI 2.45\u0026ndash;2.56 in 2022). Among secondary outcomes, the time to in-hospital death followed a similar pattern to overall mortality, with significantly elevated risks early in the pandemic and showed a clear reduction by 2022. Other outcomes, such as mechanical ventilation and pulmonary embolism, showed an initial increase in risk followed by a decline over the same period.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eUsing NIS data 2019\u0026ndash;2022, this analysis demonstrates that while COVID-19 was associated with substantially higher in-hospital mortality and adverse outcomes among CHF patients early in the pandemic, its impact progressively declined by 2022, converging to levels comparable with non-COVID respiratory infections.\u003c/p\u003e","manuscriptTitle":"Impact of Respiratory Infections on Hospitalized Congestive Heart Failure Patients: A Retrospective Analysis of NIS Database (2019–2022)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-06 19:11:46","doi":"10.21203/rs.3.rs-8575946/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-02-17T13:26:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"38242721096297204882809628435350353244","date":"2026-02-12T19:04:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"208119719574978446193778360781191236518","date":"2026-02-10T12:53:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"44674468755316661206864557492173449664","date":"2026-02-04T17:10:41+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-04T10:44:57+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-13T08:55:16+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-13T05:56:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-13T05:52:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cardiovascular Disorders","date":"2026-01-11T22:35:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"388dbc5c-2ef8-496c-953b-9d39082ca150","owner":[],"postedDate":"February 6th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-06T19:11:46+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-06 19:11:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8575946","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8575946","identity":"rs-8575946","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}