Examining the Intersection of Inflammatory Bowel Disease and COVID-19: Insights from a National Inpatient Database Study

Examining the Intersection of Inflammatory Bowel Disease and COVID-19: Insights from a National Inpatient Database Study | 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 Examining the Intersection of Inflammatory Bowel Disease and COVID-19: Insights from a National Inpatient Database Study Rubaid Azhar Dhillon, Maryam Bilal Haider, Ahmed Jamal Chaudhary, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3962562/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: This study aimed to investigate the clinical indicators and outcomes of COVID-19-positive patients with inflammatory bowel disease (IBD), focusing on age, sex, socioeconomic status, and geographic location. The objective of this study was to fill the knowledge gap regarding determinants influencing outcomes in individuals with and without IBD who contracted COVID-19, thus impacting healthcare provision. Methods: This study utilized the nationwide inpatient sample (NIS) database for the period from January to December 2020. Patients were categorized into those with COVID-19 alone (controls) and those with both COVID-19 and IBD (cases). Demographic, clinical, and hospital-related variables were analyzed using statistical methods, including t tests and chi-square tests. Logistic and multivariate regression analyses were performed to assess factors affecting mortality. Results: Among COVID-19 patients with IBD, a sex disparity was observed, with more females in the IBD group than in the non-IBD group. The mean age was similar in both groups. Hospitalizations were concentrated in the age group of 65–84 years. Ethnically, Caucasians dominated both cohorts, and Medicare was the primary payer for a greater proportion of hospitalizations in the IBD group. Hospitalizations were prevalent in urban teaching hospitals, primarily in the southern and mid-western regions of the US. There were no significant differences in mortality rates, and clinical symptoms were comparable between the two groups. Factors associated with mortality included sex, age, and specific existing health conditions. Conclusion: Contrary to the initial hypothesis, the presence of IBD among COVID-19 patients did not significantly impact mortality rates. However, certain clinical indicators and outcomes are influenced by individual factors such as age, sex, and underlying health conditions. This study emphasizes the need for careful monitoring of COVID-19 patients with IBD, particularly those with additional risk factors. Further research is necessary to fully understand the biochemical interactions and implications of IBD in the context of COVID-19. This comprehensive study contributes valuable insights to healthcare authorities, aiding in patient management and outcome optimization. Inflammatory Bowel Disease Coronavirus Disease 2019 Nationwide inpatient sample Background Toward the close of 2019, a novel pathogen known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged within Wuhan, China [ 1 ]. Subsequent to its initial appearance in China, this virus rapidly disseminated across the globe, prompting the World Health Organization (WHO) to declare a worldwide pandemic on March 12, 2020 [ 1 ]. According to the existing body of knowledge, individuals with preexisting underlying health conditions, advanced age, and a compromised immune system are inclined to face increased susceptibility to contracting the virus [ 2 ]. In the event of infection, these particular patient demographics are more susceptible to experiencing complications, thus exerting an adverse impact on their overall prognosis. Inflammatory bowel disease (IBD) encompasses a chronic, immune-mediated inflammatory disorder affecting the digestive tract, comprising ulcerative colitis and Crohn's disease. The underlying pathogenesis of IBD is believed to involve immune response dysregulation toward resident microorganisms in genetically predisposed individuals [ 3 ]. The primary objective of IBD treatment is to regulate this heightened immune response. However, therapeutic interventions for IBD render patients more susceptible to infections. Despite the absence of definitive evidence, it remains uncertain whether individuals with inflammatory bowel disease (IBD) are inherently more prone to contracting COVID-19. Nevertheless, the underlying disease mechanisms and pharmacological treatments for IBD could render these patients more susceptible to the virus [ 2 ]. The cellular entry of a virus is contingent upon binding to the angiotensin converting enzyme (ACE2) receptor protein. This receptor is ubiquitously distributed across organs, including the lungs, heart, kidneys, stomach, and, notably, ileum and colon [ 4 ]. Interestingly, in IBD patients, the ACE2 receptor is upregulated, potentially increasing susceptibility to the virus. An analysis of tissue samples from IBD patients revealed greater ACE2 expression in Crohn's disease patients than in those with ulcerative colitis [ 5 ]. Furthermore, the immunosuppressive therapies prescribed for IBD patients can further compromise their resistance to infections [ 4 ]. Despite these implications, the World Health Organization (WHO) has not issued specific protective recommendations for IBD patients in the context of COVID-19 [ 2 ]. Throughout the pandemic, the International Organization for the Study of IBD (IOIBD) has provided consistent guidance, advocating for the uninterrupted continuation of therapies while advising temporary discontinuation only in cases of active infection [ 6 ]. Given the substantial incidence of IBD across the United States, our objective was to discern the clinical indicators and consequences observed among COVID-19-positive IBD patients, specifically in relation to age, sex, socioeconomic status, and geographic location. By harnessing the national inpatient database, our intention was to narrow the knowledge gap pertaining to the determinants influencing outcomes in individuals with and without IBD who contracted COVID-19, thereby impacting the broader landscape of healthcare provision in the US. Considering the intricate nature of COVID-19, a comprehensive, multidisciplinary strategy might be imperative when dealing with IBD patients, with the potential to enhance patient outcomes in this context. Materials and Methods We conducted an analysis of the nationwide inpatient sample (NIS) database, focusing on the period from January 2020 to December 2020. The NIS database is a comprehensive and publicly accessible collection of hospitalization data in the United States. It serves the purpose of generating insights into inpatient usage, expenses, quality, and results at both the national and regional levels [ 7 ]. Our investigation employed the International Classification of Diseases (ICD)-10 codes for diagnoses and procedures [ 8 ]. To safeguard the privacy of individual patients, medical professionals, and hospitals, all identifying information in the dataset was removed. Consequently, this research was considered exempt from Institutional Review Board (IRB) approval by Wayne State University, following the Health Insurance Portability and Accountability Act regulations [ 9 ]. The study included patients with either a primary or secondary diagnosis of COVID-19. Our study included patients diagnosed with both inflammatory bowel disease (IBD) and ulcerative colitis. The study population was categorized into two groups: those with COVID-19 alone (controls) and those with both COVID-19 and IBD (cases). Outcomes The main objectives of this study were twofold: first, to assess demographic differences between individuals with COVID-19 with and without coexisting IBD and, second, to identify factors contributing to in-hospital mortality among COVID-19 patients with IBD. The secondary objectives involved the analysis of hospital utilization metrics, including inpatient mortality rates, length of hospital stay (LOS), and the total cost of care associated with inpatient hospital services for COVID-19 patients with IBD. Variables We conducted a comparative analysis between two cohorts: COVID-19 patients diagnosed with IBD (patients) and those without IBD (controls). We assessed demographic attributes (age, sex, race, primary insurance coverage, and socioeconomic status), clinical manifestations, pertinent comorbidities, substance abuse, and hospital-related outcomes in both groups. Statistical analysis Statistical analyses were conducted using SAS software (SAS Institute Inc., Cary, NC, United States). Continuous variables, including age, total charges, and length of stay, are represented as the mean ± standard deviation, while categorical variables are presented as frequencies and calculated percentages. Group comparisons between individuals with and without IBD were performed utilizing Student’s t test for continuous variables and Rao-Scott chi-square tests for categorical variables. Univariate analysis was carried out employing logistic regression, while multivariate analysis was accomplished through a weighted multilevel mixed-effects model utilizing the Glimmix procedure with maximum likelihood estimation and Gauss–Hermite quadrature likelihood approximation. The exclusion criteria included patients younger than 18 years of age who were categorized into four subgroups according to the HCUP standard categories (18–44, 45–64, 65–84, and ≥ 85 years) for the purpose of group-level comparisons. Instances of missing values were categorized as either "missing" or "unknown." All hypothesis testing was conducted at a two-tailed significance level of 0.05 (where a P value < 0.05 was deemed to indicate statistical significance). Results Within the amassed dataset, a conspicuous gender disparity emerged in the IBD group compared with the non-IBD cohort, with a prevalence of 53.6% females in the former and 47.2% in the latter (P<0.001). Conversely, a notable male preponderance manifested within the non-IBD group. The mean age within both groups displayed a negligible difference: 64.7 ± 16.1 for the non-IBD group and 64.3 ± 15.7 for the IBD group. The IBD group was further partitioned into subgroups, with Crohn's disease (CD) accounting for a greater proportion at 51.5%, while ulcerative colitis (UC) constituted 48.5%. Predominantly, hospitalizations within both the IBD and non-IBD cohorts were concentrated in the age bracket of 65–84 years, followed closely by the age group of 45–64 years (P<0.001) (Table 1). Ethnically, Caucasians represented more than half of the hospitalizations in both cohorts: 51% in the non-IBD group and 74.4% in the IBD group. Noteworthy differences were noted regarding Hispanics: 20% in the non-IBD cohort and 8.5% in the IBD cohort. Medicare was the primary payer for a greater proportion of hospitalizations (56.9%) in the IBD group than in the non-IBD cohort (52.2%). Similarly, a greater percentage of IBD patients had a primary payer status of "private" (30.6%), in contrast to 27.6% among non-IBD patients. Bed size requirements were notably similar between the two groups, although a greater portion of IBD patients necessitated larger bed sizes (47.7%) than did non-IBD patients (45.4%). Regarding their geographical distribution and affiliation with teaching institutions, a considerable percentage of hospitalizations occurred within urban teaching hospitals for both cohorts (68.9% in the non-IBD cohort and 70.9% in the IBD cohort). Geographically, a substantial contingent of patients in both groups originated from the southern and mid-western/north central regions of the United States. The routine discharge rates were almost equivalent between non-IBD and IBD patients (54.6% versus 53.7%). Conversely, a notable upswing was observed in IBD hospitalizations designated for Home Health Care (HCC) (15.3%). While scrutinizing mortality rates, slightly higher mortality was evident among non-IBD patients (11.2%) than among IBD patients (10.3%). There were no significant differences in the clinical symptoms between the two groups, although both groups experienced higher levels of symptoms such as malaise and fatigue, diarrhea, and nausea and vomiting. Through both univariate and multivariate analyses, we identified sex, age, and specific existing health conditions (such as neurological disorders, weight loss, and immune disorders) (Table 2). On the other hand, there was no significant difference observed between length of stay and total hospital charges when comparing both cohorts (Table 3). Discussion The available data regarding the clinical attributes and outcomes within the cohort of COVID-19 patients, considering the presence or absence of IBD, are notably limited. The precise extent of infection risk among individuals with IBD remains unclear and is potentially influenced by variables such as age or genetic predisposition. Throughout the pandemic, there has been a heightened focus on the management and prognosis of IBD patients who have contracted the infection. In the initial stages of the pandemic, a handful of studies suggested that individuals with IBD might be at a lower risk of contracting COVID-19 than the broader population. Notably, investigations conducted by Ren Mao et al. in China [ 10 ] and Carlos Taxonera et al. in Italy [ 11 ] reported no COVID-19 cases within the IBD populations they examined. This finding was corroborated by a meta-analysis undertaken by Aziz et al. in 2020 [ 12 ], which synthesized findings from six studies encompassing a collective IBD patient sample of 9177 individuals. The meta-analysis demonstrated an aggregate incidence of 0.3% COVID-19 in the IBD patient population, a figure falling within the lower spectrum of the general population's incidence range (0.2–4.0%). Notably, the enhanced adherence of IBD patients to hygienic and preventive measures might confound the relationship between the two diseases, warranting cautious interpretation. According to the CDC [ 13 ], 3.1 million (1.3%) adults in the USA are diagnosed with IBD, which includes both Crohn’s disease and ulcerative colitis. Given the dearth of comprehensive guidelines and available data pertaining to the interaction between COVID-19 and this specific patient demographic, we undertook a study aimed at scrutinizing IBD patients who were also diagnosed with COVID-19. This study entailed a comparative evaluation, contrasting IBD patients with their non-IBD counterparts across multiple dimensions, including sociodemographic attributes, clinical manifestations of COVID-19, concurrent comorbidities, duration of hospitalization, and mortality rates. A retrospective cohort study conducted in the United States to assess the risk and outcomes of COVID-19 in IBD patients revealed a detrimental impact of steroid use on patient outcomes. Notably, this study reported a lower incidence of COVID-19 in the IBD patient population than in the non-IBD patient population [ 14 ]. However, within the COVID-19-affected IBD cohort, a heightened likelihood of hospitalization and critical care was observed, potentially attributed to some patients experiencing an IBD flare at the 3-month follow-up [ 14 ]. This may explain the larger bed size observed in our data among the IBD cohort than among the non-IBD cohort. Given the susceptibility of IBD patients to complications, whether attributed to advanced age, underlying conditions, or the use of biological agents, vigilant postdischarge monitoring is warranted. This observation may also explain the greater reliance on home health care (HCC) for IBD patients in our dataset than for their non-IBD counterparts. Using nationwide patient sample (NIS) data, Nguyen et al. analyzed US hospitals for the presence of methicillin-resistant Staphylococcus aureus (MRSA) infection in IBD patients [ 15 ]. The study demonstrated an augmented MRSA risk in IBD patients, correlated with a heightened fatality rate [ 15 ]. Alongside the consideration of the presence of COVID-19 among IBD patients, prudent measures against nosocomial infections within this patient demographic population have become imperative. Our data revealed that there was a greater percentage of females in the IBD cohort. It is well known that female sex is a risk factor for the development of IBD; however, the complex pathogenesis of IBD also involves genetic susceptibility and external environmental triggers such as medication use and dietary changes [ 16 ]. A study conducted in the USA over the span of five years revealed a greater incidence of IBD among females than among males [ 16 ]. However, a large-scale analysis in 2019 of 11 Asian-Pacific countries revealed a significantly greater incidence of IBD among the male population [ 17 ]. This suggests that sex-based differences may be correlated with environmental and geographical factors in disease epidemiology. A male predominance was also observed in an IBD meta-analysis conducted in China, and the articles included in this meta-analysis mainly consisted of patients with low-grade severity when compared to the IBD cohorts from Belgium and France [ 18 ]. This could suggest that the incidence and prevalence of sex-based differences are correlated with disease severity. According to several large-scale studies, a female predominance has been observed in patients with inflammatory bowel disease in Western countries [ 19 , 20 , 21 ]. Hence, this may explain the greater number of females observed in our cohort of COVID-19 patients with IBD. Apart from the genetic, sex, environmental, and geographical factors that have been examined, the greater occurrence of IBD in females might also be associated with the use of oral contraceptives [ 22 ]. In a substantial cohort study conducted in the United States involving more than 200,000 women, a connection was established between the use of oral contraceptives and increased susceptibility to IBD [ 22 ]. Similarly, a separate case‒control study utilizing the United Kingdom General Practice Research Database also indicated a heightened risk of IBD linked to the utilization of oral contraceptives [ 23 ]. Moreover, within the limits of the limited available data, gender disparities have been noted in terms of COVID-19 hospitalization and mortality. An analysis encompassing data provided by the CDC revealed that more than a million COVID-19 cases in the United States indicated a greater frequency of ICU admissions and elevated fatality rates among males compared to females [ 24 ]. The mechanism underlying this sex-specific susceptibility to COVID-19 is potentially linked to ACE2 and transmembrane protease serine 2 (TMPRSS2) [ 25 ]. As previously discussed, given the correlation between increased ACE2 expression and increased COVID-19 susceptibility, research has revealed increased ACE2 expression among males [ 25 , 26 ]. Furthermore, the expression of TMPRSS2, a significant player in COVID-19 cell entry, is increased in males due to the presence of androgen receptors [ 27 ]. These mechanisms may explain the male predominance observed in our non-IBD cohort, where the presence of COVID-19 and comorbidities were sufficient to increase the mortality rate to a rate similar to that of the IBD cohort. While ACE2 is also expressed in females, the inhibitory impact of estrogen on ACE2 may confer some level of defense against COVID-19 [ 28 ]. However, a study conducted on IBD patients with a history of COVID-19 infection reported that the prevalence of long COVID-19 was greater among female patients [ 25 , 29 ]. Another study on long COVID-19 in IBD patients also reported the same findings [ 30 , 31 ]. Due to the difference in immune response based on sex, it seems that females may have a continued systemic inflammatory reaction for long COVID-19 symptoms to develop. Thus, continuous monitoring is crucial for the early identification of complications in these patients. Further research is essential to determine the influence of long COVID-19 on the clinical progression of IBD patients. Our study revealed comparable mortality rates between the IBD and non-IBD patient groups. A US cohort study utilizing federal health data also reported no difference in mortality between these groups in the presence of COVID-19 [ 32 ]. During the pandemic, it is possible that only the most critical patients were admitted and that the increase in SARS-CoV-2 infection had no effect on patient outcomes. With SARS-CoV-2 detected in stool samples and ACE2 upregulation, one might assume that IBD patients are at a greater risk of infection [ 33 ]. However, according to the literature, there is no correlation between these factors and the infectivity rate or severity of COVID-19 in IBD patients. The use of immune-mediated therapies in IBD patients might increase the risk of infection; however, it is hypothesized that these same therapies could also provide protection against the cytokine storm or inflammatory response associated with severe COVID-19 [ 34 ]. According to the data released by the three largest tertiary IBD centers in Wuhan, China, no cases of COVID-19 were reported at these centers [ 34 ]. Another set of data was also released by a tertiary center located in northern Italy, which had one of the highest COVID-19 rates early in the pandemic. Based on the data, 522 IBD patients admitted to this center during that time reported no cases of COVID-19 for the remainder of their stay at the hospital [ 35 ]. It is quite possible that immunosuppressive treatment might have offered protection against COVID-19 in these IBD patients. This may explain the similar mortality rates observed in our data among IBD and non-IBD patients. Our data demonstrated that the majority of COVID-19 patients with IBD were admitted to urban teaching hospitals, particularly in the southern and midwestern regions. A meta-analysis from China on IBD highlighted a sudden increase in cases in southeastern areas following the adoption of a westernized lifestyle [ 36 ]. This sudden rise suggests that environmental triggers underpin the disease, encompassing factors such as socioeconomic status, sanitation, infections, medications, and lifestyle practices [ 37 ]. Multiple studies, mirroring our findings, affirm that IBD is more prevalent in urban than in rural settings [ 38 , 39 ]. The discussed environmental risk factors for IBD are more commonly found in urban regions of western nations, elevating the risk of IBD development among residents. A study conducted in Sweden reported an increased risk of IBD among families with low socioeconomic status [ 40 ]. In our study, there was no significant correlation between the median income of families and IBD, which suggests that factors other than socioeconomic status influenced the development of the disease in these patients. However, it is quite possible that a portion of the patients analyzed in our study who did not have proper access to healthcare during the pandemic due to financial constraints may have had a higher fatality rate in both cohorts. Our data revealed that more than half of the patients in both cohorts were treated with Medicare, and the remaining patients were treated with Medicaid and private insurance. A study was conducted using the State Inpatient Database, where the prevalence of fragmentation in patient care was reported to be among one in four IBD patients and was associated with poor visit outcomes [ 41 ]. Fragmentation has been linked to certain factors, such as Medicaid recipients, preexisting neurological conditions, substance misuse, and urgent readmissions [ 41 ]. Our study aligns with this, as we connected neurological comorbidities and immune disorders to in-hospital mortality among IBD patients. Substance abuse showed no correlation in our dataset; however, a subset of IBD patients had Medicaid ties, warranting vigilant monitoring and tailored interventions for enhanced outcomes among vulnerable groups. Our retrospective study represents the most comprehensive assessment to date of the COVID-19 patient population with IBD, evaluating both epidemiology and outcomes. To date, our study is the first to thoroughly analyze COVID-19 hospitalizations with and without IBD to identify factors associated with high-risk individuals. Our analysis integrated comorbidities, predictors of mortality, and clinical characteristics to assess patient outcomes. Given the restricted accessibility of centralized patient databases, population-based studies on COVID-19 hospitalizations for IBD patients within the United States have been limited. Our research thus contributes pivotal insights to healthcare authorities concerning the factors governing IBD incidence and prevalence amid COVID-19 hospitalizations. A significant strength of our study lies in its comprehensive comparison of COVID-19 hospitalizations with and without IBD, facilitating a nuanced comprehension of mortality influencers in both cohorts. Nonetheless, we recognize certain limitations inherent to this study. When utilizing extensive databases such as the NIS, potential distortion could arise from errors within the ICD-10 diagnostic coding system. Additionally, inpatient discharge data may solely represent participating hospitals within the Healthcare Cost and Utilization Project (HCUP) [ 42 ]. Moreover, the NIS database lacks information regarding disease severity or treatment details. The geographical distribution of patients revealed variations in terms of underlying comorbidities, genetic predispositions, and IBD medications, potentially impacting COVID-19 risk. Furthermore, given that COVID-19 can exacerbate gastrointestinal symptoms in non-IBD patients, distinguishing between IBD patients and non-IBD patients could be challenging [ 43 ]. Conclusion In conclusion, this retrospective study indicated that the presence of IBD among COVID-19 patients does not significantly impact mortality. Nevertheless, the IBD condition can influence the clinical trajectory of these patients, subject to individual factors such as underlying comorbidities, age, sex, and environmental triggers. Vigilant monitoring of these patients is crucial, as the long-term implications of IBD in COVID-19 patients remain uncertain. Additional research is necessary to validate the influence of these factors on outcomes. Although one might hypothesize that IBD patients are predisposed to COVID-19 complications, our findings reveal comparable lengths of stay and routine discharge in both cohorts. This could be attributed to accessible healthcare and timely interventions that averted complications. Given the intricacies of COVID-19, further investigation is essential to comprehend the biochemical interactions impacting the gastrointestinal system. Abbreviations IBD - Inflammatory bowel disease NIS - Nationwide inpatient sample WHO - World Health Organization IOIBD - International Organization for the Study of IBD ACE2 - Angiotensin converting enzyme SARS-CoV-2 - Severe acute respiratory syndrome coronavirus 2 LOS – Length of Stay IRB - Institutional Review Board ICD - International classification of diseases CD - Crohn’s Disease UC - Ulcerative Colitis HCC - Home health Care HCUP - Healthcare Cost and Utilization Project TMPRSS2 - Transmembrane protease serine 2 MRSA - Methicillin-resistant Staphylococcus aureus Declarations Ethical Approval: Not Applicable Consent for Publication: Not Applicable Availability of data and materials: The datasets generated and/or analyzed during current study are publicly available from the National Inpatient Sample (NIS) database. Competing Interests: The authors declare that they have no competing interests. Funding: None Authors’ Contributions: In the development of our research, each author played a pivotal role. RD was instrumental in conceptualizing the study framework and led the data analysis segment, providing critical insights that shaped our findings. MBH contributed extensively to the literature review, meticulously sourcing and synthesizing relevant studies to establish a solid foundation for our research objectives. AJC took charge of the methodology section, designing the study's approach with precision and overseeing the data collection process to ensure accuracy and reliability. Lastly, ZA played a key role in drafting and revising the manuscript, ensuring the clarity of presentation and coherence of the study's arguments. Together, these contributions were vital in the completion of our research project. Acknowledgements: Not applicable References Magro F, Rahier JF, Abreu C, MacMahon E, Hart A, van der Woude CJ, Gordon H, Adamina M, Viget N, Vavricka S, Kucharzik T. 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Assessing environmental risk factors affecting the inflammatory bowel diseases: a joint workshop of the Crohn's & Colitis Foundations of Canada and the USA. Inflammatory bowel diseases. 2008 Aug 1;14(8):1139-46. Klement E, Lysy J, Hoshen M, Avitan M, Goldin E, Israeli E. Childhood hygiene is associated with the risk for inflammatory bowel disease: a population-based study. Official journal of the American College of Gastroenterology| ACG. 2008 Jul 1;103(7):1775-82. EKBOM A, ADAMI HO, HELMICK CG, JONZON A, ZACK MM. Perinatal risk factors for inflammatory bowel disease: a case-control study. American journal of epidemiology. 1990 Dec 1;132(6):1111-9. Cohen-Mekelburg SA, Rosenblatt R, Gold S, Steinlauf AF, Burakoff R, Scherl E, Unruh M. Su1863-Fragmented Care is Prevalent Among Hospitalized Inflammatory Bowel Disease Patients and is Associated with Worse Outcomes. Gastroenterology. 2018 May 1;154(6):S-612. Alexoff A, Roginsky G, Zhou Y, Kalenda M, Minuskin K, Ehrenpreis ED. Inpatient costs for patients with inflammatory bowel disease and acute pancreatitis. Inflammatory Bowel Diseases. 2016 May 1;22(5):1095-100. Galanopoulos M, Gkeros F, Doukatas A, Karianakis G, Pontas C, Tsoukalas N, Viazis N, Liatsos C, Mantzaris GJ. COVID-19 pandemic: Pathophysiology and manifestations from the gastrointestinal tract. World journal of gastroenterology. 2020 Aug 8;26(31):4579. Tables Table 1: Comparison of patient demographics, hospital characteristics, and clinical presentations among COVID-19 patients with and without IBD. Demographics and Hospital Characteristics Non-IBD Weighted n (%) IBD Weighted n (%) P value Weighted Total, n (%) 1,043,535 (99.45%) 5750 (0.55%) Ulcerative colitis - 2790 (48.5%) Crohn’s disease - 2960 (51.5%) Sex <.0001 2 Female 492,185 (47.2%) 3080 (53.6%) Male 551,350 (52.8%) 2670 (46.4%) Age (y), mean (SD) 64.7 ± 16.1 64.3 ± 15.7 0.3327 1 Age groups (years) 0.0061 3 18-44 125,625 (12.0%) 685 (11.9%) 45-64 357,510 (34.3%) 2010 (34.9%) 65-84 441,085 (42.3%) 2580 (44.9%) >=85 119,315 (11.4%) 475 (8.3%) Race/Ethnicity <.0001 3 White 531,660 (51.0%) 4275 (74.4%) Black 187,240 (17.9%) 630 (11.0%) Hispanic 208,490 (20.0%) 490 (8.5%) Asian or Pacific Islander 32,740 (3.1%) 60 (1.0%) Native American 10,550 (1.0%) 5 (0.1%) Other 72,855 (7.0%) 290 (5.0%) Primary Payer status <.0001 3 Medicare 544,890 (52.2%) 3270 (56.9%) Medicaid 121,030 (11.6%) 475 (8.3%) Private 288,625 (27.6%) 1760 (30.6%) Self-Pay 35,715 (3.4%) 80 (1.4%) No Charge 2575 (0.3%) 25 (0.4%) Other 50,700 (4.9%) 140 (2.4%) Median household income for patient's ZIP Code <.0001 3 0-25 352,135 (33.7%) 1500 (26.1%) 25-50 284,225 (27.2%) 1555(27.0%) 50-75 224,920 (21.6%) 1400 (24.4%) 75-100 165,855 (15.9%) 1210 (21.0%) Other 16,400 (1.6%) 85 (1.5%) Hospital Bed Size 0.3018 3 Small 268,205 (25.7%) 1425 (24.8%) Medium 301,705 (28.9%) 1580 (27.5%) Large 473,625 (45.4%) 2745 (47.7%) Location/teaching status of the hospital 0.3522 3 Rural 122,615 (11.8%) 605 (10.5%) Urban nonteaching 201,530 (19.3%) 1070 (18.6%) Urban teaching 719,390 (68.9%) 4075 (70.9%) Hospital region <.0001 3 Northeast 184,215 (17.6%) 1175 (20.4%) Midwest or North Central 242,720 (23.3%) 1745 (30.4%) South 437,106 (41.9%) 2015 (35.0%) West 179,494 (17.2%) 815 (14.2%) Discharge Characteristics 0.4038 Routine Discharge 570,100 (54.6%) 3085 (53.7%) Transfer to Short-term Hospital 30,780 (3.0%) 165 (2.9%) Transfer to other facilities 185,940 (17.8%) 1025 (17.8%) Home Health Care (HHC) 140,070 (13.4%) 880 (15.3%) In-Hospital Mortality 116,645 (11.2%) Overall 595 (10.3%) Crohn’s Disease 305 (5.30%) Ulcerative Colitis 290 (5.00%) Clinical Presentation Non-IBD Weighted n (%) IBD Weighted n (%) Fever 14215 (1.4%) 75 (1.3%) 0.8652 2 Cough 10525 (1.0%) 60 (1.1%) 0.9121 2 Shortness of breath 17780 (1.7%) 135 (2.3%) 0.0890 2 Malaise and fatigue 46615 (4.5%) 215 (3.7%) 0.2290 2 Anorexia 11795 (1.1%) 50 (0.9%) 0.4062 2 Altered Mental Status 5435 (0.5%) 10 (0.2%) 0.1034 2 Abdominal pain 9810 (0.9%) 75 (1.3%) 0.1965 2 Diarrhea 61460 ( 5.9%) 245 (4.3%) 0.0187 2 Nausea and Vomiting 23730 (2.3%) 85 (1.5%) 0.0681 2 Loss of small/Taste 6990 (0.7%) 65 (1.0%) 0.2699 2 1 Two-sample Student t test, 2-tailed for comparing means of two continuous variables. 2 Rao‒Scott chi‒square 2-tailed test for associations between two categorical variables. 3 Rao‒Scott chi‒square test, 2-tailed test for 2-by- n tables. Statistical significance illustrated that the two groups differed. Table 2: Univariate and multivariate analyses of demographics and clinical factors associated with in-hospital mortality in IBD patients with COVID-19. Mortality Unadjusted odds ratio 1 (95%CI) P value Adjusted odds ratio 2 (95%CI) P value Univariate Analysis Multivariate Analysis Gender, Female vs. Male 0.72 (0.49 – 1.05) 0.0907 0.60 (0.48 – 0.77) <.0001 Age groups (years) 18-44 Reference NA Reference NA 45-64 8.2 (1.1 – 61.6) 0.0397 13.1 (4.82 – 35.5) <.0001 65-84 22.4 (3.09 – 162.5) 0.0021 37.3 (12.9 – 107.2) =85 40.9 (5.41 – 309.9) 0.0003 79.3 (25.3 – 248.2) <.0001 Race/Ethnicity White Reference NA Reference NA Black 0.62 (0.31 – 1.27) 0.1917 0.59 (0.37 – 1.02) NS Hispanic 0.82 (0.34 – 1.68) 0.5851 1.39 (0.91 – 2.13) NS Asian or Pacific Islander 0.74 (0.09 – 5.76) 0.7704 0.33 (0.06 – 2.15) NS Native American - NS - NS Other 0.76 (0.30 – 1.96) 0.5748 0.67 (0.38 – 1.22) NS Primary Payer status Medicare Reference NA Reference NA Medicaid 0.55 (0.26 – 1.17) 0.1189 1.43 (0.85 – 2.39) NS Private 0.27 (0.15 – 0.47) <.0001 0.70 (0.48 – 1.03) NS Self-Pay - NS - NS No Charge - NS - NS Other 0.46 (0.11 – 1.96) 0.2931 1.08 (0.47 – 2.45) NS Median household income for patient's ZIP Code 0-25 Reference NA Reference NA 25-50 0.99 (0.59 – 1.68) 0.9858 0.99 (0.59 – 1.68) NS 50-75 0.89 (0.51 – 1.54) 0.6721 0.89 (0.51 – 1.54) NS 75-100 1.18 (0.69 – 2.02) 0.5431 1.18 (0.69 – 2.02) NS Other 0.54 (0.07 – 4.23) 0.5594 0.54 (0.07 – 4.23) NS Comorbidities AIDS 0.54 (0.07 – 4.23) 0.9715 0.49 (0.09 – 2.52) 0.3253 Deficiency anemias 1.46 (0.94 – 2.24) 0.0893 0.97 (0.74 – 1.29) 0.8498 Autoimmune conditions 1.25 (0.64 – 2.41) 0.5171 1.83 (1.21 – 2.78) 0.0054 Chronic blood loss anemia 1.94 (0.41 – 9.09) 0.3998 2.12 (0.46 – 9.78) 0.2147 Coagulopathy 1.75 (1.07 – 2.87) 0.0255 1.56 (1.14 – 2.13) 0.0063 Asthma 0.53 (0.25 – 1.11) 0.0955 1.14 (0.74 – 1.74) 0.5491 COPD and Bronchiectasis 1.40 (0.90 – 2.18) 0.1345 1.12 (0.85 – 1.48) 0.4329 Acute Pulmonary Embolism 1.12 (0.39 – 3.24) 0.8313 1.53 (0.74 – 3.16) 0.2264 Pulmonary circulation disease 0.66 (0.15 – 2.82) 0.5756 0.21 (0.08 – 1.48) 0.0025 Coronary Artery Disease 1.48 (0.95 – 2.31) 0.0813 0.91 (0.68 – 1.20) 0.4861 Peripheral vascular disease 1.55 (0.68 – 3.54) 0.2997 1.07 (0.63 – 1.81) 0.8024 Hypertension, complicated 1.95 (1.30 – 2.91) 0.0011 0.89 (0.58 – 1.37) 0.5973 Hypertension, uncomplicated 0.87 (0.59 – 1.30) 0.5024 1.06 (0.80 – 1.42) 0.6666 Cerebrovascular disease 4.46 (2.19 – 9.40) <.0001 4.65 (2.34 – 9.23) 0.0002 Heart failure 2.47 (1.61 – 3.79) <.0001 1.62 (1.10 – 2.37) 0.0143 Valvular disease 1.18 (0.52 – 2.65) 0.6948 0.63 (0.38 – 1.06) 0.078 Clostridioides difficile 1.75 (0.38 – 8.1) 0.4756 1.51 (0.47 – 4.81) 0.4272 Liver disease, mild 1.04 (0.49 – 2.22) 0.9243 1.43 (0.88 – 2.32) 0.1461 Liver disease, moderate to severe 2.20 (0.61 – 7.90) 0.2282 1.24 (0.36 – 4.26) 0.691 Renal failure, moderate 1.48 (0.88 – 2.48) 0.1379 1.29 (0.86 – 1.94) 0.2208 Renal failure, severe 2.06 (1.01 – 4.2) 0.0477 2.02 (1.19 – 3.44) 0.0113 Diabetes mellitus with chronic complications 1.20 (0.76 – 1.90) 0.4421 0.77 (0.57 – 1.04) 0.0876 Diabetes mellitus without chronic complications 1.12 (0.62 – 2.02) 0.7154 1.16 (0.80 – 1.68) 0.4243 Malignant Neoplasms 1.39 (0.82– 2.35) 0.2187 0.89 (0.64 – 1.23) 0.4787 Paralysis 1.63 (0.62– 4.32) 0.3248 0.38 (0.17 – 0.88) 0.0272 Hypothyroidism 0.88 (0.52– 1.47) 0.6107 0.56 (0.41– 0.78) 0.0007 Other thyroid disorders 1.16 (0.26 – 5.13) 0.8469 1.75 (0.59 – 5.16) 0.2597 Dementia 1.86 (1.08 – 3.22) 0.0255 0.52 (0.36 – 0.76) 0.0011 Depression 1.17 (0.73 – 1.88) 0.5159 1.05 (0.78 – 1.40) 0.7463 Neurological disorders affecting movement 1.83 (0.79 – 4.23) 0.1558 1.67 (0.97 – 2.89) 0.0629 Other neurological disorders 5.43 (3.52 – 8.39) <.0001 4.66 (3.31 – 6.56) <.0001 Seizures and epilepsy 0.98 (0.38 – 2.53) 0.9732 1.27 (0.69 – 2.31) 0.4229 Peptic ulcer with bleeding 2.18 (0.24 – 19.6) 0.4884 0.46 (0.04 –5.13) 0.3815 Obesity 0.91 (0.58 – 1.43) 0.6896 1.19 (0.90 – 1.57) 0.2214 Weight loss 3.51 (2.14 – 5.75) <.0001 17.5 (6.25 – 49.2) <.0001 Malnutrition 3.07 (1.82 – 5.17) <.0001 0.23 0.08 – 0.64) 0.0062 Immunity Disorders 1.60 (0.79 – 3.22) 0.1906 2.90 (1.81 – 4.65) <.0001 Use of Steroids 0.40 (0.16 – 1.02) 0.0531 0.39 (0.24 – 0.65) 0.0004 Use of NSAIDs 0.57 (0.08 – 4.39) 0.5926 0.64 (0.17 – 2.37) 0.4306 Substance Use Smoking 0.87 (0.58– 1.30) 0.5019 0.84 (0.66– 1.08) 0.1774 Alcohol Abuse 1.46 (0.50– 4.3) 0.4910 1.70 (0.81– 3.62) 0.1492 Drug Abuse - NS - NS 1 Univariate analysis was performed with logistic regression. 2 Multivariate analysis was performed with weighted multilevel mixed effect models. Table 3: Comparison of inpatient mortality, mean total charges, and length of stay between COVID-19 patients with IBD. vs. matched (age-, sex-, race) non-IBD NIS 2000. Mortality Length of Stay Total Charges Odds Ratio (95%CI) P value Difference (95%CI) P value Difference (95%CI) P value COVID with IBD 1.02 (0.78 – 1.34) 0.8851 0.49 (-0.17 – 1.16) 0.1501 $ 5379 (-$4707 – $15465) 0.2958 COVID without IBD Reference NA Reference NA Reference NA Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. 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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-3962562","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":274908606,"identity":"aaa05f24-a5b8-489e-b250-1bee1e1cf359","order_by":0,"name":"Rubaid Azhar Dhillon","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYDACCQYGZiAlZwDmGVgQr8XYAEwZSBCvJXEDmGIgQov57ObHnwtq7qVvZ+8/uuFHgQQDf3t3Al4tMneOGRjPOFacu7PnMNvNHqDDJM6c3YDfXRIJBsk8bAm5G24ks93gAWoxkMglpCX9w2GefwnpBkAtN/8QpyXHsJm3LSEBpOU2cbbInClm5u1LMNxw5rDZbRkDCR7CfpFu3/yZ51uCvMHxxmc33/yxkeNv78WvBQPwkKZ8FIyCUTAKRgFWAAAbKUKyeRLpSQAAAABJRU5ErkJggg==","orcid":"","institution":"Riphah Medical College","correspondingAuthor":true,"prefix":"","firstName":"Rubaid","middleName":"Azhar","lastName":"Dhillon","suffix":""},{"id":274908607,"identity":"04001006-be9f-45dc-8547-d6f89138dbfd","order_by":1,"name":"Maryam Bilal Haider","email":"","orcid":"","institution":"University of Chicago Medical Center/NorthShore","correspondingAuthor":false,"prefix":"","firstName":"Maryam","middleName":"Bilal","lastName":"Haider","suffix":""},{"id":274908608,"identity":"62fc53fd-2f9d-4a9b-8ba9-2d84b88247fd","order_by":2,"name":"Ahmed Jamal Chaudhary","email":"","orcid":"","institution":"DMC/Wayne State University-Sinai Grace Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ahmed","middleName":"Jamal","lastName":"Chaudhary","suffix":""},{"id":274908609,"identity":"70a2c452-4d5a-464f-ade9-15f0ddd5eb8c","order_by":3,"name":"Zahra Abbas","email":"","orcid":"","institution":"Sharif Medical and Dental College","correspondingAuthor":false,"prefix":"","firstName":"Zahra","middleName":"","lastName":"Abbas","suffix":""}],"badges":[],"createdAt":"2024-02-16 23:16:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3962562/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3962562/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54843343,"identity":"2d18ff37-ba97-4a57-ba9b-e3f88e88885e","added_by":"auto","created_at":"2024-04-17 14:26:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":383545,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3962562/v1/7bcf3760-3f9c-441d-856b-30667eff0d12.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Examining the Intersection of Inflammatory Bowel Disease and COVID-19: Insights from a National Inpatient Database Study","fulltext":[{"header":"Background","content":"\u003cp\u003eToward the close of 2019, a novel pathogen known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged within Wuhan, China [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Subsequent to its initial appearance in China, this virus rapidly disseminated across the globe, prompting the World Health Organization (WHO) to declare a worldwide pandemic on March 12, 2020 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. According to the existing body of knowledge, individuals with preexisting underlying health conditions, advanced age, and a compromised immune system are inclined to face increased susceptibility to contracting the virus [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In the event of infection, these particular patient demographics are more susceptible to experiencing complications, thus exerting an adverse impact on their overall prognosis.\u003c/p\u003e \u003cp\u003eInflammatory bowel disease (IBD) encompasses a chronic, immune-mediated inflammatory disorder affecting the digestive tract, comprising ulcerative colitis and Crohn's disease. The underlying pathogenesis of IBD is believed to involve immune response dysregulation toward resident microorganisms in genetically predisposed individuals [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The primary objective of IBD treatment is to regulate this heightened immune response. However, therapeutic interventions for IBD render patients more susceptible to infections. Despite the absence of definitive evidence, it remains uncertain whether individuals with inflammatory bowel disease (IBD) are inherently more prone to contracting COVID-19. Nevertheless, the underlying disease mechanisms and pharmacological treatments for IBD could render these patients more susceptible to the virus [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe cellular entry of a virus is contingent upon binding to the angiotensin converting enzyme (ACE2) receptor protein. This receptor is ubiquitously distributed across organs, including the lungs, heart, kidneys, stomach, and, notably, ileum and colon [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Interestingly, in IBD patients, the ACE2 receptor is upregulated, potentially increasing susceptibility to the virus. An analysis of tissue samples from IBD patients revealed greater ACE2 expression in Crohn's disease patients than in those with ulcerative colitis [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Furthermore, the immunosuppressive therapies prescribed for IBD patients can further compromise their resistance to infections [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Despite these implications, the World Health Organization (WHO) has not issued specific protective recommendations for IBD patients in the context of COVID-19 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Throughout the pandemic, the International Organization for the Study of IBD (IOIBD) has provided consistent guidance, advocating for the uninterrupted continuation of therapies while advising temporary discontinuation only in cases of active infection [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGiven the substantial incidence of IBD across the United States, our objective was to discern the clinical indicators and consequences observed among COVID-19-positive IBD patients, specifically in relation to age, sex, socioeconomic status, and geographic location. By harnessing the national inpatient database, our intention was to narrow the knowledge gap pertaining to the determinants influencing outcomes in individuals with and without IBD who contracted COVID-19, thereby impacting the broader landscape of healthcare provision in the US. Considering the intricate nature of COVID-19, a comprehensive, multidisciplinary strategy might be imperative when dealing with IBD patients, with the potential to enhance patient outcomes in this context.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eWe conducted an analysis of the nationwide inpatient sample (NIS) database, focusing on the period from January 2020 to December 2020. The NIS database is a comprehensive and publicly accessible collection of hospitalization data in the United States. It serves the purpose of generating insights into inpatient usage, expenses, quality, and results at both the national and regional levels [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Our investigation employed the International Classification of Diseases (ICD)-10 codes for diagnoses and procedures [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. To safeguard the privacy of individual patients, medical professionals, and hospitals, all identifying information in the dataset was removed. Consequently, this research was considered exempt from Institutional Review Board (IRB) approval by Wayne State University, following the Health Insurance Portability and Accountability Act regulations [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe study included patients with either a primary or secondary diagnosis of COVID-19. Our study included patients diagnosed with both inflammatory bowel disease (IBD) and ulcerative colitis. The study population was categorized into two groups: those with COVID-19 alone (controls) and those with both COVID-19 and IBD (cases).\u003c/p\u003e\n\u003ch3\u003eOutcomes\u003c/h3\u003e\n\u003cp\u003eThe main objectives of this study were twofold: first, to assess demographic differences between individuals with COVID-19 with and without coexisting IBD and, second, to identify factors contributing to in-hospital mortality among COVID-19 patients with IBD. The secondary objectives involved the analysis of hospital utilization metrics, including inpatient mortality rates, length of hospital stay (LOS), and the total cost of care associated with inpatient hospital services for COVID-19 patients with IBD.\u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eVariables\u003c/h2\u003e \u003cp\u003eWe conducted a comparative analysis between two cohorts: COVID-19 patients diagnosed with IBD (patients) and those without IBD (controls). We assessed demographic attributes (age, sex, race, primary insurance coverage, and socioeconomic status), clinical manifestations, pertinent comorbidities, substance abuse, and hospital-related outcomes in both groups.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were conducted using SAS software (SAS Institute Inc., Cary, NC, United States). Continuous variables, including age, total charges, and length of stay, are represented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, while categorical variables are presented as frequencies and calculated percentages. Group comparisons between individuals with and without IBD were performed utilizing Student\u0026rsquo;s t test for continuous variables and Rao-Scott chi-square tests for categorical variables.\u003c/p\u003e \u003cp\u003eUnivariate analysis was carried out employing logistic regression, while multivariate analysis was accomplished through a weighted multilevel mixed-effects model utilizing the Glimmix procedure with maximum likelihood estimation and Gauss\u0026ndash;Hermite quadrature likelihood approximation. The exclusion criteria included patients younger than 18 years of age who were categorized into four subgroups according to the HCUP standard categories (18\u0026ndash;44, 45\u0026ndash;64, 65\u0026ndash;84, and \u0026ge;\u0026thinsp;85 years) for the purpose of group-level comparisons. Instances of missing values were categorized as either \"missing\" or \"unknown.\"\u003c/p\u003e \u003cp\u003eAll hypothesis testing was conducted at a two-tailed significance level of 0.05 (where a P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was deemed to indicate statistical significance).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eWithin the amassed dataset, a conspicuous gender disparity emerged in the IBD group\u0026nbsp;compared\u0026nbsp;with the non-IBD cohort, with a prevalence of 53.6% females in the former and 47.2% in the latter (P\u0026lt;0.001). Conversely, a notable male preponderance manifested within the non-IBD group. The mean age within both groups displayed a negligible difference: 64.7 \u0026plusmn; 16.1 for the non-IBD group and 64.3 \u0026plusmn; 15.7 for the IBD group. The IBD group was further partitioned into subgroups, with Crohn\u0026apos;s disease (CD) accounting for a\u0026nbsp;greater\u0026nbsp;proportion at 51.5%, while ulcerative colitis (UC) constituted 48.5%. Predominantly, hospitalizations within both\u0026nbsp;the IBD and non-IBD cohorts were concentrated in the age bracket of 65\u0026ndash;84 years, followed closely by the age group of\u0026nbsp;45\u0026ndash;64 years\u0026nbsp;(P\u0026lt;0.001) (Table 1).\u003c/p\u003e\n\u003cp\u003eEthnically, Caucasians represented more than half of\u0026nbsp;the hospitalizations in both cohorts: 51% in the non-IBD\u0026nbsp;group and 74.4% in the IBD\u0026nbsp;group. Noteworthy differences were noted regarding Hispanics:\u0026nbsp;20% in the non-IBD cohort and 8.5% in the IBD cohort. Medicare was the primary payer for a greater proportion of hospitalizations (56.9%) in the IBD group\u0026nbsp;than\u0026nbsp;in the non-IBD cohort (52.2%). Similarly, a\u0026nbsp;greater\u0026nbsp;percentage of IBD patients had a primary payer status of \u0026quot;private\u0026quot; (30.6%), in contrast to 27.6% among non-IBD patients. Bed size requirements were notably similar between the two groups, although a greater portion of IBD\u0026nbsp;patients\u0026nbsp;necessitated larger bed sizes (47.7%)\u0026nbsp;than did\u0026nbsp;non-IBD\u0026nbsp;patients\u0026nbsp;(45.4%).\u003c/p\u003e\n\u003cp\u003eRegarding their geographical distribution and affiliation with teaching institutions, a considerable percentage of hospitalizations occurred within urban teaching hospitals for both cohorts (68.9% in the non-IBD cohort and 70.9% in the IBD cohort). Geographically, a substantial contingent of patients in both groups originated from the southern and mid-western/north central regions of the United States.\u003c/p\u003e\n\u003cp\u003eThe routine discharge rates were almost equivalent between non-IBD and IBD patients (54.6% versus 53.7%). Conversely, a notable upswing was observed in IBD hospitalizations designated for Home Health Care (HCC) (15.3%). While scrutinizing mortality rates, slightly higher mortality was evident among non-IBD patients (11.2%) than among IBD patients (10.3%). There were no significant differences in the clinical symptoms between the two groups, although both groups experienced higher levels of symptoms such as malaise and fatigue, diarrhea, and nausea and vomiting. Through both univariate and multivariate analyses, we identified sex, age, and specific existing health conditions (such as neurological disorders, weight loss, and immune disorders) (Table 2). On the other hand, there was no significant difference observed between length of stay and total hospital charges when comparing both cohorts (Table 3).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe available data regarding the clinical attributes and outcomes within the cohort of COVID-19 patients, considering the presence or absence of IBD, are notably limited. The precise extent of infection risk among individuals with IBD remains unclear and is potentially influenced by variables such as age or genetic predisposition. Throughout the pandemic, there has been a heightened focus on the management and prognosis of IBD patients who have contracted the infection. In the initial stages of the pandemic, a handful of studies suggested that individuals with IBD might be at a lower risk of contracting COVID-19 than the broader population. Notably, investigations conducted by Ren Mao et al. in China [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] and Carlos Taxonera et al. in Italy [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] reported no COVID-19 cases within the IBD populations they examined. This finding was corroborated by a meta-analysis undertaken by Aziz et al. in 2020 [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], which synthesized findings from six studies encompassing a collective IBD patient sample of 9177 individuals. The meta-analysis demonstrated an aggregate incidence of 0.3% COVID-19 in the IBD patient population, a figure falling within the lower spectrum of the general population's incidence range (0.2\u0026ndash;4.0%). Notably, the enhanced adherence of IBD patients to hygienic and preventive measures might confound the relationship between the two diseases, warranting cautious interpretation.\u003c/p\u003e \u003cp\u003eAccording to the CDC [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], 3.1\u0026nbsp;million (1.3%) adults in the USA are diagnosed with IBD, which includes both Crohn\u0026rsquo;s disease and ulcerative colitis. Given the dearth of comprehensive guidelines and available data pertaining to the interaction between COVID-19 and this specific patient demographic, we undertook a study aimed at scrutinizing IBD patients who were also diagnosed with COVID-19. This study entailed a comparative evaluation, contrasting IBD patients with their non-IBD counterparts across multiple dimensions, including sociodemographic attributes, clinical manifestations of COVID-19, concurrent comorbidities, duration of hospitalization, and mortality rates.\u003c/p\u003e \u003cp\u003eA retrospective cohort study conducted in the United States to assess the risk and outcomes of COVID-19 in IBD patients revealed a detrimental impact of steroid use on patient outcomes. Notably, this study reported a lower incidence of COVID-19 in the IBD patient population than in the non-IBD patient population [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. However, within the COVID-19-affected IBD cohort, a heightened likelihood of hospitalization and critical care was observed, potentially attributed to some patients experiencing an IBD flare at the 3-month follow-up [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. This may explain the larger bed size observed in our data among the IBD cohort than among the non-IBD cohort. Given the susceptibility of IBD patients to complications, whether attributed to advanced age, underlying conditions, or the use of biological agents, vigilant postdischarge monitoring is warranted. This observation may also explain the greater reliance on home health care (HCC) for IBD patients in our dataset than for their non-IBD counterparts. Using nationwide patient sample (NIS) data, Nguyen et al. analyzed US hospitals for the presence of methicillin-resistant \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (MRSA) infection in IBD patients [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The study demonstrated an augmented MRSA risk in IBD patients, correlated with a heightened fatality rate [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Alongside the consideration of the presence of COVID-19 among IBD patients, prudent measures against nosocomial infections within this patient demographic population have become imperative.\u003c/p\u003e \u003cp\u003eOur data revealed that there was a greater percentage of females in the IBD cohort. It is well known that female sex is a risk factor for the development of IBD; however, the complex pathogenesis of IBD also involves genetic susceptibility and external environmental triggers such as medication use and dietary changes [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. A study conducted in the USA over the span of five years revealed a greater incidence of IBD among females than among males [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, a large-scale analysis in 2019 of 11 Asian-Pacific countries revealed a significantly greater incidence of IBD among the male population [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. This suggests that sex-based differences may be correlated with environmental and geographical factors in disease epidemiology. A male predominance was also observed in an IBD meta-analysis conducted in China, and the articles included in this meta-analysis mainly consisted of patients with low-grade severity when compared to the IBD cohorts from Belgium and France [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. This could suggest that the incidence and prevalence of sex-based differences are correlated with disease severity. According to several large-scale studies, a female predominance has been observed in patients with inflammatory bowel disease in Western countries [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Hence, this may explain the greater number of females observed in our cohort of COVID-19 patients with IBD. Apart from the genetic, sex, environmental, and geographical factors that have been examined, the greater occurrence of IBD in females might also be associated with the use of oral contraceptives [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In a substantial cohort study conducted in the United States involving more than 200,000 women, a connection was established between the use of oral contraceptives and increased susceptibility to IBD [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Similarly, a separate case‒control study utilizing the United Kingdom General Practice Research Database also indicated a heightened risk of IBD linked to the utilization of oral contraceptives [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Moreover, within the limits of the limited available data, gender disparities have been noted in terms of COVID-19 hospitalization and mortality. An analysis encompassing data provided by the CDC revealed that more than a million COVID-19 cases in the United States indicated a greater frequency of ICU admissions and elevated fatality rates among males compared to females [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The mechanism underlying this sex-specific susceptibility to COVID-19 is potentially linked to ACE2 and transmembrane protease serine 2 (TMPRSS2) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. As previously discussed, given the correlation between increased ACE2 expression and increased COVID-19 susceptibility, research has revealed increased ACE2 expression among males [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Furthermore, the expression of TMPRSS2, a significant player in COVID-19 cell entry, is increased in males due to the presence of androgen receptors [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. These mechanisms may explain the male predominance observed in our non-IBD cohort, where the presence of COVID-19 and comorbidities were sufficient to increase the mortality rate to a rate similar to that of the IBD cohort. While ACE2 is also expressed in females, the inhibitory impact of estrogen on ACE2 may confer some level of defense against COVID-19 [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. However, a study conducted on IBD patients with a history of COVID-19 infection reported that the prevalence of long COVID-19 was greater among female patients [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Another study on long COVID-19 in IBD patients also reported the same findings [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Due to the difference in immune response based on sex, it seems that females may have a continued systemic inflammatory reaction for long COVID-19 symptoms to develop. Thus, continuous monitoring is crucial for the early identification of complications in these patients. Further research is essential to determine the influence of long COVID-19 on the clinical progression of IBD patients.\u003c/p\u003e \u003cp\u003eOur study revealed comparable mortality rates between the IBD and non-IBD patient groups. A US cohort study utilizing federal health data also reported no difference in mortality between these groups in the presence of COVID-19 [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. During the pandemic, it is possible that only the most critical patients were admitted and that the increase in SARS-CoV-2 infection had no effect on patient outcomes. With SARS-CoV-2 detected in stool samples and ACE2 upregulation, one might assume that IBD patients are at a greater risk of infection [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. However, according to the literature, there is no correlation between these factors and the infectivity rate or severity of COVID-19 in IBD patients. The use of immune-mediated therapies in IBD patients might increase the risk of infection; however, it is hypothesized that these same therapies could also provide protection against the cytokine storm or inflammatory response associated with severe COVID-19 [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. According to the data released by the three largest tertiary IBD centers in Wuhan, China, no cases of COVID-19 were reported at these centers [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Another set of data was also released by a tertiary center located in northern Italy, which had one of the highest COVID-19 rates early in the pandemic. Based on the data, 522 IBD patients admitted to this center during that time reported no cases of COVID-19 for the remainder of their stay at the hospital [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. It is quite possible that immunosuppressive treatment might have offered protection against COVID-19 in these IBD patients. This may explain the similar mortality rates observed in our data among IBD and non-IBD patients.\u003c/p\u003e \u003cp\u003eOur data demonstrated that the majority of COVID-19 patients with IBD were admitted to urban teaching hospitals, particularly in the southern and midwestern regions. A meta-analysis from China on IBD highlighted a sudden increase in cases in southeastern areas following the adoption of a westernized lifestyle [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. This sudden rise suggests that environmental triggers underpin the disease, encompassing factors such as socioeconomic status, sanitation, infections, medications, and lifestyle practices [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Multiple studies, mirroring our findings, affirm that IBD is more prevalent in urban than in rural settings [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The discussed environmental risk factors for IBD are more commonly found in urban regions of western nations, elevating the risk of IBD development among residents. A study conducted in Sweden reported an increased risk of IBD among families with low socioeconomic status [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In our study, there was no significant correlation between the median income of families and IBD, which suggests that factors other than socioeconomic status influenced the development of the disease in these patients. However, it is quite possible that a portion of the patients analyzed in our study who did not have proper access to healthcare during the pandemic due to financial constraints may have had a higher fatality rate in both cohorts. Our data revealed that more than half of the patients in both cohorts were treated with Medicare, and the remaining patients were treated with Medicaid and private insurance. A study was conducted using the State Inpatient Database, where the prevalence of fragmentation in patient care was reported to be among one in four IBD patients and was associated with poor visit outcomes [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Fragmentation has been linked to certain factors, such as Medicaid recipients, preexisting neurological conditions, substance misuse, and urgent readmissions [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Our study aligns with this, as we connected neurological comorbidities and immune disorders to in-hospital mortality among IBD patients. Substance abuse showed no correlation in our dataset; however, a subset of IBD patients had Medicaid ties, warranting vigilant monitoring and tailored interventions for enhanced outcomes among vulnerable groups.\u003c/p\u003e \u003cp\u003eOur retrospective study represents the most comprehensive assessment to date of the COVID-19 patient population with IBD, evaluating both epidemiology and outcomes. To date, our study is the first to thoroughly analyze COVID-19 hospitalizations with and without IBD to identify factors associated with high-risk individuals. Our analysis integrated comorbidities, predictors of mortality, and clinical characteristics to assess patient outcomes. Given the restricted accessibility of centralized patient databases, population-based studies on COVID-19 hospitalizations for IBD patients within the United States have been limited. Our research thus contributes pivotal insights to healthcare authorities concerning the factors governing IBD incidence and prevalence amid COVID-19 hospitalizations. A significant strength of our study lies in its comprehensive comparison of COVID-19 hospitalizations with and without IBD, facilitating a nuanced comprehension of mortality influencers in both cohorts. Nonetheless, we recognize certain limitations inherent to this study. When utilizing extensive databases such as the NIS, potential distortion could arise from errors within the ICD-10 diagnostic coding system. Additionally, inpatient discharge data may solely represent participating hospitals within the Healthcare Cost and Utilization Project (HCUP) [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Moreover, the NIS database lacks information regarding disease severity or treatment details. The geographical distribution of patients revealed variations in terms of underlying comorbidities, genetic predispositions, and IBD medications, potentially impacting COVID-19 risk. Furthermore, given that COVID-19 can exacerbate gastrointestinal symptoms in non-IBD patients, distinguishing between IBD patients and non-IBD patients could be challenging [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this retrospective study indicated that the presence of IBD among COVID-19 patients does not significantly impact mortality. Nevertheless, the IBD condition can influence the clinical trajectory of these patients, subject to individual factors such as underlying comorbidities, age, sex, and environmental triggers. Vigilant monitoring of these patients is crucial, as the long-term implications of IBD in COVID-19 patients remain uncertain. Additional research is necessary to validate the influence of these factors on outcomes.\u003c/p\u003e \u003cp\u003eAlthough one might hypothesize that IBD patients are predisposed to COVID-19 complications, our findings reveal comparable lengths of stay and routine discharge in both cohorts. This could be attributed to accessible healthcare and timely interventions that averted complications. Given the intricacies of COVID-19, further investigation is essential to comprehend the biochemical interactions impacting the gastrointestinal system.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eIBD - Inflammatory bowel disease\u003c/p\u003e\n\u003cp\u003eNIS - Nationwide inpatient sample\u003c/p\u003e\n\u003cp\u003eWHO - World Health Organization\u003c/p\u003e\n\u003cp\u003eIOIBD - International Organization for the Study of IBD\u003c/p\u003e\n\u003cp\u003eACE2 - Angiotensin converting enzyme\u003c/p\u003e\n\u003cp\u003eSARS-CoV-2 - Severe acute respiratory syndrome coronavirus 2\u003c/p\u003e\n\u003cp\u003eLOS \u0026ndash; Length of Stay\u003c/p\u003e\n\u003cp\u003eIRB - Institutional Review Board\u003c/p\u003e\n\u003cp\u003eICD - International classification of diseases\u003c/p\u003e\n\u003cp\u003eCD - Crohn\u0026rsquo;s Disease\u003c/p\u003e\n\u003cp\u003eUC - Ulcerative Colitis\u003c/p\u003e\n\u003cp\u003eHCC - Home health Care\u003c/p\u003e\n\u003cp\u003eHCUP - Healthcare Cost and Utilization Project\u003c/p\u003e\n\u003cp\u003eTMPRSS2 - Transmembrane protease serine 2\u003c/p\u003e\n\u003cp\u003eMRSA - Methicillin-resistant Staphylococcus aureus\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthical Approval: Not Applicable\u003c/p\u003e\n\u003cp\u003eConsent for Publication: Not Applicable\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials: The datasets generated and/or analyzed during current study are publicly available\u0026nbsp;from the National Inpatient Sample (NIS) database.\u003c/p\u003e\n\u003cp\u003eCompeting Interests: The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding: None\u003c/p\u003e\n\u003cp\u003eAuthors\u0026rsquo; Contributions: In the development of our research, each author played a pivotal role. RD was instrumental in conceptualizing the study framework and led the data analysis segment, providing critical insights that shaped our findings. MBH contributed extensively to the literature review, meticulously sourcing and synthesizing relevant studies to establish a solid foundation for our research objectives. AJC took charge of the methodology section, designing the study\u0026apos;s approach with precision and overseeing the data collection process to ensure accuracy and reliability. Lastly, ZA played a key role in drafting and revising the manuscript, ensuring the clarity of presentation and coherence of the study\u0026apos;s arguments. Together, these contributions were vital in the completion of our research project.\u003c/p\u003e\n\u003cp\u003eAcknowledgements: Not applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eMagro F, Rahier JF, Abreu C, MacMahon E, Hart A, van der Woude CJ, Gordon H, Adamina M, Viget N, Vavricka S, Kucharzik T. Inflammatory bowel disease management during the COVID-19 outbreak: the ten do\u0026rsquo;s and don\u0026rsquo;ts from the ECCO-COVID taskforce. Journal of Crohn\u0026apos;s and Colitis. 2020 Oct;14(Supplement_3):S798-806.\u003c/li\u003e\n \u003cli\u003eGrunert PC, Reuken PA, Stallhofer J, Teich N, Stallmach A. Inflammatory bowel disease in the COVID-19 pandemic: the patients\u0026rsquo; perspective. Journal of Crohn\u0026apos;s and Colitis. 2020 Dec;14(12):1702-8.\u003c/li\u003e\n \u003cli\u003eAnanthakrishnan AN. Environmental risk factors for inflammatory bowel diseases: a review. 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The disease burden and clinical characteristics of inflammatory bowel disease in the Chinese population: a systematic review and meta-analysis. International journal of environmental research and public health. 2017 Mar;14(3):238.\u003c/li\u003e\n \u003cli\u003eThia KT, Loftus Jr EV, Sandborn WJ, Yang SK. An update on the epidemiology of inflammatory bowel disease in Asia. Official journal of the American College of Gastroenterology| ACG. 2008 Dec 1;103(12):3167-82.\u003c/li\u003e\n \u003cli\u003eKappelman MD, Rifas\u0026ndash;Shiman SL, Kleinman K, Ollendorf D, Bousvaros A, Grand RJ, Finkelstein JA. The prevalence and geographic distribution of Crohn\u0026rsquo;s disease and ulcerative colitis in the United States. Clinical Gastroenterology and Hepatology. 2007 Dec 1;5(12):1424-9.\u003c/li\u003e\n \u003cli\u003eBernstein CN, Blanchard JF, Kliewer E, Wajda A. Cancer risk in patients with inflammatory bowel disease: a population‐based study. Cancer. 2001 Feb 15;91(4):854-62.\u003c/li\u003e\n \u003cli\u003eKhalili H, Higuchi LM, Ananthakrishnan AN, Richter JM, Feskanich D, Fuchs CS, Chan AT. Oral contraceptives, reproductive factors and risk of inflammatory bowel disease. Gut. 2013 Aug 1;62(8):1153-9.\u003c/li\u003e\n \u003cli\u003eGarc\u0026iacute;a Rodr\u0026iacute;guez LA, GONZ\u0026Aacute;LEZ‐P\u0026Eacute;REZ A, Johansson S, Wallander MA. Risk factors for inflammatory bowel disease in the general population. Alimentary pharmacology \u0026amp; therapeutics. 2005 Aug;22(4):309-15.\u003c/li\u003e\n \u003cli\u003eStokes EK, Zambrano LD, Anderson KN, Marder EP, Raz KM, Felix SE, Tie Y, Fullerton KE. Coronavirus disease 2019 case surveillance\u0026mdash;United States, january 22\u0026ndash;may 30, 2020. Morbidity and Mortality Weekly Report. 2020 Jun 6;69(24):759.\u003c/li\u003e\n \u003cli\u003eCai H. Sex difference and smoking predisposition in patients with COVID-19. The Lancet Respiratory Medicine. 2020 Apr 1;8(4):e20.\u003c/li\u003e\n \u003cli\u003eGargaglioni LH, Marques DA. Let\u0026rsquo;s talk about sex in the context of COVID-19. Journal of applied physiology. 2020 Jun 1;128(6):1533-8.\u003c/li\u003e\n \u003cli\u003eHoffmann M, Kleine-Weber H, Schroeder S, Kr\u0026uuml;ger N, Herrler T, Erichsen S, Schiergens TS, Herrler G, Wu NH, Nitsche A, M\u0026uuml;ller MA. SARS-CoV-2 cell entry depends on ACE2 and TMPRSS2 and is blocked by a clinically proven protease inhibitor. cell. 2020 Apr 16;181(2):271-80.\u003c/li\u003e\n \u003cli\u003eSalvatori S, Baldassarre F, Mossa M, Monteleone G. Long COVID in Inflammatory Bowel Diseases. \u003cem\u003eJournal of Clinical Medicine\u003c/em\u003e. 2021; 10(23):5575.\u0026nbsp;\u003ca href=\"https://doi.org/10.3390/jcm10235575\"\u003ehttps://doi.org/10.3390/jcm10235575\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003eTorjesen I. Covid-19: Middle aged women face greater risk of debilitating long term symptoms. \u003cem\u003eBMJ News\u003c/em\u003e. 2021; 372:n829\u003c/li\u003e\n \u003cli\u003eQamar MA, Martins RS, Dhillon RA, Tharwani A, Irfan O, Suriya QF, Rizwan W, Khan JA, bin Sarwar Zubairi A. Residual symptoms and the quality of life in individuals recovered from COVID-19 infection: A survey from Pakistan. Annals of Medicine and Surgery. 2022 Mar 1;75:103361.\u003c/li\u003e\n \u003cli\u003eMolodecky NA, Kaplan GG. Environmental risk factors for inflammatory bowel disease. Gastroenterology \u0026amp; hepatology. 2010 May;6(5):339.\u003c/li\u003e\n \u003cli\u003eSingh S, Khan A, Chowdhry M, Bilal M, Kochhar GS, Clarke K. Risk of severe coronavirus disease 2019 in patients with inflammatory bowel disease in the United States: a multicenter research network study. Gastroenterology. 2020 Oct 1;159(4):1575-8.\u003c/li\u003e\n \u003cli\u003eXiao F, Tang M, Zheng X, Liu Y, Li X, Shan H. Evidence for gastrointestinal infection of SARS-CoV-2. Gastroenterology. 2020 May 1;158(6):1831-3.\u003c/li\u003e\n \u003cli\u003eChen C, Zhang XR, Ju ZY, He WF. Advances in the research of mechanism and related immunotherapy on the cytokine storm induced by coronavirus disease 2019. Zhonghua shao shang za zhi= Zhonghua shaoshang zazhi= Chinese journal of burns. 2020 Jun 1;36(6):471-5.\u003c/li\u003e\n \u003cli\u003eNorsa L, Indriolo A, Sansotta N, Cosimo P, Greco S, D\u0026rsquo;Antiga L. Uneventful course in patients with inflammatory bowel disease during the severe acute respiratory syndrome coronavirus 2 outbreak in Northern Italy. Gastroenterology. 2020 Jul 1;159(1):371-2.\u003c/li\u003e\n \u003cli\u003eLi X, Song P, Li J, Tao Y, Li G, Li X, Yu Z. The disease burden and clinical characteristics of inflammatory bowel disease in the Chinese population: a systematic review and meta-analysis. International journal of environmental research and public health. 2017 Mar;14(3):238.\u003c/li\u003e\n \u003cli\u003eMolodecky NA, Kaplan GG. Environmental risk factors for inflammatory bowel disease. Gastroenterology \u0026amp; hepatology. 2010 May;6(5):339.\u003c/li\u003e\n \u003cli\u003eBernstein CN. Assessing environmental risk factors affecting the inflammatory bowel diseases: a joint workshop of the Crohn\u0026apos;s \u0026amp; Colitis Foundations of Canada and the USA. Inflammatory bowel diseases. 2008 Aug 1;14(8):1139-46.\u003c/li\u003e\n \u003cli\u003eKlement E, Lysy J, Hoshen M, Avitan M, Goldin E, Israeli E. Childhood hygiene is associated with the risk for inflammatory bowel disease: a population-based study. Official journal of the American College of Gastroenterology| ACG. 2008 Jul 1;103(7):1775-82.\u003c/li\u003e\n \u003cli\u003eEKBOM A, ADAMI HO, HELMICK CG, JONZON A, ZACK MM. Perinatal risk factors for inflammatory bowel disease: a case-control study. American journal of epidemiology. 1990 Dec 1;132(6):1111-9.\u003c/li\u003e\n \u003cli\u003eCohen-Mekelburg SA, Rosenblatt R, Gold S, Steinlauf AF, Burakoff R, Scherl E, Unruh M. Su1863-Fragmented Care is Prevalent Among Hospitalized Inflammatory Bowel Disease Patients and is Associated with Worse Outcomes. Gastroenterology. 2018 May 1;154(6):S-612.\u003c/li\u003e\n \u003cli\u003eAlexoff A, Roginsky G, Zhou Y, Kalenda M, Minuskin K, Ehrenpreis ED. Inpatient costs for patients with inflammatory bowel disease and acute pancreatitis. Inflammatory Bowel Diseases. 2016 May 1;22(5):1095-100.\u003c/li\u003e\n \u003cli\u003eGalanopoulos M, Gkeros F, Doukatas A, Karianakis G, Pontas C, Tsoukalas N, Viazis N, Liatsos C, Mantzaris GJ. COVID-19 pandemic: Pathophysiology and manifestations from the gastrointestinal tract. World journal of gastroenterology. 2020 Aug 8;26(31):4579.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1:\u003c/strong\u003e Comparison of\u0026nbsp;patient demographics, hospital\u0026nbsp;characteristics, and clinical\u0026nbsp;presentations\u0026nbsp;among COVID-19\u0026nbsp;patients\u0026nbsp;with and without IBD.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"661\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDemographics and Hospital Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-IBD\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eWeighted n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIBD\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eWeighted n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eWeighted Total, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e1,043,535 (99.45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e5750 (0.55%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eUlcerative colitis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e2790 (48.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eCrohn\u0026rsquo;s disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e2960 (51.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e492,185 (47.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e3080 (53.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e551,350 (52.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e2670\u0026nbsp;(46.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eAge (y), mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e64.7\u0026nbsp;\u0026plusmn; 16.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e64.3\u0026nbsp;\u0026plusmn; 15.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e0.3327\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge groups (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e0.0061\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003e18-44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e125,625 (12.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e685 (11.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003e45-64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e357,510 (34.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e2010 (34.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003e65-84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e441,085 (42.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e2580 (44.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;=85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e119,315 (11.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e475 (8.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace/Ethnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e531,660 (51.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e4275 (74.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e187,240 (17.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e630 (11.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e208,490 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e490 (8.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eAsian or Pacific Islander\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e32,740 (3.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e60 (1.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eNative American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e10,550 (1.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e5 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e72,855 (7.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e290 (5.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimary Payer status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eMedicare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e544,890 (52.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e3270 (56.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eMedicaid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e121,030 (11.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e475 (8.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003ePrivate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e288,625 (27.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1760 (30.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eSelf-Pay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e35,715 (3.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e80 (1.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eNo Charge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e2575 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e25 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e50,700 (4.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e140 (2.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian household income for patient\u0026apos;s ZIP Code\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003e0-25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e352,135 (33.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1500 (26.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003e25-50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e284,225 (27.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1555(27.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;50-75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e224,920 (21.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1400 (24.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003e75-100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e165,855 (15.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1210 (21.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e16,400 (1.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e85 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospital Bed Size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e0.3018\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eSmall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e268,205 (25.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1425 (24.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e301,705 (28.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1580 (27.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eLarge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e473,625 (45.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e2745 (47.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLocation/teaching status of the hospital\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e0.3522\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e122,615 (11.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e605 (10.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eUrban nonteaching\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e201,530 (19.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1070 (18.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eUrban teaching\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e719,390 (68.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e4075 (70.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospital region\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eNortheast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e184,215 (17.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1175 (20.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eMidwest or North Central\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e242,720 (23.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1745 (30.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eSouth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e437,106 (41.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e2015 (35.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eWest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e179,494 (17.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e815 (14.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDischarge Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e0.4038\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eRoutine Discharge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e570,100 (54.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e3085 (53.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eTransfer to Short-term Hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e30,780 (3.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e165 (2.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eTransfer to other facilities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e185,940 (17.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1025 (17.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eHome Health Care (HHC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e140,070 (13.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e880 (15.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.83661119515885%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eIn-Hospital Mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.71104387291982%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e116,645 (11.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.49016641452345%\" valign=\"top\"\u003e\n \u003cp\u003eOverall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.708018154311649%\" valign=\"top\"\u003e\n \u003cp\u003e595 (10.3%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.254160363086234%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.476683937823836%\" valign=\"top\"\u003e\n \u003cp\u003eCrohn\u0026rsquo;s Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.523316062176164%\" valign=\"top\"\u003e\n \u003cp\u003e305 (5.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.476683937823836%\" valign=\"top\"\u003e\n \u003cp\u003eUlcerative Colitis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.523316062176164%\" valign=\"top\"\u003e\n \u003cp\u003e290 (5.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical Presentation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-IBD\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eWeighted n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIBD\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eWeighted n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eFever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e14215 (1.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e75 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e0.8652\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eCough\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e10525 (1.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e60 (1.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e0.9121\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eShortness of breath\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e17780 (1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e135 (2.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e0.0890\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eMalaise and fatigue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e46615 (4.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e215 (3.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e0.2290\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eAnorexia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e11795 (1.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e50 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e0.4062\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eAltered Mental Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e5435 (0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e10 (0.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e0.1034\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eAbdominal pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e9810 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e75 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e0.1965\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eDiarrhea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e61460 (\u003cstrong\u003e5.9%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e245 (4.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e0.0187\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eNausea and Vomiting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e23730 (2.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e85 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e0.0681\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.87878787878788%\" valign=\"top\"\u003e\n \u003cp\u003eLoss of small/Taste\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.757575757575758%\" valign=\"top\"\u003e\n \u003cp\u003e6990 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.09090909090909%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e65 (1.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.272727272727273%\" valign=\"top\"\u003e\n \u003cp\u003e0.2699\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e1\u0026nbsp;\u003c/sup\u003eTwo-sample Student \u003cem\u003et\u003c/em\u003e test, 2-tailed for comparing means of two continuous variables.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003e Rao‒Scott chi‒square\u0026nbsp;2-tailed\u0026nbsp;test\u0026nbsp;for\u0026nbsp;associations between two categorical variables.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003e Rao‒Scott chi‒square test, 2-tailed test for 2-by-\u003cem\u003en\u003c/em\u003e tables. Statistical significance illustrated that the two groups differed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u003c/strong\u003e Univariate and multivariate analyses of demographics and clinical factors associated with in-hospital mortality in IBD patients with COVID-19.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMortality\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnadjusted odds ratio\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted odds ratio\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUnivariate Analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMultivariate Analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGender, Female vs. Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.72 (0.49 \u0026ndash; 1.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0907\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.60 (0.48 \u0026ndash; 0.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge groups (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18-44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45-64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.2 (1.1 \u0026ndash; 61.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0397\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.1 (4.82 \u0026ndash; 35.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65-84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22.4 (3.09 \u0026ndash; 162.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e37.3 (12.9 \u0026ndash; 107.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;=85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40.9 (5.41 \u0026ndash; 309.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e79.3 (25.3 \u0026ndash; 248.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace/Ethnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.62 (0.31 \u0026ndash; 1.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.1917\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.59 (0.37 \u0026ndash; 1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.82 (0.34 \u0026ndash; 1.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.5851\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.39 (0.91 \u0026ndash; 2.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAsian or Pacific Islander\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.74 (0.09 \u0026ndash; 5.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.7704\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.33 (0.06 \u0026ndash; 2.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNative American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.76 (0.30 \u0026ndash; 1.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.5748\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.67 (0.38 \u0026ndash; 1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimary Payer status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMedicare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMedicaid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.55 (0.26 \u0026ndash; 1.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.1189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.43 (0.85 \u0026ndash; 2.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrivate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.27 (0.15 \u0026ndash; 0.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.70 (0.48 \u0026ndash; 1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSelf-Pay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNo Charge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.46 (0.11 \u0026ndash; 1.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.2931\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.08 (0.47 \u0026ndash; 2.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian household income for patient\u0026apos;s ZIP Code\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0-25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e25-50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.99 (0.59 \u0026ndash; 1.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.9858\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.99 (0.59 \u0026ndash; 1.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;50-75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.89 (0.51 \u0026ndash; 1.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.6721\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.89 (0.51 \u0026ndash; 1.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75-100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.18 (0.69 \u0026ndash; 2.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.5431\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.18 (0.69 \u0026ndash; 2.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.54 (0.07 \u0026ndash; 4.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.5594\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.54 (0.07 \u0026ndash; 4.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAIDS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.54 (0.07 \u0026ndash; 4.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.9715\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.49 (0.09 \u0026ndash; 2.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.3253\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDeficiency anemias\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.46 (0.94 \u0026ndash; 2.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0893\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.97 (0.74 \u0026ndash; 1.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.8498\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAutoimmune conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.25 (0.64 \u0026ndash; 2.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.5171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.83 (1.21 \u0026ndash; 2.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.0054\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChronic blood loss anemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.94 (0.41 \u0026ndash; 9.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.3998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.12 (0.46 \u0026ndash; 9.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.2147\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCoagulopathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.75 (1.07 \u0026ndash; 2.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.56 (1.14 \u0026ndash; 2.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.0063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAsthma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.53 (0.25 \u0026ndash; 1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0955\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.14 (0.74 \u0026ndash; 1.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.5491\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCOPD and Bronchiectasis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.40 (0.90 \u0026ndash; 2.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.1345\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.12 (0.85 \u0026ndash; 1.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.4329\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAcute Pulmonary Embolism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.12 (0.39 \u0026ndash; 3.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.8313\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.53 (0.74 \u0026ndash; 3.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.2264\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePulmonary circulation disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.66 (0.15 \u0026ndash; 2.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.5756\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.21 (0.08 \u0026ndash; 1.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.0025\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCoronary Artery Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.48 (0.95 \u0026ndash; 2.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0813\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.91 (0.68 \u0026ndash; 1.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.4861\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePeripheral vascular disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.55 (0.68 \u0026ndash; 3.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.2997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.07 (0.63 \u0026ndash; 1.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.8024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHypertension, complicated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.95 (1.30 \u0026ndash; 2.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.89 (0.58 \u0026ndash; 1.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.5973\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHypertension, uncomplicated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.87 (0.59 \u0026ndash; 1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.5024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.06 (0.80 \u0026ndash; 1.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.6666\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCerebrovascular disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.46 (2.19 \u0026ndash; 9.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.65 (2.34 \u0026ndash; 9.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.0002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHeart failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.47 (1.61 \u0026ndash; 3.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.62 (1.10 \u0026ndash; 2.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.0143\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eValvular disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.18 (0.52 \u0026ndash; 2.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.6948\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.63 (0.38 \u0026ndash; 1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eClostridioides difficile\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.75 (0.38 \u0026ndash; 8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.4756\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.51 (0.47 \u0026ndash; 4.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.4272\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLiver disease, mild\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.04 (0.49 \u0026ndash; 2.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.9243\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.43 (0.88 \u0026ndash; 2.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.1461\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLiver disease, moderate to severe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.20 (0.61 \u0026ndash; 7.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.2282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.24 (0.36 \u0026ndash; 4.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.691\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRenal failure, moderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.48 (0.88 \u0026ndash; 2.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.1379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.29 (0.86 \u0026ndash; 1.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.2208\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRenal failure, severe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.06 (1.01 \u0026ndash; 4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0477\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.02 (1.19 \u0026ndash; 3.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.0113\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDiabetes mellitus with chronic complications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.20 (0.76 \u0026ndash; 1.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.4421\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.77 (0.57 \u0026ndash; 1.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.0876\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDiabetes mellitus without chronic complications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.12 (0.62 \u0026ndash; 2.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.7154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.16 (0.80 \u0026ndash; 1.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.4243\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMalignant Neoplasms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.39 (0.82\u0026ndash; 2.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.2187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.89 (0.64 \u0026ndash; 1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.4787\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eParalysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.63 (0.62\u0026ndash; 4.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.3248\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.38 (0.17 \u0026ndash; 0.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.0272\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHypothyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.88 (0.52\u0026ndash; 1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.6107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.56 (0.41\u0026ndash; 0.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.0007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOther thyroid disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.16 (0.26 \u0026ndash; 5.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.8469\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.75 (0.59 \u0026ndash; 5.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.2597\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDementia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.86 (1.08 \u0026ndash; 3.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.52 (0.36 \u0026ndash; 0.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.0011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.17 (0.73 \u0026ndash; 1.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.5159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.05 (0.78 \u0026ndash; 1.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.7463\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNeurological disorders affecting movement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.83 (0.79 \u0026ndash; 4.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.1558\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.67 (0.97 \u0026ndash; 2.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.0629\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOther neurological disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.43 (3.52 \u0026ndash; 8.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.66 (3.31 \u0026ndash; 6.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSeizures and epilepsy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.98 (0.38 \u0026ndash; 2.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.9732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.27 (0.69 \u0026ndash; 2.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.4229\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePeptic ulcer with bleeding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.18 (0.24 \u0026ndash; 19.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.4884\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.46 (0.04 \u0026ndash;5.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.3815\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.91 (0.58 \u0026ndash; 1.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.6896\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.19 (0.90 \u0026ndash; 1.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.2214\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWeight loss\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.51 (2.14 \u0026ndash; 5.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17.5 (6.25 \u0026ndash; 49.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMalnutrition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.07 (1.82 \u0026ndash; 5.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.23 0.08 \u0026ndash; 0.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.0062\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eImmunity Disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.60 (0.79 \u0026ndash; 3.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.1906\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.90 (1.81 \u0026ndash; 4.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUse of Steroids\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.40 (0.16 \u0026ndash; 1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.39 (0.24 \u0026ndash; 0.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.0004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUse of NSAIDs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.57 (0.08 \u0026ndash; 4.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.5926\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.64 (0.17 \u0026ndash; 2.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.4306\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubstance Use\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.87 (0.58\u0026ndash; 1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.5019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.84 (0.66\u0026ndash; 1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.1774\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAlcohol Abuse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.46 (0.50\u0026ndash; 4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.4910\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.70 (0.81\u0026ndash; 3.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.1492\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDrug Abuse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e1\u0026nbsp;\u003c/sup\u003eUnivariate analysis\u0026nbsp;was\u0026nbsp;performed with logistic regression.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003e Multivariate analysis was performed with weighted multilevel mixed effect models.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3:\u003c/strong\u003e Comparison of inpatient mortality, mean total charges, and length of stay between COVID-19 patients with IBD. vs. matched (age-, sex-, race) non-IBD NIS 2000.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"643\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.751166407465007%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"26.438569206842924%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eMortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.149300155520994%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eLength of Stay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.66096423017107%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eTotal Charges\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.751166407465007%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.195956454121305%\" valign=\"top\"\u003e\n \u003cp\u003eOdds Ratio\u003c/p\u003e\n \u003cp\u003e(95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.242612752721618%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.684292379471227%\" valign=\"top\"\u003e\n \u003cp\u003eDifference\u003c/p\u003e\n \u003cp\u003e(95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.465007776049767%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003evalue\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.418351477449455%\" valign=\"top\"\u003e\n \u003cp\u003eDifference\u003c/p\u003e\n \u003cp\u003e(95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.242612752721618%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.751166407465007%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCOVID with IBD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.195956454121305%\" valign=\"top\"\u003e\n \u003cp\u003e1.02 (0.78 \u0026ndash; 1.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.242612752721618%\" valign=\"top\"\u003e\n \u003cp\u003e0.8851\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.684292379471227%\" valign=\"top\"\u003e\n \u003cp\u003e0.49 (-0.17 \u0026ndash; 1.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.465007776049767%\" valign=\"top\"\u003e\n \u003cp\u003e0.1501\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.418351477449455%\" valign=\"top\"\u003e\n \u003cp\u003e$\u0026nbsp;5379\u003c/p\u003e\n \u003cp\u003e(-$4707 \u0026ndash; $15465)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.242612752721618%\" valign=\"top\"\u003e\n \u003cp\u003e0.2958\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.751166407465007%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCOVID without IBD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.195956454121305%\" valign=\"top\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.242612752721618%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.684292379471227%\" valign=\"top\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.465007776049767%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.418351477449455%\" valign=\"top\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.242612752721618%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Inflammatory Bowel Disease, Coronavirus Disease 2019, Nationwide inpatient sample","lastPublishedDoi":"10.21203/rs.3.rs-3962562/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3962562/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis study aimed to investigate the clinical indicators and outcomes of COVID-19-positive patients with inflammatory bowel disease (IBD), focusing on age, sex, socioeconomic status, and geographic location. The objective of this study was to fill the knowledge gap regarding determinants influencing outcomes in individuals with and without IBD who contracted COVID-19, thus impacting healthcare provision.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis study utilized the nationwide inpatient sample (NIS) database for the period from January to December 2020. Patients were categorized into those with COVID-19 alone (controls) and those with both COVID-19 and IBD (cases). Demographic, clinical, and hospital-related variables were analyzed using statistical methods, including t tests and chi-square tests. Logistic and multivariate regression analyses were performed to assess factors affecting mortality.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAmong COVID-19 patients with IBD, a sex disparity was observed, with more females in the IBD group than in the non-IBD group. The mean age was similar in both groups. Hospitalizations were concentrated in the age group of 65\u0026ndash;84 years. Ethnically, Caucasians dominated both cohorts, and Medicare was the primary payer for a greater proportion of hospitalizations in the IBD group. Hospitalizations were prevalent in urban teaching hospitals, primarily in the southern and mid-western regions of the US. There were no significant differences in mortality rates, and clinical symptoms were comparable between the two groups. Factors associated with mortality included sex, age, and specific existing health conditions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eContrary to the initial hypothesis, the presence of IBD among COVID-19 patients did not significantly impact mortality rates. However, certain clinical indicators and outcomes are influenced by individual factors such as age, sex, and underlying health conditions. This study emphasizes the need for careful monitoring of COVID-19 patients with IBD, particularly those with additional risk factors. Further research is necessary to fully understand the biochemical interactions and implications of IBD in the context of COVID-19. This comprehensive study contributes valuable insights to healthcare authorities, aiding in patient management and outcome optimization.\u003c/p\u003e","manuscriptTitle":"Examining the Intersection of Inflammatory Bowel Disease and COVID-19: Insights from a National Inpatient Database Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-27 07:06:45","doi":"10.21203/rs.3.rs-3962562/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fde76d7d-362a-4d0d-9ebf-1866df1f5224","owner":[],"postedDate":"February 27th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-17T14:26:44+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-27 07:06:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3962562","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3962562","identity":"rs-3962562","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}