One-Year Mortality and Associated Factors in Older Hospitalized COVID-19 Survivors: A Nationwide Cohort Study in Korea

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Methods Using a COVID-19 dataset from the Korean National Health Insurance System, this study’s evaluation period spanned from October 8, 2020, to December 31, 2021. The primary outcome was the 1-year mortality rate following hospital discharge. A logistic regression model was employed for multivariable analysis to estimate the odds ratios for the outcomes, and the Kaplan-Meier method was used to analyze differences in 1-year survival rates. Results Of the 66,810 COVID-19 patients aged 60 years or older who were hospitalized during the study period, the in-hospital mortality rate was 4.8% (n = 3219). Among the survivors (n = 63,369), the 1-year mortality rate was 4.9% (n = 3093). Non-survivors, compared to survivors, were significantly older (79.2 ± 9.5 vs. 68.9 ± 7.8, P < .001) and exhibited a lower rate of COVID-19 vaccination (63.1% vs. 91.8%, P < .001). Additionally, non-survivors experienced a higher incidence of organ dysfunction, and a greater proportion required mechanical ventilation (14.6% vs. 1.0%, P < .001) and extracorporeal membrane oxygenation (4.0% vs. 0.1%, P < .001). Multivariable logistic regression analysis identified older age, male sex, immunosuppression, organ dysfunction, severity of illness, and corticosteroid use during hospitalization as factors associated with death within 1 year after hospital discharge. However, vaccination was found to have a long-term protective effect against mortality among COVID-19 survivors. Conclusions and Implications The 1-year mortality rate after hospital discharge for older COVID-19 patients was comparable to the in-hospital mortality rate for these patients in Korea. The long-term mortality rate among hospitalized older COVID-19 patients was influenced by demographic factors and the severity of illness experienced during hospitalization. Health sciences/Medical research Health sciences/Risk factors COVID-19 Survivors Mortality Age Factors Critical Illness Figures Figure 1 Figure 2 Figure 3 Introduction The manifestations of COVID-19 range from asymptomatic cases to life-threatening acute respiratory distress syndrome 1 . It is estimated that approximately 16% of patients with COVID-19 succumb to the disease while hospitalized 2 . Even after recovering from the acute phase of the illness, long-term symptoms may persist in COVID-19 survivors 3 . Long COVID syndrome can affect various organ systems and can manifest with a variety of symptoms, such as fatigue, chest pain, and cough. Factors such as immune dysregulation, autoimmunity, and endothelial abnormalities may play crucial roles in the development of long COVID syndrome 4 . The enduring impact of COVID-19 extends beyond physical and mental health issues to include increased mortality. Iwashyna et al. found that individuals who had contracted COVID-19 faced a twofold increase in mortality risk within 2 years compared to those not infected with SARS-CoV-2 5 . The risk of long-term mortality is affected by factors such as age and the severity of the SARS-CoV-2 infection 6,7 . A Swedish nationwide cohort study (N = 8392) reported a 360-day mortality rate of 29.8% following intensive care unit (ICU) admission, with male sex, advanced age, and various comorbidities being significant contributors to mortality 6 . The severity of COVID-19 is often gauged by the type of oxygen therapy administered 8 , but the correlation between the severity of the disease and long-term mortality remains unclear. Additionally, Hägglöf et al. observed that the 1-year mortality rate was 1.33 times higher in men than in women 6 . However, given the considerable variation in long-term mortality rates from COVID-19 across different countries and regions 9 , such findings should be interpreted with caution. While several studies have been conducted 6,7,9 , data on the long-term mortality of COVID-19 survivors, particularly among older adults, and the associated risk factors remain scarce. In Korea, the mortality rate from COVID-19 was relatively low, attributed to stringent quarantine measures 10 , but the older demographic experienced an increase in excess mortality during the pandemic 11 . Therefore, this study aimed to investigate the 1-year mortality rate and associated risk factors among older survivors of COVID-19. Results Study Population During the study period, 576,613 patients were confirmed to have COVID-19 (Fig. 1 ). After excluding patients under 60 years of age (n = 433,943) and those not hospitalized (n = 75,860), 66,810 older patients with COVID-19 were hospitalized. Additionally, we excluded patients who died in the hospital (n = 3219, representing a 4.8% in-hospital mortality rate) and those with missing data (n = 222). Ultimately, 63,369 survivors of hospitalized COVID-19 were analyzed. Within 1 year, we compared survivors (n = 60,276, 95.1%) to non-survivors (n = 3093, 4.9%). Patient Characteristics Compared with survivors, non-survivors were significantly older (79.2 ± 9.5 vs. 68.9 ± 7.8, P < .001), had a higher proportion of males (50.4% vs. 47.3%, P < .001), and were less vaccinated (63.1% vs. 91.8%, P < .001) (Table 1 ). During hospitalization, the incidence of supplemental oxygen or no oxygen was 94.8% among survivors and 68.8% among non-survivors, with the latter group receiving 12.6% HFNC, 14.6% MV, and 4.0% ECMO (Table 2 ). Non-survivors were more likely to receive medications such as IL-6 inhibitors (4.6% vs. 0.9%, P < .001), antiplatelets (29.6% vs. 9.8%, P < .001), corticosteroids (55.4% vs. 22.4%, P < .001), and vasopressors (25.4% vs. 1.6%, P < .001). Table 1 Baseline Characteristics at Admission Variable Total (n = 63,369) 1-Year Survivors (n = 60,276) 1-Year Non-Survivors (n = 3093) P Value Age (years) 69.4 ± 8.2 68.9 ± 7.8 79.2 ± 9.5 < .001 Age group (%) 60–69 38,628 (61.0) 38,030 (63.1) 598 (19.3) < .001 70–79 16,056 (25.3) 15,191 (25.2) 865 (28.0) ≥80 8,685 (13.7) 7055 (11.7) 1630 (52.7) Male (%) 30,065 (47.4) 28,506 (47.3) 1559 (50.4) < .001 CCI 0.7 ± 1.2 0.6 ± 1.1 2.0 ± 1.9 < .001 Comorbidity (%) Diabetes 12,371 (19.5) 11,114 (18.4) 1257 (40.6) < .001 Hypertension 12,769 (20.2) 11,267 (18.7) 1502 (48.6) < .001 Congestive heart failure 2453 (3.9) 2147 (3.6) 306 (9.9) < .001 Cerebrovascular disease 2125 (3.4) 1710 (2.8) 415 (13.4) < .001 Dementia 4144 (6.5) 3223 (5.3) 921 (29.8) < .001 Chronic pulmonary disease 7841 (12.4) 7196 (11.9) 645 (20.9) < .001 COPD or Asthma 1338 (2.1) 1087 (1.8) 251 (8.1) < .001 Chronic liver disease 4858 (7.7) 4367 (7.2) 491 (15.9) < .001 Chronic kidney disease 835 (1.3) 629 (1.0) 206 (6.7) < .001 Malignancy 700 (1.1) 448 (0.7) 252 (8.1) < .001 Immunosuppression * 1178 (1.9) 675 (1.1) 503 (16.3) < .001 Income level (%) < .001 Q1 (lowest) 17,004 (26.8) 15,986 (26.5) 1018 (32.9) Q2 12,057 (19.0) 11,599 (19.2) 458 (14.8) Q3 14,091 (22.2) 13,542 (22.5) 549 (17.7) Q4 (highest) 20,217 (31.9) 19,149 (31.8) 1068 (34.5) Vaccinated (%) 57,278 (90.4) 55,326 (91.8) 1952 (63.1) < .001 Numbers are presented as n (%) or mean ± standard deviation. COPD, chronic obstructive pulmonary disease; CCI, Charlson Comorbidity Index. * Immunosuppression includes malignancies, human immunodeficiency virus infection, organ transplantation, or prescribed corticosteroids for ≥ 30 days during hospitalization. Table 2 Severity of Illness and Management During Hospitalization Variables Total (n = 63,369) 1-Year Survivors (n = 60,276) 1-Year Non-Survivors (n = 3093) P value Organ dysfunction (%) Cardiovascular 551 (0.9) 303 (0.5) 248 (8.0) < .001 Respiratory 1203 (1.9) 779 (1.3) 424 (13.7) < .001 Neurologic 1679 (2.6) 1364 (2.3) 315 (10.2) < .001 Hematologic 1521 (2.4) 1263 (2.1) 258 (8.3) < .001 Hepatic 125 (0.2) 84 (0.1) 41 (1.3) < .001 Renal 679 (1.1) 418 (0.7) 261 (8.4) < .001 Metabolic 107 (0.2) 84 (0.1) 23 (0.7) < .001 No. of organ dysfunctions (%) < .001 0 58,527 (92.4) 56,480 (93.7) 2047 (66.2) 1 4078 (6.4) 3390 (5.6) 688 (22.2) 2 567 (0.9) 330 (0.5) 237 (7.7) 3 142 (0.2) 59 (0.1) 83 (2.7) ≥ 4 55 (0.1) 17 (0.0) 38 (1.2) Severity of illness (%) < .001 No oxygen or supplemental oxygen 59,296 (93.6) 57,169 (94.8) 2127 (68.8) HFNC 2818 (4.4) 2429 (4.0) 389 (12.6) MV 1071 (1.7) 619 (1.0) 452 (14.6) ECMO 184 (0.3) 59 (0.1) 125 (4.0) Medications (%) Hydroxychloroquine 135 (0.2) 117 (0.2) 18 (0.6) < .001 Macrolides * 1837 (2.9) 1679 (2.8) 158 (5.1) < .001 IL-6 inhibitor † 701 (1.1) 560 (0.9) 141 (4.6) < .001 Antiplatelet 6817 (10.8) 5900 (9.8) 917 (29.6) < .001 Corticosteroids 15,196 (24.0) 13,483 (22.4) 1713 (55.4) < .001 Vasopressors 1735 (2.7) 950 (1.6) 785 (25.4) < .001 Renal replacement therapy 460 (0.7) 338 (0.6) 122 (3.9) < .001 Length of hospital stay (days) 16 ± 11 15 ± 10 31 ± 14 < .001 ICU admission (%) 809 (1.3) 392 (0.7) 417 (13.5) < .001 Length of ICU stay (days) 12 ± 12 11 ± 12 13 ± 12 .003 Duration of MV (days) 18 ± 15 15 ± 14 22 ± 16 < .001 Duration of ECMO (days) 21 ± 17 18 ± 13 22 ± 18 .071 Numbers are presented as n (%) or mean ± standard deviation. HFNC, high-flow nasal cannula; MV, mechanical ventilation; ECMO, extracorporeal membrane oxygenation; IL-6, interleukin-6; ICU, intensive care unit. * Macrolides include azithromycin and clarithromycin. † IL-6 inhibitors include tocilizumab, siltuximab, and baricitinib. Complications and Healthcare Usage After Hospital Discharge Compared with survivors, non-survivors had higher rates of complications: sepsis (21.0% vs. 1.3%, P < .001), pulmonary embolism (4.6% vs. 0.9%, P < 0.001), lower gastrointestinal bleeding (6.1% vs. 1.5%, P < 0.001), and ischemic stroke (13.8% vs. 6.0%, P < 0.001), respectively. Moreover, non-survivors had higher incidence rates of rehospitalization (83.0% vs. 27.6%, P < 0.001), ICU admission (21.1% vs. 1.7%, P < 0.001) and ER visit (75.7 vs. 33.9, P < 0.001) (Table 3 ). Table 3 Complications and Healthcare Usage after Hospital Discharge Variables Total (n = 63,369) 1-Year Survivors (n = 60,276) 1-Year Non-Survivors (n = 3093) P value Complications Post–COVID-19 condition (%) 2528 (4.0) 2374 (3.9) 154 (5.0) < .001 Sepsis (%) 1407 (2.2) 758 (1.3) 649 (21.0) < .001 Septic shock (%) 308 (0.5) 106 (0.2) 202 (6.5) < .001 Myocardial infarction (%) 917 (1.4) 835 (1.4) 82 (2.7) < .001 Thrombosis event (%) Deep vein thrombosis 600 (0.9) 496 (0.8) 104 (3.4) < .001 Pulmonary embolism 695 (1.1) 552 (0.9) 143 (4.6) < .001 Bleeding events (%) Upper gastrointestinal bleeding 839 (1.3) 797 (1.3) 42 (1.4) .524 Lower gastrointestinal bleeding 1074 (1.7) 884 (1.5) 190 (6.1) < .001 Stroke (%) Ischemic 4072 (6.4) 3646 (6.0) 426 (13.8) < .001 Hemorrhagic 740 (1.2) 622 (1.0) 118 (3.8) < .001 Ischemic or hemorrhagic 429 (0.7) 388 (0.6) 41 (1.3) < .001 Transient ischemic attack (%) 943 (1.5) 918 (1.5) 25 (0.8) .005 Healthcare usage Rehospitalization (%) 19,218 (30.3) 16,652 (27.6) 2566 (83.0) < .001 Hospital length of stay (days) 63 ± 75 62 ± 74 84 ± 87 < .001 Use of MV (%) 919 (1.5) 274 (0.5) 645 (20.9) < .001 Use of vasopressors (%) 4732 (7.5) 3259 (5.4) 1473 (47.6) < .001 ICU admission (%) 1656 (2.6) 1002 (1.7) 654 (21.1) < .001 Length of ICU stay (days) 10 ± 16 6 ± 10 15 ± 21 < .001 OPD visit (%) 58,572 (92.4) 57,146 (94.8) 1426 (46.1) < .001 ED visit (%) 22,779 (35.9) 20,439 (33.9) 2340 (75.7) < .001 Hospital discharge to ER visit (days) 113 ± 111 122 ± 112 39 ± 69 < .001 Numbers are presented as n (%) or mean ± standard deviation. MV, mechanical ventilation; ICU, intensive care unit; OPD, outpatient department; ED, emergency department. Risk Factors for 1-year Mortality The multivariable logistic regression models for 1-year mortality, as depicted in Table 4 , indicate that older age and COVID-19 severity are significant risk factors for 1-year mortality (Figs. 2 and 3 ). Additionally, male sex (OR 1.45 [95% CI 1.32–1.59], P < .001), immunosuppression (OR 2.48 [95% CI 2.20–2.81], P < .001), vaccination (OR 0.18 [95% CI 0.16–0.20], P < .001), macrolide use (OR 0.45 [95% CI 0.35–0.57], P < .001), antiplatelet therapy (OR 0.66 [95% CI 0.60–0.73], P < .001), corticosteroid treatment (OR 1.16 [95% CI 1.05–1.29], P < .003), renal replacement therapy (OR 2.28 [95% CI 1.69–3.07], P < .001), and the number of organ dysfunctions were all significantly associated with 1-year mortality. Table 4 Univariate and Multivariable Logistic Regression Model for 1-Year Mortality among COVID-19 Survivors Variable Univariate Analysis Multivariable Analysis OR (95% CI) P value OR (95% CI) P value Age group < .001 < .001 60–69 Reference Reference 70–79 3.62 (3.26–4.03) 3.61 (3.19–4.09) ≥ 80 14.69 (13.33–16.19) 19.60 (17.41–22.07) Male 1.13 (1.05–1.22) < .001 1.45 (1.32–1.59) < .001 CCI < .001 .807 ≤ 1 Reference Reference ≥ 2 2.04 (1.88–2.21) 0.99 (0.89–1.10) Immunosuppression 2.80 (2.55–3.07) < .001 2.48 (2.20–2.81) < .001 Vaccination 0.15 (0.14–0.17) < .001 0.18 (0.16–0.20) < .001 No. of organ dysfunction < .001 < .001 0 Reference Reference 1 2.84 (2.60–3.10) 1.35 (1.21–1.50) 2 11.38 (9.94–13.02) 2.63 (2.17–3.19) 3 33.20 (25.83–42.67) 4.12 (2.85–5.97) ≥ 4 84.82 (49.59–145.07) 8.12 (3.76–17.55) Severity of COVID-19 < .001 < .001 No oxygen or supplemental oxygen therapy Reference Reference HFNC 27.50 (23.09–32.77) 12.73 (10.17–15.93) MV 60.39 (51.84–70.35) 33.31 (26.28–42.23) ECMO 142.88 (80.52–253.51) 89.92 (45.80–176.56) Hydroxychloroquine 0.79 (0.46–1.34) .377 0.84 (0.43–1.61) .594 Macrolides 0.50 (0.41–0.60) < .001 0.45 (0.35–0.57) < .001 IL-6 inhibitor 3.50 (1.57–7.84) .002 0.67 (0.19–2.39) .540 Antiplatelet 1.13 (1.04–1.22) < .001 0.66 (0.60–0.73) < .001 Corticosteroids 2.13 (1.98–2.29) < .001 1.16 (1.05–1.29) .003 Renal replacement therapy 6.70 (5.48–8.20) < .001 2.28 (1.69–3.07) < .001 ICU admission after discharge 15.86 (14.26–17.64) < .001 1.14 (0.93–1.39) .211 OR, odds ratio; CI, confidence interval; CCI, Charlson Comorbidity Index; HFNC, high-flow nasal cannula; MV, mechanical ventilation; ECMO, extracorporeal membrane oxygenation; IL-6, interleukin 6; ICU, intensive care unit. Change in Quality of Life Compared to the period before the diagnosis of COVID-19, there was an increase in job loss among patients after they contracted COVID-19 (24.1% vs. 21.8%, P < .001) (Table S6). Furthermore, there was a significant rise in both mild to moderate and severe disabilities following a COVID-19 diagnosis (8.6% vs. 9.3%, P < .001; and 4.1% vs. 4.6%, P < .001). Among the survivors of COVID-19, the most frequently reported symptoms included myalgia (24.3%), anxiety (14.1%), and chest pain (13.6%) (Table S7). Depression was also prevalent (12.2%), with cough being the most common respiratory symptom (8.8%). Discussion Using nationwide data, we evaluated the 1-year mortality and associated symptoms and complications in COVID-19 survivors aged 60 years and older in Korea. The mortality rate of COVID-19 survivors within 1 year was 4.9%, closely mirroring the in-hospital mortality rate of 4.8%. Factors linked to one-year mortality included older age, male sex, the severity of COVID-19, immunosuppression, organ dysfunction, and corticosteroid use. Vaccination before contracting COVID-19 proved advantageous. When compared to the period before the diagnosis, the post-COVID-19 quality of life diminished, particularly in terms of employment and disability status. Survivors of COVID-19 were found to suffer from a range of physical and mental sequelae. Several studies have documented long-term mortality among patients with COVID-19 6,7,9,12–14 . A systematic review and meta-analysis of nine studies reported a 1-year post-discharge all-cause mortality rate for COVID-19 at 7.87% 9 . However, these rates varied significantly from country to country, with one-year mortality rates reported as high as approximately 12% in Italy and the United Kingdom, and as low as approximately 2% in Brazil and Sweden. This discrepancy may be attributed to the varying capacities of countries to hospitalize patients and the lack of standardized criteria for discharging patients with COVID-19 9 . Long-term mortality is affected by various factors, including the severity of the illness and age 6,9,12,13,15 . In a study focusing on COVID-19 patients discharged from the ICU, the 1-year mortality rate reached 29.9% 6 . Age also plays a critical role; Di Bari et al. found that the 1-year mortality rate for COVID-19 patients over 75 years old, hospitalized via the ED, was as high as 48.4%, in contrast to 33.9% for non-COVID-19 patients 14 . Our study, which included patients over 60 years of age, observed a relatively low 1-year mortality rate of 4.9%. These aforementioned studies included more severely ill patients, with more than 50% requiring intensive care 6,12 , whereas only 1.7% of the patients in our study required MV, which may account for the observed difference in mortality rates. A nationwide cohort study from Estonia indicated that underlying diseases, such as cardiovascular disease, cancer, and respiratory system diseases, were linked to increased long-term mortality in COVID-19 patients aged 60 years or older 16 . Our findings suggest that several factors, both prior to and following hospital discharge, are associated with long-term mortality. Organ dysfunction and the severity of illness during hospitalization are influential on long-term survival. Specifically, when compared to patients who either did not require oxygen therapy or received supplemental oxygen therapy alone, those who were treated with HFNC and MV experienced 12.7 and 33.3 times higher 1-year mortality, respectively. Notably, corticosteroids, which are administered to critically ill COVID-19 patients to mitigate the inflammatory response 17 , were associated with poor outcomes. This association may be due to the more frequent use of corticosteroids in severely ill patients. Nevertheless, given that corticosteroid use is tied to serious adverse reactions such as septic shock and invasive fungal infections 18 , the potential for detrimental long-term effects of corticosteroids cannot be disregarded. Hägglöf et al. found that men had a 1.33 times higher 360-day mortality risk than women in a Swedish nationwide study of COVID-19 ICU patients 6 . Similarly, a German nationwide cohort study indicated that being female was a protective factor against 6-month mortality in COVID-19 patients (OR, 0.63 in females) 19 . While these studies typically included more male than female patients, our study comprised fewer male patients at 47.4%. Nevertheless, our research demonstrated that male sex was associated with poorer long-term mortality compared to female (OR, 1.45). Although no definitive theoretical hypothesis has been established to explain the gender disparities in long-term mortality among COVID-19 patients, biological and sociocultural differences between men and women are evident. Such differences may contribute to higher rates of ICU admissions and the prevalence of sepsis in men 20 . Zettersten et al. proposed that the increased risk of adverse long-term outcomes in male COVID-19 patients might be attributable to the influence of sex hormones on inflammation 21 . Vaccines designed to prevent COVID-19 infection offer protection against severe disease and death 22 . Moreover, vaccines have a sustained effect on reducing post-COVID-19 conditions (OR of vaccination, 0.57) 23 , and long-term health consequences 24 . Consistent with our study results (OR of vaccination for 1-year mortality, 0.18), Lam et al. demonstrated the potential of vaccination in lowering the risk of long-term mortality following a COVID-19 infection 24 . Compared to patients who received a complete and booster dose of vaccination, those who were unvaccinated faced a higher risk of all-cause mortality within 1 year. One possible explanation for this finding is that vaccines, by reducing the severity of COVID-19, lead to a decreased risk of long-COVID conditions 25 . Additionally, vaccines may diminish long-term mortality by curtailing the exaggerated inflammatory immune response linked to viral persistence 26 . We found that numerous patients endured a variety of physical and mental issues after being discharged from the hospital following COVID-19. These persistent symptoms are known to be associated with female sex and older age 23 . We also found that 1-year non-survivors experienced various critical events, such as sepsis, myocardial infarction, pulmonary thromboembolism, stroke, and gastrointestinal bleeding, more frequently than survivors. While some studies have suggested that disease severity is not linked to post–COVID-19 condition 23,27,28 , our study findings indicate that patients who were critically ill during hospitalization were more likely to suffer from long-term complications and mortality. This discrepancy may arise because previous studies on long-COVID syndrome relied on data collected using ICD-10 codes (e.g., U09.9), or based on mild symptom reports 29 . Severe COVID-19 that necessitates hospitalization can provoke a more intense immune response and cytokine storm, potentially leading to more prolonged organ damage. Our study had several limitations. First, because it was a retrospective registry-based study, we could not collect information on complications during hospitalization and detailed demographics, such as smoking history or body mass index. Additionally, data on functional dependencies or cognitive impairment, which are recognized risk factors for rehospitalization or death, were not available 30 . Second, it is challenging to ascertain whether the causes of rehospitalization, ED or OPD visits, and post-discharge complications were directly related to COVID-19. Third, this study included only patients in the early phase of the COVID-19 pandemic and did not account for patients affected by various COVID-19 variants, potentially limiting the generalizability of the findings. The Korean government’s stringent quarantine policies led to a relatively low number of initial patients with COVID-19. Furthermore, the enrollment period for this dataset was restricted to allow for the assessment of 1-year post-discharge mortality. Despite these limitations, our study is a comprehensive nationwide study with a large cohort, providing insights into the natural history of hospitalized older patients with COVID-19. Conclusion The 1-year mortality after hospital discharge for patients with COVID-19 was found to be comparable to the in-hospital mortality rate in Korea. The long-term mortality of hospitalized COVID-19 patients is influenced by factors such as age and the severity of illness experienced during hospitalization. It is imperative that we maintain vigilance and provide thorough care for older patients who have undergone critical care, even after their discharge from the hospital. Methods Data Source and Ethical Statement This study used the K-COV-N database, which is linked to the Korean National Health Insurance Service (NHIS) database, the nationwide COVID-19 vaccination registry, and COVID-19-positive patient information from the Korea Disease Control and Prevention Agency (KDCA). The NHIS database encompasses healthcare claims for approximately 97% of the population in the Republic of Korea. Diagnoses are recorded using the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes, and prescription information for drugs and procedures is compiled in the NHIS database to facilitate financial support for treatment expenses. Data extraction was conducted by an independent medical record technician at the NHIS center, unaffiliated with this study. The study protocol was approved by the institutional review board of Chung-Ang University (1041078-20221111-BR-010). Informed consent was waived because data analyses were performed retrospectively using anonymized data from the South Korean NHIS database. All procedures in this study were performed according to the relevant guidelines and regulations. Study Design and Population The study encompassed patients with confirmed COVID-19 who were hospitalized between October 8, 2020, and December 31, 2021. Older adults, defined as individuals aged 60 years or above, who were hospitalized within 2 weeks following a confirmed COVID-19 diagnosis, were categorized as older hospitalized patients with COVID-19 31 . The analysis focused on patients who were discharged alive. Exclusion criteria included: ( 1 ) age under 60 years, ( 2 ) absence of hospitalization within 14 days post-COVID-19 diagnosis, ( 3 ) death during hospitalization, and ( 4 ) lack of sufficient clinical data. Data Collection and Definitions Patient characteristics encompassed age, sex, comorbidities, Charlson Comorbidity Index (CCI) using ICD-10 codes, and income level at hospital admission (Table S1 ). Income levels were categorized into four quartiles, ranging from Q1, the lowest, to Q4, the highest. Immunosuppression was defined as the presence of any malignancies, HIV or AIDS, organ transplantation, or the prescription of corticosteroids for 30 days or more during hospitalization 32 . The assessment of organ dysfunction, severity of illness, and various treatments was conducted during hospitalization. Organ dysfunction included conditions affecting the cardiovascular, respiratory, neurologic, hematologic, hepatic, renal, and metabolic systems (Table S2). The severity of COVID-19 was evaluated using an ordinal scale: no oxygen or supplemental oxygen group, high-flow nasal cannula (HFNC), mechanical ventilation (MV), and extracorporeal membrane oxygenation (ECMO) (Table S3) 8 . Medications prescribed included hydroxychloroquine, macrolides, IL-6 inhibitors, antiplatelet agents, corticosteroids, and vasopressors. Additionally, data on renal replacement therapy, hospital stay duration, ICU admission, ICU stay length, MV duration, and ECMO duration were compiled. The primary outcome of this study was the 1-year mortality rate following hospital discharge. Healthcare usage within the first year after discharge was documented, including rehospitalization, hospital stay length, MV usage, vasopressor usage, ICU admission, ICU stay length, outpatient department (OPD) visits, emergency department (ED) visits, and transitions from hospital discharge to ED visits. After discharge, survivors’ ICD-10 codes related to various complications were investigated, including post–COVID-19 condition, sepsis, septic shock, myocardial infarction, thrombotic events (deep vein thrombosis and pulmonary embolism), bleeding events (upper and lower gastrointestinal bleeding), strokes (ischemic, hemorrhagic, and mixed), and transient ischemic attacks (Table S4). Long-term symptoms experienced during healthcare usage were also investigated (Table S5) 15 . Changes in patients’ status before and after COVID-19 diagnoses were assessed based on employment, disability, and annual income levels. The types of disability included physical, brain lesions, visual, hearing, speech, intellectual, mental, renal, heart, respiratory, hepatopathy, intestinal and urinary fistulae, and epilepsy. Each disability was rigorously classified according to legal standards by specialist physicians in each respective field, with a grading system ranging from 1 to 6 33 . Grades 1 through 3 were considered severe disabilities, while grades 4 through 6 were categorized as mild to moderate disabilities, respectively. Statistical Analysis Categorical variables are presented as numbers (percentages), and continuous variables are presented as median (interquartile range). To compare differences between 1-year survivors and non-survivors, the chi-square test and Student’s t-test were used for categorical and continuous variables, respectively. McNemar’s test was performed to compare changes in quality of life before and after the diagnosis of COVID-19. Multivariable logistic regression analyses were conducted to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for factors associated with 1-year mortality. Variables with P < .1 in univariate analysis and those deemed clinically relevant were included in the multivariable logistic regression model. After addressing multicollinearity among variables, the final multivariable regression model comprised age, sex, CCI, immunosuppression, vaccination status, number of organ dysfunctions, severity of COVID-19 (no oxygen or supplemental oxygen therapy, HFNC, MV, and ECMO), hydroxychloroquine, macrolides, IL-6 inhibitor, antiplatelet, corticosteroids, renal replacement therapy, and ICU admission post-discharge. The OR for each variable was reported with a 95% CI. Additionally, Kaplan-Meier curves were plotted up to 1 year from the index date, and differences between age groups, sex, and severity of illness were compared using log-rank tests. Sankey diagrams visualized the overall distribution of variables according to age group, COVID-19 severity, in-hospital mortality, and overall 1-year mortality for COVID-19. Statistical analyses were executed using SAS Enterprise software version 7.1 (SAS Inc., Cary, NC, USA) and R Studio software version 4.3.1 (R Studio Inc., Boston, MA, USA), with statistical significance established at P < .05. Declarations Authors’ contributions MSB and SYJ conceived and designed the study. EK, JYK, SYJ, and MSB collected the primary data and conducted data analyses. EK, KMM, TWK, WYK, SYJ, and MSB interpreted the results and prepared the first draft. All the authors revised the draft for important intellectual content and approved the final manuscript submitted for publication. Availability of data and materials The datasets used and analyzed in the current study are available from the corresponding author upon reasonable request. Author information Eunji Kim 1 , Jeong-Yeon Kim 1 , Kyoung Min Moon 2 , Tae Wan Kim 2 , Won-Young Kim 2 , Sun‑Young Jung 1,3 *, Moon Seong Baek 2,4 * 1 Department of Global Innovative Drugs, The Graduate School of Chung‑Ang University, Chung‑Ang University, Seoul, Republic of Korea 2 Department of Internal Medicine, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Republic of Korea 3 College of Pharmacy, Chung‑Ang University, Seoul, Republic of Korea 4 Biomedical Research Institute, Chung-Ang University Hospital, Seoul, Republic of Korea Ethics approval and consent to participate The study protocol was approved by the Institutional Review Board of Chung-Ang University (1041078-20221111-BR-010). Informed consent was waived because data analyses were performed retrospectively using anonymized data from the South Korean NHIS database. All procedures in this study were performed according to the relevant guidelines and regulations. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Funding This study was supported by a research grant from the Biomedical Research Institute of Chung-Ang University Hospital (2023). References Thygesen, J. H. et al. COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records. Lancet Digit Health 4, e542-e557. https://doi.org/10.1016/s2589-7500(22)00091-7 (2022). Baptista, A., Vieira, A. M., Capela, E., Julião, P. & Macedo, A. COVID-19 fatality rates in hospitalized patients: A new systematic review and meta-analysis. J Infect Public Health 16, 1606–1612. https://doi.org/10.1016/j.jiph.2023.07.006 (2023). Huang, L. et al. Health outcomes in people 2 years after surviving hospitalisation with COVID-19: a longitudinal cohort study. Lancet Respir Med 10, 863–876. https://doi.org/10.1016/s2213-2600(22)00126-6 (2022). Davis, H. E., McCorkell, L., Vogel, J. M. & Topol, E. J. Long COVID: major findings, mechanisms and recommendations. Nat Rev Microbiol 21, 133–146. https://doi.org/10.1038/s41579-022-00846-2 (2023). Iwashyna, T. J. et al. Late Mortality After COVID-19 Infection Among US Veterans vs Risk-Matched Comparators: A 2-Year Cohort Analysis. JAMA Intern Med. https://doi.org/10.1001/jamainternmed.2023.3587 (2023). Hägglöf, E., Bell, M., Zettersten, E., Engerström, L. & Larsson, E. Long-term survival after intensive care for COVID-19: a nationwide cohort study of more than 8000 patients. Ann Intensive Care 13, 76. https://doi.org/10.1186/s13613-023-01156-3 (2023). Guillon, A., Laurent, E., Godillon, L., Kimmoun, A. & Grammatico-Guillon, L. Long-term mortality of elderly patients after intensive care unit admission for COVID-19. Intensive Care Med 47, 710–712. https://doi.org/10.1007/s00134-021-06399-x (2021). Dodd, L. E. et al. Endpoints for randomized controlled clinical trials for COVID-19 treatments. Clin Trials 17, 472–482. https://doi.org/10.1177/1740774520939938 (2020). Ramzi, Z. S. Hospital readmissions and post-discharge all-cause mortality in COVID-19 recovered patients; A systematic review and meta-analysis. Am J Emerg Med 51, 267–279. https://doi.org/10.1016/j.ajem.2021.10.059 (2022). Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020-21. Lancet 399, 1513–1536. https://doi.org/10.1016/s0140-6736(21)02796-3 (2022). Han, C., Jang, H. & Oh, J. Excess mortality during the Coronavirus disease pandemic in Korea. BMC Public Health 23, 1698. https://doi.org/10.1186/s12889-023-16546-2 (2023). Santos, M. M. S. et al. Predictors of early and long-term mortality after ICU discharge in critically ill COVID-19 patients: A prospective cohort study. PLoS One 18, e0293883. https://doi.org/10.1371/journal.pone.0293883 (2023). Pourhoseingholi, M. A. et al. Predicting 1-year post-COVID-19 mortality based on chest computed tomography scan. J Med Virol 93, 5694–5696. https://doi.org/10.1002/jmv.27146 (2021). Di Bari, M. et al. COVID-19, Vulnerability, and Long-Term Mortality in Hospitalized and Nonhospitalized Older Persons. J Am Med Dir Assoc 23, 414–420.e411. https://doi.org/10.1016/j.jamda.2021.12.009 (2022). Mizrahi, B. et al. Long covid outcomes at one year after mild SARS-CoV-2 infection: nationwide cohort study. Bmj 380, e072529. https://doi.org/10.1136/bmj-2022-072529 (2023). Uusküla, A. et al. Long-term mortality following SARS-CoV-2 infection: A national cohort study from Estonia. Lancet Reg Health Eur 18, 100394. https://doi.org/10.1016/j.lanepe.2022.100394 (2022). Horby, P. et al. Dexamethasone in Hospitalized Patients with Covid-19. N Engl J Med 384, 693–704. https://doi.org/10.1056/NEJMoa2021436 (2021). Munch, M. W. et al. Effect of 12 mg vs 6 mg of Dexamethasone on the Number of Days Alive Without Life Support in Adults With COVID-19 and Severe Hypoxemia: The COVID STEROID 2 Randomized Trial. Jama 326, 1807–1817. https://doi.org/10.1001/jama.2021.18295 (2021). Günster, C. et al. 6-month mortality and readmissions of hospitalized COVID-19 patients: A nationwide cohort study of 8,679 patients in Germany. PLoS One 16, e0255427. https://doi.org/10.1371/journal.pone.0255427 (2021). Merdji, H. et al. Sex and gender differences in intensive care medicine. Intensive Care Med 49, 1155–1167. https://doi.org/10.1007/s00134-023-07194-6 (2023). Zettersten, E. et al. Long-term outcome after intensive care for COVID-19: differences between men and women-a nationwide cohort study. Crit Care 25, 86. https://doi.org/10.1186/s13054-021-03511-x (2021). Graña, C. et al. Efficacy and safety of COVID-19 vaccines. Cochrane Database Syst Rev 12, Cd015477 . https://doi.org/10.1002/14651858.Cd015477 (2022). Tsampasian, V. et al. Risk Factors Associated With Post-COVID-19 Condition: A Systematic Review and Meta-analysis. JAMA Intern Med 183, 566–580. https://doi.org/10.1001/jamainternmed.2023.0750 (2023). Lam, I. C. H. et al. Persistence in risk and effect of COVID-19 vaccination on long-term health consequences after SARS-CoV-2 infection. Nat Commun 15, 1716. https://doi.org/10.1038/s41467-024-45953-1 (2024). Fernández-de-Las-Peñas, C. et al. Differences in Long-COVID Symptoms between Vaccinated and Non-Vaccinated (BNT162b2 Vaccine) Hospitalized COVID-19 Survivors Infected with the Delta Variant. Vaccines (Basel) 10. https://doi.org/10.3390/vaccines10091481 (2022). Buonsenso, D., Piazza, M., Boner, A. L. & Bellanti, J. A. Long COVID: A proposed hypothesis-driven model of viral persistence for the pathophysiology of the syndrome. Allergy Asthma Proc 43, 187–193. https://doi.org/10.2500/aap.2022.43.220018 (2022). Pazukhina, E. et al. Prevalence and risk factors of post-COVID-19 condition in adults and children at 6 and 12 months after hospital discharge: a prospective, cohort study in Moscow (StopCOVID). BMC Med 20, 244. https://doi.org/10.1186/s12916-022-02448-4 (2022). Munblit, D. et al. Incidence and risk factors for persistent symptoms in adults previously hospitalized for COVID-19. Clin Exp Allergy 51, 1107–1120. https://doi.org/10.1111/cea.13997 (2021). Patients Diagnosed with Post-COVID Conditions: An Analysis of Private Healthcare Claims Using the Oficial ICD-10 Diagnostic Code. http://resource.nlm.nih.gov/9918504887106676 . Bowles, K. H. et al. Surviving COVID-19 After Hospital Discharge: Symptom, Functional, and Adverse Outcomes of Home Health Recipients. Ann Intern Med 174, 316–325. https://doi.org/10.7326/m20-5206 (2021). Nyberg, T. et al. Risk of hospital admission for patients with SARS-CoV-2 variant B.1.1.7: cohort analysis. Bmj 373, n1412. https://doi.org/10.1136/bmj.n1412 (2021). Baek, M. S., Lee, M. T., Kim, W. Y., Choi, J. C. & Jung, S. Y. COVID-19-related outcomes in immunocompromised patients: A nationwide study in Korea. PLoS One 16, e0257641. https://doi.org/10.1371/journal.pone.0257641 (2021). Choi, H. R., Song, I. A. & Oh, T. K. Quality of life and mortality among survivors of acute respiratory distress syndrome in South Korea: a nationwide cohort study. J Anesth 36, 230–238. https://doi.org/10.1007/s00540-022-03036-9 (2022). Additional Declarations No competing interests reported. Supplementary Files Supplementaryfile.docx Cite Share Download PDF Status: Published Journal Publication published 22 Oct, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 05 Jul, 2024 Reviews received at journal 01 Jul, 2024 Reviews received at journal 01 Jul, 2024 Reviewers agreed at journal 19 Jun, 2024 Reviewers agreed at journal 19 Jun, 2024 Reviewers agreed at journal 19 Jun, 2024 Reviewers invited by journal 12 Jun, 2024 Editor assigned by journal 12 Jun, 2024 Editor invited by journal 22 May, 2024 Submission checks completed at journal 20 May, 2024 First submitted to journal 15 May, 2024 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. 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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-4427690","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":307217964,"identity":"f5a4850b-da74-4766-95df-46ea7d5c6c18","order_by":0,"name":"Eunji Kim","email":"","orcid":"","institution":"The Graduate School of Chung‑Ang University, Chung‑Ang University","correspondingAuthor":false,"prefix":"","firstName":"Eunji","middleName":"","lastName":"Kim","suffix":""},{"id":307217965,"identity":"4af00018-07e2-48df-9b66-3ce1ca3eee08","order_by":1,"name":"Jeong-Yeon Kim","email":"","orcid":"","institution":"The Graduate School of Chung‑Ang University, Chung‑Ang University","correspondingAuthor":false,"prefix":"","firstName":"Jeong-Yeon","middleName":"","lastName":"Kim","suffix":""},{"id":307217966,"identity":"b0d6ea41-54ba-4996-bad4-f4260adbe06e","order_by":2,"name":"Kyoung Min Moon","email":"","orcid":"","institution":"Chung-Ang University Hospital, Chung-Ang University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Kyoung","middleName":"Min","lastName":"Moon","suffix":""},{"id":307217967,"identity":"ea025c9c-09ec-48c9-bcb6-993d38d144a1","order_by":3,"name":"Tae Wan Kim","email":"","orcid":"","institution":"Chung-Ang University Hospital, Chung-Ang University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Tae","middleName":"Wan","lastName":"Kim","suffix":""},{"id":307217968,"identity":"64dc64fe-d09d-40a3-a9f7-d996faf18311","order_by":4,"name":"Won-Young Kim","email":"","orcid":"","institution":"Chung-Ang University Hospital, Chung-Ang University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Won-Young","middleName":"","lastName":"Kim","suffix":""},{"id":307217969,"identity":"c141c277-57b6-4716-a23a-18d2a67a1659","order_by":5,"name":"Sun‑Young Jung","email":"","orcid":"","institution":"The Graduate School of Chung‑Ang University, Chung‑Ang University","correspondingAuthor":false,"prefix":"","firstName":"Sun‑Young","middleName":"","lastName":"Jung","suffix":""},{"id":307217970,"identity":"bcf7f44d-979f-40e9-a07c-3daede5359fc","order_by":6,"name":"Moon Seong Baek","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvklEQVRIiWNgGAWjYDACZgYDhg8GNjBuAnFaGGcUpJGihYHBgJnnw2EStBgcZ974gMfgvDz/jATGDz8Y0vIJaznMVmwgYXDbcMaNBGbJHoYcywZCWswO85hJGBjcTmC4kcAgzcBQYUDQFrCWBINzCfJAW34Tr+WAwYEEgxsJbEBbcghrsQf6xbDBINlw45mHbZY9BmmEtUj2H974+M8fO3m548mHb/yoSCasBQkwNgADkBQNo2AUjIJRMApwAgCMCDcUh+g2rgAAAABJRU5ErkJggg==","orcid":"","institution":"Chung-Ang University Hospital, Chung-Ang University College of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Moon","middleName":"Seong","lastName":"Baek","suffix":""}],"badges":[],"createdAt":"2024-05-16 01:21:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4427690/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4427690/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-76871-3","type":"published","date":"2024-10-22T15:58:09+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":57721901,"identity":"7e6e5467-9c5e-40d8-887a-92137918dc83","added_by":"auto","created_at":"2024-06-04 19:00:16","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":244378,"visible":true,"origin":"","legend":"\u003cp\u003eInclusion and exclusion flowchart.\u003c/p\u003e","description":"","filename":"fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-4427690/v1/85a9db9417802c3dfcc61053.png"},{"id":57721903,"identity":"9265960e-46e4-4aa8-848f-fad4d00c1afb","added_by":"auto","created_at":"2024-06-04 19:00:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1341536,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier analysis of 1-year survival data according to (A) age group, (B) sex, (C) and severity of illness. HFNC, high-flow nasal cannula; MV, mechanical ventilation; ECMO, extracorporeal membrane oxygenation.\u003c/p\u003e","description":"","filename":"fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-4427690/v1/98aebedd1dfb6c4d6ada77ce.png"},{"id":57721905,"identity":"88edd9c0-9988-4c3c-af61-4ee0e56f061e","added_by":"auto","created_at":"2024-06-04 19:00:17","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":803198,"visible":true,"origin":"","legend":"\u003cp\u003eSankey diagram of 1-year mortality among COVID-19 survivors. (A) Entire study cohort; (B) patients treated with HFNC, MV, or ECMO. HFNC, high-flow nasal cannula; MV, mechanical ventilation; ECMO, extracorporeal membrane oxygenation.\u003c/p\u003e","description":"","filename":"fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-4427690/v1/8d1099dcf0bd0966ae6dd43e.png"},{"id":67682833,"identity":"d040862d-abf5-4bbc-8cc7-87f69707d973","added_by":"auto","created_at":"2024-10-28 16:15:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3576086,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4427690/v1/29429708-fb5d-4afc-91f2-9df245b8ed91.pdf"},{"id":57721902,"identity":"af7d843e-5146-4d3b-852b-3735eae29709","added_by":"auto","created_at":"2024-06-04 19:00:16","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":57751,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-4427690/v1/110350e920c1ef4be8c8f15f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"One-Year Mortality and Associated Factors in Older Hospitalized COVID-19 Survivors: A Nationwide Cohort Study in Korea","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe manifestations of COVID-19 range from asymptomatic cases to life-threatening acute respiratory distress syndrome\u003csup\u003e1\u003c/sup\u003e. It is estimated that approximately 16% of patients with COVID-19 succumb to the disease while hospitalized\u003csup\u003e2\u003c/sup\u003e. Even after recovering from the acute phase of the illness, long-term symptoms may persist in COVID-19 survivors\u003csup\u003e3\u003c/sup\u003e. Long COVID syndrome can affect various organ systems and can manifest with a variety of symptoms, such as fatigue, chest pain, and cough. Factors such as immune dysregulation, autoimmunity, and endothelial abnormalities may play crucial roles in the development of long COVID syndrome\u003csup\u003e4\u003c/sup\u003e. The enduring impact of COVID-19 extends beyond physical and mental health issues to include increased mortality. Iwashyna et al. found that individuals who had contracted COVID-19 faced a twofold increase in mortality risk within 2 years compared to those not infected with SARS-CoV-2\u003csup\u003e5\u003c/sup\u003e. The risk of long-term mortality is affected by factors such as age and the severity of the SARS-CoV-2 infection\u003csup\u003e6,7\u003c/sup\u003e. A Swedish nationwide cohort study (N\u0026thinsp;=\u0026thinsp;8392) reported a 360-day mortality rate of 29.8% following intensive care unit (ICU) admission, with male sex, advanced age, and various comorbidities being significant contributors to mortality\u003csup\u003e6\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe severity of COVID-19 is often gauged by the type of oxygen therapy administered\u003csup\u003e8\u003c/sup\u003e, but the correlation between the severity of the disease and long-term mortality remains unclear. Additionally, H\u0026auml;ggl\u0026ouml;f et al. observed that the 1-year mortality rate was 1.33 times higher in men than in women\u003csup\u003e6\u003c/sup\u003e. However, given the considerable variation in long-term mortality rates from COVID-19 across different countries and regions\u003csup\u003e9\u003c/sup\u003e, such findings should be interpreted with caution. While several studies have been conducted\u003csup\u003e6,7,9\u003c/sup\u003e, data on the long-term mortality of COVID-19 survivors, particularly among older adults, and the associated risk factors remain scarce. In Korea, the mortality rate from COVID-19 was relatively low, attributed to stringent quarantine measures\u003csup\u003e10\u003c/sup\u003e, but the older demographic experienced an increase in excess mortality during the pandemic\u003csup\u003e11\u003c/sup\u003e. Therefore, this study aimed to investigate the 1-year mortality rate and associated risk factors among older survivors of COVID-19.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Population\u003c/h2\u003e \u003cp\u003eDuring the study period, 576,613 patients were confirmed to have COVID-19 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). After excluding patients under 60 years of age (n\u0026thinsp;=\u0026thinsp;433,943) and those not hospitalized (n\u0026thinsp;=\u0026thinsp;75,860), 66,810 older patients with COVID-19 were hospitalized. Additionally, we excluded patients who died in the hospital (n\u0026thinsp;=\u0026thinsp;3219, representing a 4.8% in-hospital mortality rate) and those with missing data (n\u0026thinsp;=\u0026thinsp;222). Ultimately, 63,369 survivors of hospitalized COVID-19 were analyzed. Within 1 year, we compared survivors (n\u0026thinsp;=\u0026thinsp;60,276, 95.1%) to non-survivors (n\u0026thinsp;=\u0026thinsp;3093, 4.9%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003ePatient Characteristics\u003c/h2\u003e \u003cp\u003eCompared with survivors, non-survivors were significantly older (79.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.5 vs. 68.9\u0026thinsp;\u0026plusmn;\u0026thinsp;7.8, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), had a higher proportion of males (50.4% vs. 47.3%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), and were less vaccinated (63.1% vs. 91.8%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). During hospitalization, the incidence of supplemental oxygen or no oxygen was 94.8% among survivors and 68.8% among non-survivors, with the latter group receiving 12.6% HFNC, 14.6% MV, and 4.0% ECMO (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Non-survivors were more likely to receive medications such as IL-6 inhibitors (4.6% vs. 0.9%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), antiplatelets (29.6% vs. 9.8%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), corticosteroids (55.4% vs. 22.4%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), and vasopressors (25.4% vs. 1.6%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline Characteristics at Admission\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;63,369)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1-Year Survivors (n\u0026thinsp;=\u0026thinsp;60,276)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1-Year Non-Survivors (n\u0026thinsp;=\u0026thinsp;3093)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.4\u0026thinsp;\u0026plusmn;\u0026thinsp;8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68.9\u0026thinsp;\u0026plusmn;\u0026thinsp;7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38,628 (61.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38,030 (63.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e598 (19.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16,056 (25.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15,191 (25.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e865 (28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8,685 (13.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7055 (11.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1630 (52.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30,065 (47.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28,506 (47.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1559 (50.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidity (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12,371 (19.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11,114 (18.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1257 (40.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12,769 (20.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11,267 (18.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1502 (48.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCongestive heart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2453 (3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2147 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e306 (9.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCerebrovascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2125 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1710 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e415 (13.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDementia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4144 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3223 (5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e921 (29.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic pulmonary disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7841 (12.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7196 (11.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e645 (20.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD or Asthma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1338 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1087 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e251 (8.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic liver disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4858 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4367 (7.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e491 (15.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic kidney disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e835 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e629 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e206 (6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalignancy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e700 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e448 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e252 (8.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImmunosuppression\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1178 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e675 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e503 (16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome level (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ1 (lowest)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17,004 (26.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15,986 (26.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1018 (32.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12,057 (19.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11,599 (19.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e458 (14.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14,091 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13,542 (22.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e549 (17.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ4 (highest)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20,217 (31.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19,149 (31.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1068 (34.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaccinated (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57,278 (90.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55,326 (91.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1952 (63.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNumbers are presented as n (%) or mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eCOPD, chronic obstructive pulmonary disease; CCI, Charlson Comorbidity Index.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e*\u003c/sup\u003eImmunosuppression includes malignancies, human immunodeficiency virus infection, organ transplantation, or prescribed corticosteroids for \u0026ge;\u0026thinsp;30 days during hospitalization.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSeverity of Illness and Management During Hospitalization\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;63,369)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1-Year Survivors (n\u0026thinsp;=\u0026thinsp;60,276)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1-Year Non-Survivors (n\u0026thinsp;=\u0026thinsp;3093)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrgan dysfunction (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiovascular\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e551 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e303 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e248 (8.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1203 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e779 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e424 (13.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeurologic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1679 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1364 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e315 (10.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHematologic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1521 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1263 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e258 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e125 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e679 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e418 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e261 (8.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetabolic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e107 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of organ dysfunctions (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58,527 (92.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56,480 (93.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2047 (66.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4078 (6.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3390 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e688 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e567 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e330 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e237 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e142 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeverity of illness (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo oxygen or supplemental oxygen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59,296 (93.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57,169 (94.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2127 (68.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHFNC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2818 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2429 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e389 (12.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1071 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e619 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e452 (14.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eECMO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e184 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e125 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedications (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHydroxychloroquine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e135 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMacrolides\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1837 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1679 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e158 (5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6 inhibitor\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e701 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e560 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e141 (4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntiplatelet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6817 (10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5900 (9.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e917 (29.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCorticosteroids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15,196 (24.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13,483 (22.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1713 (55.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVasopressors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1735 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e950 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e785 (25.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal replacement therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e460 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e338 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e122 (3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of hospital stay (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u0026thinsp;\u0026plusmn;\u0026thinsp;11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31\u0026thinsp;\u0026plusmn;\u0026thinsp;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICU admission (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e809 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e392 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e417 (13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of ICU stay (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of MV (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026thinsp;\u0026plusmn;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22\u0026thinsp;\u0026plusmn;\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of ECMO (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u0026thinsp;\u0026plusmn;\u0026thinsp;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u0026thinsp;\u0026plusmn;\u0026thinsp;13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22\u0026thinsp;\u0026plusmn;\u0026thinsp;18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.071\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNumbers are presented as n (%) or mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eHFNC, high-flow nasal cannula; MV, mechanical ventilation; ECMO, extracorporeal membrane oxygenation; IL-6, interleukin-6; ICU, intensive care unit.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e*\u003c/sup\u003eMacrolides include azithromycin and clarithromycin.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003eIL-6 inhibitors include tocilizumab, siltuximab, and baricitinib.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eComplications and Healthcare Usage After Hospital Discharge\u003c/h2\u003e \u003cp\u003eCompared with survivors, non-survivors had higher rates of complications: sepsis (21.0% vs. 1.3%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), pulmonary embolism (4.6% vs. 0.9%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), lower gastrointestinal bleeding (6.1% vs. 1.5%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and ischemic stroke (13.8% vs. 6.0%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), respectively. Moreover, non-survivors had higher incidence rates of rehospitalization (83.0% vs. 27.6%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), ICU admission (21.1% vs. 1.7%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and ER visit (75.7 vs. 33.9, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComplications and Healthcare Usage after Hospital Discharge\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;63,369)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1-Year Survivors (n\u0026thinsp;=\u0026thinsp;60,276)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1-Year Non-Survivors (n\u0026thinsp;=\u0026thinsp;3093)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost\u0026ndash;COVID-19 condition (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2528 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2374 (3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e154 (5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSepsis (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1407 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e758 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e649 (21.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeptic shock (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e308 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e202 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyocardial infarction (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e917 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e835 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThrombosis event (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeep vein thrombosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e600 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e496 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e104 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulmonary embolism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e695 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e552 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e143 (4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBleeding events (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpper gastrointestinal bleeding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e839 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e797 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.524\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLower gastrointestinal bleeding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1074 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e884 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e190 (6.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroke (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIschemic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4072 (6.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3646 (6.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e426 (13.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemorrhagic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e740 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e622 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e118 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIschemic or hemorrhagic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e429 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e388 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransient ischemic attack (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e943 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e918 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealthcare usage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRehospitalization (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19,218 (30.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16,652 (27.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2566 (83.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital length of stay (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63\u0026thinsp;\u0026plusmn;\u0026thinsp;75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62\u0026thinsp;\u0026plusmn;\u0026thinsp;74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84\u0026thinsp;\u0026plusmn;\u0026thinsp;87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse of MV (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e919 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e274 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e645 (20.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse of vasopressors (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4732 (7.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3259 (5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1473 (47.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICU admission (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1656 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1002 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e654 (21.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of ICU stay (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u0026thinsp;\u0026plusmn;\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOPD visit (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58,572 (92.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57,146 (94.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1426 (46.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eED visit (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22,779 (35.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20,439 (33.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2340 (75.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital discharge to ER visit (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113\u0026thinsp;\u0026plusmn;\u0026thinsp;111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e122\u0026thinsp;\u0026plusmn;\u0026thinsp;112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39\u0026thinsp;\u0026plusmn;\u0026thinsp;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNumbers are presented as n (%) or mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eMV, mechanical ventilation; ICU, intensive care unit; OPD, outpatient department; ED, emergency department.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eRisk Factors for 1-year Mortality\u003c/h2\u003e \u003cp\u003eThe multivariable logistic regression models for 1-year mortality, as depicted in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, indicate that older age and COVID-19 severity are significant risk factors for 1-year mortality (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Additionally, male sex (OR 1.45 [95% CI 1.32\u0026ndash;1.59], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), immunosuppression (OR 2.48 [95% CI 2.20\u0026ndash;2.81], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), vaccination (OR 0.18 [95% CI 0.16\u0026ndash;0.20], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), macrolide use (OR 0.45 [95% CI 0.35\u0026ndash;0.57], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), antiplatelet therapy (OR 0.66 [95% CI 0.60\u0026ndash;0.73], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), corticosteroid treatment (OR 1.16 [95% CI 1.05\u0026ndash;1.29], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.003), renal replacement therapy (OR 2.28 [95% CI 1.69\u0026ndash;3.07], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), and the number of organ dysfunctions were all significantly associated with 1-year mortality.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and Multivariable Logistic Regression Model for 1-Year Mortality among COVID-19 Survivors\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnivariate Analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMultivariable Analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.62 (3.26\u0026ndash;4.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.61 (3.19\u0026ndash;4.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.69 (13.33\u0026ndash;16.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.60 (17.41\u0026ndash;22.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.13 (1.05\u0026ndash;1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.45 (1.32\u0026ndash;1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.807\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.04 (1.88\u0026ndash;2.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.99 (0.89\u0026ndash;1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImmunosuppression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.80 (2.55\u0026ndash;3.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.48 (2.20\u0026ndash;2.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaccination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.15 (0.14\u0026ndash;0.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.18 (0.16\u0026ndash;0.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of organ dysfunction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.84 (2.60\u0026ndash;3.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.35 (1.21\u0026ndash;1.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.38 (9.94\u0026ndash;13.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.63 (2.17\u0026ndash;3.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.20 (25.83\u0026ndash;42.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.12 (2.85\u0026ndash;5.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84.82 (49.59\u0026ndash;145.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.12 (3.76\u0026ndash;17.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeverity of COVID-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo oxygen or supplemental oxygen therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHFNC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.50 (23.09\u0026ndash;32.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.73 (10.17\u0026ndash;15.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60.39 (51.84\u0026ndash;70.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.31 (26.28\u0026ndash;42.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eECMO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e142.88 (80.52\u0026ndash;253.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e89.92 (45.80\u0026ndash;176.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHydroxychloroquine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.79 (0.46\u0026ndash;1.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.84 (0.43\u0026ndash;1.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.594\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMacrolides\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.50 (0.41\u0026ndash;0.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.45 (0.35\u0026ndash;0.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6 inhibitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.50 (1.57\u0026ndash;7.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.67 (0.19\u0026ndash;2.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.540\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntiplatelet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.13 (1.04\u0026ndash;1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.66 (0.60\u0026ndash;0.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCorticosteroids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.13 (1.98\u0026ndash;2.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.16 (1.05\u0026ndash;1.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal replacement therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.70 (5.48\u0026ndash;8.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.28 (1.69\u0026ndash;3.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICU admission after discharge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.86 (14.26\u0026ndash;17.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.14 (0.93\u0026ndash;1.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.211\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eOR, odds ratio; CI, confidence interval; CCI, Charlson Comorbidity Index; HFNC, high-flow nasal cannula; MV, mechanical ventilation; ECMO, extracorporeal membrane oxygenation; IL-6, interleukin 6; ICU, intensive care unit.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eChange in Quality of Life\u003c/h2\u003e \u003cp\u003eCompared to the period before the diagnosis of COVID-19, there was an increase in job loss among patients after they contracted COVID-19 (24.1% vs. 21.8%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001) (Table S6). Furthermore, there was a significant rise in both mild to moderate and severe disabilities following a COVID-19 diagnosis (8.6% vs. 9.3%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001; and 4.1% vs. 4.6%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001). Among the survivors of COVID-19, the most frequently reported symptoms included myalgia (24.3%), anxiety (14.1%), and chest pain (13.6%) (Table S7). Depression was also prevalent (12.2%), with cough being the most common respiratory symptom (8.8%).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eUsing nationwide data, we evaluated the 1-year mortality and associated symptoms and complications in COVID-19 survivors aged 60 years and older in Korea. The mortality rate of COVID-19 survivors within 1 year was 4.9%, closely mirroring the in-hospital mortality rate of 4.8%. Factors linked to one-year mortality included older age, male sex, the severity of COVID-19, immunosuppression, organ dysfunction, and corticosteroid use. Vaccination before contracting COVID-19 proved advantageous. When compared to the period before the diagnosis, the post-COVID-19 quality of life diminished, particularly in terms of employment and disability status. Survivors of COVID-19 were found to suffer from a range of physical and mental sequelae.\u003c/p\u003e \u003cp\u003eSeveral studies have documented long-term mortality among patients with COVID-19\u003csup\u003e6,7,9,12\u0026ndash;14\u003c/sup\u003e. A systematic review and meta-analysis of nine studies reported a 1-year post-discharge all-cause mortality rate for COVID-19 at 7.87%\u003csup\u003e9\u003c/sup\u003e. However, these rates varied significantly from country to country, with one-year mortality rates reported as high as approximately 12% in Italy and the United Kingdom, and as low as approximately 2% in Brazil and Sweden. This discrepancy may be attributed to the varying capacities of countries to hospitalize patients and the lack of standardized criteria for discharging patients with COVID-19\u003csup\u003e9\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eLong-term mortality is affected by various factors, including the severity of the illness and age\u003csup\u003e6,9,12,13,15\u003c/sup\u003e. In a study focusing on COVID-19 patients discharged from the ICU, the 1-year mortality rate reached 29.9%\u003csup\u003e6\u003c/sup\u003e. Age also plays a critical role; Di Bari et al. found that the 1-year mortality rate for COVID-19 patients over 75 years old, hospitalized via the ED, was as high as 48.4%, in contrast to 33.9% for non-COVID-19 patients\u003csup\u003e14\u003c/sup\u003e. Our study, which included patients over 60 years of age, observed a relatively low 1-year mortality rate of 4.9%. These aforementioned studies included more severely ill patients, with more than 50% requiring intensive care\u003csup\u003e6,12\u003c/sup\u003e, whereas only 1.7% of the patients in our study required MV, which may account for the observed difference in mortality rates.\u003c/p\u003e \u003cp\u003eA nationwide cohort study from Estonia indicated that underlying diseases, such as cardiovascular disease, cancer, and respiratory system diseases, were linked to increased long-term mortality in COVID-19 patients aged 60 years or older\u003csup\u003e16\u003c/sup\u003e. Our findings suggest that several factors, both prior to and following hospital discharge, are associated with long-term mortality. Organ dysfunction and the severity of illness during hospitalization are influential on long-term survival. Specifically, when compared to patients who either did not require oxygen therapy or received supplemental oxygen therapy alone, those who were treated with HFNC and MV experienced 12.7 and 33.3 times higher 1-year mortality, respectively. Notably, corticosteroids, which are administered to critically ill COVID-19 patients to mitigate the inflammatory response\u003csup\u003e17\u003c/sup\u003e, were associated with poor outcomes. This association may be due to the more frequent use of corticosteroids in severely ill patients. Nevertheless, given that corticosteroid use is tied to serious adverse reactions such as septic shock and invasive fungal infections\u003csup\u003e18\u003c/sup\u003e, the potential for detrimental long-term effects of corticosteroids cannot be disregarded.\u003c/p\u003e \u003cp\u003eH\u0026auml;ggl\u0026ouml;f et al. found that men had a 1.33 times higher 360-day mortality risk than women in a Swedish nationwide study of COVID-19 ICU patients\u003csup\u003e6\u003c/sup\u003e. Similarly, a German nationwide cohort study indicated that being female was a protective factor against 6-month mortality in COVID-19 patients (OR, 0.63 in females)\u003csup\u003e19\u003c/sup\u003e. While these studies typically included more male than female patients, our study comprised fewer male patients at 47.4%. Nevertheless, our research demonstrated that male sex was associated with poorer long-term mortality compared to female (OR, 1.45). Although no definitive theoretical hypothesis has been established to explain the gender disparities in long-term mortality among COVID-19 patients, biological and sociocultural differences between men and women are evident. Such differences may contribute to higher rates of ICU admissions and the prevalence of sepsis in men\u003csup\u003e20\u003c/sup\u003e. Zettersten et al. proposed that the increased risk of adverse long-term outcomes in male COVID-19 patients might be attributable to the influence of sex hormones on inflammation\u003csup\u003e21\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eVaccines designed to prevent COVID-19 infection offer protection against severe disease and death\u003csup\u003e22\u003c/sup\u003e. Moreover, vaccines have a sustained effect on reducing post-COVID-19 conditions (OR of vaccination, 0.57)\u003csup\u003e23\u003c/sup\u003e, and long-term health consequences\u003csup\u003e24\u003c/sup\u003e. Consistent with our study results (OR of vaccination for 1-year mortality, 0.18), Lam et al. demonstrated the potential of vaccination in lowering the risk of long-term mortality following a COVID-19 infection\u003csup\u003e24\u003c/sup\u003e. Compared to patients who received a complete and booster dose of vaccination, those who were unvaccinated faced a higher risk of all-cause mortality within 1 year. One possible explanation for this finding is that vaccines, by reducing the severity of COVID-19, lead to a decreased risk of long-COVID conditions\u003csup\u003e25\u003c/sup\u003e. Additionally, vaccines may diminish long-term mortality by curtailing the exaggerated inflammatory immune response linked to viral persistence\u003csup\u003e26\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWe found that numerous patients endured a variety of physical and mental issues after being discharged from the hospital following COVID-19. These persistent symptoms are known to be associated with female sex and older age\u003csup\u003e23\u003c/sup\u003e. We also found that 1-year non-survivors experienced various critical events, such as sepsis, myocardial infarction, pulmonary thromboembolism, stroke, and gastrointestinal bleeding, more frequently than survivors. While some studies have suggested that disease severity is not linked to post\u0026ndash;COVID-19 condition\u003csup\u003e23,27,28\u003c/sup\u003e, our study findings indicate that patients who were critically ill during hospitalization were more likely to suffer from long-term complications and mortality. This discrepancy may arise because previous studies on long-COVID syndrome relied on data collected using ICD-10 codes (e.g., U09.9), or based on mild symptom reports\u003csup\u003e29\u003c/sup\u003e. Severe COVID-19 that necessitates hospitalization can provoke a more intense immune response and cytokine storm, potentially leading to more prolonged organ damage.\u003c/p\u003e \u003cp\u003eOur study had several limitations. First, because it was a retrospective registry-based study, we could not collect information on complications during hospitalization and detailed demographics, such as smoking history or body mass index. Additionally, data on functional dependencies or cognitive impairment, which are recognized risk factors for rehospitalization or death, were not available\u003csup\u003e30\u003c/sup\u003e. Second, it is challenging to ascertain whether the causes of rehospitalization, ED or OPD visits, and post-discharge complications were directly related to COVID-19. Third, this study included only patients in the early phase of the COVID-19 pandemic and did not account for patients affected by various COVID-19 variants, potentially limiting the generalizability of the findings. The Korean government\u0026rsquo;s stringent quarantine policies led to a relatively low number of initial patients with COVID-19. Furthermore, the enrollment period for this dataset was restricted to allow for the assessment of 1-year post-discharge mortality. Despite these limitations, our study is a comprehensive nationwide study with a large cohort, providing insights into the natural history of hospitalized older patients with COVID-19.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe 1-year mortality after hospital discharge for patients with COVID-19 was found to be comparable to the in-hospital mortality rate in Korea. The long-term mortality of hospitalized COVID-19 patients is influenced by factors such as age and the severity of illness experienced during hospitalization. It is imperative that we maintain vigilance and provide thorough care for older patients who have undergone critical care, even after their discharge from the hospital.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eData Source and Ethical Statement\u003c/h2\u003e \u003cp\u003eThis study used the K-COV-N database, which is linked to the Korean National Health Insurance Service (NHIS) database, the nationwide COVID-19 vaccination registry, and COVID-19-positive patient information from the Korea Disease Control and Prevention Agency (KDCA). The NHIS database encompasses healthcare claims for approximately 97% of the population in the Republic of Korea. Diagnoses are recorded using the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes, and prescription information for drugs and procedures is compiled in the NHIS database to facilitate financial support for treatment expenses. Data extraction was conducted by an independent medical record technician at the NHIS center, unaffiliated with this study.\u003c/p\u003e \u003cp\u003e The study protocol was approved by the institutional review board of Chung-Ang University (1041078-20221111-BR-010). Informed consent was waived because data analyses were performed retrospectively using anonymized data from the South Korean NHIS database. All procedures in this study were performed according to the relevant guidelines and regulations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Population\u003c/h2\u003e \u003cp\u003eThe study encompassed patients with confirmed COVID-19 who were hospitalized between October 8, 2020, and December 31, 2021. Older adults, defined as individuals aged 60 years or above, who were hospitalized within 2 weeks following a confirmed COVID-19 diagnosis, were categorized as older hospitalized patients with COVID-19\u003csup\u003e31\u003c/sup\u003e. The analysis focused on patients who were discharged alive. Exclusion criteria included: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) age under 60 years, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) absence of hospitalization within 14 days post-COVID-19 diagnosis, (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) death during hospitalization, and (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) lack of sufficient clinical data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eData Collection and Definitions\u003c/h2\u003e \u003cp\u003ePatient characteristics encompassed age, sex, comorbidities, Charlson Comorbidity Index (CCI) using ICD-10 codes, and income level at hospital admission (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Income levels were categorized into four quartiles, ranging from Q1, the lowest, to Q4, the highest.\u003c/p\u003e \u003cp\u003eImmunosuppression was defined as the presence of any malignancies, HIV or AIDS, organ transplantation, or the prescription of corticosteroids for 30 days or more during hospitalization\u003csup\u003e32\u003c/sup\u003e. The assessment of organ dysfunction, severity of illness, and various treatments was conducted during hospitalization. Organ dysfunction included conditions affecting the cardiovascular, respiratory, neurologic, hematologic, hepatic, renal, and metabolic systems (Table S2). The severity of COVID-19 was evaluated using an ordinal scale: no oxygen or supplemental oxygen group, high-flow nasal cannula (HFNC), mechanical ventilation (MV), and extracorporeal membrane oxygenation (ECMO) (Table S3)\u003csup\u003e8\u003c/sup\u003e. Medications prescribed included hydroxychloroquine, macrolides, IL-6 inhibitors, antiplatelet agents, corticosteroids, and vasopressors. Additionally, data on renal replacement therapy, hospital stay duration, ICU admission, ICU stay length, MV duration, and ECMO duration were compiled.\u003c/p\u003e \u003cp\u003eThe primary outcome of this study was the 1-year mortality rate following hospital discharge. Healthcare usage within the first year after discharge was documented, including rehospitalization, hospital stay length, MV usage, vasopressor usage, ICU admission, ICU stay length, outpatient department (OPD) visits, emergency department (ED) visits, and transitions from hospital discharge to ED visits. After discharge, survivors\u0026rsquo; ICD-10 codes related to various complications were investigated, including post\u0026ndash;COVID-19 condition, sepsis, septic shock, myocardial infarction, thrombotic events (deep vein thrombosis and pulmonary embolism), bleeding events (upper and lower gastrointestinal bleeding), strokes (ischemic, hemorrhagic, and mixed), and transient ischemic attacks (Table S4). Long-term symptoms experienced during healthcare usage were also investigated (Table S5)\u003csup\u003e15\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eChanges in patients\u0026rsquo; status before and after COVID-19 diagnoses were assessed based on employment, disability, and annual income levels. The types of disability included physical, brain lesions, visual, hearing, speech, intellectual, mental, renal, heart, respiratory, hepatopathy, intestinal and urinary fistulae, and epilepsy. Each disability was rigorously classified according to legal standards by specialist physicians in each respective field, with a grading system ranging from 1 to 6\u003csup\u003e33\u003c/sup\u003e. Grades 1 through 3 were considered severe disabilities, while grades 4 through 6 were categorized as mild to moderate disabilities, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eCategorical variables are presented as numbers (percentages), and continuous variables are presented as median (interquartile range). To compare differences between 1-year survivors and non-survivors, the chi-square test and Student\u0026rsquo;s t-test were used for categorical and continuous variables, respectively. McNemar\u0026rsquo;s test was performed to compare changes in quality of life before and after the diagnosis of COVID-19. Multivariable logistic regression analyses were conducted to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for factors associated with 1-year mortality. Variables with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.1 in univariate analysis and those deemed clinically relevant were included in the multivariable logistic regression model. After addressing multicollinearity among variables, the final multivariable regression model comprised age, sex, CCI, immunosuppression, vaccination status, number of organ dysfunctions, severity of COVID-19 (no oxygen or supplemental oxygen therapy, HFNC, MV, and ECMO), hydroxychloroquine, macrolides, IL-6 inhibitor, antiplatelet, corticosteroids, renal replacement therapy, and ICU admission post-discharge. The OR for each variable was reported with a 95% CI. Additionally, Kaplan-Meier curves were plotted up to 1 year from the index date, and differences between age groups, sex, and severity of illness were compared using log-rank tests. Sankey diagrams visualized the overall distribution of variables according to age group, COVID-19 severity, in-hospital mortality, and overall 1-year mortality for COVID-19. Statistical analyses were executed using SAS Enterprise software version 7.1 (SAS Inc., Cary, NC, USA) and R Studio software version 4.3.1 (R Studio Inc., Boston, MA, USA), with statistical significance established at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMSB and SYJ conceived and designed the\u0026nbsp;study. EK, JYK, SYJ, and MSB collected the primary data and conducted data analyses. EK, KMM, TWK, WYK, SYJ, and MSB interpreted the results and prepared the first draft. All\u0026nbsp;the\u0026nbsp;authors revised the draft for important intellectual content and approved the final manuscript submitted for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed in the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEunji Kim\u003csup\u003e1\u003c/sup\u003e, Jeong-Yeon Kim\u003csup\u003e1\u003c/sup\u003e, Kyoung Min Moon\u003csup\u003e2\u003c/sup\u003e, Tae Wan Kim\u003csup\u003e2\u003c/sup\u003e, Won-Young Kim\u003csup\u003e2\u003c/sup\u003e, Sun‑Young Jung\u003csup\u003e1,3\u003c/sup\u003e*, Moon Seong Baek\u003csup\u003e2,4\u003c/sup\u003e*\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eDepartment of Global Innovative Drugs, The Graduate School of Chung‑Ang\u0026nbsp;University, Chung‑Ang University, Seoul, Republic of Korea\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003eDepartment of Internal Medicine, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Republic of Korea\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003eCollege of Pharmacy, Chung‑Ang University, Seoul, Republic of Korea\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e4\u003c/sup\u003eBiomedical Research Institute, Chung-Ang University Hospital, Seoul, Republic of Korea\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by the Institutional Review Board of Chung-Ang University (1041078-20221111-BR-010). Informed consent was waived because data analyses were performed retrospectively using anonymized data from the South Korean NHIS database.\u0026nbsp;All procedures in this study were performed according to the relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by a research grant from the Biomedical Research Institute of Chung-Ang University Hospital (2023).\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eThygesen, J. H. \u003cem\u003eet al.\u003c/em\u003e COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records. Lancet Digit Health 4, e542-e557. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/s2589-7500(22)00091-7\u003c/span\u003e\u003cspan address=\"10.1016/s2589-7500(22)00091-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaptista, A., Vieira, A. M., Capela, E., Juli\u0026atilde;o, P. \u0026amp; Macedo, A. COVID-19 fatality rates in hospitalized patients: A new systematic review and meta-analysis. 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PLoS One 16, e0257641. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0257641\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0257641\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChoi, H. R., Song, I. A. \u0026amp; Oh, T. K. Quality of life and mortality among survivors of acute respiratory distress syndrome in South Korea: a nationwide cohort study. J Anesth 36, 230\u0026ndash;238. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00540-022-03036-9\u003c/span\u003e\u003cspan address=\"10.1007/s00540-022-03036-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"COVID-19, Survivors, Mortality, Age Factors, Critical Illness","lastPublishedDoi":"10.21203/rs.3.rs-4427690/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4427690/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study aimed to evaluate the 1-year mortality rate among older patients with COVID-19 discharged from hospital and to identify the risk factors associated with this outcome.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing a COVID-19 dataset from the Korean National Health Insurance System, this study’s evaluation period spanned from October 8, 2020, to December 31, 2021. The primary outcome was the 1-year mortality rate following hospital discharge. A logistic regression model was employed for multivariable analysis to estimate the odds ratios for the outcomes, and the Kaplan-Meier method was used to analyze differences in 1-year survival rates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOf the 66,810 COVID-19 patients aged 60 years or older who were hospitalized during the study period, the in-hospital mortality rate was 4.8% (n = 3219). Among the survivors (n = 63,369), the 1-year mortality rate was 4.9% (n = 3093). Non-survivors, compared to survivors, were significantly older (79.2 ± 9.5 vs. 68.9 ± 7.8, \u003cem\u003eP\u003c/em\u003e \u0026lt; .001) and exhibited a lower rate of COVID-19 vaccination (63.1% vs. 91.8%, \u003cem\u003eP\u003c/em\u003e \u0026lt; .001). Additionally, non-survivors experienced a higher incidence of organ dysfunction, and a greater proportion required mechanical ventilation (14.6% vs. 1.0%, \u003cem\u003eP\u003c/em\u003e \u0026lt; .001) and extracorporeal membrane oxygenation (4.0% vs. 0.1%, \u003cem\u003eP\u003c/em\u003e \u0026lt; .001). Multivariable logistic regression analysis identified older age, male sex, immunosuppression, organ dysfunction, severity of illness, and corticosteroid use during hospitalization as factors associated with death within 1 year after hospital discharge. However, vaccination was found to have a long-term protective effect against mortality among COVID-19 survivors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions and Implications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 1-year mortality rate after hospital discharge for older COVID-19 patients was comparable to the in-hospital mortality rate for these patients in Korea. The long-term mortality rate among hospitalized older COVID-19 patients was influenced by demographic factors and the severity of illness experienced during hospitalization.\u003c/p\u003e","manuscriptTitle":"One-Year Mortality and Associated Factors in Older Hospitalized COVID-19 Survivors: A Nationwide Cohort Study in Korea","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-04 19:00:11","doi":"10.21203/rs.3.rs-4427690/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-05T07:37:43+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-02T02:55:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-01T13:14:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"221176091113201233758517542133122983382","date":"2024-06-19T22:46:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"235035526781618417187081073685780170947","date":"2024-06-19T14:23:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"117533118304564015824279134010325355557","date":"2024-06-19T14:16:38+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-12T19:35:48+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-12T19:34:45+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-05-22T10:50:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-20T04:35:17+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-05-16T01:20:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6fc3a47f-a5ca-45c8-acd7-3a581343b6ae","owner":[],"postedDate":"June 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":32448229,"name":"Health sciences/Medical research"},{"id":32448230,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2024-10-28T16:12:33+00:00","versionOfRecord":{"articleIdentity":"rs-4427690","link":"https://doi.org/10.1038/s41598-024-76871-3","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-10-22 15:58:09","publishedOnDateReadable":"October 22nd, 2024"},"versionCreatedAt":"2024-06-04 19:00:11","video":"","vorDoi":"10.1038/s41598-024-76871-3","vorDoiUrl":"https://doi.org/10.1038/s41598-024-76871-3","workflowStages":[]},"version":"v1","identity":"rs-4427690","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4427690","identity":"rs-4427690","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}