Assessment of the Efficacy and Safety of Baricitinib Treatment in COVID-19 Patients: a real-world study

Assessment of the Efficacy and Safety of Baricitinib Treatment in COVID-19 Patients: a real-world study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Assessment of the Efficacy and Safety of Baricitinib Treatment in COVID-19 Patients: a real-world study Mengyu Cheng, Junyan Zhang, Zhifeng Xue, Jian Li, Zhigang Pang, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4418170/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Backgroud This retrospective cohort study assessed the real-world effectiveness and safety of Baricitinib (BAR) in hospitalized adult patients with severe or critical COVID-19 infection. Methods Utilizing real-world data. Propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) were applied to address imbalances in baseline characteristics. The Cox regression model was employed to assess the hazard ratio of treatment efficacy, utilizing both unmatched and matched datasets. The primary outcome focused on all-cause mortality among hospitalized patients. Results Among initially screened 2,731 adults with COVID-19 infection, 2,454 were included in this analysis (2,312 non-BAR, 142 BAR). In total, there were 39 deaths, with 36 occurring in the non-BAR group and 3 in the BAR group. Multivariable Cox regression analysis demonstrated that BAR was associated with a lower risk of all-cause mortality (hazard ratio [HR] = 0.24, 95% confidence interval [CI] 0.07–0.83, p < 0.024). Analysis based on the PSM datasets consistently showed that BAR reduced the risk of all-cause mortality in 1:1 (HR = 0.10, 95% CI 0.01–0.86), 1:2 (HR = 0.11, 95% CI 0.01–0.88, p = 0.038), and 1:3 (HR = 0.08, 95% CI 0.01–0.66) matched databases. Analysis based on the IPTW dataset also indicated that BAR reduced the risk of all-cause mortality (HR = 0.06, 95% CI 0.01–0.41, p = 0.004). The incidence of Venous Thrombosis Events (VTE) was higher in the BAR group compared to the non-BAR group (11.27% vs. 6.14%, p = 0.016). Conclusions BAR demonstrated effectiveness in reducing all-cause mortality in hospitalized COVID-19 patients, with an acceptable safety profile. BAR COVID-19 infection SARS-CoV-2 Real-world study Retrospective cohort All cause of mortality Figures Figure 1 Figure 2 Introduction The COVID-19 pandemic, triggered by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants, is continuously evolving and is poised to remain a significant public health concern in the foreseeable future[ 1 ]. In comparison to other mutant strains, the SARS-CoV-2 Omicron variant has demonstrated significantly heightened transmissibility and a greater propensity for immune evasion[ 2 , 3 ]. Several studies have highlighted the tropism of the Omicron variant towards the upper respiratory tract[ 4 – 6 ]. Since December 2022, there has been a significant increase in the number of COVID-19 cases in mainland China, including those classified as severe or critical. Presently, available treatment options for COVID-19 primarily consist of antiviral therapy[ 7 ], Janus kinase inhibitors[ 8 ], neutralizing therapy[ 9 ] and steroids[ 10 ]. Our comprehension of the impact of various categories of potential treatments has markedly advanced due to their diversity. Particularly, effectiveness and safety are fundamental considerations in formulating treatment strategies for patients with severe or critical COVID-19 infection during the surge outbreak. The pronounced pulmonary inflammatory responses observed in patients with severe or critical COVID-19 infection indicate the potential efficacy of anti-inflammatory medications in clinical settings. In practice, counteracting hyperinflammatory responses has been linked to clinical benefits. For example, IL-6 receptor antagonists like tocilizumab have shown potential to enhance clinical outcomes in critical cases of COVID-19 infection by reducing cytokine release and the production of acute phase proteins[ 11 ]. Baricitinib (BAR), an oral selective Janus kinase 1/2 inhibitor, is approved for patients with autoimmune diseases owing to its recognized anti-inflammatory properties, such as rheumatoid arthritis[ 12 ], atopic dermatitis[ 13 ], and alopecia areata[ 14 ]. BAR has been demonstrated to inhibit the release of multiple cytokines, including IL-6 and interferon-gamma[ 12 ], and to disrupt the binding of SARS-CoV-2 to the angiotensin-converting enzyme 2 receptor[ 15 ]. Several observational cohort studies have indicated that BAR reduces mortality and the risk of progression to invasive mechanical ventilation in hospitalized patients with COVID-19 infection. Moreover, when compared to tocilizumab, BAR has been associated with a lower risk of elevated liver enzyme levels[ 16 – 18 ]. The collective randomized evidence available to date indicates that JAK inhibitors, primarily BAR, decrease mortality in patients hospitalized for COVID-19 by approximately one-fifth[ 18 ]. However, in a clinical trial investigating the efficacy and safety of BAR in treating severe or critical COVID-19, the trial was prematurely halted due to insufficient external evidence and being underpowered to conclusively determine any potential survival benefit of BAR in severe/critical COVID-19 cases[ 15 ]. In China, the safety and efficacy of BAR in patients with Omicron infection remain unclear, warranting further investigation through additional trials and real-world studies. Previously, the combination of BAR with corticosteroids was endorsed by the World Health Organization guidelines for patients with severe or critical COVID-19 infection[ 19 ], particularly for hospitalized patients requiring supplemental oxygen, non-invasive or invasive mechanical ventilation, or extracorporeal membrane oxygenation[ 20 ]. However, there is still a lack of evidence from real-world studies documenting the efficacy and safety of BAR for COVID-19-infected patients in China. Therefore, we conducted a retrospective, single-center cohort study to assess the real-world efficacy and safety of BAR for adult patients with severe or critical COVID-19 infection. Methods Ethics approval This study was performed according to the Helsinki declaration of 1975 and was approved by the ethics committee in the Shanxi Bethune Hospital of Shanxi Academy of Medical Sciences (YXL-2023-254), with a waiver granted for patient consents. Study design This was a real-world retrospective cohort study evaluating the efficacy and safety of BAR among adult hospitalized patients with severe/critical COVID-19 infection in Shanxi Bethune Hospital, China. Between October 5th, 2022 and February 1st, 2023, hospitalized patients should have a confirmed diagnosis of COVID-19 infection according to a positive nucleic acid assay of SARS-CoV-2, in accordance with the “Diagnosis and Treatment Plan for COVID-19 Infection (Trial Version 10)”, issued by the National Health Commission[ 21 ]. Eligible patients were also required to meet the following inclusion criteria: Eligible patients were adults (≥ 18 years) with SARS-CoV-2 infection; Exclusion criteria were 1) imminent death, anticipated hospital discharge or transfer within ≤ 48 hours after diagnosis, or 2) administration of standard of care for ≤ 48 hours after diagnosis, 3) receipt of any biologics agents such as interleukin-6 or Janus kinase inhibitors before COVID-19 infection diagnosis, 4) The usage of BAR beyond 96 hours of hospitalization; 5) pregnancy or breastfeeding This study was approved by the ethics committee of Shanxi Bethune Hospital (YXL-2023-254). Treatments According to the Diagnosis and Treatment Plan for COVID-19 Infection (Trial Version 10)[ 21 ], the hospitalized patients with COVID-19 infection were given routine treatment depending on their individual status, including oxygen therapy, oral administration of azivudine (5mg/day) or Nirmatrelvir-Ritonavir (300mg-100mg/12h) for anti-virus therapy, and glucocorticoid therapy (dexamethasone 5-7.5 mg/day or methylprednisolone injection 40–80 mg/day) so on until hospital discharge or death. During the routine treatment process, based on the clinical usage standards of BAR, the eligible patients were administered BAR tablets orally within four days after hospital admission (4 mg/day) or within 48 hours of the intensive care unit. In addition, patients with glomerular filtration rates below 60 ml/min received halved-dose BAR (2 mg/day) for admission for up to 14 days, and the patient was permanently stopped if the patient was discharged from the hospital. Besides the above treatments, individuals who received BAR were classified as the BAR group, while the others were classified as the non-BAR group. Safety assessment The safety profile includes treatment adverse events that occur from the treatment initiation to the endpoint. We also recorded any serious adverse events, such as gastrointestinal perforation, cardiovascular malignancy, venous thrombotic events, and secondary infections. Statistical analysis The primary endpoint was all causes of mortality during hospitalization. The duration of survival was calculated from the date of hospital admission until death from any causes or the date of discharge. Continuous variables were reported as mean followed by the standard deviation (SD) or median (interquartile ranges, Q1 ~ Q3), and categorical variables were reported as percentage or proportion (%). Student’s t-test and Wilcoxon rank-sum test were used for normally and abnormally distributed quantitative data. Chi-square or Fisher’s exact test analyzed categorical variables. Cox proportional hazards models were applied to analyze the relevant risk of all causes of mortality and reported as hazard ratio (HR) followed by a 95% confidence interval (CI). To balance patients in these two groups, propensity score matching (PSM) was performed with a caliper set at 0.02. Datasets were generated with the ratios of 1:1, 1:2, and 1:3 for the BAR group vs. the non-BAR group. Additionally, an inverse probability of treatment weighting (IPTW) dataset was generated to balance fundamental variables across these groups. All hypothesis tests were two-sided, with statistical significance defined as a p-value < 0.05. Statistical analyses were performed using Stata SE 13 (Serial number 401306302851), R software version 3.6.1 ( http://cran.r-project.org/ ), and easy-R ( www.empowerstats.com ). The sample size was determined assuming a 5% mortality rate in the entire population, coupled with a BAR hazard ratio (HR) of 0.3, employing α = 0.05, β = 0.2. With a 1:10 ratio, the total sample size was 1320, comprising 120 subjects in the BAR group and 1200 in the non-BAR group. Results Participants A total of 2,731 hospitalized patients with COVID-19 infection were initially screened, and 2,454 patients were ultimately included in this analysis, as depicted in Fig. 1 . Among these, 142 were classified into the BAR group, while the remaining 2,312 were assigned to the non-BAR group. Table 1 provides an overview of the general characteristics of all participants, including those from the PSM dataset with a 1:1 ratio. Table 1 General Characteristics of Before and After PSM Unmatched Data PSM Data (1:1 ratio) non-BAR (n = 2312) BAR (n = 142) P-value non-BAR (n = 123) BAR (n = 123) P-value SMD Age mean ± sd 64.23 ± 19.64 83.36 ± 4.03 < 0.001 82.28 ± 7.53 83.26 ± 4.32 0.214 0.159 Sex [n (%)] male 1235 (53.42%) 88 (61.97%) 0.047 73 (59.35%) 77 (62.60%) 0.601 0.067 Smoking [n (%)] no 1810 (78.29%) 105 (73.94%) 0.345 92 (74.80%) 91 (73.98%) 0.605 0.128 yes 474 (20.50%) 36 (25.35%) 31 (25.20%) 31 (25.20%) unknown 28 (1.21%) 1 (0.70%) 0 (0.00%) 1 (0.81%) Disease’s severity [n (%)] moderate 1154 (49.91%) 11 (7.75%) < 0.001 14 (11.38%) 11 (8.94%) 0.179 0.238 sever 1053 (45.54%) 114 (80.28%) 92 (74.80%) 103 (83.74%) critical 105 (4.54%) 17 (11.97%) 17 (13.82%) 9 (7.32%) ILD [n (%)] 37 (1.60%) 3 (2.11%) 0.640 1 (0.81%) 3 (2.44%) 0.313 0.129 COPD [n (%)] 74 (3.20%) 5 (3.52%) 0.834 2 (1.63%) 5 (4.07%) 0.250 0.147 ARDS [n (%)] 15 (0.65%) 0 (0.00%) 0.336 0 0 NA < 0.001 Hypertension [n (%)] no 1534 (66.35%) 93 (65.49%) 0.860 81 (65.85%) 80 (65.04%) 0.893 0.017 yes 774 (33.48%) 49 (34.51%) 42 (34.15%) 43 (34.96%) unknown 4 (0.17%) 0 (0.00%) CHD [n (%)] no 2183 (94.42%) 127 (89.44%) 0.033 115 (93.50%) 110 (89.43%) 0.254 0.146 yes 125 (5.41%) 15 (10.56%) 8 (6.50%) 13 (10.57%) unknown 4 (0.17%) 0 (0.00%) Stroke [n (%)] no 1857 (80.32%) 111 (78.17%) 0.793 97 (78.86%) 96 (78.05%) 0.877 0.020 yes 454 (19.64%) 31 (21.83%) 26 (21.14%) 27 (21.95%) unknown 1 (0.04%) 0 (0.00%) Diabetics [n (%)] no 1693 (73.23%) 94 (66.20%) 0.180 80 (65.04%) 86 (69.92%) 0.414 0.104 yes 618 (26.73%) 48 (33.80%) 43 (34.96%) 37 (30.08%) unknown 1 (0.04%) 0 (0.00%) Malignant tumors 309 (13.37%) 14 (9.86%) 0.230 14 (11.38%) 12 (9.76%) 0.678 0.053 Hematologic disorders [n (%)] no 1855 (80.23%) 108 (76.06%) 0.461 92 (74.80%) 94 (76.42%) 0.767 0.038 yes 456 (19.72%) 34 (23.94%) 31 (25.20%) 29 (23.58%) unknown 1 (0.04%) 0 (0.00%) Renal dysfunction [n (%)] no 2092 (90.48%) 129 (90.85%) 113 (91.87%) 111 (90.24%) 0.485 0.154 yes 218 (9.43%) 13 (9.15%) 0.935 9 (7.32%) 12 (9.76%) unknown 2 (0.09%) 0 (0.00%) 1 (0.81%) 0 (0.00%) Liver dysfunction [n (%)] no 2065 (89.32%) 125 (88.03%) 0.825 110 (89.43%) 108 (87.80%) 0.688 0.051 yes 245 (10.60%) 17 (11.97%) 13 (10.57%) 15 (12.20%) unknown 2 (0.09%) 0 (0.00%) Neutrophil (10 9 /L) [n (%)] ≤ 7 1866 (80.71%) 90 (63.38%) 7 427 (18.47%) 51 (35.92%) 39 (31.71%) 40 (32.52%) unknown 19 (0.82%) 1 (0.70%) 2 (1.63%) 1 (0.81%) Lymphocyte (10 9 /L) [n (%)] ≤ 0.8 976 (42.21%) 81 (57.04%) 0.002 75 (60.98%) 70 (56.91%) 0.646 0.119 > 0.8 1317 (56.96%) 60 (42.25%) 46 (37.40%) 52 (42.28%) unknown 19 (0.82%) 1 (0.70%) 2 (1.63%) 1 (0.81%) Oxygen saturation [n (%)] ≤ 93% 601 (25.99%) 70 (49.30%) 93% 1184 (51.21%) 67 (47.18%) 52 (42.28%) 65 (52.85%) unknown 527 (22.79%) 5 (3.52%) 3 (2.44%) 4 (3.25%) D-Dimer (ng/ml) [n (%)] ≤ 1500 1874 (81.06%) 101 (71.13%) 1500 203 (8.78%) 28 (19.72%) 19 (15.45%) 21 (17.07%) unknown 235 (10.16%) 13 (9.15%) 12 (9.76%) 11 (8.94%) Glucocorticoids [n (%)] no 732 (31.66%) 0 (0.00%) < 0.001 yes 1576 (68.17%) 142 (100.00%) 123 (100%) 123 (100%) NA < 0.001 unknown 4 (0.17%) 0 (0.00%) Anti-virus [n (%)] 1165 (50.39%) 88 (61.97%) 0.007 82 (66.67%) 74 (60.16%) 0.290 0.135 Oxygen therapy [n (%)] 1865 (80.67%) 133 (93.66%) < 0.001 119 (96.75%) 114 (92.68%) 0.154 0.182 BAR: Baricitinib; non-BAR: Non-Baricitinib; ILD: Interstitial Lung Disease; COPD: Chronic Obstructive Pulmonary Disease; ARDS: Acute Respiratory Distress Syndrome; CHD: Coronary Heart Disease; PSM: Propensity Score Matching; SMD: Standard Mean Difference For more detailed information regarding the participants’ general characteristics, please consult eTable 1 in the appendix. Additionally, eTable 2 in the appendix contains the results of laboratory tests and details of therapeutic regimens for all participants. The general characteristics of the PSM datasets with 1:2 and 1:3 ratios are presented in eTable 3 and eTable 4 in the appendix, respectively. Primary endpoint Within the treatment period, 36 participants from the non-BAR group and 3 from the BAR group deceased (2.11% vs. 1.56%, p = 0.782) (eTable 5 in the appendix). Cox regression analysis of data from all participants The results of univariate analysis indicate that being female (HR = 0.30, 95% CI 0.14 ~ 0.64, p = 0.02), having lymphocyte counts above 0.8×10 9 /L (HR = 0.36, 95% CI 0.18 ~ 0.69, p = 0.002), and maintaining oxygen saturation above 93% (HR = 0.59, 95% CI 0.37 ~ 0.93, p = 0.024) are associated with a decreased risk of all-cause mortality. Conversely, being above 80 years old (HR = 3.50, 95% CI 1.86 ~ 6.60, p < 0.001), having neutrophil counts exceeding 7×10 9 /L (HR = 3.81, 95% CI 2.32 ~ 6.25, p < 0.001), having a higher disease severity (HR = 21.27, 95% CI 11.36 ~ 39.84, p < 0.001), experiencing Acute Respiratory Distress Syndrome (ARDS) (HR = 30.81, 95% CI 11.79 ~ 80.54, p < 0.001), and having renal dysfunction (HR = 2.28, 95% CI 1.07 ~ 4.83, p = 0.032) are associated with an increased risk of all-cause mortality (Table 2 ). Table 2 Cox Regression Analysis of Mortality for All Participants Univariate Analysis (n = 2,454) Multivariate Analysis (n = 2,454) HR 95% CI P-value HR 95% CI P-value Sex (female) 0.30 0.14–0.64 0.002 0.58 0.25–1.33 0.199 Age (above 80) 3.50 1.86–6.60 7×10 9 /L 3.81 2.32–6.25 0.8×10 9 /L 0.36 0.18–0.69 0.002 0.50 0.27–0.94 0.032 Oxygen saturation > 93% 0.59 0.37–0.93 0.024 1.17 0.72–1.88 0.529 D-dimer > 1500 1.38 0.90–2.09 0.136 Diseases severity 21.27 11.36–39.84 < 0.001 15.71 7.78–31.74 < 0.001 ILD 3.77 0.91–15.70 0.068 2.88 0.65–12.77 0.163 COPD 1.54 0.37–6.39 0.553 ARDS 30.81 11.79–80.54 < 0.001 3.42 1.00–11.74 0.051 Hypertension 1.44 0.77–2.70 0.255 CHD 2.16 0.91–5.10 0.080 1.00 0.42–2.41 0.996 Stroke 1.51 0.75–3.02 0.249 Diabetics 1.20 0.61–2.37 0.600 Malignant tumors 1.67 0.79–3.53 0.176 Hematologic disorders 0.85 0.38–1.94 0.706 Renal dysfunction 2.28 1.07–4.83 0.032 1.02 0.45–2.32 0.967 Liver dysfunction 1.15 0.45–2.90 0.773 Glucocorticoids 2.23 0.96–5.19 0.062 1.03 0.37–2.84 0.962 Anti-virus 1.39 0.74–2.63 0.305 Oxygen therapy 1.05 0.46–2.39 0.904 Baricitinib 0.85 0.26–2.77 0.782 0.24 0.07–0.83 0.024 LD: Interstitial Lung Disease; COPD: Chronic Obstructive Pulmonary Disease; ARDS: Acute Respiratory Distress Syndrome; CHD: Coronary Heart Disease; HR: Hazard ratio; CI: Confidence Interval Table 2 also presents the results of the multivariate analysis, which further confirmed that being above 80 years old (HR = 2.04, 95% CI 1.02 ~ 4.05, p = 0.043) and having a higher disease severity (HR = 15.71, 95% CI 7.78 ~ 31.74, p < 0.001) are associated with an increased risk of all-cause mortality. On the contrary, having a lymphocyte count above 0.8×10 9 /L (HR = 0.50, 95% CI 0.27 ~ 0.94, p = 0.032) and receiving BAR treatment (HR = 0.24, 95% CI 0.07 ~ 0.83, p = 0.024) are related to a reduced risk of all-cause mortality. Cox regression analysis of data from PSM datasets Table 3 reveals that the PSM dataset with a 1:1 ratio consists of 123 patients from the BAR group and an additional 123 patients from the non-BAR group. BAR is associated with a reduction in the incidence of all-cause mortality (HR = 0.10, 95% CI 0.01 ~ 0.86, p = 0.035) (Fig. 2 ). Table 3 Cox Regression Analysis of Mortality for PSM Datasets HR 95%CI Lower 95%CI Upper P-value PSM ratio = 1:1 (BAR = 123, non-BAR = 123) Baricitinib 0.10 0.01 0.86 0.035 PSM ratio = 1:2 (BAR = 123, non-BAR = 205) Age > 80 1.16 1.05 1.30 0.005 Baricitinib 0.11 0.01 0.88 0.038 PSM ratio = 1:3 (BAR = 123, non-BAR = 267) Age > 80 2.25 0.62 8.15 0.218 Baricitinib 0.08 0.01 0.66 0.019 BAR: Baricitinib; non-BAR: Non-Baricitinib; PSM: Propensity Score Matching; HR: Hazard ratio; CI: Confidence Interval Furthermore, the analysis of the PSM dataset with a 1:2 ratio (HR = 0.11, 95% CI 0.01 ~ 0.88, p = 0.038) and a 1:3 ratio (HR = 0.08, 95% CI 0.01 ~ 0.66, p = 0.019) reaffirms the same trend, confirming that BAR reduces the incidence of all-cause mortality (Table 3 ). Cox regression analysis of data from IPTW datasets The general characteristics of the IPTW dataset are presented in eTable 6 in the appendix. Since some variables are not well-balanced, multivariate Multiple Cox regression was also conducted. eTable 7 in the appendix demonstrates that patients over 80 years of age (HR = 2.98, 95% CI 1.33 ~ 6.69, p = 0.008) and higher disease severity (HR = 13.58, 95% CI 7.03 ~ 26.23, p < 0.001) are associated with an increased incidence of all-cause mortality. The use of BAR reduced the risk of the primary endpoint (HR = 0.06, 95% CI 0.01 ~ 0.41, p = 0.004). Safety outcomes The overall incidence of adverse events was comparable among the BAR group (30.28%) and the non-BAR group (25.39%) (Table 4 ). The most frequent events which did not differ between the BAR group and the non-BAR group consisted of co or secondary infection (17.61% vs. 13.28%, p = 0.143), followed by venous thrombosis events (11.27% vs. 6.14%, p = 0.016), cardiovascular events (0.70% vs. 3.89%, p = 0.051), and gastrointestinal perforation (0.00% vs. 0.04%, p = 0.804). No adverse events resulting in treatment discontinuation were identified. Table 4 Adverse Events in all participants ALL(n = 2454) non-BAR(n = 2312) BAR (n = 142) P-value 630 (25.67%) 587 (25.39%) 43 (30.28%) 0.347 Gastrointestinal Perforation 1 (0.04%) 1 (0.04%) 0 (0.00%) 0.804 Cardiovascular Event 91 (3.71%) 90 (3.89%) 1 (0.70%) 0.051 cardiovascular death 32 (1.30%) 31 (1.34%) 1 (0.70%) 0.516 myocardial infarction 10 (0.41%) 10 (0.43%) 0 (0.00%) 0.432 stroke 53 (2.16%) 53 (2.29%) 0 (0.00%) 0.068 Venous Thrombosis Event 158 (6.44%) 142 (6.14%) 16 (11.27%) 0.016 pulmonary Embolism 17 (0.69%) 14 (0.61%) 3 (2.11%) 0.036 lower limb thrombosis 127 (5.18%) 112 (4.84%) 15 (10.56%) 0.003 thrombosis in other locations 22 (0.90%) 22 (0.95%) 0 (0.00%) 0.243 Co or Secondary Infection 332 (13.53%) 307 (13.28%) 25 (17.61%) 0.143 bacteria 151 (6.15%) 138 (5.97%) 13 (9.15%) 0.125 fungus 28 (1.14%) 23 (0.99%) 5 (3.52%) 0.006 tubercle bacillus 3 (0.12%) 3 (0.13%) 0 (0.00%) 0.668 influenza virus 126 (5.13%) 116 (5.02%) 10 (7.04%) 0.289 chlamydia 64 (2.61%) 64 (2.77%) 0 (0.00%) 0.045 Discussion This retrospective cohort study has demonstrated the efficacy and safety of oral administration of BAR for a 14-day period among hospitalized patients with COVID-19 infection, most of whom had severe or critical illnesses. Overall, BAR treatment was associated with an 88.5% reduction in the risk of mortality from any cause. Similar findings were observed in PSM analyses at ratios of 1:2 and 1:3. Furthermore, BAR treatment initiated 96 hours or more after hospital admission did not significantly lower the mortality rate compared to treatment initiated earlier. Therefore, patients with severe or critical COVID-19 illness may benefit from BAR treatment initiated within four days of hospital admission. A meta-analysis was conducted to assess the efficacy and safety of BAR in the treatment of hospitalized adults with COVID-19. The results indicate that BAR has resulted in accelerated recovery and reduced hospitalization duration for COVID-19 patients, particularly excluding those in critical condition[ 22 ]. A prior study has documented the efficacy of BAR among patients with COVID-19 infection in a double-blind, randomized phase 3 trial. The objective of this study was to assess the efficacy in terms of the risk reduction for progression to severe COVID-19 infection[ 23 ]. The cumulative randomized evidence to date indicates that JAK inhibitors, primarily BAR, reduce mortality in hospitalized patients with COVID-19 by approximately one-fifth[ 18 ]. The exploratory trial was conducted across 18 hospitals in Argentina, Brazil, Mexico, and the USA to assess the efficacy and safety of BAR in combination with standard care for critically ill hospitalized adults with COVID-19 requiring invasive mechanical ventilation or extracorporeal membrane oxygenation. This study found that in critically ill hospitalized patients with COVID-19 receiving invasive mechanical ventilation or extracorporeal membrane oxygenation, treatment with BAR, in combination with standard care including corticosteroids, reduced mortality compared to placebo. This reduction in mortality aligns with the observed mortality reduction in less severely ill patients in the primary COV-BARRIER study population[ 24 ]. While a more recent randomized, double-blind phase 3 trial examined the efficacy and safety of BAR among hospitalized patients with severe or critical COVID-19 infection, the trial was prematurely terminated, rendering it underpowered to reach a definitive conclusion[ 15 ]. However, there is currently no definitive evidence regarding the effectiveness of BAR in complex scenarios such as severe or critical illness in China, where numerous variants of COVID-19 are prevalent and spreading extensively. Consequently, the efficacy of BAR among hospitalized patients with COVID-19 infection has largely remained uncertain. Our study encompassed a substantial number of hospitalized patients with COVID-19 infection, the majority of whom were afflicted with various sub-variants of the Omicron variant. Additionally, most of our study population experienced severe or critical illness. Moreover, our PSM analyses were conducted at ratios of 1:1, 1:2, and 1:3, which helped eliminate other confounding factors associated with severe or critical illness treated with BAR. Our findings are in line with currently reported results and offer significant guidance for the treatment of COVID-19 patients in China. However, it should be noted that the limitation of our study lies in the current absence of multicenter clinical trials in China. Currently, there have been several monoclonal antibodies, such as sotrovimab[ 25 ] and bamlanivimab[ 26 ] that have been demonstrated to markedly reduce the risk for progression to severe COVID-19 infection. Most of these require intravenous or subcutaneous administration in a medical facility or center. The oral administration of BAR may constitute an advantage for convenient administration, in the hospital and community settings, among COVID-19-infected patients. No serious adverse events leading to treatment discontinuation were identified throughout our study. The most commonly reported adverse events included secondary infection caused by bacteria or influenza virus, as well as venous thromboembolism, which were deemed unrelated to BAR treatment by the site investigator. It is worth noting that COVID-19-infected patients with severe or critical illness may often exhibit compromised immunity, which can predispose them to secondary infections [ 27 ] or venous circulation dysregulation [ 28 ]. Our findings suggest that BAR may be safe for treating severe or critical COVID-19 infection. However, the concurrent use of BAR and corticosteroids may potentially increase the risk of adverse drug interactions, underscoring the need for monitoring adverse events closely. Our study has several limitations. Firstly, the majority of patients were infected with the prevailing Omicron variant, raising uncertainty about whether BAR provides similar therapeutic benefits to COVID-19-infected patients associated with other emerging variants. Secondly, we did not collect blood or sputum samples for further immune response profiling, including cytokine production, after initiating BAR treatment. Therefore, we cannot elucidate the molecular mechanisms underlying the therapeutic benefits conferred by the anti-inflammatory effects. In conclusion, BAR, when administered alongside corticosteroids, proved efficacious and safe for treating hospitalized COVID-19-infected patients with severe or critical illness. However, further validation is needed to determine the optimal time window for treatment initiation, which may be within 4 days after hospital admission. Conclusion Our study shows that the use of BAR in combination with corticosteroids has been proven to be effective and safe in treating hospitalized COVID-19-infected patients with severe or critical illness. Our findings highlight the medication window of BAR in the clinical practice of treating hospitalized COVID-19-infected patients with severe or critical illness in China. Declarations Patient and public involvement Patients or the public were not involved in the design, or conduct, or reporting or dissemination plans of this study. Funding This work received Sino-German Center for Research Promotion's (SGC) rapid Response Funding for Bilateral Collaborative Proposals Between China and Germany in COVID-19 Related Research (Project No. C-0065), financial grants from the Natural Science Foundation of Shanxi Province (No. 201901D111414), Key Scientific Research Project of COVID-19 Infection Emergency Treatment of Shanxi Bethune Hospital (2023xg01), 2023 COVID-19 Research Project of Shanxi Provincial Health Commission (No.2023XG001; No.2023XG005), Four “Batches” Innovation Project of Invigorating Medical through Science and Technology of Shanxi Province (2023XM003), Research Project Supported by Shanxi Scholarship Council of China (No. 2020 − 178), and Fund Program for the Scientific Activities of Selected Returned Overseas Professionals in Shanxi Province (No. 20200029). Author Contribution Authors ContributorsMengyu Chen: Investigation, Resources, Writing-Original DraftJunyan Zhang: Investigation, Resources, Writing-Original Draft, Formal analysis, Data curation, MethodologyZhifeng Xue: Investigation, Resources, Writing-Original Draft, Data curationJian Li: Formal analysis, Data curation, MethodologyZhigang Pang: Investigation, ResourcesRuiying Wang: Formal analysis, Data curation, MethodologyLei Wang: Formal analysis, Data curation, MethodologyPing Li: Investigation, Resources, MethodologyChristian Kurts: Writing-review & EditingJia Wei: Supervision, Conceptualization, Project administration, Funding acquisitionQi Mei: Investigation, Resources, Writing-Original Draft, Formal analysisShuang Wei: Supervision, Conceptualization, Writing-Original Draft, Writing-review & Editing, Project administration, Funding acquisitionXiansheng Liu: Supervision, Conceptualization, Project administration, Funding acquisitionAll authors reviewed the manuscript. Acknowledgement All the authors would like to thank Bothwin Clinical Study Consultant for their dedication to supporting figure-making and data analysis. Availability of data and materials The dataset supporting the conclusions of this article is included within the article and its additional appendix. Competing interests All authors declare no conflict of interest related to the present study. References Ciotti M, Ciccozzi M, Pieri M, Bernardini S. The covid-19 pandemic: Viral variants and vaccine efficacy. Crit Rev Clin Lab Sci. 2022;59:66–75. http://dor.org/10.1080/10408363.2021.1979462 . Rathinasamy M, Kandhasamy S. An exploratory study on the propagation of sars-cov-2 variants: Omicron is the most predominant variant. J Med Virol. 2022;94:2414–21. http://dor.org/10.1002/jmv.27634 . Fan Y, Li X, Zhang L, Wan S, Zhang L, Zhou F. Sars-cov-2 omicron variant: Recent progress and future perspectives. Signal Transduct Target Ther. 2022;7141. http://dor.org/10.1038/s41392-022-00997-x . 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Murakami N, Hayden R, Hills T, Al-Samkari H, Casey J, Del Sorbo L, Lawler PR, Sise ME, Leaf DE. Therapeutic advances in covid-19. Nat Rev Nephrol. 2023;19:38–52. http://dor.org/10.1038/s41581-022-00642-4 . Tocilizumab in patients admitted to hospital with covid-19. (A randomised, controlled, open-label, platform trial. Lancet. 2021;397:1637–45. http://dor.org/10.1016/s0140-6736(21)00676-0 . Taylor PC, Takeuchi T, Burmester GR, Durez P, Smolen JS, Deberdt W, Issa M, Terres JR, Bello N, Winthrop KL. Safety of baricitinib for the treatment of rheumatoid arthritis over a median of 4.6 and up to 9.3 years of treatment: Final results from long-term extension study and integrated database. Ann Rheum Dis. 2022;81335–43. http://dor.org/10.1136/annrheumdis-2021-221276 . Bieber T, Reich K, Paul C, Tsunemi Y, Augustin M, Lacour JP, Ghislain PD, Dutronc Y, Liao R, Yang FE, Brinker D, DeLozier AM, Meskimen E, Janes JM, Eyerich K. Efficacy and safety of baricitinib in combination with topical corticosteroids in patients with moderate-to-severe atopic dermatitis with inadequate response, intolerance or contraindication to ciclosporin: Results from a randomized, placebo-controlled, phase iii clinical trial (breeze-ad4). Br J Dermatol. 2022;187338–52. http://dor.org/10.1111/bjd.21630 . King B, Ohyama M, Kwon O, Zlotogorski A, Ko J, Mesinkovska NA, Hordinsky M, Dutronc Y, Wu WS, McCollam J, Chiasserini C, Yu G, Stanley S, Holzwarth K, DeLozier AM, Sinclair R. Two phase 3 trials of baricitinib for alopecia areata. N Engl J Med. 2022;386:1687–99. http://dor.org/10.1056/NEJMoa2110343 . Trøseid M, Arribas JR, Assoumou L, Holten AR, Poissy J, Terzić V, Mazzaferri F, Baño JR, Eustace J, Hites M, Joannidis M, Paiva JA, Reuter J, Püntmann I, Patrick-Brown T, Westerheim E, Nezvalova-Henriksen K, Beniguel L, Dahl TB, Bouscambert M, Halanova M, Péterfi Z, Tsiodras S, Rezek M, Briel M, Ünal S, Schlegel M, Ader F, Lacombe K, Amdal CD, Rodrigues S, Tonby K, Gaudet A, Heggelund L, Mootien J, Johannessen A, Møller JH, Pollan BD, Tveita AA, Kildal AB, Richard JC, Dalgard O, Simensen VC, Baldé A, de Gastines L, Del Álamo M, Aydin B, Lund-Johansen F, Trabaud MA, Diallo A, Halvorsen B, Røttingen JA, Tacconelli E, Yazdanpanah Y, Olsen IC, Costagliola D. Efficacy and safety of baricitinib in hospitalized adults with severe or critical covid-19 (bari-solidact): A randomised, double-blind, placebo-controlled phase 3 trial. Crit Care. 2023;27. 9.http://dor.org/10.1186/s13054-022-04205-8 . Lakatos B, Szabó BG, Bobek I, Kiss-Dala N, Gáspár Z, Riczu A, Petrik B, Farkas BF, Sebestyén G, Gopcsa L, Bekő G, Sinkó J, Reményi P, Szlávik J, Mathiász D. Vályi-Nagy, Baricitinib vs tocilizumab treatment for hospitalized adult patients with severe covid-19 and associated cytokine storm: A prospective, investigational, real-world study. Int J Infect Dis. 2022;125233–40. http://dor.org/10.1016/j.ijid.2022.10.037 . Karolyi M, Gruebl A, Omid S, Saak M, Pawelka E, Hoepler W, Kelani H, Kuran A, Laferl H, Ott C, Pereyra D, Santol J, Seitz T, Traugott M, Assinger A, Wenisch C, Zoufaly A. Tocilizumab vs. Baricitinib in hospitalized severe covid-19 patients: Results from a real-world cohort, Infection. (51)(2023) 851–58 http://dor.org/10.1007/s15010-022-01915-7 . Baricitinib in patients admitted to hospital with covid-19. (recovery): A randomised, controlled, open-label, platform trial and updated meta-analysis, Lancet. (400)(2022) 359 – 68 .http://dor.org/ 10.1016/s0140-6736(22)01109-6 . Therapeutics and covid-19. Living guideline ( https://apps.Who.Int/iris/handle/10665/359774 ). Coronavirus disease. 2019 (covid-19) treatment guidelines ( https://www.Ncbi.Nlm.Nih.Gov/books/nbk570371/ ). Diagnosis. and treatment protocol for covid-19 patients (tentative 10th version), Health Care Science. (2)(2023) 10–24. http://dor.org/10.1002/hcs2.36 . Sun J, Wang S, Ma X, Wei Q, Peng Y, Bai Y, Miao G, Meng C, Liu P. Efficacy and safety of baricitinib for the treatment of hospitalized adults with covid-19: A systematic review and meta-analysis. Eur J Med Res. 2023;28:536. http://dor.org/10.1186/s40001-023-01403-0 . Marconi VC, Ramanan AV, de Bono S, Kartman CE, Krishnan V, Liao R, Piruzeli MLB, Goldman JD, Alatorre-Alexander J, de Cassia Pellegrini R, Estrada V, Som M, Cardoso A, Chakladar S, Crowe B, Reis P, Zhang X, Adams DH, Ely EW. Efficacy and safety of baricitinib for the treatment of hospitalised adults with covid-19 (cov-barrier): A randomised, double-blind, parallel-group, placebo-controlled phase 3 trial. Lancet Respir Med. 2021;91407–18. http://dor.org/10.1016/s2213-2600(21)00331-3 . Ely EW, Ramanan AV, Kartman CE, de Bono S, Liao R, Piruzeli MLB, Goldman JD, Saraiva JFK, Chakladar S, Marconi VC. Efficacy and safety of baricitinib plus standard of care for the treatment of critically ill hospitalised adults with covid-19 on invasive mechanical ventilation or extracorporeal membrane oxygenation: An exploratory, randomised, placebo-controlled trial. Lancet Respir Med. 2022;10327–36. http://dor.org/10.1016/s2213-2600(22)00006-6 . Gupta A, Gonzalez-Rojas Y, Juarez E, Crespo Casal M, Moya J, Falci DR, Sarkis E, Solis J, Zheng H, Scott N, Cathcart AL, Hebner CM, Sager J, Mogalian E, Tipple C, Peppercorn A, Alexander E, Pang PS, Free A, Brinson C, Aldinger M, Shapiro AE. Early treatment for covid-19 with sars-cov-2 neutralizing antibody sotrovimab. N Engl J Med. 2021;3851941–50. http://dor.org/10.1056/NEJMoa2107934 . Dougan M, Nirula A, Azizad M, Mocherla B, Gottlieb RL, Chen P, Hebert C, Perry R, Boscia J, Heller B, Morris J, Crystal C, Igbinadolor A, Huhn G, Cardona J, Shawa I, Kumar P, Adams AC, Van Naarden J, Custer KL, Durante M, Oakley G, Schade AE, Holzer TR, Ebert PJ, Higgs RE, Kallewaard NL, Sabo J, Patel DR, Dabora MC, Klekotka P, Shen L, Skovronsky DM. Bamlanivimab plus etesevimab in mild or moderate covid-19. N Engl J Med. 2021;3851382–92. .http://dor.org/10.1056/NEJMoa2102685 . Swets MC, Russell CD, Harrison EM, Docherty AB, Lone N, Girvan M, Hardwick HE, Visser LG, Openshaw PJM, Groeneveld GH, Semple MG, Baillie JK. Sars-cov-2 co-infection with influenza viruses, respiratory syncytial virus, or adenoviruses, Lancet. (399)(2022) 1463–64. http://dor.org/10.1016/s0140-6736(22)00383-x . Perico L, Benigni A, Casiraghi F, Ng LFP, Renia L, Remuzzi G. Immunity, endothelial injury and complement-induced coagulopathy in covid-19. Nat Rev Nephrol. 2021;17:46–64. http://dor.org/10.1038/s41581-020-00357-4 . Additional Declarations No competing interests reported. Supplementary Files BARCOVIDappendix.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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09:48:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4418170/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4418170/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":57447648,"identity":"e3ecec6f-ca07-4fd1-b0bb-400ace2edd06","added_by":"auto","created_at":"2024-05-30 19:44:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":24863,"visible":true,"origin":"","legend":"\u003cp\u003eIdentification of BAR recipients (BAR group) and their matched controls (non-BAR group) among patients hospitalized with COVID-19 during the study period. 2312 controls were matched to both treatment groups.\u003c/p\u003e","description":"","filename":"Fig1.BARCOVIDPatientsdiagram.png","url":"https://assets-eu.researchsquare.com/files/rs-4418170/v1/7e726bd0c1722ac1f7e80f45.png"},{"id":57447647,"identity":"82639dc2-68c0-45aa-8972-73552875481f","added_by":"auto","created_at":"2024-05-30 19:44:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":11855,"visible":true,"origin":"","legend":"\u003cp\u003eProbability of Overall Mortality\u003c/p\u003e","description":"","filename":"Fig2.ProbabitilyofOverallMortality.png","url":"https://assets-eu.researchsquare.com/files/rs-4418170/v1/e1561e1e4ebf9ce1ce57b069.png"},{"id":70604960,"identity":"4d4844b9-3b62-4e8d-9f18-95a0ac008497","added_by":"auto","created_at":"2024-12-04 21:31:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":977660,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4418170/v1/3bcb4d66-7180-4025-878c-df7d066502ae.pdf"},{"id":57447649,"identity":"1e6c2592-fb7a-48f1-884b-cb0d6d1b9c2e","added_by":"auto","created_at":"2024-05-30 19:44:01","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":55372,"visible":true,"origin":"","legend":"","description":"","filename":"BARCOVIDappendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-4418170/v1/07febdafd2e83775310a4d39.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessment of the Efficacy and Safety of Baricitinib Treatment in COVID-19 Patients: a real-world study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe COVID-19 pandemic, triggered by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants, is continuously evolving and is poised to remain a significant public health concern in the foreseeable future[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In comparison to other mutant strains, the SARS-CoV-2 Omicron variant has demonstrated significantly heightened transmissibility and a greater propensity for immune evasion[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Several studies have highlighted the tropism of the Omicron variant towards the upper respiratory tract[\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Since December 2022, there has been a significant increase in the number of COVID-19 cases in mainland China, including those classified as severe or critical. Presently, available treatment options for COVID-19 primarily consist of antiviral therapy[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], Janus kinase inhibitors[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], neutralizing therapy[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and steroids[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Our comprehension of the impact of various categories of potential treatments has markedly advanced due to their diversity. Particularly, effectiveness and safety are fundamental considerations in formulating treatment strategies for patients with severe or critical COVID-19 infection during the surge outbreak.\u003c/p\u003e \u003cp\u003eThe pronounced pulmonary inflammatory responses observed in patients with severe or critical COVID-19 infection indicate the potential efficacy of anti-inflammatory medications in clinical settings. In practice, counteracting hyperinflammatory responses has been linked to clinical benefits. For example, IL-6 receptor antagonists like tocilizumab have shown potential to enhance clinical outcomes in critical cases of COVID-19 infection by reducing cytokine release and the production of acute phase proteins[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Baricitinib (BAR), an oral selective Janus kinase 1/2 inhibitor, is approved for patients with autoimmune diseases owing to its recognized anti-inflammatory properties, such as rheumatoid arthritis[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], atopic dermatitis[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], and alopecia areata[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. BAR has been demonstrated to inhibit the release of multiple cytokines, including IL-6 and interferon-gamma[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], and to disrupt the binding of SARS-CoV-2 to the angiotensin-converting enzyme 2 receptor[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Several observational cohort studies have indicated that BAR reduces mortality and the risk of progression to invasive mechanical ventilation in hospitalized patients with COVID-19 infection. Moreover, when compared to tocilizumab, BAR has been associated with a lower risk of elevated liver enzyme levels[\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The collective randomized evidence available to date indicates that JAK inhibitors, primarily BAR, decrease mortality in patients hospitalized for COVID-19 by approximately one-fifth[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, in a clinical trial investigating the efficacy and safety of BAR in treating severe or critical COVID-19, the trial was prematurely halted due to insufficient external evidence and being underpowered to conclusively determine any potential survival benefit of BAR in severe/critical COVID-19 cases[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In China, the safety and efficacy of BAR in patients with Omicron infection remain unclear, warranting further investigation through additional trials and real-world studies.\u003c/p\u003e \u003cp\u003ePreviously, the combination of BAR with corticosteroids was endorsed by the World Health Organization guidelines for patients with severe or critical COVID-19 infection[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], particularly for hospitalized patients requiring supplemental oxygen, non-invasive or invasive mechanical ventilation, or extracorporeal membrane oxygenation[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. However, there is still a lack of evidence from real-world studies documenting the efficacy and safety of BAR for COVID-19-infected patients in China. Therefore, we conducted a retrospective, single-center cohort study to assess the real-world efficacy and safety of BAR for adult patients with severe or critical COVID-19 infection.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eEthics approval\u003c/h2\u003e \u003cp\u003e This study was performed according to the Helsinki declaration of 1975 and was approved by the ethics committee in the Shanxi Bethune Hospital of Shanxi Academy of Medical Sciences (YXL-2023-254), with a waiver granted for patient consents.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eThis was a real-world retrospective cohort study evaluating the efficacy and safety of BAR among adult hospitalized patients with severe/critical COVID-19 infection in Shanxi Bethune Hospital, China. Between October 5th, 2022 and February 1st, 2023, hospitalized patients should have a confirmed diagnosis of COVID-19 infection according to a positive nucleic acid assay of SARS-CoV-2, in accordance with the \u0026ldquo;Diagnosis and Treatment Plan for COVID-19 Infection (Trial Version 10)\u0026rdquo;, issued by the National Health Commission[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Eligible patients were also required to meet the following inclusion criteria: Eligible patients were adults (\u0026ge;\u0026thinsp;18 years) with SARS-CoV-2 infection; Exclusion criteria were 1) imminent death, anticipated hospital discharge or transfer within \u0026le;\u0026thinsp;48 hours after diagnosis, or 2) administration of standard of care for \u0026le;\u0026thinsp;48 hours after diagnosis, 3) receipt of any biologics agents such as interleukin-6 or Janus kinase inhibitors before COVID-19 infection diagnosis, 4) The usage of BAR beyond 96 hours of hospitalization; 5) pregnancy or breastfeeding This study was approved by the ethics committee of Shanxi Bethune Hospital (YXL-2023-254).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eTreatments\u003c/h2\u003e \u003cp\u003eAccording to the Diagnosis and Treatment Plan for COVID-19 Infection (Trial Version 10)[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], the hospitalized patients with COVID-19 infection were given routine treatment depending on their individual status, including oxygen therapy, oral administration of azivudine (5mg/day) or Nirmatrelvir-Ritonavir (300mg-100mg/12h) for anti-virus therapy, and glucocorticoid therapy (dexamethasone 5-7.5 mg/day or methylprednisolone injection 40\u0026ndash;80 mg/day) so on until hospital discharge or death. During the routine treatment process, based on the clinical usage standards of BAR, the eligible patients were administered BAR tablets orally within four days after hospital admission (4 mg/day) or within 48 hours of the intensive care unit. In addition, patients with glomerular filtration rates below 60 ml/min received halved-dose BAR (2 mg/day) for admission for up to 14 days, and the patient was permanently stopped if the patient was discharged from the hospital. Besides the above treatments, individuals who received BAR were classified as the BAR group, while the others were classified as the non-BAR group.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSafety assessment\u003c/h2\u003e \u003cp\u003eThe safety profile includes treatment adverse events that occur from the treatment initiation to the endpoint. We also recorded any serious adverse events, such as gastrointestinal perforation, cardiovascular malignancy, venous thrombotic events, and secondary infections.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe primary endpoint was all causes of mortality during hospitalization. The duration of survival was calculated from the date of hospital admission until death from any causes or the date of discharge. Continuous variables were reported as mean followed by the standard deviation (SD) or median (interquartile ranges, Q1\u0026thinsp;~\u0026thinsp;Q3), and categorical variables were reported as percentage or proportion (%). Student\u0026rsquo;s t-test and Wilcoxon rank-sum test were used for normally and abnormally distributed quantitative data. Chi-square or Fisher\u0026rsquo;s exact test analyzed categorical variables. Cox proportional hazards models were applied to analyze the relevant risk of all causes of mortality and reported as hazard ratio (HR) followed by a 95% confidence interval (CI).\u003c/p\u003e \u003cp\u003eTo balance patients in these two groups, propensity score matching (PSM) was performed with a caliper set at 0.02. Datasets were generated with the ratios of 1:1, 1:2, and 1:3 for the BAR group vs. the non-BAR group. Additionally, an inverse probability of treatment weighting (IPTW) dataset was generated to balance fundamental variables across these groups.\u003c/p\u003e \u003cp\u003eAll hypothesis tests were two-sided, with statistical significance defined as a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Statistical analyses were performed using Stata SE 13 (Serial number 401306302851), R software version 3.6.1 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://cran.r-project.org/\u003c/span\u003e\u003cspan address=\"http://cran.r-project.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and easy-R (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.empowerstats.com\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.empowerstats.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe sample size was determined assuming a 5% mortality rate in the entire population, coupled with a BAR hazard ratio (HR) of 0.3, employing α\u0026thinsp;=\u0026thinsp;0.05, β\u0026thinsp;=\u0026thinsp;0.2. With a 1:10 ratio, the total sample size was 1320, comprising 120 subjects in the BAR group and 1200 in the non-BAR group.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eA total of 2,731 hospitalized patients with COVID-19 infection were initially screened, and 2,454 patients were ultimately included in this analysis, as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Among these, 142 were classified into the BAR group, while the remaining 2,312 were assigned to the non-BAR group. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e provides an overview of the general characteristics of all participants, including those from the PSM dataset with a 1:1 ratio.\u003c/p\u003e \u003cp\u003e \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\u003eGeneral Characteristics of Before and After PSM\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eUnmatched Data\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003ePSM Data (1:1 ratio)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003enon-BAR\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;2312)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBAR \u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;142)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003enon-BAR\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;123)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBAR \u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;123)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSMD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003emean\u0026thinsp;\u0026plusmn;\u0026thinsp;sd\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.23\u0026thinsp;\u0026plusmn;\u0026thinsp;19.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83.36\u0026thinsp;\u0026plusmn;\u0026thinsp;4.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e82.28\u0026thinsp;\u0026plusmn;\u0026thinsp;7.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e83.26\u0026thinsp;\u0026plusmn;\u0026thinsp;4.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.159\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003emale\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1235 (53.42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88 (61.97%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e73 (59.35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e77 (62.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSmoking [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eno\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1810 (78.29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e105 (73.94%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e92 (74.80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e91 (73.98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.605\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.128\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eyes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e474 (20.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (25.35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31 (25.20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e31 (25.20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eunknown\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (1.21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (0.81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eDisease\u0026rsquo;s severity [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003emoderate\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1154 (49.91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (7.75%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14 (11.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11 (8.94%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.238\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003esever\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1053 (45.54%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e114 (80.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e92 (74.80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e103 (83.74%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ecritical\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105 (4.54%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (11.97%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17 (13.82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9 (7.32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eILD [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (1.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (2.11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.640\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (0.81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3 (2.44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74 (3.20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (3.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (1.63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (4.07%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARDS [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (0.65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eHypertension [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eno\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1534 (66.35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93 (65.49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.860\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e81 (65.85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e80 (65.04%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.893\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eyes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e774 (33.48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49 (34.51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42 (34.15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e43 (34.96%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eunknown\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (0.17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCHD [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eno\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2183 (94.42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e127 (89.44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e115 (93.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e110 (89.43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.146\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eyes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e125 (5.41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (10.56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8 (6.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13 (10.57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eunknown\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (0.17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eStroke [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eno\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1857 (80.32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e111 (78.17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.793\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97 (78.86%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e96 (78.05%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.877\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eyes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e454 (19.64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31 (21.83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26 (21.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e27 (21.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eunknown\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.04%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eDiabetics [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eno\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1693 (73.23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94 (66.20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e80 (65.04%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e86 (69.92%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.104\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eyes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e618 (26.73%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48 (33.80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43 (34.96%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37 (30.08%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eunknown\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.04%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalignant tumors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e309 (13.37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (9.86%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14 (11.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12 (9.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.678\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eHematologic disorders [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eno\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1855 (80.23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e108 (76.06%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.461\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e92 (74.80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e94 (76.42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.767\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eyes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e456 (19.72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34 (23.94%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31 (25.20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e29 (23.58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eunknown\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.04%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eRenal dysfunction [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eno\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2092 (90.48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e129 (90.85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e113 (91.87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e111 (90.24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.485\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eyes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e218 (9.43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (9.15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9 (7.32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12 (9.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eunknown\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.09%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (0.81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eLiver dysfunction [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eno\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2065 (89.32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e125 (88.03%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e110 (89.43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e108 (87.80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.688\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eyes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e245 (10.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (11.97%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13 (10.57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15 (12.20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eunknown\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.09%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eNeutrophil (10\u003csup\u003e9\u003c/sup\u003e/L) [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003e\u0026le;\u0026thinsp;7\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1866 (80.71%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90 (63.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e82 (66.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e82 (66.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.841\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003e\u0026gt;\u0026thinsp;7\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e427 (18.47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51 (35.92%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e39 (31.71%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40 (32.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eunknown\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (0.82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (1.63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (0.81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eLymphocyte (10\u003csup\u003e9\u003c/sup\u003e/L) [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003e\u0026le;\u0026thinsp;0.8\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e976 (42.21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81 (57.04%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e75 (60.98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e70 (56.91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.646\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003e\u0026gt;\u0026thinsp;0.8\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1317 (56.96%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60 (42.25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e46 (37.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e52 (42.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eunknown\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (0.82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (1.63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (0.81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eOxygen saturation [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003e\u0026le;\u0026thinsp;93%\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e601 (25.99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70 (49.30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e68 (55.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e54 (43.90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003e\u0026gt;\u0026thinsp;93%\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1184 (51.21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67 (47.18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e52 (42.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e65 (52.85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eunknown\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e527 (22.79%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (3.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3 (2.44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (3.25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eD-Dimer (ng/ml) [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003e\u0026le;\u0026thinsp;1500\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1874 (81.06%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e101 (71.13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e92 (74.80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e91 (73.98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.928\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003e\u0026gt;\u0026thinsp;1500\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e203 (8.78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 (19.72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19 (15.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21 (17.07%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eunknown\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e235 (10.16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (9.15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12 (9.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11 (8.94%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eGlucocorticoids [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eno\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e732 (31.66%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eyes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1576 (68.17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e142 (100.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e123 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e123 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eunknown\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (0.17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnti-virus [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1165 (50.39%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88 (61.97%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e82 (66.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e74 (60.16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOxygen therapy [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1865 (80.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e133 (93.66%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e119 (96.75%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e114 (92.68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.182\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eBAR: Baricitinib; non-BAR: Non-Baricitinib; ILD: Interstitial Lung Disease; COPD: Chronic Obstructive Pulmonary Disease; ARDS: Acute Respiratory Distress Syndrome; CHD: Coronary Heart Disease; PSM: Propensity Score Matching; SMD: Standard Mean Difference\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFor more detailed information regarding the participants\u0026rsquo; general characteristics, please consult eTable 1 in the appendix. Additionally, eTable 2 in the appendix contains the results of laboratory tests and details of therapeutic regimens for all participants. The general characteristics of the PSM datasets with 1:2 and 1:3 ratios are presented in eTable 3 and eTable 4 in the appendix, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003ePrimary endpoint\u003c/h2\u003e \u003cp\u003eWithin the treatment period, 36 participants from the non-BAR group and 3 from the BAR group deceased (2.11% vs. 1.56%, p\u0026thinsp;=\u0026thinsp;0.782) (eTable 5 in the appendix).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCox regression analysis of data from all participants\u003c/h2\u003e \u003cp\u003eThe results of univariate analysis indicate that being female (HR\u0026thinsp;=\u0026thinsp;0.30, 95% CI 0.14\u0026thinsp;~\u0026thinsp;0.64, p\u0026thinsp;=\u0026thinsp;0.02), having lymphocyte counts above 0.8\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L (HR\u0026thinsp;=\u0026thinsp;0.36, 95% CI 0.18\u0026thinsp;~\u0026thinsp;0.69, p\u0026thinsp;=\u0026thinsp;0.002), and maintaining oxygen saturation above 93% (HR\u0026thinsp;=\u0026thinsp;0.59, 95% CI 0.37\u0026thinsp;~\u0026thinsp;0.93, p\u0026thinsp;=\u0026thinsp;0.024) are associated with a decreased risk of all-cause mortality. Conversely, being above 80 years old (HR\u0026thinsp;=\u0026thinsp;3.50, 95% CI 1.86\u0026thinsp;~\u0026thinsp;6.60, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), having neutrophil counts exceeding 7\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L (HR\u0026thinsp;=\u0026thinsp;3.81, 95% CI 2.32\u0026thinsp;~\u0026thinsp;6.25, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), having a higher disease severity (HR\u0026thinsp;=\u0026thinsp;21.27, 95% CI 11.36\u0026thinsp;~\u0026thinsp;39.84, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), experiencing Acute Respiratory Distress Syndrome (ARDS) (HR\u0026thinsp;=\u0026thinsp;30.81, 95% CI 11.79\u0026thinsp;~\u0026thinsp;80.54, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and having renal dysfunction (HR\u0026thinsp;=\u0026thinsp;2.28, 95% CI 1.07\u0026thinsp;~\u0026thinsp;4.83, p\u0026thinsp;=\u0026thinsp;0.032) are associated with an increased risk of all-cause mortality (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\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\u003eCox Regression Analysis of Mortality for All Participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariate Analysis (n\u0026thinsp;=\u0026thinsp;2,454)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariate Analysis (n\u0026thinsp;=\u0026thinsp;2,454)\u003c/p\u003e \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\u003eHR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.14\u0026ndash;0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.25\u0026ndash;1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.199\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (above 80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.86\u0026ndash;6.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.02\u0026ndash;4.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.42\u0026ndash;1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophil\u0026thinsp;\u0026gt;\u0026thinsp;7\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.32\u0026ndash;6.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.82\u0026ndash;3.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.166\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte\u0026thinsp;\u0026gt;\u0026thinsp;0.8\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18\u0026ndash;0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.27\u0026ndash;0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOxygen saturation\u0026thinsp;\u0026gt;\u0026thinsp;93%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.37\u0026ndash;0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.72\u0026ndash;1.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.529\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-dimer\u0026thinsp;\u003cem\u003e\u0026gt;\u0026thinsp;1500\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.90\u0026ndash;2.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiseases severity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.36\u0026ndash;39.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.78\u0026ndash;31.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eILD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91\u0026ndash;15.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.65\u0026ndash;12.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.163\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.37\u0026ndash;6.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.553\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.79\u0026ndash;80.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u0026ndash;11.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.051\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\u003e1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.77\u0026ndash;2.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91\u0026ndash;5.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.42\u0026ndash;2.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.996\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 \u003cp\u003e1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.75\u0026ndash;3.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.61\u0026ndash;2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalignant tumors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.79\u0026ndash;3.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHematologic disorders\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.38\u0026ndash;1.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.706\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal dysfunction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.07\u0026ndash;4.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.45\u0026ndash;2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.967\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver dysfunction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.45\u0026ndash;2.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.773\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlucocorticoids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.96\u0026ndash;5.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.37\u0026ndash;2.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.962\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnti-virus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.74\u0026ndash;2.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOxygen therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.46\u0026ndash;2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaricitinib\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.26\u0026ndash;2.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.782\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.07\u0026ndash;0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eLD: Interstitial Lung Disease; COPD: Chronic Obstructive Pulmonary Disease; ARDS: Acute Respiratory Distress Syndrome; CHD: Coronary Heart Disease;\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eHR: Hazard ratio; CI: Confidence Interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e also presents the results of the multivariate analysis, which further confirmed that being above 80 years old (HR\u0026thinsp;=\u0026thinsp;2.04, 95% CI 1.02\u0026thinsp;~\u0026thinsp;4.05, p\u0026thinsp;=\u0026thinsp;0.043) and having a higher disease severity (HR\u0026thinsp;=\u0026thinsp;15.71, 95% CI 7.78\u0026thinsp;~\u0026thinsp;31.74, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) are associated with an increased risk of all-cause mortality. On the contrary, having a lymphocyte count above 0.8\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L (HR\u0026thinsp;=\u0026thinsp;0.50, 95% CI 0.27\u0026thinsp;~\u0026thinsp;0.94, p\u0026thinsp;=\u0026thinsp;0.032) and receiving BAR treatment (HR\u0026thinsp;=\u0026thinsp;0.24, 95% CI 0.07\u0026thinsp;~\u0026thinsp;0.83, p\u0026thinsp;=\u0026thinsp;0.024) are related to a reduced risk of all-cause mortality.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eCox regression analysis of data from PSM datasets\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e reveals that the PSM dataset with a 1:1 ratio consists of 123 patients from the BAR group and an additional 123 patients from the non-BAR group. BAR is associated with a reduction in the incidence of all-cause mortality (HR\u0026thinsp;=\u0026thinsp;0.10, 95% CI 0.01\u0026thinsp;~\u0026thinsp;0.86, p\u0026thinsp;=\u0026thinsp;0.035) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\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\u003eCox Regression Analysis of Mortality for PSM Datasets\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95%CI Lower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95%CI Upper\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSM ratio\u0026thinsp;=\u0026thinsp;1:1 (BAR\u0026thinsp;=\u0026thinsp;123, non-BAR\u0026thinsp;=\u0026thinsp;123)\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\u003eBaricitinib\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSM ratio\u0026thinsp;=\u0026thinsp;1:2 (BAR\u0026thinsp;=\u0026thinsp;123, non-BAR\u0026thinsp;=\u0026thinsp;205)\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\u003eAge\u0026thinsp;\u0026gt;\u0026thinsp;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaricitinib\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSM ratio\u0026thinsp;=\u0026thinsp;1:3 (BAR\u0026thinsp;=\u0026thinsp;123, non-BAR\u0026thinsp;=\u0026thinsp;267)\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\u003eAge\u0026thinsp;\u0026gt;\u0026thinsp;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.218\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaricitinib\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eBAR: Baricitinib; non-BAR: Non-Baricitinib; PSM: Propensity Score Matching; HR: Hazard ratio; CI: Confidence Interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFurthermore, the analysis of the PSM dataset with a 1:2 ratio (HR\u0026thinsp;=\u0026thinsp;0.11, 95% CI 0.01\u0026thinsp;~\u0026thinsp;0.88, p\u0026thinsp;=\u0026thinsp;0.038) and a 1:3 ratio (HR\u0026thinsp;=\u0026thinsp;0.08, 95% CI 0.01\u0026thinsp;~\u0026thinsp;0.66, p\u0026thinsp;=\u0026thinsp;0.019) reaffirms the same trend, confirming that BAR reduces the incidence of all-cause mortality (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCox regression analysis of data from IPTW datasets\u003c/h2\u003e \u003cp\u003eThe general characteristics of the IPTW dataset are presented in eTable 6 in the appendix. Since some variables are not well-balanced, multivariate Multiple Cox regression was also conducted. eTable 7 in the appendix demonstrates that patients over 80 years of age (HR\u0026thinsp;=\u0026thinsp;2.98, 95% CI 1.33\u0026thinsp;~\u0026thinsp;6.69, p\u0026thinsp;=\u0026thinsp;0.008) and higher disease severity (HR\u0026thinsp;=\u0026thinsp;13.58, 95% CI 7.03\u0026thinsp;~\u0026thinsp;26.23, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) are associated with an increased incidence of all-cause mortality. The use of BAR reduced the risk of the primary endpoint (HR\u0026thinsp;=\u0026thinsp;0.06, 95% CI 0.01\u0026thinsp;~\u0026thinsp;0.41, p\u0026thinsp;=\u0026thinsp;0.004).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eSafety outcomes\u003c/h2\u003e \u003cp\u003eThe overall incidence of adverse events was comparable among the BAR group (30.28%) and the non-BAR group (25.39%) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The most frequent events which did not differ between the BAR group and the non-BAR group consisted of co or secondary infection (17.61% vs. 13.28%, p\u0026thinsp;=\u0026thinsp;0.143), followed by venous thrombosis events (11.27% vs. 6.14%, p\u0026thinsp;=\u0026thinsp;0.016), cardiovascular events (0.70% vs. 3.89%, p\u0026thinsp;=\u0026thinsp;0.051), and gastrointestinal perforation (0.00% vs. 0.04%, p\u0026thinsp;=\u0026thinsp;0.804). No adverse events resulting in treatment discontinuation were identified.\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\u003eAdverse Events in all participants\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eALL(n\u0026thinsp;=\u0026thinsp;2454)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003enon-BAR(n\u0026thinsp;=\u0026thinsp;2312)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBAR (n\u0026thinsp;=\u0026thinsp;142)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e630 (25.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e587 (25.39%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43 (30.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.347\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastrointestinal Perforation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.04%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (0.04%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.804\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiovascular Event\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e91 (3.71%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90 (3.89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (0.70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ecardiovascular death\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32 (1.30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31 (1.34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (0.70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.516\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003emyocardial infarction\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10 (0.41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10 (0.43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.432\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003estroke\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53 (2.16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53 (2.29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVenous Thrombosis Event\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e158 (6.44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e142 (6.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16 (11.27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003epulmonary Embolism\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17 (0.69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14 (0.61%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3 (2.11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003elower limb thrombosis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e127 (5.18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e112 (4.84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15 (10.56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ethrombosis in other locations\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22 (0.90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22 (0.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.243\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo or Secondary Infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e332 (13.53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e307 (13.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25 (17.61%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.143\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ebacteria\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e151 (6.15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e138 (5.97%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13 (9.15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003efungus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28 (1.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23 (0.99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5 (3.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003etubercle bacillus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (0.12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (0.13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.668\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003einfluenza virus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e126 (5.13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e116 (5.02%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10 (7.04%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.289\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003echlamydia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64 (2.61%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64 (2.77%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis retrospective cohort study has demonstrated the efficacy and safety of oral administration of BAR for a 14-day period among hospitalized patients with COVID-19 infection, most of whom had severe or critical illnesses. Overall, BAR treatment was associated with an 88.5% reduction in the risk of mortality from any cause. Similar findings were observed in PSM analyses at ratios of 1:2 and 1:3. Furthermore, BAR treatment initiated 96 hours or more after hospital admission did not significantly lower the mortality rate compared to treatment initiated earlier. Therefore, patients with severe or critical COVID-19 illness may benefit from BAR treatment initiated within four days of hospital admission.\u003c/p\u003e \u003cp\u003eA meta-analysis was conducted to assess the efficacy and safety of BAR in the treatment of hospitalized adults with COVID-19. The results indicate that BAR has resulted in accelerated recovery and reduced hospitalization duration for COVID-19 patients, particularly excluding those in critical condition[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. A prior study has documented the efficacy of BAR among patients with COVID-19 infection in a double-blind, randomized phase 3 trial. The objective of this study was to assess the efficacy in terms of the risk reduction for progression to severe COVID-19 infection[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The cumulative randomized evidence to date indicates that JAK inhibitors, primarily BAR, reduce mortality in hospitalized patients with COVID-19 by approximately one-fifth[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The exploratory trial was conducted across 18 hospitals in Argentina, Brazil, Mexico, and the USA to assess the efficacy and safety of BAR in combination with standard care for critically ill hospitalized adults with COVID-19 requiring invasive mechanical ventilation or extracorporeal membrane oxygenation. This study found that in critically ill hospitalized patients with COVID-19 receiving invasive mechanical ventilation or extracorporeal membrane oxygenation, treatment with BAR, in combination with standard care including corticosteroids, reduced mortality compared to placebo. This reduction in mortality aligns with the observed mortality reduction in less severely ill patients in the primary COV-BARRIER study population[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. While a more recent randomized, double-blind phase 3 trial examined the efficacy and safety of BAR among hospitalized patients with severe or critical COVID-19 infection, the trial was prematurely terminated, rendering it underpowered to reach a definitive conclusion[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, there is currently no definitive evidence regarding the effectiveness of BAR in complex scenarios such as severe or critical illness in China, where numerous variants of COVID-19 are prevalent and spreading extensively. Consequently, the efficacy of BAR among hospitalized patients with COVID-19 infection has largely remained uncertain. Our study encompassed a substantial number of hospitalized patients with COVID-19 infection, the majority of whom were afflicted with various sub-variants of the Omicron variant. Additionally, most of our study population experienced severe or critical illness. Moreover, our PSM analyses were conducted at ratios of 1:1, 1:2, and 1:3, which helped eliminate other confounding factors associated with severe or critical illness treated with BAR. Our findings are in line with currently reported results and offer significant guidance for the treatment of COVID-19 patients in China. However, it should be noted that the limitation of our study lies in the current absence of multicenter clinical trials in China. Currently, there have been several monoclonal antibodies, such as sotrovimab[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] and bamlanivimab[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] that have been demonstrated to markedly reduce the risk for progression to severe COVID-19 infection. Most of these require intravenous or subcutaneous administration in a medical facility or center. The oral administration of BAR may constitute an advantage for convenient administration, in the hospital and community settings, among COVID-19-infected patients.\u003c/p\u003e \u003cp\u003eNo serious adverse events leading to treatment discontinuation were identified throughout our study. The most commonly reported adverse events included secondary infection caused by bacteria or influenza virus, as well as venous thromboembolism, which were deemed unrelated to BAR treatment by the site investigator. It is worth noting that COVID-19-infected patients with severe or critical illness may often exhibit compromised immunity, which can predispose them to secondary infections [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] or venous circulation dysregulation [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Our findings suggest that BAR may be safe for treating severe or critical COVID-19 infection. However, the concurrent use of BAR and corticosteroids may potentially increase the risk of adverse drug interactions, underscoring the need for monitoring adverse events closely.\u003c/p\u003e \u003cp\u003eOur study has several limitations. Firstly, the majority of patients were infected with the prevailing Omicron variant, raising uncertainty about whether BAR provides similar therapeutic benefits to COVID-19-infected patients associated with other emerging variants. Secondly, we did not collect blood or sputum samples for further immune response profiling, including cytokine production, after initiating BAR treatment. Therefore, we cannot elucidate the molecular mechanisms underlying the therapeutic benefits conferred by the anti-inflammatory effects.\u003c/p\u003e \u003cp\u003eIn conclusion, BAR, when administered alongside corticosteroids, proved efficacious and safe for treating hospitalized COVID-19-infected patients with severe or critical illness. However, further validation is needed to determine the optimal time window for treatment initiation, which may be within 4 days after hospital admission.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study shows that the use of BAR in combination with corticosteroids has been proven to be effective and safe in treating hospitalized COVID-19-infected patients with severe or critical illness. Our findings highlight the medication window of BAR in the clinical practice of treating hospitalized COVID-19-infected patients with severe or critical illness in China.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003ePatient and public involvement\u003c/h2\u003e \u003cp\u003ePatients or the public were not involved in the design, or conduct, or reporting or dissemination plans of this study.\u003c/p\u003e \u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work received Sino-German Center for Research Promotion's (SGC) rapid Response Funding for Bilateral Collaborative Proposals Between China and Germany in COVID-19 Related Research (Project No. C-0065), financial grants from the Natural Science Foundation of Shanxi Province (No. 201901D111414), Key Scientific Research Project of COVID-19 Infection Emergency Treatment of Shanxi Bethune Hospital (2023xg01), 2023 COVID-19 Research Project of Shanxi Provincial Health Commission (No.2023XG001; No.2023XG005), Four \u0026ldquo;Batches\u0026rdquo; Innovation Project of Invigorating Medical through Science and Technology of Shanxi Province (2023XM003), Research Project Supported by Shanxi Scholarship Council of China (No. 2020\u0026thinsp;\u0026minus;\u0026thinsp;178), and Fund Program for the Scientific Activities of Selected Returned Overseas Professionals in Shanxi Province (No. 20200029).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAuthors ContributorsMengyu Chen: Investigation, Resources, Writing-Original DraftJunyan Zhang: Investigation, Resources, Writing-Original Draft, Formal analysis, Data curation, MethodologyZhifeng Xue: Investigation, Resources, Writing-Original Draft, Data curationJian Li: Formal analysis, Data curation, MethodologyZhigang Pang: Investigation, ResourcesRuiying Wang: Formal analysis, Data curation, MethodologyLei Wang: Formal analysis, Data curation, MethodologyPing Li: Investigation, Resources, MethodologyChristian Kurts: Writing-review \u0026amp; EditingJia Wei: Supervision, Conceptualization, Project administration, Funding acquisitionQi Mei: Investigation, Resources, Writing-Original Draft, Formal analysisShuang Wei: Supervision, Conceptualization, Writing-Original Draft, Writing-review \u0026amp; Editing, Project administration, Funding acquisitionXiansheng Liu: Supervision, Conceptualization, Project administration, Funding acquisitionAll authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eAll the authors would like to thank Bothwin Clinical Study Consultant for their dedication to supporting figure-making and data analysis.\u003c/p\u003e\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e \u003cp\u003eThe dataset supporting the conclusions of this article is included within the article and its additional appendix.\u003c/p\u003e\u003ch2\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare no conflict of interest related to the present study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCiotti M, Ciccozzi M, Pieri M, Bernardini S. 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Nat Rev Nephrol. 2021;17:46\u0026ndash;64. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dor.org/10.1038/s41581-020-00357-4\u003c/span\u003e\u003cspan address=\"http://dor.10.1038/s41581-020-00357-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"BAR, COVID-19 infection, SARS-CoV-2, Real-world study, Retrospective cohort, All cause of mortality","lastPublishedDoi":"10.21203/rs.3.rs-4418170/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4418170/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackgroud\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis retrospective cohort study assessed the real-world effectiveness and safety of Baricitinib (BAR) in hospitalized adult patients with severe or critical COVID-19 infection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUtilizing real-world data. Propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) were applied to address imbalances in baseline characteristics. The Cox regression model was employed to assess the hazard ratio of treatment efficacy, utilizing both unmatched and matched datasets. The primary outcome focused on all-cause mortality among hospitalized patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong initially screened 2,731 adults with COVID-19 infection, 2,454 were included in this analysis (2,312 non-BAR, 142 BAR). In total, there were 39 deaths, with 36 occurring in the non-BAR group and 3 in the BAR group. Multivariable Cox regression analysis demonstrated that BAR was associated with a lower risk of all-cause mortality (hazard ratio [HR] = 0.24, 95% confidence interval [CI] 0.07–0.83, p \u0026lt; 0.024). Analysis based on the PSM datasets consistently showed that BAR reduced the risk of all-cause mortality in 1:1 (HR = 0.10, 95% CI 0.01–0.86), 1:2 (HR = 0.11, 95% CI 0.01–0.88, p = 0.038), and 1:3 (HR = 0.08, 95% CI 0.01–0.66) matched databases. Analysis based on the IPTW dataset also indicated that BAR reduced the risk of all-cause mortality (HR = 0.06, 95% CI 0.01–0.41, p = 0.004). The incidence of Venous Thrombosis Events (VTE) was higher in the BAR group compared to the non-BAR group (11.27% vs. 6.14%, p = 0.016).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBAR demonstrated effectiveness in reducing all-cause mortality in hospitalized COVID-19 patients, with an acceptable safety profile.\u003c/p\u003e","manuscriptTitle":"Assessment of the Efficacy and Safety of Baricitinib Treatment in COVID-19 Patients: a real-world study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-30 19:43:56","doi":"10.21203/rs.3.rs-4418170/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"10ebc6aa-8057-447e-8afa-9dfa28226710","owner":[],"postedDate":"May 30th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-20T10:08:17+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-30 19:43:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4418170","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4418170","identity":"rs-4418170","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}