Outcomes of Severe Covid-19 Among Patients Who Did and Did Not Receive Tocilizumab: A Two-year Prospective Cohort Study

Outcomes of Severe Covid-19 Among Patients Who Did and Did Not Receive Tocilizumab: A Two-year Prospective Cohort 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 Outcomes of Severe Covid-19 Among Patients Who Did and Did Not Receive Tocilizumab: A Two-year Prospective Cohort Study Branko Beronja, Tatjana Gazibara, Olja Stevanović, Nataša Nikolić, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5821416/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 Evidence about long-term effects of tocilizumab (TCZ) treatment after COVID-19 is sparse. This study explored COVID-19-related outcomes over a two-year period among people who received TCZ and those who did not. Patients were recruited from two healthcare centers in Serbia, from March 2021 to December 2022. Demographic, clinical, and laboratory data were collected from hospital records. Outcomes of COVID-19 over two years of follow-up, such as post-COVID syndrome (PCS) and mortality, were retrieved from hospital records or through telephone calls. Cumulative two-year mortality in the TCZ cohort (150; 32.8% patients) was 20.6%, and in the non-TCZ cohort (307 patients; 67.2%) 24.7%. In TCZ recipients there was a lower cumulative incidence of PCS (3.4% vs. 9.9%, p = 0.018). Predictors of two-year mortality in both cohorts included age, receiving intensive care unit treatment, having insulin-dependent diabetes, and having elevated C-reactive protein and creatinin kinase on hospital admission. In addition, chest pain on admission, being a smoker, having pre-existing respiratory diseases and cancer along with high aspartate aminotranspherase on admission were predictive of a higher two-year mortality in the non-TCZ cohort. Patients who received TCZ had lower cumulative incidence of PCS and cumulative mortality rates after two years of follow-up. This study suggests that TCZ has potential long-term health benefits for people who were hospitalized for COVID-19. Severe COVID-19 tocilizumab two-year mortality post-COVID syndrome Figures Figure 1 Figure 2 INTRODUCTION The majority of people who catch COVID-19 experience a relatively mild infection. However, approximately 2.1% of individuals with COVID-19 may require hospital treatment [ 1 ]. One underlying pathophysiological mechanism observed in severe COVID-19 is the excessive production of interleukin 6 (IL-6), which may generate the cytokine storm syndrome [ 2 ]. If left untreated, the cytokine storm can cause cardiovascular collapse, multiorgan dysfunction, and ultimately death [ 3 ]. Tocilizumab (TCZ) is a genetically engineered humanized monoclonal antibody and is being used in severe COVID-19 to reduce IL-6 levels [ 4 ]. It inhibits the T lymphocyte activation, antibody production, acute-phase protein synthesis, and hematopoietic cell proliferation [ 4 ]. The TCZ treatment includes a one-day pulse therapy of a recommended dose of 8 mg/kg (not exceeding 800 mg in total) [ 4 ]. Typically, TCZ is being administered along with corticosteroids. The effectiveness of TCZ varies across trials. Studies have found that TCZ shortens hospital stay, possibly reduces in-hospital mortality, as well as lowers the risk of needing mechanical ventilation and having poor COVID-19 outcomes [ 5 – 7 ]. The RECOVERY trial reported a 28-day mortality reduction after TCZ administration, especially when it is combined with corticosteroids [ 8 ]. However, long-term effects of TCZ treatment after hospital have not been studied to date. Thus, prospective cohort studies are essential to investigate the outcomes of TCZ + corticosteroids therapy and compare them with corticosteroids therapy alone. The available body of literature predominantly focused on 7-day and 28-day mortality in TCZ-treated patients, suggesting lower mortality rates compared to other therapeutic approaches [ 9 , 10 ]. Consistent predictors of in-hospital mortality in TCZ-treated individuals include having two or more chronic illnesses, older age, and high levels of laboratory markers at admission such as C-reactive protein (CRP), IL-6 and lactate dehydrogenase (LDH) [ 10 , 11 ]. Still, there is a lack of studies evaluating the independent impact of TCZ on two-year mortality and the onset of post-COVID syndrome (PCS) [ 12 ]. Understanding long-term effect of TCZ treatment on mortality and occurrence of PCS may help to optimize treatment strategies of severe COVID-19. The aim of this study was to compare the outcomes of COVID-19 over two years of follow-up in cohorts of patients who did and did not receive TCZ and to identify factors associated with two-year mortality in both cohorts. METHODS Setting and participants This prospective cohort study was conducted at two healthcare centers: the Clinic for Infectious and Tropical Diseases, University Clinical Center of Serbia (UCC) in Belgrade, and the general hospital "Dr Radivoj Simonovic" in Sombor. The study population was admitted to hospitals between March 1, 2021, and December 7, 2022. The Clinic for Infectious and Tropical Diseases is a referral institution for treatment of infectious diseases and is the largest hospital of its kind in the country. The General Hospital in Sombor, the principal hospital of the West Bačka District (including municipalities of Sombor, Apatin, Odžaci, and Kula in the north-west of Serbia), provides secondary level of healthcare to approximately 187,500 residents. Throughout the studied period, both hospitals operated a semi-intensive care unit (SICU) and an intensive care unit (ICU) for severe COVID-19 cases. The inclusion criteria for both cohorts were: 1) confirmed SARS-CoV-2 infection through RT-PCR or antigen testing, 2) age of 18 years or older, and 3) developing severe clinical symptoms during hospitalization which are in line with the criteria for TCZ application. The current treatment protocol for COVID-19 patients in Serbia, in accordance with the recommendations of the World Health Organization, involves the administration of TCZ when the IL-6 value exceeds 40 pg/ml, or when a threefold increase in inflammatory markers occurs within a one-day interval or a progression toward respiratory failure. The sample size calculation was based on the populations of Belgrade (approximately 1.4 million people) and the West Bačka district (roughly 190,000 people). Considering an estimated 9% of COVID-19 positive individuals, older than 60 years, requiring hospital treatment, a 95% confidence interval, and a 5% probability of alpha error, the minimum sample size per cohort is 126 participants ( https://www.calculator.net/sample-size-calculator.html ). This research adhered to the Helsinki Declaration and received ethical approval from both the Ethics Committee of the UCC (Approval no. 837/8-2024) and the Ethics Committee of the "Dr. Radivoj Simonovic" General Hospital in Sombor (Approvals no. 23-2171/2023-2 and 23-2171/2023-3). Data collection Demographic and clinical information on admission and during follow-up were extracted from electronic medical records. The collected data covered demographic characteristics (gender, age, medical history, and presence of chronic illnesses [such as hypertension, diabetes mellitus types 1 and 2, obesity, respiratory diseases like chronic obstructive pulmonary disease-COPD and asthma, kidney diseases, and malignant tumors]. Additionally, clinical data on initial COVID-19 symptoms were retrieved as well (fever, cough, fatigue, shortness of breath, and chest pain), as well as the COVID-19 vaccination status. Laboratory results on hospital admission were retrieved from electronic medical records: red blood cell count (RBC), hemoglobin (Hgb), white blood cell count (WBC), neutrophil count (Ne), lymphocyte count (Ly), D-dimer, prothrombin time (PT), international normalized ratio (INR), glycemia, creatinine (Cr), urea, albumin (Alb), procalcitonin (Pct), LDH, CRP, ferritin, alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (gGT), and creatine kinase (CK). Exposure The timing of TCZ therapy was recorded for every patient in the TCZ cohort as the number of days from the onset of COVID-19 symptoms to the adminsitration of TCZ. Follow-up During hospital treatment, patients were either discharged from hospital, while time of death was recorded for all non-surviving patients. Time when patients were discharged from hospital was also recorded. Surviving patients were further monitored and were recommended to report any subsequent health issues post-hospitalization. The graphical representation of patient monitoring points over follow-up is shown in Fig. 1. Over the second year after hospital discharge, the research team had at least one telephone call with the surviving patients from both cohorts. Patients were asked about the occurrence of long COVID or post-COVID symptoms as well as any other significant health disruptions (such as stroke, other cardiovascular diseases, or new-onset malignant tumors). According to guidelines, the PCS encompasses the following: a) persistence of any of the symptoms from the acute phase of COVID-19 and their management; b) symptoms linked to a novel illness; c) delayed-onset symptoms emerging after the resolution of the acute phase of COVID-19; and d) influence on pre-existing medical conditions or disabilities [ 13 ]. Furthermore, all patients were asked about the presence of any post-COVID symptoms, including prolonged fatigue, difficulty breathing, cough, anxiety or depression, myalgia, sleep problems, chest pain, issues with concentration and memory, hair loss, and anosmia [ 13 ]. On this occasion, patients were also asked about other health issues that could potentially trigger these symptoms. Subsequently, an analysis of medical records was conducted, focusing exclusively on symptoms unequivocally associated with PCS, i.e., those lacking alternative medical explanations. Data on patient mortality and time of death was retrieved from the electronic medical records in instances when there was no response at attempted telephone call or upon receiving notification of death from family members. Data analysis Patients were analyzed based on the administration of TCZ. Both cohorts were stratified into two groups: survivors and non-survivors based on the two-year survival data. The data analysis utilized descriptive and analytical statistical methods using the IBM SPSS-Statistics version 17.1 software (IBM Corp). A p-value of p < 0.05 was considered as statistically significant. Descriptive characteristics were presented using mean values and standard deviations for continuous variables, while frequencies and percentages were utilized for categorical variables. The normality of the distribution of continuous variables was assessed using the Kolmogorov-Smirnov test. For normally distributed continuous variables, independent samples t-tests were applied, while non-normally distributed variables underwent analysis using the nonparametric two-tailed Mann-Whitney test. Categorical variables were evaluated using Fisher's exact test (when observations per cell were fewer than five) and the Chi-square test. The Kaplan-Meier survival curve was utilized to analyze patient survival, stratified by TCZ usage, followed by an assessment of differences in the survival curve using the log-rank test. The Cox proportional hazard model was applied to identify factors associated with mortality. The independent variables were classified according to groups to avoid overadjustment of models. One group of variables contained those patient characteristics that were usually grouped together in literature. Therefore, the first model included sociodemographic characteristics, initial COVID-19 symptoms and treatment. The second model included pre-existing chronic diseases. The time to death/end of follow-up was also included in the model. Predictive models were analyzed independently for the TCZ and non-TCZ cohorts, revealing common factors associated with the two-year mortality as well as those specific to each cohort. Subsequently, all statistically significant (p < 0.05) and marginally significant (p < 0.25) variables in the univariate analysis were included in the multivariate model. RESULTS Description of the study cohorts A total of 457 patients were included in the study, with the TCZ cohort comprising 150 participants and the non-TCZ cohort consisting of 307 participants. In TCZ cohort, the majority of patients were male (101; 67.3%), of an average age of 64.47 ± 12.35 years (age range 39–91 years). Of 39 TCZ-treated patients requiring ICU treatment, 19 died, resulting in a case-fatality rate of 12.7% in the total sample and a case-fatality rate of 48.7% in all ICU-treated patients (death occurred after a median of 22 days [min-max 10–27 days] following the onset of symptoms). Over the two-year follow-up, an additional 12 patients passed away, yielding a two-year cumulative mortality rate of 20.6% in the TCZ cohort. In non-TCZ cohort, the majority of patients were female (211; 68.2%), of an average age of 63.41 ± 12.35 years (age range 37–92 years). Of 86 patients in the non-TCZ cohort who required ICU treatment, 46 died, resulting in a case-fatality rate of 14.9% in the total sample and a case-fatality rate of 53.4% in all ICU-treated patients (death occurred after a median of 20 days [min-max 9–21 days] following the onset of symptoms). Over the two-year follow-up, additional 20 patients passed away, resulting in a two-year cumulative mortality rate of 24.7% in the non-TCZ cohort. The majority of patients in both cohorts were not vaccinated (332; 72.6%). No difference in age was observed between the TCZ and non-TCZ cohorts (p = 0.664). Demographic and clinical parameters of the study cohorts are presented in Table 1 . Table 1 Demographic clinical and laboratory characteristics of the study cohort Variable Tocilizumab cohort N = 150 n(%) Non-Tocilizumab cohort N = 307 n(%) Non-survivors N = 31 n(20.66%) Survivors N = 119 n(79.33%) p Non-survivors N = 76 n(16,63%) Survivors N = 231 n(50.54%) P Age (mean ± sd) 69.59 ± 13.88 60.00 ± 12.14 0.000 76.31 ± 13.76 60.55 ± 11.94 0.000 Gender Men 21 (14.0%) 80 (53.3%) 0.712 22 (7.2%) 73 (23.9%) 0.775 Women 10 (6.7%) 39 (26.0%) 54 (17.6%) 157 (51.1%) Needing IUC treatment 28 (18.66%) 11 (7.33%) 0.000 55 (17.9%) 31 (10.1%) 0.000 Severity CT score 17.21 ± 4.94 12.15 ± 5.01 0.000 n/a n/a n/a COVID-19 vaccination 35 (23.33%) 3 (2.0%) 0.006 12 (3.9%) 67 (21.8%) 0.022 Smoking 12 (8.0%) 23 (15.33%) 0.132 47 (15.3%) 78 (25.4%) 0.000 Duration of hospital stay 17.11 ± 9.88 12.23 ± 5.84 0.018 17.32 ± 5.311 13.85 ± 6.65 0.001 Timing of TCZ therapy 17.11 ± 9.88 10.21 ± 3.18 0.000 n/a n/a n/a Initial symptoms of COVID-19 Fever 32 (21.33%) 101 (67.33%) 0.630 63 (20.5%) 193 (62.9%) 0.894 Cough 29 (19.33%) 86 (57.33%) 0.770 58 (18.9%) 180 (58.6%) 0.771 Fatigue 21 (14.0%) 68 (45.33%) 0.713 36 (11.7%) 106 (34.5%) 0.822 Shortness of breath 20 (13.33%) 33 (22.0%) 0.026 31 (10.1%) 57 (18.6%) 0.007 Chest pain 14 (9.33%) 22 (14.66%) 0.023 12 (3.9%) 14 (4.6%) 0.008 Comorbidity Hypertension 20 (13.3%) 55 (36.7%) 0.070 28 (9.1%) 73 (23.8%) 0.399 Diabetes mellitus 11 (7.3%) 18 (12.0%) 0.011 28 (9.1%) 46 (15.0%) 0.003 Insulin dependent diabetes 5 (3.3%) 3 (2.0%) 0.003 13 (4.2%) 22 (7.2%) 0.071 Oral antidiabetics 6 (4.0%) 12 (8.0%) 0.157 17 (5.5%) 24 (7.8%) 0.008 Obesity 7 (4.7%) 5 (3.3%) 0.001 7 (2.3%) 14 (4.6%) 0.345 Malignant tumors 9 (6.0%) 6 (4.0%) 0.170 10 (3.3%) 12 (3.9%) 0.020 Respiratory diseases 6 (4.0%) 7 (4.6%) 0.070 9 (6.8%) 12 (3.9%) 0.046 Chronic kidney disease 1 (0.7%) 4 (2.6%) 0.615 6 (2.0%) 3 (1.0%) 0.003 Laboratory characteristics Erythrocytes 4.13 (3.49–4.63) 4.35 (3.85–4.79) 0.501 132.0 (120.0-144.0) 4.05 (3.45–4.61) 0.820 Hemoglobin 126.0 (114.0-138.0) 132.0 (119.7–144.0) 0.727 132.0 (120.0-144.0) 125.0 (112.0-136.0) 0.646 White blood cells 6.85 (4.07–9.03) 6.0 (4.37–8.62) 0.879 6.81 (4.25–9.1) 7.0 (4.0–9.0) 0.702 Lymphocytes 1.29 (0.85–1.88) 1.13 (0.78–1.69) 0.156 1.05 (0.77–1.57) 1.37 (0.97–1.96) 0.152 Neutrophils 4.93 (3.31–6.52) 4.46 (3.12–6.67) 0.998 4.59 (3.28–6.37) 4.98 (3.44–6.68) 0.577 Monocytes 0.35 (0.22–0.55) 0.40 (0.24–0.53) 0.911 0.34 (0.23–0.58) 0.38 (0.21–0.64) 0.872 Platelets 155.0 (124.0-267.0) 172.5 (137.5-220.75) 0.144 145.0 (103.0-291.0) 184.5 (148.0-256.0) 0.096 D-dimer 0.65 (0.47–1.13) 0.63 (0.39–0.95) 0.054 0.75 (0.50–1.12) 0.97 (0.78–1.21) 0.505 Prothrombin time 13.35 (12.40–14.10) 12.9 (12.2–13.4) 0.797 12.6 (12.2–13.2) 12.5 (12.1–12.8) 0.261 International normalized ratio 1.10 (1.03–1.17) 1.08 (1.02–1.12) 0.812 1.11 (1.04–1.25) 1.42 (1.17–1.63) 0.520 Glycemia 7.2 (5.7–9.4) 6.90 (5.70-8.00) 0.192 7.0 (5.4–8.40) 6.90 (4.20–9.30) 0.771 Creatinine 88.5 (72.5-107.75) 85.0 (75.0-102.75) 0.116 90.0 (77.0-116.0) 91.1 (81.3-102.3) 0.120 Urea 6.20 (4.80–8.30) 5.50 (4.45–7.77) 0.032 3.6 (2.84–3.78) 3.20 (2.0-3.40) 0.960 Albumin 32.0 (30.5–36.0) 33.0 (30.0–36.0) 0.600 32.0 (30.0–36.0) 33.0 (31.0–36.0) 0.419 Procalcitonin 0.14 (0.08–0.67) 0.15 (0.10–0.22) 0.585 0.89 (0.14–1.23) 0.67 (0.54–0.98) 0.068 Lactate dehydrogenase 241.5 (203.0-312.75) 78.75 (36.27–178.5) 0.171 246.0 (206.0-312.0) 136.3 (56.3-198.3) 0.622 C-reactive protein 78.75 (36.27–178.50) 59.60 (25.45–98.10) 0.044 82.64 (39.31-187.36) 53.50 (24.60–82.90) 0.035 Ferritin 542.45 (393.1-1209.2) 542.2 (301.2-1060.3) 0.602 533.75 (332.0-860.5) 623.0 (387.0-797.0) 0.045 Alanine aminotransferase 50.0 (29.0–77.0) 40.50 (28.0-60.75) 0.892 49.0 (31.0-69.7) 60.0 (43.0–76.0) 0.869 Aspartate aminotransferase 32.0 (23.0-47.7) 42.0 (25.0–79.0) 0.196 49.0 (25.0–74.0) 52.0 (30.0–79.0) 0.562 Gamma glutamyl-transferase 32.5 (23.0-47.7) 36.0 (28.0-61.50) 0.207 43.5 (29.0-69.7) 57.0 (37.0–74.0) 0.608 Creatine kinase 202.0 (92.7-426.7) 128.5 (67.5-2551.50) 0.046 215.0 (92.5–315.0) 147.0 (121.0-189.0) 0.014 Interleukin 6 74.50 (39.9–87.9) 48.95 (34.3–57.6) 0.006 n/a n/a n/a Erythrocytes 4.13 (3.49–4.63) 4.35 (3.85–4.79) 0.501 132.0 (120.0-144.0) 4.05 (3.45–4.61) 0.820 Legend: CT-computerized tomography; Bolded values are statistically significant Comparison between survivors and non-survivors Non-survivors in both cohorts were older, needed the ICU treatment more frequently, had a lower vaccination coverage, longer hospital stay, and more frequent shortness of breath and chest pain upon admission. Additionally, diabetes was more common in the non-survivor group. In TCZ cohort, non-survivors more often experienced delayed administration of TCZ, had insulin-dependent diabetes mellitus, and were obese compared to survivors. In non-TCZ cohort, non-survivors were more often smokers and had a higher prevalence of pulmonary, renal, and cancers, as well as diabetes mellitus type 2 compared to survivors. Compared to survivors in both cohorts, non-survivors had higher levels of CRP and CK on hospital admission. In the TCZ cohort, non-survivors had elevated levels of IL-6 and urea upon admission compared to survivors, while non-survivors in the non-TCZ cohort had higher levels of ferritin upon admission compared to survivors. Other differences in laboratory characteristics between survivors and non-survivors in both cohorts are presented in Table 1 . Health-related events over a two-year follow-up period Prolonged fatigue over two-year follow-up period was more often reported among people in the non-TCZ cohort compared to the TCZ cohort (p = 0.040). Furthermore, patients in non-TCZ cohort were more prone to developing PCS over follow-up (p = 0.018) (Table 2 ). Cumulative incidence of PCS over two-year follow-up in the TCZ cohort was 3.4%, and in the non-TCZ cohort 9.9%. Table 2 Health-related events during the two-year follow-up periodand or causes of death of patients from non-survivors cohort Variable Survivors N = 350 n(%) TCZ cohort N = 119 n(34.0%) Non-TCZ cohort N = 231 n(66.0%) p COVID-19 reinfection 14 (4.0%) 31 (8.9%) 0.610 Rehospitalization COVID-19 2 (0.6%) 5 (1.4%) 0.759 Hospitalization - other reasons 12 (2.6%) 27 (5.9%) 0.775 Diagnosed post-COVID syndrome 4 (0.9%) 23 (5.0%) 0.040 Cardiovascular diseases 2 (0.6%) 7 (2.0%) 0.449 Coronary heart disease 1 (0.3%) 4 (1.1%) 0.506 Stroke 1 (0.3%) 7 (2%) 0.194 Subjective experience of post-COVID syndrome symptoms Prolonged fatigue 46 (13.1%) 120 (34.3%) 0.018 Difficulty breathing 16 (4.6%) 47 (13.4%) 0.111 Cough 17 (4.9%) 41 (11.7%) 0.409 Anxiety or depression 15 (4.3%) 39 (11.1%) 0.294 Myalgia 6 (1.7%) 11 (3.1%) 0.908 Sleep problems 3 (0.9%) 8 (2.3%) 0.632 Chest pain 5 (1.4%) 18 (5.1%) 0.199 Issues with concentration and memory 3 (0.9%) 10 (2.9%) 0.397 Hair loss 8 (2.3%) 16 (4.6%) 0.943 Anosmia 3 (0.9%) 5 (1.4%) 0.834 Variable - cause of death Non-Survivors N = 107 n(%) TCZ cohort N = 31 (28.97%) Non-TCZ cohort N = 76 (71.02) P COVID-19 19 (17.6%) 47 (43.9%) 0.957 Cardiovascular disease 6 (5.6%) 13 (12.1%) 0.782 Stroke 3 (2.8%) 12 (11.2%) 0.409 Malignant tumors 2 (1.9%) 4 (3.7%) 0.809 Other 1 (0.9%) 1 (0.9%) 0.437 In TCZ cohort, 14 patients had COVID-19 reinfection over the two-year follow-up (reinfection rate of 11.8%). Out of 14 reinfected patients, 2 (14.2%) required rehospitalization due to COVID-19 reinfection during the two-year follow-up. In non-TCZ cohort, 31 patients (8.9%) were reinfected with COVID-19, resulting in a reinfection rate of 14.4%. Of 31 reinfected patients, 5 (16.1%) required rehospitalization for COVID-19 infection over a two-year follow-up. Cumulative two-year mortality according to cohorts The cumulative two-year mortality in the TCZ cohort was 20.6%, with 19 patients (61.2%) dying during the initial hospitalization. During follow-up, 6 patients (19.3%) died of cerebrovascular diseases, 3 patients (9.7%) died of stroke, 2 patients (6.5%) died of cancer, and 1 patient (3.2%) died because of complications related to the COPD (Table 2 ). The cumulative two-year mortality in the non-TCZ cohort was 24.7%, with 47 patients (61.2%) dying during the initial hospitalization for COVID-19. During the two-year follow-up, 13 patients (19.3%) died of cerebrovascular diseases, 12 patients (9.7%) died of stroke, 4 patients (6.5%) died of cancer, and 1 patient (3.2%) died in a traffic accident (Table 2 ). The Kaplan-Meier survival curve suggested a statistically significant difference in two-year mortality between the TCZ and the non-TCZ cohorts (Log-rank test p < 0.001). This indicates that patients who did not receive TCZ had poorer survival compared to those who received TCZ over two years of follow-up (Fig. 1). Predictors of cumulative two-year mortality The first model identified several factors associated with two-year mortality risk in the TCZ cohort, which included older age (p = 0.004), the requirement for ICU treatment during COVID-19 (p = 0.047), and delayed administration of TCZ (p = 0.002). In the non-TCZ cohort, the multivariate model revealed that age (p < 0.001), needing ICU treatment (p < 0.001), and presence of chest pain on admission (p = 0.012) were predictive of cumulative two-year mortality in this cohort (Table 3 ). Table 3 Results of the multivariate Cox proportional hazard models: factors associated with mortality in cohorts Model 1. Tocilizumab cohort Non-Tocilizumab cohort Univariate Multivariate Univariate Multivariate HR 95% CI p HR 95% CI p HR 95% CI p HR 95% CI P Age 1.047 1.01–1.08 0.005 1.064 1.02–1.10 0.004 1.083 1.06–1.10 0.001 1.066 1.04–1.09 0.001 Gender 1.136 0.59–1.84 0.633 1.894 0.54–3.46 0.657 COVID-19 vaccination 0.648 0.26–1.58 0.340 0.558 0.31–0.81 0.045 1.737 0.97–2.35 0.322 Smoking 1.537 0.54–4.39 0.422 2.839 1.78–4.51 0.001 1.075 0.63–1.83 0.089 Severity CT score 1.262 1.15–1.38 0.001 1.209 1.08–1.35 0.001 n/a n/a n/a n/a n/a n/a Needing IUC treatment 9.388 4.39-20.0 0.001 3.321 1.01–10.8 0.047 11.214 6.75–18.6 0.001 8.091 4.49–14.5 0.001 Duration of hospital stay 1.051 1.00-1.09 0.027 1.032 0.99–1.03 0.065 1.032 0.99–1.06 0.098 1.012 1.01–1.05 0.524 Timing of TCZ therapy 1.324 1.18–1.48 0.001 1.320 1.16–1.54 0.001 n/a n/a n/a n/a n/a n/a Fever 0.604 0.23–1.57 0.302 0.940 0.51–1.70 0.838 Cough 1.012 0.91–1.24 0.956 1.087 0.64–1.18 0.758 Fatigue 1.024 0.01–2.08 0.901 1.036 0.92–1.06 0.691 Shortness of breath 1.248 1.08–2.14 0.022 1.530 0.22–3.27 0.155 1.850 0.90–2.51 0.850 Chest pain 1.280 1.14–1.56 0.001 1.834 0.65–5.14 0.248 1.401 1.22–1.74 0.004 1.716 1.37–2.37 0.012 Model 2. Univariate Multivariate Univariate Multivariate HR 95% CI p HR 95% CI p HR 95% CI p HR 95% CI p Age 1.047 1.01–1.08 0.005 1.042 1.01–1.07 0.016 1.083 1.06–1.10 0.001 1.083 1.06–1.10 0.001 Gender 1.136 0.59–1.84 0.633 1.894 1.54–2.46 0.657 COVID-19 vaccination 0.648 0.26–1.58 0.340 0.558 0.31–0.81 0.045 1.769 1.42–2.43 0.401 Smoking 1.537 0.54–4.39 0.422 2.839 1.78–4.51 0.001 2.765 1.69–4.50 0.001 Hypertension 1.016 0.50–2.05 0.965 1.811 1.50–1.29 0.377 Insulin dependent diabetes 1.257 1.10–1.62 0.003 1.398 1.14–2.12 0.042 1.562 1.30–2.02 0.001 1.856 1.42–2.72 0.039 Oral antidiabetics 1.461 0.48–3.13 0.089 1.487 0.81–1.74 0.532 1.488 1.28–1.83 0.009 1.792 0.44–2.42 0.432 Obesity 3.154 1.36–7.33 0.008 1.830 0.68–4.89 0.228 1.478 0.68–3.21 0.005 1.295 0.57–2.93 0.563 Malignant tumors 5.451 0.18–9.36 0.710 1.223 1.09–1.51 0.001 1.444 1.17–2.10 0.041 Respiratory diseases 1.535 0.97–3.78 0.426 1.086 1.04–1.20 0.001 1.100 1.04–1.23 0.001 Chronic kidney disease 2.735 0.95–7.81 0.060 2.681 0.72–5.65 0.129 1.374 0.70–2.67 0.015 1.251 0.91–1.45 0.251 Model 3. Univariate Multivariate Univariate Multivariate HR 95% CI p HR 95%CI p HR 95%CI p HR 95%CI p Age 1.047 1.01–1.08 0.005 1.057 1.01–1.10 0.010 1.083 1.06–1.10 0.001 1.070 1.05–1.09 0.001 Gender 1.136 0.59–1.84 0.633 1.894 0.74–2.46 0.657 COVID-19 vaccination 0.648 0.26–1.58 0.340 0.558 0.31–0.81 0.045 0.834 0.45–1.12 0.260 Smoking 1.537 0.54–4.39 0.422 2.839 1.78–4.51 0.001 2.399 1.48–3.89 0.001 Erythrocytes 0.932 0.61–1.21 0.544 0.926 0.65–1.31 0.665 Hemoglobin 0.994 0.97–1.01 0.593 0.988 0.95–1.01 0.661 White blood cells 1.968 0.94–2.78 0.548 1.013 0.94–1.09 0.724 Lymphocytes 1.211 0.93–1.57 0.156 0.883 0.61–1.01 0.185 Neutrophils 1.984 0.88–2.09 0.784 1.014 0.92–1.10 0.852 Monocytes 1.231 0.72–1.34 0.883 1.032 0.82–1.04 0.455 Platelets 0.971 0.94–0.99 0.844 0.999 0.99–1.01 0.718 D-dimer 1.038 0.76–1.41 0.813 1.541 0.41–2.62 0.387 Prothrombin time 1.010 0.90–1.26 0.850 0.908 0.78–1.05 0.201 international normalized ratio 0.904 0.21–3.84 0.892 0.748 0.33–1.66 0.477 Glycemia 1.019 0.92–1.12 0.717 1.988 0.91–3.89 0.751 Creatinine 1.006 0.99–1.01 0.200 1.995 1.98-2.00 0.012 2.001 0.89–3.10 0.078 Urea 1.929 0.79–2.11 0.929 1.994 0.85–3.16 0.954 Procalcitonin 1.056 0.98–1.07 0.120 1.068 0.99–1.08 0.103 1.058 1.04–1.07 0.039 1.076 0.94–1.19 0.120 Lactate dehydrogenase 1.001 0.99–1.06 0.276 1.036 0.91–1.05 0.198 C-reactive protein 1.007 1.00-1.01 0.004 1.007 1.00-1.01 0.007 1.007 1.00-1.01 0.001 1.002 0.99–1.01 0.015 Ferritin 2.000 0.99–3.01 0.574 1.999 1.99-2.00 0.040 1.999 0.98–3.01 0.119 Alanine aminotransferase 1.001 0.99–1.01 0.679 1.001 0.99–1.01 0.745 Aspartate aminotransferase 1.003 0.90–1.02 0.135 1.023 1.02–1.03 0.001 1.017 1.01–1.02 0.012 Gamma glutamyl-transferase 1.563 0.41–2.68 0.563 1.003 0.99–1.01 0.594 Creatine kinase 1.001 1.00-1.01 0.002 1.001 1.00-1.01 0.043 1.002 1.00-1.01 0.019 1.014 1.01–1.02 0.039 Interleukin 6 1.002 1.00-1.01 0.004 1.002 0.99–1.01 0.150 n/a n/a n/a n/a n/a n/a Legend: HR-hazard ratio; CI-confidence interval; Bolded values are statistically significant. In the second model for the TCZ cohort, older age (p = 0.016) and insulin-dependent diabetes (p = 0.042) were identified as predictors of two-year cumulative mortality. In the non-TCZ cohort, the multivariate model identified older age (p < 0.001), smoking (p < 0.001), insulin-dependent diabetes (p = 0.039), cancers (p = 0.041), and respiratory diseases (p < 0.001) as predictors of two-year cumulative mortality (Table 3 ). The third model for the TCZ cohort revealed that older age (p = 0.010) and higher admission values for CK (p = 0.043), IL-6 (p = 0.004), and CRP (p = 0.007) were associated with two-year mortality risk. In the non-TCZ cohort, the multivariate model identified older age (p < 0.001), smoking (p = 0.001), levated CRP (p = 0.015), AST (p = 0.012), and CK levels (p = 0.039) as predictors of two-year cumulative mortality in this cohort (Table 3 ). DISCUSSION This study found a difference in cumulative two-year mortality among patients who received and did not receive TCZ. Specifically, the TCZ cohort had cumulative two-year mortality rate of 20.6% and the non-TCZ cohort had 24.7%. The cumulative incidence rate for diagnosed PCS after two years of follow-up was 3.4% in the TCZ cohort and 9.9% in the non-TCZ cohort. Factors associated with two-year mortality in both cohorts were older age, receiving the ICU treatment, having insulin-dependent diabetes, and having elevated CRP and CK on hospital admission. In addition, factors associated with two-year mortality in the non-TCZ cohort were chest pain on admission, not being vaccinated against COVID-19, history of smoking, having respiratory diseases, and cancer along with high AST values on admission. A low cumulative mortality after two years of follow-up observed in this study supports the assumption that TCZ may have long-term beneficial effects on survival after having developed a severe form of COVID-19. Capra et al. made a comparison between patients who received the standard of care (26 patients) and those who received TCZ in addition to the standard of care (62 patients) for moderately severe COVID-19 pneumonia [ 14 ]. Patients receiving TCZ exhibited a significantly longer survival rate compared to the control groups when age, chronic illnesses and CRP were taken into consideration [ 15 ]. Although our results are similar, the former study [ 15 ] had a considerably smaller sample size, potential selection bias and a high prevalence of unknown outcomes. Considering the off-label application of TCZ, alongside a high volume of critically ill patients and its single-day administration regimen (in contrast to the extended protocols observed in non-COVID contexts), the attending physician team recommended the administration of TCZ to patients with malignancies. This decision aligned with the evidence from medical literature and experiences of other medical centers worldwide. Pre-existing malignant diseases independently predicted two-year mortality in the non-TCZ cohort, with no significant difference in cancer prevalence between cohorts. TCZ-treated patients experienced reduced biological effects of IL-6 during the inflammatory phase of CIVID-19 infection. It has been well-established that IL-6 has a remarkable systemic impact, ultimately resulting in metabolic failure, severe psychological and mental complications, and independelty contributes to mortality of cancer patients [ 16 , 17 ]. Literature findings suggest that treatment with TCZ has a potential to attenuate migratory effects of malignant cells [ 17 ]. Based on the current knowledge, it is not possible to clearly define the interaction of high concentrations of IL-6 in patients with severe COVID-19 and its impact on subsequent course of cancer. Factors linked to two-year mortality in the non-TCZ cohort primarily involved pre-existing respiratory illnesses. This may be explained by the absence of protective effect of TCZ against lung damage during acute COVID-19 infection. Early and low-dose TCZ treatment have shown to reduce mortality in COVID-19-related respiratory failure, as demonstrated by Rossi et al [ 18 ]. Experiences from Spain suggest that patients with COVID-19-related lung fibrosis exhibit higher IL-6 levels during the inflammatory phase, which may increase vulnerability in those individuals with pre-existing lung diseases [ 19 ]. Contrary, potential protective effect of TCZ in slowing lung damage progression is evident in the TCZ cohort. Recent studies focus on the release of IL-6 and granulocyte-macrophage colony-stimulating factor from the activated pathogenic T cells weeks after SARS-CoV-2 infection as a marker of further infection progression [ 20 ]. This highlights the importance of monitoring IL-6 levels to predict the risk of developing long-term COVID-19 and assess potential progression of lung damage. Chest pain as an initial symptom of COVID-19 was associated to two-year mortality in the non-TCZ cohort. Dysregulated immune response induced by SARS-CoV-2 contributes to pathogenesis of chest pain, while complications like pneumonia and acute respiratory distress syndrome (ARDS) exacerbate discomfort through lung involvement [ 21 ]. The absence of chest pain as an initial symptom may be associated with the protective effect of TCZ, which mitigated the cytokine storm and organ damage, particularly in lung tissue. Our study identified smoking and lack of vaccination as predictors of two-year mortality in the non-TCZ cohort. Emiprical data strongly associate the absence of vaccination with lung damage during and after acute COVID-19 infection [ 9 ]. Smoking, especially in excess (> 25 cigarettes per day, > 20 years of smoking), is closely correlated with severe forms of COVID-19 and poor outcomes [ 9 , 25 ]. Studies show that smoking more than 22 cigarettes daily is associated with the onset of severe COVID-19 and smokers have poorer prognosis compared to non-smokers [ 9 , 25 ]. High AST levels on hospital admission independently predicted two-year mortality in the non-TCZ cohort, suggesting that early liver lesions due to IL-6-mediated hyperinflammation may be further exacerbated when TCZ is not administered. Produced by various somatic cells including hepatocytes, IL-6 plays a crucial role in hepatic acute phase response [ 23 , 24 ]. Elevated AST in COVID-19 patients correlated with IL-6 levels, emphasizing the role of systemic inflammation in liver injury [ 23 , 24 ]. In the TCZ cohort, AST was not associated with two-year mortality, possibly due to the role of TCZ in attenuation of trans-signaling. TCZ recipients demonstrated a significantly lower cumulative incidence rate of PCS (3.4% vs. 9.9%). To the best of our knowledge, studies exploring the effect of TCZ on post COVID syndrome are lacking. According to some estimates, at least 10% of individuals with a severe SARS-CoV-2 infection will develop PCS [ 25 ]. In a study from the United States the prevalence of PCS was 7.3% in a representative sample of 3,042 adults [ 26 ]. Another study from the UK found the prevalence of post-COVID of 2.9% [ 27 ]. Therefore, TCZ may have favorable effect on occurrence of post-COVID symptoms. Lower rates of PCS in the TCZ cohort may be explained by current insights into the role of IL-6 in the pathogenesis of PCS. In TCZ cohort, there was a reduction in biological activity of IL-6 during the inflammatory phase of COVID-19 infection. Recognized for its involvement in pain perception, anxiety, depression, and inflammation, IL-6 remains the key element in the onset of PCS, influencing disease severity and survival outcomes in SARS-CoV-2 immune responses [ 29 ]. The elevation of IL-1b, IL-6, and TNF during long-term PCS reflects the persistent reprogramming of pro-inflammatory immune cells, especially in the lung macrophages, as observed in recent studies on the monocyte/macrophage compartment in COVID-19 [ 30 ]. This insight underscores the intricate interplay between cytokine dynamics and prolonged immune alterations in the period after acute COVID-19. This study has some limitations. Although we included patients from two hospitals, those treated at the university center exhibit outcome-associated factors that cannot be extrapolated to lower levels of healthcare provision. While focusing on two-year mortality and post-COVID symptoms, it lacks a detailed description on quality of life in the recovery period. Although we made effort to analyze as much data as possible, we cannot rule out unobserved confounding. CONCLUSION Our study reports a cumulative two-year mortality of 20.6% among patients with severe COVID-19 who received TCZ and 24.7% cumulative mortality in patients who did not receive TCZ. TCZ recipients had a lower cumulative incidence of PCS as well (3.4% vs. 9.9%). While predictors of two-year mortality in both cohorts overlapped, there was a much wide array of mortality predictors in the non-TCZ cohort. Based on these result, it is possible that TCZ has long-term beneficial health effects on patients who were able to receive it. More studies are warranted to confirm these results. The TCZ treatment could help optimize survival during COVID-19 recovery over the first two years. Declarations ETHICS APPROVAL STATEMENT This research adhered to the Helsinki Declaration and received ethical approval from both the Ethics Committee of the UCC (Approval no. 837/8-2024) and the Ethics Committee of the "Dr. Radivoj Simonovic" General Hospital in Sombor (Approvals no. 23-2171/2023-2 and 23-2171/2023-3). DATA AVAILABILITY STATEMENT The data supporting this study’s findings are available from the Clinic of Infectious and Tropical Diseases, University Clinical Centre of Serbia, Bulevar Oslobođenja 16, 11000 Belgrade, Serbia, and the General Hospital "Dr Radivoj Simonović," Vojvođanska 75, 25000 Sombor, Serbia. Data can be obtained from the corresponding author upon reasonable request, subject to approval by the Ethics Committees of the aforementioned institutions. DECLARATION OF COMPETING INTEREST The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. FUNDING SOURCE This study has no external funding sources; all costs were covered by the authors. Author Contribution Conceptualization, I.M. and T.G.; methodology, I.M, N.N., T.G. and B.B.; software, A.F., B.B., T.G., D.H., N.T., J.S. and O.S.; valida-tion, I.M., T.G., N.N. and D.H.; formal analysis, B.B., A.F., J.S. and T.G.; investigation, A.K., B.L., N.N.; resources, I.M., N.N., B.L., A.K., D.H., O.S.; data curation, B.B., A.F., J.S., O.S. and N.N.; writing—original draft preparation, I.M., B.B, T.G., A.F. and N.T.; writing—review and editing, B.B., T.G., and I.M. supervision, I.M.; project administration,I.M. and N.N. All authors have read and agreed to the published version of the manuscript. References Menachemi N, Dixon BE, Wools-Kaloustian KK, Yiannoutsos CT, Halverson PK. How Many SARS-CoV-2-Infected People Require Hospitalization? Using Random Sample Testing to Better Inform Preparedness Efforts. J Public Health Manag Pract. 2021 May-Jun 01;27(3):246–250. Gustine JN, Jones D. Immunopathology of Hyperinflammation in COVID-19. Am J Pathol. 2021;191:4–17. Que Y, Hu C, Wan K, Hu P, Wang R, Luo J, Li T, Ping R, Hu Q, Sun Y, Wu X, Tu L, Du Y, Chang C, Xu G. Cytokine release syndrome in COVID-19: a major mechanism of morbidity and mortality. Int Rev Immunol. 2022;41(2):217–230. European Medicines Agency. EMA recommends approval for use of RoActemra in adults with severe COVID-19. 2021. https://www.ema.europa.eu/en/news/ema-recommends-approval-use-roactemra-adults-severe-covid-19 . [accessed 4 January 2024]. Furlow, Bryant. "COVACTA trial raises questions about tocilizumab's benefit in COVID-19." The Lancet Rheumatology 2.10 (2020): e592. Mariette, Xavier, et al. "Effectiveness of tocilizumab in patients hospitalized with COVID-19: a follow-up of the CORIMUNO-TOCI-1 randomized clinical trial." JAMA Internal Medicine 181.9 (2021): 1241–1243. Mariette X, Hermine O, Tharaux PL, et al. Effectiveness of Tocilizumab in Patients Hospitalized With COVID-19: A Follow-up of the CORIMUNO-TOCI-1 Randomized Clinical Trial. JAMA Intern Med. 2021;181(9):1241–1243. RECOVERY Collaborative Group. "Tocilizumab in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial." Lancet (London, England) 397.10285 (2021): 1637. Sarabia De Ardanaz, Luis, et al. "Tocilizumab in COVID-19: factors associated with mortality before and after treatment." Frontiers in Pharmacology 12 (2021): 620187. Godolphin, Peter J., et al. "Association between tocilizumab, sarilumab and all-cause mortality at 28 days in hospitalised patients with COVID-19: A network meta-analysis." PLoS One 17.7 (2022): e0270668. Morrison, Austin R., et al. "Clinical characteristics and predictors of survival in adults with coronavirus disease 2019 receiving tocilizumab." Journal of autoimmunity 114 (2020): 102512. Oronsky, Bryan, et al. "A review of persistent post-COVID syndrome (PCS)." Clinical reviews in allergy & immunology 64.1 (2023): 66–74 Fernández-de-Las-Peñas, César, et al. "Defining post-COVID symptoms (post-acute COVID, long COVID, persistent post-COVID): an integrative classification." International journal of environmental research and public health 18.5 (2021): 2621. Capra R, De Rossi N, Mattioli F, Romanelli G, Scarpazza C, Sormani MP, Cossi S. Impact of low dose tocilizumab on mortality rate in patients with COVID-19 related pneumonia. Eur J Intern Med. 2020;76:31–35. doi: 10.1016/j.ejim.2020.05.009 . Epub 2020 May 13. Somers, Emily C., et al. "Tocilizumab for treatment of mechanically ventilated patients with COVID-19." Clinical Infectious Diseases 73.2 (2021): e445-e454. Brábek, Jan, et al. "Interleukin-6: molecule in the intersection of cancer, ageing and COVID-19." International journal of molecular sciences 21.21 (2020): 7937. Wang, Bingjie, et al. "Tocilizumab, an IL6-receptor antibody, proved effective as adjuvant therapy for cytokine storm induced by severe infection in patients with hematologic malignancy." Annals of Hematology 102.4 (2023): 961–966. Toniati, Paola, et al. "Tocilizumab for the treatment of severe COVID-19 pneumonia with hyperinflammatory syndrome and acute respiratory failure: a single center study of 100 patients in Brescia, Italy." Autoimmunity reviews 19.7 (2020): 102568. Chiner-Vives, Eusebi, et al. "Short and long-term impact of COVID-19 infection on previous respiratory diseases." Archivos de Bronconeumología 58 (2022): 39–50. Schultheiß, Christoph, et al. "The IL-1β, IL-6, and TNF cytokine triad is associated with post-acute sequelae of COVID-19." Cell Reports Medicine 3.6 (2022). Polidoro, Rafael B., et al. "Overview: systemic inflammatory response derived from lung injury caused by SARS-CoV-2 infection explains severe outcomes in COVID-19." Frontiers in immunology 11 (2020): 1626. Umnuaypornlert, Adinat, et al. "Smoking and risk of negative outcomes among COVID-19 patients: a systematic review and meta-analysis." Tobacco induced diseases 19 (2021). Mitrovic, Nikola, et al. "Influence of chronic liver diseases on the course and outcome of COVID-19." Plos one 18.7 (2023): e0288350. Effenberger, Maria, et al. "Systemic inflammation as fuel for acute liver injury in COVID-19." Digestive and Liver Disease 53.2 (2021): 158–165. Davis HE, McCorkell L, Vogel JM, Topol EJ. ‘Long COVID: major findings, mechanisms and recommendations’. Nat Rev Microbiol. 2023; 21(3):133–46. Robertson MM, Qasmieh SA, Kulkarni SG, Teasdale CA, Jones HE, McNairy M, et al. The Epidemiology of Long Coronavirus Disease in US Adults. Clin Infect Dis. 2023; 76(9):1636–45. Ayoubkhani, Daniel, and Piotr Pawelek. "Prevalence of ongoing symptoms following coronavirus (COVID-19) infection in the UK: 1 April 2021." Off Natl Stat (2021): 1–16. Arish, Mohd, et al. "COVID-19 immunopathology: from acute diseases to chronic sequelae." Journal of medical virology 95.1 (2023): e28122. Kovarik, Johannes J., et al. "A multi-omics based anti-inflammatory immune signature characterizes long COVID-19 syndrome." Iscience 26.1 (2023). Zhao, Y., Kilian, C., Turner, J.E., Bosurgi, L., Roedl, K., Bartsch, P., Gnirck, A.C., Cortesi, F., Schultheiß, C., Hellmig, M., et al. (2021). Clonal expansion and activation of tissue-resident memory-like Th17 cells expressing GM-CSF in the lungs of severe COVID-19 patients. Sci. Immunol. 6, eabf6692 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5821416","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":402636532,"identity":"e4884756-a189-4433-91a8-a31677508d05","order_by":0,"name":"Branko Beronja","email":"","orcid":"","institution":"University of Belgrade","correspondingAuthor":false,"prefix":"","firstName":"Branko","middleName":"","lastName":"Beronja","suffix":""},{"id":402636533,"identity":"c119960e-d556-480c-9890-49a2596ef2e3","order_by":1,"name":"Tatjana Gazibara","email":"","orcid":"","institution":"University of Belgrade","correspondingAuthor":false,"prefix":"","firstName":"Tatjana","middleName":"","lastName":"Gazibara","suffix":""},{"id":402636534,"identity":"b9e62801-1b46-4d61-aee1-661234579934","order_by":2,"name":"Olja Stevanović","email":"","orcid":"","institution":"University Clinical Centre of Serbia","correspondingAuthor":false,"prefix":"","firstName":"Olja","middleName":"","lastName":"Stevanović","suffix":""},{"id":402636535,"identity":"89d5d3ba-0da3-4d22-bcd2-6e239a063622","order_by":3,"name":"Nataša Nikolić","email":"","orcid":"","institution":"University Clinical Centre of Serbia","correspondingAuthor":false,"prefix":"","firstName":"Nataša","middleName":"","lastName":"Nikolić","suffix":""},{"id":402636536,"identity":"42809149-ed78-4a54-beab-065dccd4f484","order_by":4,"name":"Nevena Todorović","email":"","orcid":"","institution":"University Clinical Centre of Serbia","correspondingAuthor":false,"prefix":"","firstName":"Nevena","middleName":"","lastName":"Todorović","suffix":""},{"id":402636537,"identity":"2bbce6a0-a510-4bee-a7de-ebffc9d09eae","order_by":5,"name":"Ana Filipović","email":"","orcid":"","institution":"University Clinical Centre of Serbia","correspondingAuthor":false,"prefix":"","firstName":"Ana","middleName":"","lastName":"Filipović","suffix":""},{"id":402636538,"identity":"743ac31d-6f7a-4bb1-9f7d-0f78ef16b97e","order_by":6,"name":"Jelena Simić","email":"","orcid":"","institution":"University Clinical Centre of Serbia","correspondingAuthor":false,"prefix":"","firstName":"Jelena","middleName":"","lastName":"Simić","suffix":""},{"id":402636539,"identity":"8f420a5b-8d7f-41d1-a598-99f303fd43b0","order_by":7,"name":"Biljana Lukić","email":"","orcid":"","institution":"General Hospital \"Dr Radivoj Simonović\"","correspondingAuthor":false,"prefix":"","firstName":"Biljana","middleName":"","lastName":"Lukić","suffix":""},{"id":402636540,"identity":"cf6fd5e3-c8d7-4922-8944-3b012799d841","order_by":8,"name":"Dejan Hristović","email":"","orcid":"","institution":"Military Academy of the University of Defence","correspondingAuthor":false,"prefix":"","firstName":"Dejan","middleName":"","lastName":"Hristović","suffix":""},{"id":402636541,"identity":"ae62223b-b5ca-486b-8ef4-fb02c99dedc7","order_by":9,"name":"Aleksandra Karan","email":"","orcid":"","institution":"General Hospital \"Dr Radivoj Simonović\"","correspondingAuthor":false,"prefix":"","firstName":"Aleksandra","middleName":"","lastName":"Karan","suffix":""},{"id":402636542,"identity":"2c75aae5-3b6d-4103-8cbb-f021e5da2cd4","order_by":10,"name":"Ivana Milošević","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABHklEQVRIiWNgGAWjYBACNijNwwemDBjkQCQzUVrYoFqMCWrB0JvYQEgLn0Tyswc/GLbJsLG3P3zMU2CXvra9eQNzwS8Gef4G3scfsBkukWZu2MNwm4eN54yxMY9Bcu62M8cKmGf2MRjOOMBuJoFNC88BMwkekBaJHDbJGQYHcrfdyDFg5u1hYNzAwMaGRQdQy/Fvkn/AWtKf/wRqSTe7/wasxR6ohRmrw9h7zKQhtiSYMXwwOJBgdoPHgJnnB0MiUAsDVoex95RJyxhA/CLxwSDZcNuZtILDMxskkmccZmPDpkW+mX2b5JuK2/b8wBD7kPDHTt7s+OGNjwv+2Nj2t7dhdRgEGKDxDzC2Ac0nLkLh4A9pykfBKBgFo2BYAwCwGlYBEdac1wAAAABJRU5ErkJggg==","orcid":"","institution":"University Clinical Centre of Serbia","correspondingAuthor":true,"prefix":"","firstName":"Ivana","middleName":"","lastName":"Milošević","suffix":""}],"badges":[],"createdAt":"2025-01-13 16:11:49","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5821416/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5821416/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":74282962,"identity":"8a2cb4c5-8c36-4b83-b474-49078593e830","added_by":"auto","created_at":"2025-01-20 15:52:55","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":67843,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5821416/v1/54860728b7bafd8008de32fa.jpg"},{"id":74284283,"identity":"99f5f6bb-95e1-44f0-b6c9-f463ee6f6802","added_by":"auto","created_at":"2025-01-20 16:00:55","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":17019,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e","description":"","filename":"Fiure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5821416/v1/58c9b93eeb335a616ad9e365.jpg"},{"id":84392301,"identity":"e90849a0-fec9-4399-b468-46a2cab78be1","added_by":"auto","created_at":"2025-06-11 11:47:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1873488,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5821416/v1/07e6b096-39a7-455c-9125-1ef072116d8a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eOutcomes of Severe Covid-19 Among Patients Who Did and Did Not Receive Tocilizumab: A Two-year Prospective Cohort Study \u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe majority of people who catch COVID-19 experience a relatively mild infection. However, approximately 2.1% of individuals with COVID-19 may require hospital treatment [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. One underlying pathophysiological mechanism observed in severe COVID-19 is the excessive production of interleukin 6 (IL-6), which may generate the cytokine storm syndrome [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. If left untreated, the cytokine storm can cause cardiovascular collapse, multiorgan dysfunction, and ultimately death [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTocilizumab (TCZ) is a genetically engineered humanized monoclonal antibody and is being used in severe COVID-19 to reduce IL-6 levels [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. It inhibits the T lymphocyte activation, antibody production, acute-phase protein synthesis, and hematopoietic cell proliferation [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The TCZ treatment includes a one-day pulse therapy of a recommended dose of 8 mg/kg (not exceeding 800 mg in total) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Typically, TCZ is being administered along with corticosteroids. The effectiveness of TCZ varies across trials. Studies have found that TCZ shortens hospital stay, possibly reduces in-hospital mortality, as well as lowers the risk of needing mechanical ventilation and having poor COVID-19 outcomes [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The RECOVERY trial reported a 28-day mortality reduction after TCZ administration, especially when it is combined with corticosteroids [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, long-term effects of TCZ treatment after hospital have not been studied to date. Thus, prospective cohort studies are essential to investigate the outcomes of TCZ\u0026thinsp;+\u0026thinsp;corticosteroids therapy and compare them with corticosteroids therapy alone.\u003c/p\u003e \u003cp\u003eThe available body of literature predominantly focused on 7-day and 28-day mortality in TCZ-treated patients, suggesting lower mortality rates compared to other therapeutic approaches [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Consistent predictors of in-hospital mortality in TCZ-treated individuals include having two or more chronic illnesses, older age, and high levels of laboratory markers at admission such as C-reactive protein (CRP), IL-6 and lactate dehydrogenase (LDH) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Still, there is a lack of studies evaluating the independent impact of TCZ on two-year mortality and the onset of post-COVID syndrome (PCS) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Understanding long-term effect of TCZ treatment on mortality and occurrence of PCS may help to optimize treatment strategies of severe COVID-19.\u003c/p\u003e \u003cp\u003eThe aim of this study was to compare the outcomes of COVID-19 over two years of follow-up in cohorts of patients who did and did not receive TCZ and to identify factors associated with two-year mortality in both cohorts.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSetting and participants\u003c/h2\u003e \u003cp\u003eThis prospective cohort study was conducted at two healthcare centers: the Clinic for Infectious and Tropical Diseases, University Clinical Center of Serbia (UCC) in Belgrade, and the general hospital \"Dr Radivoj Simonovic\" in Sombor. The study population was admitted to hospitals between March 1, 2021, and December 7, 2022. The Clinic for Infectious and Tropical Diseases is a referral institution for treatment of infectious diseases and is the largest hospital of its kind in the country. The General Hospital in Sombor, the principal hospital of the West Bačka District (including municipalities of Sombor, Apatin, Odžaci, and Kula in the north-west of Serbia), provides secondary level of healthcare to approximately 187,500 residents. Throughout the studied period, both hospitals operated a semi-intensive care unit (SICU) and an intensive care unit (ICU) for severe COVID-19 cases.\u003c/p\u003e \u003cp\u003eThe inclusion criteria for both cohorts were: 1) confirmed SARS-CoV-2 infection through RT-PCR or antigen testing, 2) age of 18 years or older, and 3) developing severe clinical symptoms during hospitalization which are in line with the criteria for TCZ application. The current treatment protocol for COVID-19 patients in Serbia, in accordance with the recommendations of the World Health Organization, involves the administration of TCZ when the IL-6 value exceeds 40 pg/ml, or when a threefold increase in inflammatory markers occurs within a one-day interval or a progression toward respiratory failure.\u003c/p\u003e \u003cp\u003eThe sample size calculation was based on the populations of Belgrade (approximately 1.4\u0026nbsp;million people) and the West Bačka district (roughly 190,000 people). Considering an estimated 9% of COVID-19 positive individuals, older than 60 years, requiring hospital treatment, a 95% confidence interval, and a 5% probability of alpha error, the minimum sample size per cohort is 126 participants (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.calculator.net/sample-size-calculator.html\u003c/span\u003e\u003cspan address=\"https://www.calculator.net/sample-size-calculator.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e This research adhered to the Helsinki Declaration and received ethical approval from both the Ethics Committee of the UCC (Approval no. 837/8-2024) and the Ethics Committee of the \"Dr. Radivoj Simonovic\" General Hospital in Sombor (Approvals no. 23-2171/2023-2 and 23-2171/2023-3).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eDemographic and clinical information on admission and during follow-up were extracted from electronic medical records. The collected data covered demographic characteristics (gender, age, medical history, and presence of chronic illnesses [such as hypertension, diabetes mellitus types 1 and 2, obesity, respiratory diseases like chronic obstructive pulmonary disease-COPD and asthma, kidney diseases, and malignant tumors]. Additionally, clinical data on initial COVID-19 symptoms were retrieved as well (fever, cough, fatigue, shortness of breath, and chest pain), as well as the COVID-19 vaccination status.\u003c/p\u003e \u003cp\u003eLaboratory results on hospital admission were retrieved from electronic medical records: red blood cell count (RBC), hemoglobin (Hgb), white blood cell count (WBC), neutrophil count (Ne), lymphocyte count (Ly), D-dimer, prothrombin time (PT), international normalized ratio (INR), glycemia, creatinine (Cr), urea, albumin (Alb), procalcitonin (Pct), LDH, CRP, ferritin, alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (gGT), and creatine kinase (CK).\u003c/p\u003e\n\u003ch3\u003eExposure\u003c/h3\u003e\n\u003cp\u003eThe timing of TCZ therapy was recorded for every patient in the TCZ cohort as the number of days from the onset of COVID-19 symptoms to the adminsitration of TCZ.\u003c/p\u003e\n\u003ch3\u003eFollow-up\u003c/h3\u003e\n\u003cp\u003eDuring hospital treatment, patients were either discharged from hospital, while time of death was recorded for all non-surviving patients. Time when patients were discharged from hospital was also recorded. Surviving patients were further monitored and were recommended to report any subsequent health issues post-hospitalization. The graphical representation of patient monitoring points over follow-up is shown in Fig.\u0026nbsp;1.\u003c/p\u003e \u003cp\u003eOver the second year after hospital discharge, the research team had at least one telephone call with the surviving patients from both cohorts. Patients were asked about the occurrence of long COVID or post-COVID symptoms as well as any other significant health disruptions (such as stroke, other cardiovascular diseases, or new-onset malignant tumors). According to guidelines, the PCS encompasses the following: a) persistence of any of the symptoms from the acute phase of COVID-19 and their management; b) symptoms linked to a novel illness; c) delayed-onset symptoms emerging after the resolution of the acute phase of COVID-19; and d) influence on pre-existing medical conditions or disabilities [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurthermore, all patients were asked about the presence of any post-COVID symptoms, including prolonged fatigue, difficulty breathing, cough, anxiety or depression, myalgia, sleep problems, chest pain, issues with concentration and memory, hair loss, and anosmia [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. On this occasion, patients were also asked about other health issues that could potentially trigger these symptoms. Subsequently, an analysis of medical records was conducted, focusing exclusively on symptoms unequivocally associated with PCS, i.e., those lacking alternative medical explanations.\u003c/p\u003e \u003cp\u003eData on patient mortality and time of death was retrieved from the electronic medical records in instances when there was no response at attempted telephone call or upon receiving notification of death from family members.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003ePatients were analyzed based on the administration of TCZ.\u003c/p\u003e \u003cp\u003eBoth cohorts were stratified into two groups: survivors and non-survivors based on the two-year survival data. The data analysis utilized descriptive and analytical statistical methods using the IBM SPSS-Statistics version 17.1 software (IBM Corp). A p-value of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered as statistically significant. Descriptive characteristics were presented using mean values and standard deviations for continuous variables, while frequencies and percentages were utilized for categorical variables. The normality of the distribution of continuous variables was assessed using the Kolmogorov-Smirnov test. For normally distributed continuous variables, independent samples t-tests were applied, while non-normally distributed variables underwent analysis using the nonparametric two-tailed Mann-Whitney test. Categorical variables were evaluated using Fisher's exact test (when observations per cell were fewer than five) and the Chi-square test.\u003c/p\u003e \u003cp\u003eThe Kaplan-Meier survival curve was utilized to analyze patient survival, stratified by TCZ usage, followed by an assessment of differences in the survival curve using the log-rank test. The Cox proportional hazard model was applied to identify factors associated with mortality. The independent variables were classified according to groups to avoid overadjustment of models. One group of variables contained those patient characteristics that were usually grouped together in literature. Therefore, the first model included sociodemographic characteristics, initial COVID-19 symptoms and treatment. The second model included pre-existing chronic diseases. The time to death/end of follow-up was also included in the model.\u003c/p\u003e \u003cp\u003ePredictive models were analyzed independently for the TCZ and non-TCZ cohorts, revealing common factors associated with the two-year mortality as well as those specific to each cohort. Subsequently, all statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and marginally significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.25) variables in the univariate analysis were included in the multivariate model.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eDescription of the study cohorts\u003c/h2\u003e \u003cp\u003eA total of 457 patients were included in the study, with the TCZ cohort comprising 150 participants and the non-TCZ cohort consisting of 307 participants. In TCZ cohort, the majority of patients were male (101; 67.3%), of an average age of 64.47\u0026thinsp;\u0026plusmn;\u0026thinsp;12.35 years (age range 39\u0026ndash;91 years). Of 39 TCZ-treated patients requiring ICU treatment, 19 died, resulting in a case-fatality rate of 12.7% in the total sample and a case-fatality rate of 48.7% in all ICU-treated patients (death occurred after a median of 22 days [min-max 10\u0026ndash;27 days] following the onset of symptoms). Over the two-year follow-up, an additional 12 patients passed away, yielding a two-year cumulative mortality rate of 20.6% in the TCZ cohort.\u003c/p\u003e \u003cp\u003eIn non-TCZ cohort, the majority of patients were female (211; 68.2%), of an average age of 63.41\u0026thinsp;\u0026plusmn;\u0026thinsp;12.35 years (age range 37\u0026ndash;92 years). Of 86 patients in the non-TCZ cohort who required ICU treatment, 46 died, resulting in a case-fatality rate of 14.9% in the total sample and a case-fatality rate of 53.4% in all ICU-treated patients (death occurred after a median of 20 days [min-max 9\u0026ndash;21 days] following the onset of symptoms). Over the two-year follow-up, additional 20 patients passed away, resulting in a two-year cumulative mortality rate of 24.7% in the non-TCZ cohort. The majority of patients in both cohorts were not vaccinated (332; 72.6%). No difference in age was observed between the TCZ and non-TCZ cohorts (p\u0026thinsp;=\u0026thinsp;0.664). Demographic and clinical parameters of the study cohorts are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\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\u003eDemographic clinical and laboratory characteristics of the study cohort\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eTocilizumab cohort\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;150 n(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eNon-Tocilizumab cohort\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;307 n(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-survivors\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;31 n(20.66%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSurvivors\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;119 n(79.33%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNon-survivors\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;76 n(16,63%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSurvivors\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;231 n(50.54%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;sd)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.59\u0026thinsp;\u0026plusmn;\u0026thinsp;13.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.00\u0026thinsp;\u0026plusmn;\u0026thinsp;12.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e76.31\u0026thinsp;\u0026plusmn;\u0026thinsp;13.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e60.55\u0026thinsp;\u0026plusmn;\u0026thinsp;11.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (14.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80 (53.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.712\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22 (7.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e73 (23.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.775\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWomen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39 (26.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54 (17.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e157 (51.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eNeeding IUC treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (18.66%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (7.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55 (17.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e31 (10.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSeverity CT score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.21\u0026thinsp;\u0026plusmn;\u0026thinsp;4.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.15\u0026thinsp;\u0026plusmn;\u0026thinsp;5.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCOVID-19 vaccination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (23.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (2.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e67 (21.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.022\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (8.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23 (15.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e47 (15.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e78 (25.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDuration of hospital stay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.11\u0026thinsp;\u0026plusmn;\u0026thinsp;9.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.23\u0026thinsp;\u0026plusmn;\u0026thinsp;5.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.018\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.32\u0026thinsp;\u0026plusmn;\u0026thinsp;5.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.85\u0026thinsp;\u0026plusmn;\u0026thinsp;6.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTiming of TCZ therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.11\u0026thinsp;\u0026plusmn;\u0026thinsp;9.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.21\u0026thinsp;\u0026plusmn;\u0026thinsp;3.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInitial symptoms of COVID-19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eFever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (21.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e101 (67.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.630\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e63 (20.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e193 (62.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.894\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCough\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (19.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86 (57.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.770\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58 (18.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e180 (58.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.771\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eFatigue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (14.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68 (45.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.713\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36 (11.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e106 (34.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.822\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eShortness of breath\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (13.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33 (22.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.026\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31 (10.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e57 (18.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eChest pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (9.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (14.66%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55 (36.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28 (9.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e73 (23.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.399\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDiabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (7.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (12.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.011\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28 (9.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e46 (15.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eInsulin dependent diabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (2.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13 (4.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22 (7.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eOral antidiabetics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (4.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (8.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17 (5.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24 (7.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (4.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7 (2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.345\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMalignant tumors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (6.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (4.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.020\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eRespiratory diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (4.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.046\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eChronic kidney disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6 (2.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLaboratory characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eErythrocytes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.13 (3.49\u0026ndash;4.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.35 (3.85\u0026ndash;4.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e132.0 (120.0-144.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.05 (3.45\u0026ndash;4.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.820\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHemoglobin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e126.0 (114.0-138.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e132.0 (119.7\u0026ndash;144.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.727\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e132.0 (120.0-144.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e125.0 (112.0-136.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.646\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eWhite blood cells\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.85 (4.07\u0026ndash;9.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.0 (4.37\u0026ndash;8.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.879\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.81 (4.25\u0026ndash;9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.0 (4.0\u0026ndash;9.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.702\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLymphocytes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.29 (0.85\u0026ndash;1.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.13 (0.78\u0026ndash;1.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.05 (0.77\u0026ndash;1.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.37 (0.97\u0026ndash;1.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eNeutrophils\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.93 (3.31\u0026ndash;6.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.46 (3.12\u0026ndash;6.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.59 (3.28\u0026ndash;6.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.98 (3.44\u0026ndash;6.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.577\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMonocytes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.35 (0.22\u0026ndash;0.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.40 (0.24\u0026ndash;0.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.911\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.34 (0.23\u0026ndash;0.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.38 (0.21\u0026ndash;0.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.872\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePlatelets\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e155.0 (124.0-267.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e172.5 (137.5-220.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e145.0 (103.0-291.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e184.5 (148.0-256.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eD-dimer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.65 (0.47\u0026ndash;1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.63 (0.39\u0026ndash;0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.75 (0.50\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.97 (0.78\u0026ndash;1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.505\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eProthrombin time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.35 (12.40\u0026ndash;14.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.9 (12.2\u0026ndash;13.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.6 (12.2\u0026ndash;13.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.5 (12.1\u0026ndash;12.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.261\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eInternational normalized ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.10 (1.03\u0026ndash;1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.08 (1.02\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.11 (1.04\u0026ndash;1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.42 (1.17\u0026ndash;1.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.520\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGlycemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.2 (5.7\u0026ndash;9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.90 (5.70-8.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.0 (5.4\u0026ndash;8.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.90 (4.20\u0026ndash;9.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.771\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCreatinine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88.5 (72.5-107.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85.0 (75.0-102.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e90.0 (77.0-116.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e91.1 (81.3-102.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eUrea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.20 (4.80\u0026ndash;8.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.50 (4.45\u0026ndash;7.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.032\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.6 (2.84\u0026ndash;3.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.20 (2.0-3.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.960\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAlbumin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.0 (30.5\u0026ndash;36.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.0 (30.0\u0026ndash;36.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32.0 (30.0\u0026ndash;36.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33.0 (31.0\u0026ndash;36.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.419\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eProcalcitonin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.14 (0.08\u0026ndash;0.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.15 (0.10\u0026ndash;0.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.585\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.89 (0.14\u0026ndash;1.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.67 (0.54\u0026ndash;0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLactate dehydrogenase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e241.5 (203.0-312.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78.75 (36.27\u0026ndash;178.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e246.0 (206.0-312.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e136.3 (56.3-198.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.622\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eC-reactive protein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78.75 (36.27\u0026ndash;178.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.60 (25.45\u0026ndash;98.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.044\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e82.64 (39.31-187.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e53.50 (24.60\u0026ndash;82.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.035\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eFerritin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e542.45 (393.1-1209.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e542.2 (301.2-1060.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e533.75 (332.0-860.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e623.0 (387.0-797.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.045\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAlanine aminotransferase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.0 (29.0\u0026ndash;77.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.50 (28.0-60.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e49.0 (31.0-69.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e60.0 (43.0\u0026ndash;76.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.869\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAspartate aminotransferase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.0 (23.0-47.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.0 (25.0\u0026ndash;79.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e49.0 (25.0\u0026ndash;74.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e52.0 (30.0\u0026ndash;79.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.562\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGamma glutamyl-transferase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.5 (23.0-47.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.0 (28.0-61.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43.5 (29.0-69.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e57.0 (37.0\u0026ndash;74.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.608\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCreatine kinase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e202.0 (92.7-426.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e128.5 (67.5-2551.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.046\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e215.0 (92.5\u0026ndash;315.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e147.0 (121.0-189.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eInterleukin 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.50 (39.9\u0026ndash;87.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48.95 (34.3\u0026ndash;57.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eErythrocytes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.13 (3.49\u0026ndash;4.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.35 (3.85\u0026ndash;4.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e132.0 (120.0-144.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.05 (3.45\u0026ndash;4.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.820\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eLegend: CT-computerized tomography; Bolded values are statistically significant\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eComparison between survivors and non-survivors\u003c/h3\u003e\n\u003cp\u003eNon-survivors in both cohorts were older, needed the ICU treatment more frequently, had a lower vaccination coverage, longer hospital stay, and more frequent shortness of breath and chest pain upon admission. Additionally, diabetes was more common in the non-survivor group.\u003c/p\u003e \u003cp\u003eIn TCZ cohort, non-survivors more often experienced delayed administration of TCZ, had insulin-dependent diabetes mellitus, and were obese compared to survivors. In non-TCZ cohort, non-survivors were more often smokers and had a higher prevalence of pulmonary, renal, and cancers, as well as diabetes mellitus type 2 compared to survivors.\u003c/p\u003e \u003cp\u003eCompared to survivors in both cohorts, non-survivors had higher levels of CRP and CK on hospital admission. In the TCZ cohort, non-survivors had elevated levels of IL-6 and urea upon admission compared to survivors, while non-survivors in the non-TCZ cohort had higher levels of ferritin upon admission compared to survivors. Other differences in laboratory characteristics between survivors and non-survivors in both cohorts are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eHealth-related events over a two-year follow-up period\u003c/h2\u003e \u003cp\u003eProlonged fatigue over two-year follow-up period was more often reported among people in the non-TCZ cohort compared to the TCZ cohort (p\u0026thinsp;=\u0026thinsp;0.040). Furthermore, patients in non-TCZ cohort were more prone to developing PCS over follow-up (p\u0026thinsp;=\u0026thinsp;0.018) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Cumulative incidence of PCS over two-year follow-up in the TCZ cohort was 3.4%, and in the non-TCZ cohort 9.9%.\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\u003eHealth-related events during the two-year follow-up periodand or causes of death of patients from non-survivors cohort\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eSurvivors\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;350 n(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTCZ cohort\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;119 n(34.0%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-TCZ cohort\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;231 n(66.0%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOVID-19 reinfection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (4.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (8.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.610\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRehospitalization COVID-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.759\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitalization - other reasons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.775\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosed post-COVID syndrome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (5.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.040\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiovascular diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (2.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.449\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoronary heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.506\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 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.194\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSubjective experience of post-COVID syndrome symptoms\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProlonged fatigue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46 (13.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120 (34.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.018\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDifficulty breathing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (13.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.111\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCough\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (4.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (11.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.409\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety or depression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (11.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.294\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyalgia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (3.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.908\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep problems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.632\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChest pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (5.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.199\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIssues with concentration and memory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.397\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHair loss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.943\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnosmia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.834\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eVariable - cause of death\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNon-Survivors\u003c/b\u003e\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;107 n(%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTCZ cohort\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;31 (28.97%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-TCZ cohort N\u0026thinsp;=\u0026thinsp;76 (71.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOVID-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (17.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (43.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.957\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiovascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (5.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (12.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.782\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\u003e3 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (11.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.409\u003c/p\u003e \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\u003e2 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (3.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.809\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.437\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn TCZ cohort, 14 patients had COVID-19 reinfection over the two-year follow-up (reinfection rate of 11.8%). Out of 14 reinfected patients, 2 (14.2%) required rehospitalization due to COVID-19 reinfection during the two-year follow-up. In non-TCZ cohort, 31 patients (8.9%) were reinfected with COVID-19, resulting in a reinfection rate of 14.4%. Of 31 reinfected patients, 5 (16.1%) required rehospitalization for COVID-19 infection over a two-year follow-up.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eCumulative two-year mortality according to cohorts\u003c/h2\u003e \u003cp\u003eThe cumulative two-year mortality in the TCZ cohort was 20.6%, with 19 patients (61.2%) dying during the initial hospitalization. During follow-up, 6 patients (19.3%) died of cerebrovascular diseases, 3 patients (9.7%) died of stroke, 2 patients (6.5%) died of cancer, and 1 patient (3.2%) died because of complications related to the COPD (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe cumulative two-year mortality in the non-TCZ cohort was 24.7%, with 47 patients (61.2%) dying during the initial hospitalization for COVID-19. During the two-year follow-up, 13 patients (19.3%) died of cerebrovascular diseases, 12 patients (9.7%) died of stroke, 4 patients (6.5%) died of cancer, and 1 patient (3.2%) died in a traffic accident (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Kaplan-Meier survival curve suggested a statistically significant difference in two-year mortality between the TCZ and the non-TCZ cohorts (Log-rank test p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This indicates that patients who did not receive TCZ had poorer survival compared to those who received TCZ over two years of follow-up (Fig.\u0026nbsp;1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePredictors of cumulative two-year mortality\u003c/h2\u003e \u003cp\u003eThe first model identified several factors associated with two-year mortality risk in the TCZ cohort, which included older age (p\u0026thinsp;=\u0026thinsp;0.004), the requirement for ICU treatment during COVID-19 (p\u0026thinsp;=\u0026thinsp;0.047), and delayed administration of TCZ (p\u0026thinsp;=\u0026thinsp;0.002). In the non-TCZ cohort, the multivariate model revealed that age (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), needing ICU treatment (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and presence of chest pain on admission (p\u0026thinsp;=\u0026thinsp;0.012) were predictive of cumulative two-year mortality in this cohort (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of the multivariate Cox proportional hazard models: factors associated with mortality in cohorts\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"15\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eModel 1.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eTocilizumab cohort\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c15\" namest=\"c8\"\u003e \u003cp\u003eNon-Tocilizumab cohort\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c12\" namest=\"c8\"\u003e \u003cp\u003eUnivariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003eMultivariate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.01\u0026ndash;1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.02\u0026ndash;1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e1.06\u0026ndash;1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.04\u0026ndash;1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.59\u0026ndash;1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.633\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.894\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0.54\u0026ndash;3.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e0.657\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOVID-19 vaccination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.648\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.26\u0026ndash;1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0.31\u0026ndash;0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.045\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.737\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.97\u0026ndash;2.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.322\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\u003e1.537\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.54\u0026ndash;4.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.422\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e1.78\u0026ndash;4.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.63\u0026ndash;1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeverity CT score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.15\u0026ndash;1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.08\u0026ndash;1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeeding IUC treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.39-20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.01\u0026ndash;10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.047\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e11.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e6.75\u0026ndash;18.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e4.49\u0026ndash;14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of hospital stay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00-1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.027\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.99\u0026ndash;1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0.99\u0026ndash;1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.01\u0026ndash;1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e0.524\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTiming of TCZ therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.18\u0026ndash;1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.16\u0026ndash;1.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.604\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.23\u0026ndash;1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.940\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0.51\u0026ndash;1.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e0.838\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\" morerows=\"3\" rowspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\" morerows=\"3\" rowspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\" morerows=\"3\" rowspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCough\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91\u0026ndash;1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0.64\u0026ndash;1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e0.758\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFatigue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u0026ndash;2.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0.92\u0026ndash;1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e0.691\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShortness of breath\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.08\u0026ndash;2.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.022\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.22\u0026ndash;3.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.850\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0.90\u0026ndash;2.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e0.850\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChest pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.14\u0026ndash;1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.65\u0026ndash;5.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e1.22\u0026ndash;1.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.716\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.37\u0026ndash;2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e0.012\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eModel 2.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c12\" namest=\"c8\"\u003e \u003cp\u003eUnivariate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003eMultivariate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\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\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\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003ep\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\u003e1.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.01\u0026ndash;1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.01\u0026ndash;1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.016\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e1.06\u0026ndash;1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.06\u0026ndash;1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.59\u0026ndash;1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.633\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.894\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e1.54\u0026ndash;2.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.657\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOVID-19 vaccination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.648\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.26\u0026ndash;1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e0.558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.31\u0026ndash;0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.045\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.769\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.42\u0026ndash;2.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.401\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\u003e1.537\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.54\u0026ndash;4.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.422\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e2.839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e1.78\u0026ndash;4.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e2.765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.69\u0026ndash;4.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\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\u003e1.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.50\u0026ndash;2.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e1.50\u0026ndash;1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsulin dependent diabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.10\u0026ndash;1.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.398\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.14\u0026ndash;2.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.042\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e1.30\u0026ndash;2.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.42\u0026ndash;2.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e0.039\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOral antidiabetics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.461\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.48\u0026ndash;3.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.81\u0026ndash;1.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e1.28\u0026ndash;1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.44\u0026ndash;2.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.432\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.36\u0026ndash;7.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.68\u0026ndash;4.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.68\u0026ndash;3.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.57\u0026ndash;2.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.563\u003c/p\u003e \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\u003e5.451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18\u0026ndash;9.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.710\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e1.09\u0026ndash;1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.444\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.17\u0026ndash;2.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e0.041\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.97\u0026ndash;3.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e1.04\u0026ndash;1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.04\u0026ndash;1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic kidney disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.735\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.95\u0026ndash;7.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.681\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.72\u0026ndash;5.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.70\u0026ndash;2.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.015\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.91\u0026ndash;1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.251\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eModel 3.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c12\" namest=\"c8\"\u003e \u003cp\u003eUnivariate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003eMultivariate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\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\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\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003ep\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\u003e1.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.01\u0026ndash;1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.01\u0026ndash;1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e1.06\u0026ndash;1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.05\u0026ndash;1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.59\u0026ndash;1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.633\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"15\" rowspan=\"16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"15\" rowspan=\"16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"15\" rowspan=\"16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.894\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.74\u0026ndash;2.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.657\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOVID-19 vaccination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.648\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.26\u0026ndash;1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e0.558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.31\u0026ndash;0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.045\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.45\u0026ndash;1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.260\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\u003e1.537\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.54\u0026ndash;4.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.422\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e2.839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e1.78\u0026ndash;4.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e2.399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.48\u0026ndash;3.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eErythrocytes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.932\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.61\u0026ndash;1.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e0.926\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.65\u0026ndash;1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.665\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\" morerows=\"10\" rowspan=\"11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\" morerows=\"10\" rowspan=\"11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\" morerows=\"10\" rowspan=\"11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.97\u0026ndash;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.593\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e0.988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.95\u0026ndash;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.661\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite blood cells\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.968\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.94\u0026ndash;2.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.548\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.94\u0026ndash;1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.724\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocytes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93\u0026ndash;1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e0.883\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.61\u0026ndash;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.185\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophils\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.88\u0026ndash;2.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.784\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.92\u0026ndash;1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.852\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonocytes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.72\u0026ndash;1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.883\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.82\u0026ndash;1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.455\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelets\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.94\u0026ndash;0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.99\u0026ndash;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.718\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-dimer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.76\u0026ndash;1.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.813\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.41\u0026ndash;2.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.387\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProthrombin time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.90\u0026ndash;1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.850\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e0.908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.78\u0026ndash;1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.201\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003einternational normalized ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.21\u0026ndash;3.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e0.748\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.33\u0026ndash;1.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.477\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlycemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.92\u0026ndash;1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.717\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.91\u0026ndash;3.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.751\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.99\u0026ndash;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.995\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e1.98-2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.012\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e2.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.89\u0026ndash;3.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.929\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.79\u0026ndash;2.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.929\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.85\u0026ndash;3.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.954\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProcalcitonin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98\u0026ndash;1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.99\u0026ndash;1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e1.04\u0026ndash;1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.039\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.94\u0026ndash;1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLactate dehydrogenase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.99\u0026ndash;1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.276\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\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.91\u0026ndash;1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC-reactive protein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00-1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00-1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e1.00-1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.99\u0026ndash;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e0.015\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFerritin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.99\u0026ndash;3.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.574\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e1.99-2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.040\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.98\u0026ndash;3.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlanine aminotransferase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.99\u0026ndash;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.99\u0026ndash;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAspartate aminotransferase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.90\u0026ndash;1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e1.02\u0026ndash;1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.01\u0026ndash;1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e0.012\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGamma glutamyl-transferase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.41\u0026ndash;2.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.99\u0026ndash;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatine kinase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00-1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00-1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.043\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e1.00-1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.019\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.01\u0026ndash;1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e0.039\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterleukin 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00-1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.99\u0026ndash;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"15\"\u003eLegend: HR-hazard ratio; CI-confidence interval; Bolded values are statistically significant.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the second model for the TCZ cohort, older age (p\u0026thinsp;=\u0026thinsp;0.016) and insulin-dependent diabetes (p\u0026thinsp;=\u0026thinsp;0.042) were identified as predictors of two-year cumulative mortality. In the non-TCZ cohort, the multivariate model identified older age (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), smoking (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), insulin-dependent diabetes (p\u0026thinsp;=\u0026thinsp;0.039), cancers (p\u0026thinsp;=\u0026thinsp;0.041), and respiratory diseases (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) as predictors of two-year cumulative mortality (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe third model for the TCZ cohort revealed that older age (p\u0026thinsp;=\u0026thinsp;0.010) and higher admission values for CK (p\u0026thinsp;=\u0026thinsp;0.043), IL-6 (p\u0026thinsp;=\u0026thinsp;0.004), and CRP (p\u0026thinsp;=\u0026thinsp;0.007) were associated with two-year mortality risk. In the non-TCZ cohort, the multivariate model identified older age (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), smoking (p\u0026thinsp;=\u0026thinsp;0.001), levated CRP (p\u0026thinsp;=\u0026thinsp;0.015), AST (p\u0026thinsp;=\u0026thinsp;0.012), and CK levels (p\u0026thinsp;=\u0026thinsp;0.039) as predictors of two-year cumulative mortality in this cohort (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study found a difference in cumulative two-year mortality among patients who received and did not receive TCZ. Specifically, the TCZ cohort had cumulative two-year mortality rate of 20.6% and the non-TCZ cohort had 24.7%. The cumulative incidence rate for diagnosed PCS after two years of follow-up was 3.4% in the TCZ cohort and 9.9% in the non-TCZ cohort. Factors associated with two-year mortality in both cohorts were older age, receiving the ICU treatment, having insulin-dependent diabetes, and having elevated CRP and CK on hospital admission. In addition, factors associated with two-year mortality in the non-TCZ cohort were chest pain on admission, not being vaccinated against COVID-19, history of smoking, having respiratory diseases, and cancer along with high AST values on admission.\u003c/p\u003e \u003cp\u003eA low cumulative mortality after two years of follow-up observed in this study supports the assumption that TCZ may have long-term beneficial effects on survival after having developed a severe form of COVID-19. Capra et al. made a comparison between patients who received the standard of care (26 patients) and those who received TCZ in addition to the standard of care (62 patients) for moderately severe COVID-19 pneumonia [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Patients receiving TCZ exhibited a significantly longer survival rate compared to the control groups when age, chronic illnesses and CRP were taken into consideration [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Although our results are similar, the former study [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] had a considerably smaller sample size, potential selection bias and a high prevalence of unknown outcomes.\u003c/p\u003e \u003cp\u003eConsidering the off-label application of TCZ, alongside a high volume of critically ill patients and its single-day administration regimen (in contrast to the extended protocols observed in non-COVID contexts), the attending physician team recommended the administration of TCZ to patients with malignancies. This decision aligned with the evidence from medical literature and experiences of other medical centers worldwide. Pre-existing malignant diseases independently predicted two-year mortality in the non-TCZ cohort, with no significant difference in cancer prevalence between cohorts. TCZ-treated patients experienced reduced biological effects of IL-6 during the inflammatory phase of CIVID-19 infection.\u003c/p\u003e \u003cp\u003eIt has been well-established that IL-6 has a remarkable systemic impact, ultimately resulting in metabolic failure, severe psychological and mental complications, and independelty contributes to mortality of cancer patients [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Literature findings suggest that treatment with TCZ has a potential to attenuate migratory effects of malignant cells [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Based on the current knowledge, it is not possible to clearly define the interaction of high concentrations of IL-6 in patients with severe COVID-19 and its impact on subsequent course of cancer.\u003c/p\u003e \u003cp\u003eFactors linked to two-year mortality in the non-TCZ cohort primarily involved pre-existing respiratory illnesses. This may be explained by the absence of protective effect of TCZ against lung damage during acute COVID-19 infection. Early and low-dose TCZ treatment have shown to reduce mortality in COVID-19-related respiratory failure, as demonstrated by Rossi et al [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Experiences from Spain suggest that patients with COVID-19-related lung fibrosis exhibit higher IL-6 levels during the inflammatory phase, which may increase vulnerability in those individuals with pre-existing lung diseases [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Contrary, potential protective effect of TCZ in slowing lung damage progression is evident in the TCZ cohort. Recent studies focus on the release of IL-6 and granulocyte-macrophage colony-stimulating factor from the activated pathogenic T cells weeks after SARS-CoV-2 infection as a marker of further infection progression [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. This highlights the importance of monitoring IL-6 levels to predict the risk of developing long-term COVID-19 and assess potential progression of lung damage.\u003c/p\u003e \u003cp\u003eChest pain as an initial symptom of COVID-19 was associated to two-year mortality in the non-TCZ cohort. Dysregulated immune response induced by SARS-CoV-2 contributes to pathogenesis of chest pain, while complications like pneumonia and acute respiratory distress syndrome (ARDS) exacerbate discomfort through lung involvement [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The absence of chest pain as an initial symptom may be associated with the protective effect of TCZ, which mitigated the cytokine storm and organ damage, particularly in lung tissue.\u003c/p\u003e \u003cp\u003eOur study identified smoking and lack of vaccination as predictors of two-year mortality in the non-TCZ cohort. Emiprical data strongly associate the absence of vaccination with lung damage during and after acute COVID-19 infection [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Smoking, especially in excess (\u0026gt;\u0026thinsp;25 cigarettes per day, \u0026gt;\u0026thinsp;20 years of smoking), is closely correlated with severe forms of COVID-19 and poor outcomes [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Studies show that smoking more than 22 cigarettes daily is associated with the onset of severe COVID-19 and smokers have poorer prognosis compared to non-smokers [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHigh AST levels on hospital admission independently predicted two-year mortality in the non-TCZ cohort, suggesting that early liver lesions due to IL-6-mediated hyperinflammation may be further exacerbated when TCZ is not administered. Produced by various somatic cells including hepatocytes, IL-6 plays a crucial role in hepatic acute phase response [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Elevated AST in COVID-19 patients correlated with IL-6 levels, emphasizing the role of systemic inflammation in liver injury [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In the TCZ cohort, AST was not associated with two-year mortality, possibly due to the role of TCZ in attenuation of trans-signaling.\u003c/p\u003e \u003cp\u003eTCZ recipients demonstrated a significantly lower cumulative incidence rate of PCS (3.4% vs. 9.9%). To the best of our knowledge, studies exploring the effect of TCZ on post COVID syndrome are lacking. According to some estimates, at least 10% of individuals with a severe SARS-CoV-2 infection will develop PCS [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In a study from the United States the prevalence of PCS was 7.3% in a representative sample of 3,042 adults [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Another study from the UK found the prevalence of post-COVID of 2.9% [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Therefore, TCZ may have favorable effect on occurrence of post-COVID symptoms.\u003c/p\u003e \u003cp\u003eLower rates of PCS in the TCZ cohort may be explained by current insights into the role of IL-6 in the pathogenesis of PCS. In TCZ cohort, there was a reduction in biological activity of IL-6 during the inflammatory phase of COVID-19 infection. Recognized for its involvement in pain perception, anxiety, depression, and inflammation, IL-6 remains the key element in the onset of PCS, influencing disease severity and survival outcomes in SARS-CoV-2 immune responses [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The elevation of IL-1b, IL-6, and TNF during long-term PCS reflects the persistent reprogramming of pro-inflammatory immune cells, especially in the lung macrophages, as observed in recent studies on the monocyte/macrophage compartment in COVID-19 [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. This insight underscores the intricate interplay between cytokine dynamics and prolonged immune alterations in the period after acute COVID-19.\u003c/p\u003e \u003cp\u003eThis study has some limitations. Although we included patients from two hospitals, those treated at the university center exhibit outcome-associated factors that cannot be extrapolated to lower levels of healthcare provision. While focusing on two-year mortality and post-COVID symptoms, it lacks a detailed description on quality of life in the recovery period. Although we made effort to analyze as much data as possible, we cannot rule out unobserved confounding.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eOur study reports a cumulative two-year mortality of 20.6% among patients with severe COVID-19 who received TCZ and 24.7% cumulative mortality in patients who did not receive TCZ. TCZ recipients had a lower cumulative incidence of PCS as well (3.4% vs. 9.9%). While predictors of two-year mortality in both cohorts overlapped, there was a much wide array of mortality predictors in the non-TCZ cohort. Based on these result, it is possible that TCZ has long-term beneficial health effects on patients who were able to receive it. More studies are warranted to confirm these results. The TCZ treatment could help optimize survival during COVID-19 recovery over the first two years.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eETHICS APPROVAL STATEMENT\u003c/h2\u003e \u003cp\u003eThis research adhered to the Helsinki Declaration and received ethical approval from both the Ethics Committee of the UCC (Approval no. 837/8-2024) and the Ethics Committee of the \"Dr. Radivoj Simonovic\" General Hospital in Sombor (Approvals no. 23-2171/2023-2 and 23-2171/2023-3).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eDATA AVAILABILITY STATEMENT\u003c/h2\u003e \u003cp\u003eThe data supporting this study\u0026rsquo;s findings are available from the Clinic of Infectious and Tropical Diseases, University Clinical Centre of Serbia, Bulevar Oslobođenja 16, 11000 Belgrade, Serbia, and the General Hospital \"Dr Radivoj Simonović,\" Vojvođanska 75, 25000 Sombor, Serbia. Data can be obtained from the corresponding author upon reasonable request, subject to approval by the Ethics Committees of the aforementioned institutions.\u003c/p\u003e \u003c/div\u003e\u003cp\u003e \u003ch2\u003eDECLARATION OF COMPETING INTEREST\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFUNDING SOURCE\u003c/h2\u003e \u003cp\u003eThis study has no external funding sources; all costs were covered by the authors.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization, I.M. and T.G.; methodology, I.M, N.N., T.G. and B.B.; software, A.F., B.B., T.G., D.H., N.T., J.S. and O.S.; valida-tion, I.M., T.G., N.N. and D.H.; formal analysis, B.B., A.F., J.S. and T.G.; investigation, A.K., B.L., N.N.; resources, I.M., N.N., B.L., A.K., D.H., O.S.; data curation, B.B., A.F., J.S., O.S. and N.N.; writing\u0026mdash;original draft preparation, I.M., B.B, T.G., A.F. and N.T.; writing\u0026mdash;review and editing, B.B., T.G., and I.M. supervision, I.M.; project administration,I.M. and N.N. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMenachemi N, Dixon BE, Wools-Kaloustian KK, Yiannoutsos CT, Halverson PK. How Many SARS-CoV-2-Infected People Require Hospitalization? Using Random Sample Testing to Better Inform Preparedness Efforts. J Public Health Manag Pract. 2021 May-Jun 01;27(3):246\u0026ndash;250.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGustine JN, Jones D. Immunopathology of Hyperinflammation in COVID-19. Am J Pathol. 2021;191:4\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQue Y, Hu C, Wan K, Hu P, Wang R, Luo J, Li T, Ping R, Hu Q, Sun Y, Wu X, Tu L, Du Y, Chang C, Xu G. Cytokine release syndrome in COVID-19: a major mechanism of morbidity and mortality. Int Rev Immunol. 2022;41(2):217\u0026ndash;230.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEuropean Medicines Agency. EMA recommends approval for use of RoActemra in adults with severe COVID-19. 2021. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ema.europa.eu/en/news/ema-recommends-approval-use-roactemra-adults-severe-covid-19\u003c/span\u003e\u003cspan address=\"https://www.ema.europa.eu/en/news/ema-recommends-approval-use-roactemra-adults-severe-covid-19\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. [accessed 4 January 2024].\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFurlow, Bryant. \"COVACTA trial raises questions about tocilizumab's benefit in COVID-19.\" The Lancet Rheumatology 2.10 (2020): e592.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMariette, Xavier, et al. \"Effectiveness of tocilizumab in patients hospitalized with COVID-19: a follow-up of the CORIMUNO-TOCI-1 randomized clinical trial.\" JAMA Internal Medicine 181.9 (2021): 1241\u0026ndash;1243.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMariette X, Hermine O, Tharaux PL, et al. Effectiveness of Tocilizumab in Patients Hospitalized With COVID-19: A Follow-up of the CORIMUNO-TOCI-1 Randomized Clinical Trial. JAMA Intern Med. 2021;181(9):1241\u0026ndash;1243.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRECOVERY Collaborative Group. \"Tocilizumab in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial.\" Lancet (London, England) 397.10285 (2021): 1637.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSarabia De Ardanaz, Luis, et al. \"Tocilizumab in COVID-19: factors associated with mortality before and after treatment.\" Frontiers in Pharmacology 12 (2021): 620187.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGodolphin, Peter J., et al. \"Association between tocilizumab, sarilumab and all-cause mortality at 28 days in hospitalised patients with COVID-19: A network meta-analysis.\" PLoS One 17.7 (2022): e0270668.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorrison, Austin R., et al. \"Clinical characteristics and predictors of survival in adults with coronavirus disease 2019 receiving tocilizumab.\" Journal of autoimmunity 114 (2020): 102512.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOronsky, Bryan, et al. \"A review of persistent post-COVID syndrome (PCS).\" Clinical reviews in allergy \u0026amp; immunology 64.1 (2023): 66\u0026ndash;74\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFern\u0026aacute;ndez-de-Las-Pe\u0026ntilde;as, C\u0026eacute;sar, et al. \"Defining post-COVID symptoms (post-acute COVID, long COVID, persistent post-COVID): an integrative classification.\" International journal of environmental research and public health 18.5 (2021): 2621.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCapra R, De Rossi N, Mattioli F, Romanelli G, Scarpazza C, Sormani MP, Cossi S. Impact of low dose tocilizumab on mortality rate in patients with COVID-19 related pneumonia. Eur J Intern Med. 2020;76:31\u0026ndash;35. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ejim.2020.05.009\u003c/span\u003e\u003cspan address=\"10.1016/j.ejim.2020.05.009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2020 May 13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSomers, Emily C., et al. \"Tocilizumab for treatment of mechanically ventilated patients with COVID-19.\" Clinical Infectious Diseases 73.2 (2021): e445-e454.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBr\u0026aacute;bek, Jan, et al. \"Interleukin-6: molecule in the intersection of cancer, ageing and COVID-19.\" International journal of molecular sciences 21.21 (2020): 7937.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang, Bingjie, et al. \"Tocilizumab, an IL6-receptor antibody, proved effective as adjuvant therapy for cytokine storm induced by severe infection in patients with hematologic malignancy.\" Annals of Hematology 102.4 (2023): 961\u0026ndash;966.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eToniati, Paola, et al. \"Tocilizumab for the treatment of severe COVID-19 pneumonia with hyperinflammatory syndrome and acute respiratory failure: a single center study of 100 patients in Brescia, Italy.\" Autoimmunity reviews 19.7 (2020): 102568.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChiner-Vives, Eusebi, et al. \"Short and long-term impact of COVID-19 infection on previous respiratory diseases.\" Archivos de Bronconeumolog\u0026iacute;a 58 (2022): 39\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchulthei\u0026szlig;, Christoph, et al. \"The IL-1β, IL-6, and TNF cytokine triad is associated with post-acute sequelae of COVID-19.\" Cell Reports Medicine 3.6 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePolidoro, Rafael B., et al. \"Overview: systemic inflammatory response derived from lung injury caused by SARS-CoV-2 infection explains severe outcomes in COVID-19.\" Frontiers in immunology 11 (2020): 1626.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUmnuaypornlert, Adinat, et al. \"Smoking and risk of negative outcomes among COVID-19 patients: a systematic review and meta-analysis.\" Tobacco induced diseases 19 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMitrovic, Nikola, et al. \"Influence of chronic liver diseases on the course and outcome of COVID-19.\" Plos one 18.7 (2023): e0288350.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEffenberger, Maria, et al. \"Systemic inflammation as fuel for acute liver injury in COVID-19.\" Digestive and Liver Disease 53.2 (2021): 158\u0026ndash;165.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavis HE, McCorkell L, Vogel JM, Topol EJ. \u0026lsquo;Long COVID: major findings, mechanisms and recommendations\u0026rsquo;. Nat Rev Microbiol. 2023; 21(3):133\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRobertson MM, Qasmieh SA, Kulkarni SG, Teasdale CA, Jones HE, McNairy M, et al. The Epidemiology of Long Coronavirus Disease in US Adults. Clin Infect Dis. 2023; 76(9):1636\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAyoubkhani, Daniel, and Piotr Pawelek. \"Prevalence of ongoing symptoms following coronavirus (COVID-19) infection in the UK: 1 April 2021.\" Off Natl Stat (2021): 1\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArish, Mohd, et al. \"COVID-19 immunopathology: from acute diseases to chronic sequelae.\" Journal of medical virology 95.1 (2023): e28122.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKovarik, Johannes J., et al. \"A multi-omics based anti-inflammatory immune signature characterizes long COVID-19 syndrome.\" Iscience 26.1 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao, Y., Kilian, C., Turner, J.E., Bosurgi, L., Roedl, K., Bartsch, P., Gnirck, A.C., Cortesi, F., Schulthei\u0026szlig;, C., Hellmig, M., et al. (2021). Clonal expansion and activation of tissue-resident memory-like Th17 cells expressing GM-CSF in the lungs of severe COVID-19 patients. Sci. Immunol. 6, eabf6692\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":"Severe COVID-19, tocilizumab, two-year mortality, post-COVID syndrome","lastPublishedDoi":"10.21203/rs.3.rs-5821416/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5821416/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEvidence about long-term effects of tocilizumab (TCZ) treatment after COVID-19 is sparse. This study explored COVID-19-related outcomes over a two-year period among people who received TCZ and those who did not. Patients were recruited from two healthcare centers in Serbia, from March 2021 to December 2022. Demographic, clinical, and laboratory data were collected from hospital records. Outcomes of COVID-19 over two years of follow-up, such as post-COVID syndrome (PCS) and mortality, were retrieved from hospital records or through telephone calls. Cumulative two-year mortality in the TCZ cohort (150; 32.8% patients) was 20.6%, and in the non-TCZ cohort (307 patients; 67.2%) 24.7%. In TCZ recipients there was a lower cumulative incidence of PCS (3.4% vs. 9.9%, p\u0026thinsp;=\u0026thinsp;0.018). Predictors of two-year mortality in both cohorts included age, receiving intensive care unit treatment, having insulin-dependent diabetes, and having elevated C-reactive protein and creatinin kinase on hospital admission. In addition, chest pain on admission, being a smoker, having pre-existing respiratory diseases and cancer along with high aspartate aminotranspherase on admission were predictive of a higher two-year mortality in the non-TCZ cohort. Patients who received TCZ had lower cumulative incidence of PCS and cumulative mortality rates after two years of follow-up. This study suggests that TCZ has potential long-term health benefits for people who were hospitalized for COVID-19.\u003c/p\u003e","manuscriptTitle":"Outcomes of Severe Covid-19 Among Patients Who Did and Did Not Receive Tocilizumab: A Two-year Prospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-20 15:52:50","doi":"10.21203/rs.3.rs-5821416/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":"6ae95ad3-7c41-44ed-82c9-198c213f4415","owner":[],"postedDate":"January 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-11T11:38:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-20 15:52:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5821416","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5821416","identity":"rs-5821416","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}