Intravenous High-dose Anakinra Drops Venous Thrombosis and Myocardial Infarction in Severe and Critical COVID-19 Patients: A Propensity Score Matched Study

Intravenous High-dose Anakinra Drops Venous Thrombosis and Myocardial Infarction in Severe and Critical COVID-19 Patients: A Propensity Score Matched 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 Article Intravenous High-dose Anakinra Drops Venous Thrombosis and Myocardial Infarction in Severe and Critical COVID-19 Patients: A Propensity Score Matched Study Ramazan Çakmak, Servet Yüce, Mustafa Ay, Muhammed Hamdi Uyar, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3994466/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Introduction : In our study, we aimed to evaluate the effect of high-dose intravenous anakinra treatment on the development of thrombotic events in severe and critical COVID-19 patients. Material and methods : This retrospective observational study was conducted at a tertiary referral center in Aksaray, Turkey. The study population consisted of two groups as follows; the patients receiving high-dose intravenous anakinra (anakinra group) added to background therapy and the patients treated with standard of care (SoC) as a historical control group. Age, gender, mcHIS scores, and comorbidities such as DM, HT, and CHD of the patients were determined as the variables to be matched. Results : We included 114 patients in SoC and 139 patients in the Anakinra group in the study. Development of any thromboembolic event (5% vs 12.3%, p = 0.038; OR:4.3) and PTE (2.9% vs 9.6%, p = 0.023; OR:5.1) were lower in the Anakinra group than SoC. No patient experienced CVA and/or clinically evident DVT both in two arms. After 1:1 PS matching, 88 patients in SoC and 88 patients in the Anakinra group were matched and included in the analysis. In survival analysis, the development of any thromboembolic event, PTE, and MI were higher in SoC compared to Anakinra. Survival rate was also lower in patients with SoC arm than Anakinra in patients who had any thromboembolic event as well as MI. Conclusion : In our study, the development of thrombosis was associated with hyperinflammation in patients with severe and critical COVID-19. Intravenous high-dose anakinra treatment decreases both venous and arterial events in patients with COVID-19. Biological sciences/Immunology Biological sciences/Microbiology Health sciences/Rheumatology Anakinra COVID-19 thrombosis inflammasome hyperinflammation Figures Figure 1 Figure 2 Figure 3 Bullet points An important proportion of COVID-19 patients experienced venous and/or arterial thrombotic events despite anticoagulant prophylaxis in patients with COVID-19. In our study, the development of thrombosis was associated with hyperinflammation as well as disease severity in patients with severe and critical COVID-19. Intravenous high-dose anakinra treatment decreases both pulmonary thrombosis and myocardial infarction compared to standard of care in patients with COVID-19. Introduction Coronavirus-19 (COVID-19) is an emerging infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and affects many organs mainly upper and lower respiratory tracts. Disease severity of COVID-19 ranges from asymptomatic and/or mild symptoms to potential life-threatening disease including acute respiratory distress syndrome (ARDS), multi-organ failure, and even death. Several risk factors such as male gender, advanced age, some comorbidities including diabetes mellitus (DM), hypertension (HT) and coronary heart disease (CHD), and immunosuppressive treatment were described for the development of poor prognosis as well as severe course in COVID-19 [ 1 ]. Hyperinflammation (cytokine storm) is one of the main features of severe disease in COVID-19 and is also closely associated with poor outcomes including ARDS, the need for oxygen therapy, and higher mortality [ 2 ]. Several immunomodulatory treatments such as corticosteroids, baricitinib, anakinra, and tocilizumab were found to be effective in COVID-19 patients with signs of hyperinflammation [ 3 ] [ 4 ] [ 5 ] [ 6 ]. In addition to cytokine storm, some patients suffer from thrombotic events including myocardial infarction (MI), cerebrovascular accident (CVA), and venous thromboembolism (VTE) such as deep vein thrombosis (DVT) and pulmonary thromboembolism (PTE) during the course of COVID-19 [ 7 ]. Thereby, prophylactic use of anticoagulant and/or antiaggregant therapies were applied especially in hospitalized COVID-19 patients in daily practice [ 8 ]. However, some studies have shown that reduced mortality with prophylactic use of anticoagulant therapy reduces mortality [ 9 ] [ 10 ] and also the development of thromboembolic events [ 11 ], there are conflicting results with the benefit of anticoagulant therapy in terms of mortality and/or thrombosis [ 12 ]. Moreover, it is not known whether immunomodulatory therapy reduces thromboembolic events in patients with severe COVID-19. In our study, we aimed to evaluate the effect of high-dose intravenous anakinra treatment on the development of thrombotic events in severe and critical COVID-19 patients. Material and Methods Patients and data: This retrospective observational study, which includes secondary analysis of our previous study [ 13 ], was conducted at a tertiary referral center in Aksaray, Turkey. Diagnosis of COVID-19 was performed by typical computer tomography (CT) findings in addition to clinical signs and symptoms and confirmed with positive polymerase chain reaction (PCR). The study population consisted of two groups as follows; the patients receiving high-dose intravenous anakinra (anakinra group) added to background therapy between 01.09.2021 and 01.02.2022 and the patients treated with standard of care (SoC) as historical control group who were hospitalized between 01.07.2021 and 01.09.2021. COVID-19 disease severity was evaluated according to the National Institute of Health (NIH) severity scale and only severe and critically ill patients who followed up in the ward were included in the study [ 14 ]. The study has been performed in accordance with the Declaration of Helsinki and the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule. An informed consent was obtained for the study. Institutional Review Board approval was also obtained from the Aksaray University Ethics Committee (date/number: 24.02.2022, 2022/04–09). Laboratory evaluation Laboratory values such as hemogram, liver enzymes, troponin levels, C-reactive protein (CRP) (mg/dL), ferritin (pg/mL), d-dimer (pg/mL), lactate dehydrogenase (LDH) (U/L), procalcitonin (pg/dL) at the admission and consecutive days (procalcitonin was every other day but others were once in a day); the peak levels of CRP, ferritin, d-dimer and LDH levels were recorded. The inflammatory state of the patients was evaluated and derived based on the COVID hyperinflammatory syndrome score (cHIS) and it was calculated according to the combination of neutrophil and lymphocyte counts at the admission and the peak levels of CRP, ferritin, D-dimer, and LDH during to the follow-up [ 15 ]. The item of fever was removed due to its lower frequency (<%10) in both arms. Therefore, the maximum score of the new version of the cHIS score was 5 points (modified cHIS [mcHIS] score) was calculated in both groups [ 13 ]. Treatment protocol and outcome All patients received background corticosteroid therapy with 80 mg/day methylprednisolone (or its equivalent) and enoxaparin 0.4 mg/day at the admission and continued consecutive days (SoC). Anakinra was added to the background treatment in patients who did not respond to initial treatment for at least two days or concomitantly with steroids in patients with higher risk and/or critical illness at admission and continued until discharge or death. The average starting dose of anakinra was 400 mg/day intravenously and increased gradually to a maximum of 1600 mg/day if necessary (10 mg/kg/day). Anakinra dose adjustment was performed by the same experienced physician in COVID-19 (MB) according to daily clinical (respiratory symptoms, degree of oxygen supply, presence of fever) and laboratory findings. Diagnosis of PTE was confirmed by thorax CT-angiography in patients with prominent d-dimer increase despite a decrease in acute phase reactants (APR) such as CRP and ferritin and/or increase in need of oxygen therapy and respiratory distress despite the decrease in levels of APRs. Diagnosis of MI was made according to the Thygesen et al. study [ 16 ]. Severe infection was defined as the development of opportunistic infection, need for intravenous antibiotics, sepsis, or requirement of intensive care unit (ICU) admission or development of death due to secondary infection. Statistical analysis In our study, the 22.0 version (IBM, Armonk, NY, USA) of the SPSS (Statistical Package for the Social Sciences) program was used for statistical analysis of data. In descriptive statistics, discrete​ ​and continuous numerical variables were expressed as mean, ± standard deviation, or median (minimum-maximum). Categorical variables were expressed as number of cases (%). Cross-table statistics were used to compare categorical variables (Chi-Square, Fisher’s exact test). Normally distributed parametric data were compared with Student's t-test and non-parametric data that did not meet normal distribution were compared with Mann Whitney U and Kruskal Wallis tests. Correlation analysis was performed by Pearson or Spearman method according to normality distribution. ​Kaplan-Meier and log-rank methods were used for survival analysis. Multivariate analysis was performed by using logistic regression. Sensitivity and specificity calculations were performed by Receiver operating characteristic (ROC) analysis. p < 0.05 value was considered statistically significant. Propensity score matching The first step in Propensity Score Matching (PSM) is to identify the covariates from which to calculate propensity scores (PS). Age, gender, mcHIS scores, and comorbidities such as DM, HT, and CHD of the patients were determined as the variables to be matched. The PS matching was done as 1:1 with the nearest neighbor method. The caliper value was 0.2. When matching, we performed this analysis by assigning values ​​according to the averages of the parameters with missing data. PSM was performed with the SPSS package program 28.0.1 using the R package program and an auxiliary plugin (PS matching 3.0 SPE). Dot-plot of standardized mean differences for all covariates before and after PS matching was shown in supplementary Fig. 1. Jitter plots for trend scores and line plots of standardized differences were described in supplemental Figs. 2 and 3, respectively. Results Analysis Before PS Matching We included 114 patients in SoC and 139 patients in the Anakinra group in the study. The baseline clinical and laboratory features of the patients are described in Table 1. Frequency of male gender (51.8% vs 39.5%, p=0.05; Odds ratio [OR]: 3.8), chronic renal failure (CRF) (20% vs 5.3%, p=0.001; OR: 11.9), critical illness (61.2% vs 40.4%, p=0.001, OR:10.9) were higher in Anakinra group than SoC. Additionally, median (IQR) duration of hospitalization (11 [12] vs 9 [7.3] days; p=0.03), mcHIS scores (p<0.001), baseline NLR (p=0.002) and d-dimer levels (p=0.04), peak levels of CRP (p=0.012), ferritin (p<0.001), d-dimer (p=0.002), LDH (p<0.001) levels were higher in Anakinra receiving patients than SoC. Development of any thromboembolic event (5% vs 12.3%, p=0.038; OR:4.3) and PTE (2.9% vs 9.6%, p=0.023; OR:5.1) were lower in the Anakinra group than SoC. No patient experienced CVA and/or clinically evident DVT both in two arms. Although severe infection, pneumothorax, and MI were not different between the two arms (p=0.1, p=0.1, and p=0.2, respectively); ICU admission (39.6% vs 22%, p=0.003; OR:9) and mortality (36.7% vs 27%, p=0.026; OR:) were higher in Anakinra group compared to SoC before PS matching analysis (table 1). Patients experienced any thromboembolic event had longer duration of hospitalization (p=0.03), higher vaccination counts (p=0.028), more frequent CHD (p=0.001; OR:11.8), critical disease (p=0.001; OR:10.6), higher mcHIS scores (p<0.001), lower NLR (p=0.002) and higher baseline d-dimer levels (p=0.04), higher peak levels of CRP (p=0.012), ferritin (p<0.001), d-dimer (p=0.002), and LDH (p<0.001). Development of thrombosis was also higher in patients who had mortality (62% vs 28%, p=0.001; OR:10.4) in univariate analysis (table 2). Patients developed PTE had longer duration of hospitalization (p=0.03), higher vaccination counts (p=0.03), critical disease (p=0.005; OR:7.8), higher mcHIS scores (p<0.001), and higher baseline d-dimer levels (p=0.04), higher peak levels of CRP (p=0.012), ferritin (p<0.001), d-dimer (p=0.002), and LDH (p<0.001). Development of PTE was also higher in patients who had severe infection (p=0.028; OR:4.8), pneumothorax (p=0.046; OR:4), MI (p<0.001; OR:12.6), and SoC (p=0.023; OR: 5.1) in univariate analysis (table 3). In multivariate analysis, peak d-dimer levels (p<0.001, OR:1.1, 95% Confidence interval [CI]: 1.05-1.16), critical illness (p=0.044, OR:9.5, 95% CI: 1.06-85.5), and SoC (compared to Anakinra) (p=0.002, OR:11.2, 95% CI: 2.47-51.1) were associated with development of any thromboembolic event (supplementary table). Analysis After PS Matching After 1:1 PS matching, 88 patients in SoC and 88 patients in the Anakinra group were matched and included in the analysis. The baseline clinical and laboratory features of the patients are described in Table 1. After adjustment of potential confounders age, gender, presence of comorbidities (DM, HT, CHD, CRF, chronic lung disease, and malignancy), disease severity, vaccination history, and mcHIS scores were not different between the two groups (table 1). Only baseline d-dimer and peak levels of LDH were higher in the Anakinra arm compared to SoC (p=0.05 and p<0.001). Severe infection (28.4% vs 16%, p=0.05; OR:3.9), development of any thromboembolic event (15.9% vs 3.4%, p=0.005; OR:7.9), PTE (12.5% vs 3.4%, p=0.026; OR:5), MI (6.8% vs 0, p=0.013; OR:6.2) were higher in SoC arm compared to Anakinra. ICU requirement and mortality did not differ between the two arms (p=0.2 and p=0.4, respectively). Patients who experienced any thromboembolic event had more frequent CHD (p=0.04; OR:4.1), critical illness (p<0.001; OR:12.5), lower hemoglobin and baseline ferritin levels (p=0.03 and p=0.04, respectively), higher mcHIS scores (p=0.001), higher peak levels of CRP (p<0.001), d-dimer (p<0.001), LDH (p=0.038). Furthermore, severe infection (41% vs 20.3%, p=0.05; OR:3.9) and mortality (64.7% vs 27.7%, p=0.002; OR:9.8) were higher in patients who had any thromboembolic event than those had not (table 2). Similarly, PTE was higher in patients who had critical illness (p=0.002; OR:9.5), lower hemoglobin and ferritin levels (p=0.02 and p=0.04, respectively), higher mcHIS score (p=0.002), peak levels of CRP (p<0.001), d-dimer (p<0.001), pneumothorax (p=0.03; OR:4.8), MI (p<0.001; OR:15), and mortality (p=0.03; OR:4.7) (table 3). PTE development was associated with peak levels of d-dimer levels (p=0.02, OR:1.08, 95% CI: 1.01-1.15) in multivariate analysis. Development of MI was higher in patients who had history of CHD and malignancy (p=0.007; OR:7.3 and p=0.02; OR:5.5, respectively), critical illness (p=0.02; OR:5.4), higher mcHIS scores (p=0.02), peak levels of CRP (p=0.043), d-dimer (p=0.03), LDH (p=0.004) (table 4). MI was also higher in SoC (P=0.016; OR:6.2) and patients had mortality (p<0.001; OR:13.7) in univariate analysis. MI development was associated with the history of CHD (p=0.038, OR:6.9, 95% CI:1.1-42.3) and PTE (p=0.008, OR:11.5, 95% CI:1.9-69.5) in multivariate analysis. In survival analysis, development of any thromboembolic event, PTE, and MI were higher in SoC compared to Anakinra (Log-Rank; p=0.003 [figure 1], p=0.003 [supplementary figure 4], and p=0.007 [supplementary figure 5], respectively). Survival rate was also lower in patients with the SoC arm than Anakinra in patients who had any thromboembolic event as well as MI (Log-Rank; p=0.03 [figure 2] and p<0.001 [figure 3], respectively). The survival rate of patients with and without PTE did not differ in patients with COVID-19 (supplementary figure 6). ROC analysis revealed a cut-off value of d-dimer for the development of any thromboembolic event 16.75 (Area under curve [AUC]: 0.804, p<0.001 [95% CI: 0.710-0.898]) with 61.9% sensitivity and 84.8% specificity (likelihood ratio [LR]:4), for the development of PTE 14.97 (AUC: 0.867, p<0.001 [95% CI: 0.774-0.960]) with 86.7% sensitivity and 83.5% specificity (LR:5.3), for the development of MI 5.83 (AUC: 0.736, p<0.016 [95% CI: 0.585-0.887]) with 66.7% sensitivity and 66.7% specificity (LR:2) (Supplementary figure 7,8, and 9, respectively). Cut-off value of mcHIS score for the development of any thromboembolic event 3.5 (AUC: 0.726, p=0.001 [95% CI: 0.632-0.821]) with 71.4% sensitivity and 63.2% specificity (LR:1.94), for the development of PTE 3.5 (AUC: 0.740, p=0.002 [95% CI: 0.624-0.855]) with 73.3% sensitivity and 62.4% specificity (LR:1.95), for the development of MI 3.5 (AUC: 0.750, p=0.01 [95% CI: 0.630-0.870]) with 77.8% sensitivity and 61.7% specificity (LR:2) (Supplementary figure 10,11, and 12, respectively). A cut-off value of peak levels of CRP for the development of any thromboembolic event 171.2 mg/L (AUC: 0.780, p<0.001 [95% CI: 0.684-0.875]) with 76.5% sensitivity and 72.3% specificity (LR:2.8), for the development of PTE 201 mg/L (AUC: 0.800, p<0.001 [95% CI: 0.694-0.905]) with 71.4% sensitivity and 78.4% specificity (LR:3.3), for the development of MI 145.3 mg/L (AUC: 0.743, p=0.043 [95% CI: 0.629-0.857]) with 100% sensitivity and 54.7% specificity (LR:2.2) (Supplementary figure 13,14, and 15, respectively). Other results of ROC analysis are shown in Table 5 and supplementary figures 16 and 17). Discussion It is well known that higher mortality rates and poor outcomes are mainly associated with the development of cytokine storms in patients with COVID-19 [ 17 ]. Cytokine storm is a hyperinflammatory state that is seen in several conditions such as hematological malignancies, infectious diseases, and rheumatological conditions including adult-onset still disease (AOSD), and systemic lupus erythematosus [ 18 ]. Development of cytokine storm depends on the excessive production of several cytokines including interleukin-1 (IL-1), IL-6, tumor necrosis factor-alpha (TNF-α), and type 1 interferon (IFN) triggered by SARS-CoV-2 in COVID-19 [ 19 ]. Recent studies revealed the importance of pulmonary macrophages’ activation secondary to SARS-CoV-2 (23), which results in inflammasome activation in COVID-19 [ 20 ] [ 21 ]. Inflammasomes are essential in the host defense against microorganisms including viruses that are present in various innate immune cells such as neutrophils, macrophages, and dendritic cells. Activation of inflammasomes leads to the cleavage of pro-IL-1β to produce active IL-1β [ 22 ], and is responsible for the development of various immune-mediated diseases such as Familial Mediterranean Fever (FMF), gout, and AOSD [ 23 ]. Furthermore, the safety and efficacy of IL-1 blockade in these diseases were established in these conditions [ 24 ]. Anakinra is an IL-1 receptor antagonist which is widely used in several rheumatological diseases such as FMF, AOSD, and gout [ 25 ] [ 26 ] [ 27 ] and also several hyperinflammatory conditions such as cancer-related hemophagocytic syndrome, chimeric antigen receptor-modified (CAR) T cell-associated cytokine storm, and macrophage activation syndrome [ 28 ] [ 29 ] [ 30 ]. Safety and efficacy of Anakinra was also established in COVID-19-associated cytokine storm [ 3 ]. Intravenous and high-dose anakinra is an emerging therapeutic option both in rheumatology, other hyperinflammatory conditions, and COVID-19 [ 31 ] [ 32 ] [ 33 ]. Intravenous administration of anakinra ensures higher and faster maximum plasma concentration compared to the subcutaneous form [ 34 ]. Daily dose adjustment of anakinra may allow early intervention of the cytokine storm according to daily clinical status, as well as withdrawing the drug in case of infection or other complications. Additionally, intravenous high-dose anakinra treatment reduced mortality in our previous study [ 13 ]. Thromboembolic events are common in COVID-19 which is a remarkable finding from the beginning of the pandemic [ 7 ]. In the Middeldorp et al. study overall VTE frequency was 20% which was higher in patients in ICU (47%) than ward (3.3%). In the former study, ICU admission, increased d-dimer, and NLR levels were associated with the development of VTE which were similar to our results. In another observational study with 3334 patients, 16% of patients experienced a thrombotic event which 6.2% of them were VTE and 11.1% were arterial events (1.6% stroke and 8.9% MI) [ 35 ]. The former study also revealed an association between the development of thrombosis and a prior history of CHD and increased d-dimer levels which were consistent with our results. In the former study, thrombotic events were also higher in patients who had critical disease and/or deceased compared to those who had not. In a study with COVID-19-related deceased patients, although 9% of the patients had macroscopic thrombosis, most of the patients (87%) had microscopic evidence of thrombosis accompanying intense inflammation in autopsy specimens [ 36 ]. The authors also concluded a pathologic link between inflammation and thrombosis in the former study. In our study, higher mcHIS score and its components such as d-dimer and CRP levels in patients who experienced thrombosis suggest that hyperinflammation is one of the key factors for the development of thrombotic events in patients with COVID-19. Moreover, the fact that higher values of peak levels of CRP, d-dimer, LDH, and ferritin than those baseline levels emphasize the crucial role of hyperinflammation in the development of thrombotic events. This finding was also consistent with our previous results regarding the close association between peak levels of these laboratory tests and poor outcomes [ 13 ]. In our study, the lower frequency of PTE in the anakinra group was a remarkable finding even though the anakinra group had more severe disease before propensity score matching [ 37 ]. This finding persists after the PS matching procedure. As already known, endothelial dysfunction, thrombophilia, and stasis are the main contributors to the development of venous thrombosis according to Virchow’s triad. In COVID-19, endothelial dysfunction appears to be a more prominent factor in the development of thrombosis [ 38 ]. In our study, none of the patients with PTE had clinically evident DVT which suggests COVID-19-related pulmonary thrombosis is an in-situ thrombosis rather than embolism which was claimed by Gabrielli et. al. study [ 39 ]. In our study, all patients received background anticoagulant prophylaxis in two arms but could not prevent thrombotic events. This situation is recently called ‘inflammothrombosis’ which is similar to Behçet’s disease (BD) associated venous thrombosis. While DVT and PT (in situ thrombosis, not embolism) may develop in BD separately, DVT is not expected to cause embolism due to its inflammatory nature (firmly attached to the vascular wall). Therefore, the definition of pulmonary thrombosis may be more accurate than pulmonary embolism in patients with COVID-19 similar to BD. Furthermore, while anticoagulant therapy does not prevent vascular thrombosis in BD patients, anti-inflammatory treatment improves vascular outcomes such as recanalization and prevention of relapses [ 40 ]. In light of these data, pulmonary thrombosis in COVID-19 may be mainly associated with pulmonary inflammatory environment rather than stasis or other components of Virchow’s triad and develops in situ thrombosis rather than embolism. Therefore, anti-inflammatory treatment may reduce thrombosis risk beyond the anticoagulant treatment in patients with severe COVID-19 which was shown in our study. However, it should be kept in mind that limited data is showing the efficacy of anti-inflammatory therapy as an anticoagulant effect in patients with COVID-19. Inflammation is an important contributor to the development of cardiovascular disease including acute coronary syndromes (ACS). During the pandemic arterial thrombotic events such as CVA and MI were increased in patients with COVID-19 [ 41 ] [ 42 ]. The NLRP3 (NOD [nucleotide oligomerization domain]-, LRR [leucine-rich repeat]-, and PYD [pyrin domain]-containing protein 3) [NLRP3] inflammasome, an innate immune signaling complex, is the key mediator of IL-1 family cytokine production. Recent evidence has shown that NLRP3 inflammasome activation has a crucial role in leading higher IL-1 production for the development of ACS [ 43 ]. Furthermore, colchicine, an inflammasome inhibitor was found to be effective for the prevention of MI in patients before ACS history [ 44 ]. Similarly, canakinumab is an IL-1β monoclonal antibody that decreases composite cardiovascular events including MI, stroke, coronary revascularization, and cardiovascular death in the CANTOS study [ 45 ]. In our study, the decreased incidence of MI with Anakinra was consistent with previous studies. Additionally, higher mcHIS scores in patients who had MI compared with had not emphasized the crucial role of hyperinflammation in the development of arterial events. This study has some strengths and limitations. The retrospective design of the study was the main limitation although the controlled design of the study adjusting potential confounders by PS matching was important to prevent bias. We could not perform Doppler USG screening in patients who had PTE since it did not cause a change in treatment and critical situation of the patients. Diagnosis of MI could not be confirmed with cardiac catheterization. Having missing data is also a limitation of the study. On the other hand, the fact that the study is conducted in a single center enables homogeneity in terms of patient population and treatment decisions that are made by a single physician. Conclusions Thromboembolic events were seen despite the anticoagulant prophylaxis in our study. Development of thrombosis was associated with hyperinflammation in patients with severe and critical COVID-19. Intravenous high-dose anakinra treatment decreases both venous and arterial events in patients with COVID-19. Declarations Funding: No specific funding was received from any bodies in the public, commercial, or not-for-profit sectors to carry out the work described in this article. Conflicts of Interest: The authors declare no conflicts of interest. Availability of data and material: The Dataset of the study is available from the corresponding author upon reasonable request. Code availability: Not applicable. Author contributions: MB and RÇ designed and planned the study, RÇ, SY, MA, MHU, and MİK collected the data, SY and MB carried out the data evaluation and basic analyses, all authors contributed to the follow-up of the patients and interpretation of results. RÇ and MB wrote the first draft, and all authors provided critical feedback for the last version. Ethics approval : Individual informed written patient consent and Institutional Review Board approval was obtained from Aksaray University Ethics Committee (date/number: 24.02.2022, 2022/04-09). Acknowledgments: Many thanks to Prof. Ahmet Gül for shedding light of our way. References Verity R, Okell LC, Dorigatti I, Winskill P, Whittaker C, Imai N, Cuomo-Dannenburg G, Thompson H, Walker PGT, Fu H, et al: Estimates of the severity of coronavirus disease 2019: a model-based analysis. Lancet Infect Dis 2020, 20:669–677. Tufan A, Avanoğlu Güler A, Matucci-Cerinic M: COVID-19, immune system response, hyperinflammation and repurposing antirheumatic drugs. Turk J Med Sci 2020, 50:620–632. Kyriazopoulou E, Poulakou G, Milionis H, Metallidis S, Adamis G, Tsiakos K, Fragkou A, Rapti A, Damoulari C, Fantoni M, et al: Early treatment of COVID-19 with anakinra guided by soluble urokinase plasminogen receptor plasma levels: a double-blind, randomized controlled phase 3 trial. Nat Med 2021, 27:1752–1760. Marconi VC, Ramanan AV, de Bono S, Kartman CE, Krishnan V, Liao R, Piruzeli MLB, Goldman JD, Alatorre-Alexander J, de Cassia Pellegrini R, et al: Efficacy and safety of baricitinib for the treatment of hospitalised adults with COVID-19 (COV-BARRIER): a randomised, double-blind, parallel-group, placebo-controlled phase 3 trial. Lancet Respir Med 2021, 9:1407–1418. Horby P, Lim WS, Emberson JR, Mafham M, Bell JL, Linsell L, Staplin N, Brightling C, Ustianowski A, Elmahi E, et al: Dexamethasone in Hospitalized Patients with Covid-19. N Engl J Med 2021, 384:693–704. Tocilizumab in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial. Lancet 2021, 397:1637–1645. Asakura H, Ogawa H: COVID-19-associated coagulopathy and disseminated intravascular coagulation. Int J Hematol 2021, 113:45–57. Middeldorp S, Coppens M, van Haaps TF, Foppen M, Vlaar AP, Müller MCA, Bouman CCS, Beenen LFM, Kootte RS, Heijmans J, et al: Incidence of venous thromboembolism in hospitalized patients with COVID-19. J Thromb Haemost 2020, 18:1995–2002. Tang N, Bai H, Chen X, Gong J, Li D, Sun Z: Anticoagulant treatment is associated with decreased mortality in severe coronavirus disease 2019 patients with coagulopathy. J Thromb Haemost 2020, 18:1094–1099. Albani F, Sepe L, Fusina F, Prezioso C, Baronio M, Caminiti F, Di Maio A, Faggian B, Franceschetti ME, Massari M, et al: Thromboprophylaxis with enoxaparin is associated with a lower death rate in patients hospitalized with SARS-CoV-2 infection. A cohort study. EClinicalMedicine 2020, 27:100562. Lachant DJ, Lachant NA, Kouides P, Rappaport S, Prasad P, White RJ: Chronic therapeutic anticoagulation is associated with decreased thrombotic complications in SARS-CoV-2 infection. J Thromb Haemost 2020, 18:2640–2645. Sadeghipour P, Talasaz AH, Rashidi F, Sharif-Kashani B, Beigmohammadi MT, Farrokhpour M, Sezavar SH, Payandemehr P, Dabbagh A, Moghadam KG, et al: Effect of Intermediate-Dose vs Standard-Dose Prophylactic Anticoagulation on Thrombotic Events, Extracorporeal Membrane Oxygenation Treatment, or Mortality Among Patients With COVID-19 Admitted to the Intensive Care Unit: The INSPIRATION Randomized Clinical Trial. Jama 2021, 325:1620–1630. Bektaş M, Yüce S, Ay M, Uyar MH, Önder ME, Kılıç M: High-dose intravenous anakinra treatment is safe and effective in severe and critical COVID-19 patients: a propensity score-matched study in a single center. Inflammopharmacology 2023, 31:787–797. COVID-19 Treatment Guidelines Panel. Coronavirus Disease 2019 (COVID-19) Treatment Guidelines. [ https://www.covid19treatmentguidelines.nih.gov/ . ] Webb BJ, Peltan ID, Jensen P, Hoda D, Hunter B, Silver A, Starr N, Buckel W, Grisel N, Hummel E, et al: Clinical criteria for COVID-19-associated hyperinflammatory syndrome: a cohort study. Lancet Rheumatol 2020, 2:e754-e763. Thygesen K, Alpert JS, Jaffe AS, Chaitman BR, Bax JJ, Morrow DA, White HD: Fourth Universal Definition of Myocardial Infarction (2018). J Am Coll Cardiol 2018, 72:2231–2264. Gustine JN, Jones D: Immunopathology of Hyperinflammation in COVID-19. Am J Pathol 2021, 191:4–17. Jarczak D, Nierhaus A: Cytokine Storm-Definition, Causes, and Implications. Int J Mol Sci 2022, 23. Chen G, Wu D, Guo W, Cao Y, Huang D, Wang H, Wang T, Zhang X, Chen H, Yu H, et al: Clinical and immunological features of severe and moderate coronavirus disease 2019. J Clin Invest 2020, 130:2620–2629. Junqueira C, Crespo Â, Ranjbar S, de Lacerda LB, Lewandrowski M, Ingber J, Parry B, Ravid S, Clark S, Schrimpf MR, et al: FcγR-mediated SARS-CoV-2 infection of monocytes activates inflammation. Nature 2022, 606:576–584. Sefik E, Qu R, Junqueira C, Kaffe E, Mirza H, Zhao J, Brewer JR, Han A, Steach HR, Israelow B, et al: Inflammasome activation in infected macrophages drives COVID-19 pathology. Nature 2022, 606:585–593. Vora SM, Lieberman J, Wu H: Inflammasome activation at the crux of severe COVID-19. Nat Rev Immunol 2021, 21:694–703. Gabay C, Lamacchia C, Palmer G: IL-1 pathways in inflammation and human diseases. Nat Rev Rheumatol 2010, 6:232–241. Dinarello CA: Interleukin-1 in the pathogenesis and treatment of inflammatory diseases. Blood 2011, 117:3720–3732. Marko L, Shemer A, Lidar M, Grossman C, Druyan A, Livneh A, Kivity S: Anakinra for colchicine refractory familial Mediterranean fever: a cohort of 44 patients. Rheumatology (Oxford) 2021, 60:2878–2883. Giacomelli R, Sota J, Ruscitti P, Campochiaro C, Colafrancesco S, Dagna L, Iacono D, Iannone F, Lopalco G, Sfriso P, Cantarini L: The treatment of adult-onset Still's disease with anakinra, a recombinant human IL-1 receptor antagonist: a systematic review of literature. Clin Exp Rheumatol 2021, 39:187–195. Saag KG, Khanna PP, Keenan RT, Ohlman S, Osterling Koskinen L, Sparve E, Åkerblad AC, Wikén M, So A, Pillinger MH, Terkeltaub R: A Randomized, Phase II Study Evaluating the Efficacy and Safety of Anakinra in the Treatment of Gout Flares. Arthritis Rheumatol 2021, 73:1533–1542. Bami S, Vagrecha A, Soberman D, Badawi M, Cannone D, Lipton JM, Cron RQ, Levy CF: The use of anakinra in the treatment of secondary hemophagocytic lymphohistiocytosis. Pediatr Blood Cancer 2020, 67:e28581. Strati P, Ahmed S, Kebriaei P, Nastoupil LJ, Claussen CM, Watson G, Horowitz SB, Brown ART, Do B, Rodriguez MA, et al: Clinical efficacy of anakinra to mitigate CAR T-cell therapy-associated toxicity in large B-cell lymphoma. Blood Adv 2020, 4:3123–3127. Grom AA, Horne A, De Benedetti F: Macrophage activation syndrome in the era of biologic therapy. Nat Rev Rheumatol 2016, 12:259–268. Nigrovic PA, Mannion M, Prince FH, Zeft A, Rabinovich CE, van Rossum MA, Cortis E, Pardeo M, Miettunen PM, Janow G, et al: Anakinra as first-line disease-modifying therapy in systemic juvenile idiopathic arthritis: report of forty-six patients from an international multicenter series. Arthritis Rheum 2011, 63:545–555. Mehta P, Cron RQ, Hartwell J, Manson JJ, Tattersall RS: Silencing the cytokine storm: the use of intravenous anakinra in haemophagocytic lymphohistiocytosis or macrophage activation syndrome. Lancet Rheumatol 2020, 2:e358-e367. Phadke O, Rouster-Stevens K, Giannopoulos H, Chandrakasan S, Prahalad S: Intravenous administration of anakinra in children with macrophage activation syndrome. Pediatr Rheumatol Online J 2021, 19:98. Saunders BN, Kuijpers MV, Sloan JJ, Gertner E: Continuous IV infusion of anakinra. Front Pharmacol 2023, 14:1162742. Bilaloglu S, Aphinyanaphongs Y, Jones S, Iturrate E, Hochman J, Berger JS: Thrombosis in Hospitalized Patients With COVID-19 in a New York City Health System. Jama 2020, 324:799–801. Khismatullin RR, Ponomareva AA, Nagaswami C, Ivaeva RA, Montone KT, Weisel JW, Litvinov RI: Pathology of lung-specific thrombosis and inflammation in COVID-19. J Thromb Haemost 2021, 19:3062–3072. Bektaş M, Yüce S, Ay M, Uyar MH, Önder ME, Kılıç M: High-dose intravenous anakinra treatment is safe and effective in severe and critical COVID-19 patients: a propensity score-matched study in a single center. Inflammopharmacology 2023:1–11. Ahmed S, Zimba O, Gasparyan AY: Thrombosis in Coronavirus disease 2019 (COVID-19) through the prism of Virchow's triad. Clin Rheumatol 2020, 39:2529–2543. Gabrielli M, Lamendola P, Esperide A, Valletta F, Franceschi F: COVID-19 and thrombotic complications: Pulmonary thrombosis rather than embolism? Thromb Res 2020, 193:98. Bettiol A, Alibaz-Oner F, Direskeneli H, Hatemi G, Saadoun D, Seyahi E, Prisco D, Emmi G: Vascular Behçet syndrome: from pathogenesis to treatment. Nat Rev Rheumatol 2023, 19:111–126. Stein LK, Mayman NA, Dhamoon MS, Fifi JT: The emerging association between COVID-19 and acute stroke. Trends Neurosci 2021, 44:527–537. Knight R, Walker V, Ip S, Cooper JA, Bolton T, Keene S, Denholm R, Akbari A, Abbasizanjani H, Torabi F, et al: Association of COVID-19 With Major Arterial and Venous Thrombotic Diseases: A Population-Wide Cohort Study of 48 Million Adults in England and Wales. Circulation 2022, 146:892–906. Afrasyab A, Qu P, Zhao Y, Peng K, Wang H, Lou D, Niu N, Yuan D: Correlation of NLRP3 with severity and prognosis of coronary atherosclerosis in acute coronary syndrome patients. Heart Vessels 2016, 31:1218–1229. Tardif JC, Kouz S, Waters DD, Bertrand OF, Diaz R, Maggioni AP, Pinto FJ, Ibrahim R, Gamra H, Kiwan GS, et al: Efficacy and Safety of Low-Dose Colchicine after Myocardial Infarction. N Engl J Med 2019, 381:2497–2505. Everett BM, MacFadyen JG, Thuren T, Libby P, Glynn RJ, Ridker PM: Inhibition of Interleukin-1β and Reduction in Atherothrombotic Cardiovascular Events in the CANTOS Trial. J Am Coll Cardiol 2020, 76:1660–1670. Tables Table 1 : Baseline clinical and laboratory features and outcomes of the patients before and after Propensity-score (PS) Matching Before PS Matching After PS Matching Variables Anakinra (n=139) SoC (n=114) p value (OR) Anakinra (n=88) SoC (n=88) p value (OR) Age, years, median (IQR) 71 (25) 65.5 (23) 0.09 70 (29) 66.5 (24) 0.6 Gender, male, n (%) 72 (51.8) 45 (39.5) 0.05 (3.8) 40 (45.5) 41 (46.6) 0.9 Duration of hospitalization (days), median (IQR) 11 (12) 9 (7.3) 0.03 10 (13) 10 (9) 0.8 Comorbidities, n (%) Diabetes mellitus 36/137 (26.3) 39 (34.2) 0.17 27 (30.7) 29 (33) 0.7 Hypertension 79/135 (58.5) 64 (56) 0.7 49/86 (57) 53 (60.2) 0.7 Coronary heart disease 24/135 (17.8) 24 (21) 0.5 19/86 (22) 19 (21.6) 0.9 Chronic renal failure 28 (20) 6 (5.3) 0.001 (11.9) 15/75 (19.2) 22 (25) 0.4 Chronic obstructive lung disease 22/136 (16.2) 19 (16.7) 0.9 14/86 (16.3) 14 (16) 1 Malignancy 16/138 (11.6) 8 (7) 0.2 6 (6.8) 8 (9.1) 0.6 Vaccination history 44/86 (51.2) 26/63 (41.3) 0.2 31/58 (53.4) 18/48 (37.5) 0.1 Disease severity, n (%) NIH score 3 (severe) 54 (38.8) 68 (59.6) 0.001 (10.9) 36 (41) 46 (52) 0.1 NIH score 4 (Critical) 85 (61.2) 46 (40.4) 52 (59) 42 (48) Vaccination history, median (IQR) 2 (1) 2 (0) 0.9 3 (1) 2 (1.5) 0.13 mcHIS score, median (IQR) 3 (1) 3 (3) <0.001 3 (2) 3 (2) 0.5 Laboratory results Neutrophil to lymphocyte ratio, median (IQR) 6.8 (8) 4.4 (4.44) 0.002 6.9 (8.2) 4.6 (5.4) 0.06 Hemoglobin (g/L), mean±SD 13.2±2.2 13.2±2 0.6 13.3±2.3 13.2±2 0.5 Creatinine (mg/dL), median (IQR) 0.9 (0.47) 0.83 (0.52) 0.5 0.84 (0.54) 0.9 (0.68) 0.4 Prokalsitonin (pg/dL), median (IQR) 0.2 (0.46) 0.16 (0.31) 0.7 0.18 (0.43) 0.18 (0.62) 0.5 C-reactive protein (mg/L), median (IQR) 1 116 (113) 100.3 (100.3) 0.4 115 (133) 107 (107) 0.9 2 148 (120) 126 (88) 0.012 141 (152) 141.2 (90) 0.7 3 11.4 (64) 13.1 (91) 0.5 10.4 (58.8) 14.5 (101) 0.2 Ferritin (pg/mL), median (IQR) 1 393 (592) 322 (423) 0.076 334.5 (590.5) 302 (371) 0.16 2 714 (969) 378 (660) <0.001 630 (811) 495 (873) 0.12 3 392 (590) 268 (480) 0.007 379 (427) 313 (630) 0.7 D-dimer (pg/mL), median (IQR) 1 1.2 (1.1) 0.85 (1.05) 0.04 1.24 (1.14) 1 (1) 0.05 2 4.1 (12.2) 2.25 (5) 0.002 2.75 (14.8) 2.7 (6.8) 0.4 3 1.4 (4.1) 1.14 (2.14) 0.15 1.37 (3.3) 1.2 (3.6) 0.9 Lactate dehydrogenase (U/L), median (IQR) 1 404 (220) 414 (229) 0.7 398.5 (219) 399.5 (210) 0.5 2 559 (266) 408 (237) <0.001 570 (259) 425 (269) <0.001 3 357 (231) 334 (170) 0.03 366.5 (204) 345.5 (195) 0.15 Outcomes, n (%) Severe infection 19/128 (14.8) 26 (22.8) 0.1 13/82 (16) 25 (28.4) 0.05 (3.9) Pneumothorax 3/134 (2.2) 0 0.1 2/86 (2.3) 0,00 0.15 Development of any thrombotic event 7 (5) 14 (12.3) 0.038 (4.3) 3 (3.4) 14 (15.9) 0.005 (7.9) Pulmonary thromboembolism 4 (2.9) 11 (9.6) 0.023 (5.1) 3 (3.4) 11 (12.5) 0.026 (5) Myocardial infarction 3 (2.2) 6 (5.3) 0.2 0 6 (6.8) 0.013 (6.2) ICU requirement 55 (39.6) 25 (22) 0.003 (9) 33 (37.5) 24 (27.3) 0.2 Mortality 51 (36.7) 27 (23.7) 0.026 (5) 30 (34.1) 25 (28.4) 0.4 PS: Propensity score, SoC: Standard of care, OR: Odds ratio, IQR: Interquartile range, ICU: Intensive care unit, 1: Baseline levels, 2: Peak levels, 3: Last levels Table 2: Univariate analysis of the patients who had any thromboembolic event before and after Propensity-score (PS) Matching Patients with thrombosis before PSM Patients with thrombosis after PSM Variables Yes (n=21) No (n=232) p value (OR) Yes (n=17) No (n=159) p value (OR) Age, years, median (IQR) 71 (22) 68 (25) 0.09 71 (26) 69 (26) 0.5 Gender, male, n (%) 13 (62) 104(45) 0.1 10 (58.8) 71 (44.7) 0.3 Duration of hospitalization (days), median (IQR) 11 (10) 9.5 (10) 0.03 11 (10) 10 (10) 0.4 Comorbidities, n (%) Diabetes mellitus 7 (33.3) 68/230 (29.6) 0.7 5 (29.4) 51 (32) 0.8 Hypertension 13 (62) 130/228 (57) 0.7 10 (58.8) 92 (58.6) 1 Coronary heart disease 10 (47.6) 38/228 (16.7) 0.001 (11.8) 7 (41.2) 31 (19.7) 0.04 (4.1) Chronic renal failure 4 (19) 30 (13) 0.4 4 (23.5) 33 (22) 0.9 Chronic obstructive lung disease 4 (19) 37/229 (16.2) 0.7 4 (23.5) 24 (15.3) 0.4 Malignancy 3 (14.3) 21/231 (9) 0.4 3 (17.6) 11 (7) 0.12 Vaccination history 5/13 (38.5) 65/136 (48) 0.5 4/10 (40) 45/96 (47) 0.7 Disease severity, n (%) NIH score 3 (severe) 3 (14.3) 119 (51.3) 0.001 (10.6) 1 (6) 81 (61) <0.001 (12.5) NIH score 4 (Critical) 18 (85.7) 113 (48.7) 16 (94) 78 (49) Vaccination counts, median (IQR) 3 (1.5) 2 (1) 0.028 2.5 (1.75) 2 (1) 1 mcHIS score, median (IQR) 4 (2) 3 (2) <0.001 4 (2) 3 (2) 0.001 Laboratory results Neutrophil to lymphocyte ratio, median (IQR) 5.6 (10.5) 5.6 (5.8) 0.002 4 (10.8) 5.9 (6.7) 0.7 Hemoglobin (g/L), mean±SD 12.6±1.7 13.3±2.2 0.6 12.4±1.5 13.3±2.2 0.03 Creatinine (mg/dL), median (IQR) 0.94 (0.73) 0.84 (0.48) 0.5 0.94 (0.67) 0.85 (0.53) 0.7 Prokalsitonin (pg/dL), median (IQR) 0.2 (0.7) 0.2 (0.43) 0.7 0.12 (1.1) 0.2 (0.45) C-reactive protein (mg/L), median (IQR) 1 118 (123) 108 (107) 0.4 110 (106) 107 (119) 0.9 2 212.5 (121) 137.5 (95) 0.012 212.5 (113) 135 (98) <0.001 3 87.4 (144) 11.5 (64) 0.5 121 (152) 11.4 (75) 0.014 Ferritin (pg/mL), median (IQR) 1 204.5 (603) 371 (545) 0.08 172 (223) 336 (544) 0.04 2 714 (735) 546 (867) <0.001 694 (735) 532 (853) 0.4 3 551.4 (695) 331.5 (483) 0.007 551 (680) 331.5 (483) 0.044 D-dimer (pg/mL), median (IQR) 1 1.44 (2) 1.15 (1.1) 0.04 0.75 (1.95) 1.2 (1.1) 0.4 2 21 (28) 2.7 (7.3) 0.002 23.8 (25) 2.56 (6.2) <0.001 3 5.6 (32.7) 1.2 (2.3) 0.15 19.7 (32) 1.18 (1.9) <0.001 Lactate dehydrogenase (U/L), median (IQR) 1 418 (268) 409 (215) 0.7 418 (154) 398 (207) 0.8 2 655 (487) 476 (271) <0.001 663 (540) 490 (277) 0.038 3 482 (518) 348 (169) 0.03 482 (506) 351 (164) 0.012 Outcomes, n (%) Severe infection 7 (33.3) 38/221 (17.2) 0.07 7 (41) 31/153 (20.3) 0.05 (3.9) Pneumothorax 1 (4.8) 2/227 (0.9) 0.1 1 (6) 1/157 (0.6) 0.054 Treatment Anakinra 7 (5) 132 (95) 0.038 (4.3) 3 (17.6) 85 (53.5) 0.005 (7.9) SoC 14 (12.3) 100 (87.7) 14 (82.4) 74 (46.5) ICU requirement 10 (47.6) 70 (30.2) 0.1 8 (47) 49 (31) 0.17 Mortality 13 (62) 65 (28) 0.001 (10.4) 11 (64.7) 44 (27.7) 0.002 (9.8) PSM: Propensity score-matching, SoC: Standard of care, OR: Odds ratio, IQR: Interquartile range, ICU: Intensive care unit, 1: Baseline levels, 2: Peak levels, 3: Last levels Table 3 : Univariate analysis of the patients who had pulmonary thromboembolism before and after Propensity-score (PS) Matching Patients with pulmonary thromboembolism before PSM Patients with pulmonary thromboembolism after PSM Variables Yes (n=15) No (n=238) p value (OR) Yes (n=14) No (n=162) p value (OR) Age, years, median (IQR) 71 (23) 68.5 (25) 0.09 68.5 (22) 69.5 (27) 0.9 Gender, male, n (%) 8 (53.3) 109 (45.8) 0.6 8 (57) 73 (45) 0.4 Duration of hospitalization (days), median (IQR) 10 (5) 10 (10) 0.03 10.5 (5.75) 10 (10) 0.6 Comorbidities, n (%) Diabetes mellitus 3 (20) 72/236 (30.5) 0.4 3 (21.4) 53 (32.7) 0.4 Hypertension 8 (53.3) 135/234 (57.7) 0.7 8 (57) 94/160 (58.8) 0.9 Coronary heart disease 5 (33.3) 43/234 (18.4) 0.16 5 (35.7) 33/160 (20.6) 0.2 Chronic renal failure 3 (20) 31 (13) 0.4 3 (21.4) 21 (13) 0.4 Chronic obstructive lung disease 3 (20) 38/235 (16.2) 0.7 3 (21.4) 25/160 (15.6) 0.6 Malignancy 2 (13.3) 22/237 (9.3) 0.6 2 (14.3) 12 (7.4) 0.4 Vaccination history 4/10 (40) 66/139 (47.5) 0.6 4/9 (44.4) 45/97 (46.4) 0.9 Disease severity, n (%) NIH score 3 (severe) 2 (13.3) 120 (50.4) 0.005 (7.8) 1 (7) 81 (50) 0.002 (9.5) NIH score 4 (Critical) 13 (86.7) 118 (49.6) 13 (93) 81 (50) Vaccination history, median (IQR) 2.5 (1.75) 2 (1) 0.03 2.5 (1.75) 2 (1) 1 mcHIS score, median (IQR) 4 (2) 3 (2) <0.001 4.5 (2) 3 (2) 0.002 Laboratory results Neutrophil to lymphocyte ratio, median (IQR) 7.6 (12.2) 5.6 (5.7) 0.5 7.5 (12) 5.8 (6.5) 0.8 Hemoglobin (g/L), mean±SD 12.6±1.9 13.3±2.1 0.6 12.2±1.5 13.6±2.2 0.02 Creatinine (mg/dL), median (IQR) 0.94 (0.7) 0.84 (0.5) 0.5 1 (0.7) 0.85 (0.52) 0.6 Prokalsitonin (pg/dL), median (IQR) 0.13 (0.5) 0.2 (0.43) 0.7 0.1 (1.1) 0.2 (0.45) 0.7 C-reactive protein (mg/L), median (IQR) 1 110 (110) 108 (105) 0.4 114 (120) 107 (118) 0.6 2 212.5 (122) 138.6 (96) 0.012 216 (119) 136.5 (97.4) <0.001 3 87.4 (158) 11.6 (68) 0.5 91 (160) 11.6 (80.5) 0.1 Ferritin (pg/mL), median (IQR) 1 203 (413) 379 (543.5) 0.08 172.4 (223) 336 (544) 0.04 2 693.6 (739) 552 (863) <0.001 633 (800) 545.7 (853) 0.6 3 551.4 (614) 335.5 (487) 0.007 533.7 (699) 333 (486) 0.18 D-dimer (pg/mL), median (IQR) 1 1.1 (4.8) 1.17 (1.1) 0.04 0.75 (1.95) 1.2 (1.1) 0.4 2 31.8 (18.2) 2.7 (7.4) 0.002 33.4 (18.6) 2.6 (6.3) <0.001 3 22.3 (31.5) 1.2 (2.3) 0.15 27 (31) 1.2 (1.9) <0.001 Lactate dehydrogenase (U/L), median (IQR) 1 428.5 (207) 409 (219) 0.7 418 (154) 398 (207) 0.8 2 633 (426) 477 (282) <0.001 615.5 (468) 496 (282) 0.16 3 482 (495) 348 (171) 0.03 472 (517) 355 (166) 0.044 Outcomes, n (%) Severe infection 6 (40) 39/227 (17.2) 0.028 (4.8) 6 (43) 32/156 (20.5) 0.055 Pneumothorax 1 (6.7) 2/233 (0.9) 0.046 (4) 1 (7) 1/160 (0.6) 0.03 (4.8) Myocardial infarction 3 (20) 6 (2.5) <0.001 (12.6) 3 (21.4) 3 (1.9) <0.001 (15) Treatment Anakinra 4 (3) 135 (97) 0.023 (5.1) 3 (3.4) 85 (96.6) 0.026 (5) SoC 11 (9.6) 103 (90.4) 11 (12.5) 77 (87.5) ICU requirement 5 (33.3) 75 (31.5) 0.9 5 (35.7) 52 (32) 0.8 Mortality 8 (53.3) 70 (29.4) 0.052 8 (57) 47 (29) 0.03 (4.7) PSM: Propensity score-matching, SoC: Standard of care, OR: Odds ratio, IQR: Interquartile range, ICU: Intensive care unit, 1: Baseline levels, 2: Peak levels, 3: Last levels Table 4: Univariate analysis of the patients who had myocardial infarction after Propensity-score (PS) Matching Patients with MI after PSM Variables Yes (n=6) No (n=170) p value (OR) Age, years, median (IQR) 77.5 (33) 69 (26) 0.1 Gender, male, n (%) 5 (83.3) 76 (44.7) 0.06 Duration of hospitalization (days), median (IQR) 9 (14.5) 10 (9.3) 0.9 Comorbidities, n (%) Diabetes mellitus 2 (33.3) 54 (31.8) 0.9 Hypertension 3 (50) 99/168 (59) 0.7 Coronary heart disease 4 (66.7) 34/168 (20.2) 0.007 (7.3) Chronic renal failure 1 (16.7) 23 (13.5) 0.8 Chronic obstructive lung disease 2 (33.3) 26/168 (15.5) 0.2 Malignancy 2 (33.3) 12 (7) 0.02 (5.5) Vaccination history 1/4 (25) 48/102 (47) 0.4 Disease severity, n (%) NIH score 3 (severe) 0 82 (48.2) 0.02 (5.4) NIH score 4 (Critical) 6 (100) 88 (51.8) Vaccination history, median (IQR) 2 (1) 0.5 mcHIS score, median (IQR) 4.5 (1.25) 3 (2) 0.02 Laboratory results Neutrophil to lymphocyte ratio, median (IQR) 4 (6) 5.9 (6.8) 0.6 Hemoglobin (g/L), mean±SD 12.8±1.3 13.3±2.2 0.5 Creatinine (mg/dL), median (IQR) 1 (0.66) 0.87 (0.54) 0.5 Prokalsitonin (pg/dL), median (IQR) NA 0.18 (0.44) NA C-reactive protein (mg/L), median (IQR) 1 129 (164) 107 (117) 0.6 2 144.8 (74) 138.6 (110) 0.043 3 207.6 (80) 11.5 (80) 0.003 Ferritin (pg/mL), median (IQR) 1 NA 331 (545) NA 2 1001 (761) 542 (848) 0.096 3 1001 (687) 333 (483) 0.009 D-dimer (pg/mL), median (IQR) 1 NA 1.2 (1.1) NA 2 27.3 (32.1) 2.7 (8.6) 0.03 3 27.3 (33) 1.2 (2.8) 0.005 Lactate dehydrogenase (U/L), median (IQR) 1 390 (97) 399 (206) 0.8 2 998 (759) 488 (278) 0.004 3 582.5 (684) 355 (172) 0.016 Outcomes, n (%) Severe infection 3 (50) 35/164 (21.3) 0.1 Pneumothorax 0 2/168 (1.2) 0.8 Treatment Anakinra 0 88 (100) 0.013 (6.2) SoC 6 (6.8) 82 (93.2) ICU requirement 4 (66.7) 53 (31.2) 0.07 Mortality 6 (100) 49 (28.8) <0.001 (13.7) PSM: Propensity score-matching, SoC: Standard of care, OR: Odds ratio, IQR: Interquartile range, ICU: Intensive care unit, 1: Baseline levels, 2: Peak levels, 3: Last levels Table 5 : ROC analysis of laboratory features of the patients for development of thromboembolic events in patients with COVID-19 Variables Cut-off value Area under curve p value (95% CI) Sensitivity Specificity Likelihood ratio mcHIS score Any thrombosis 3.5 0.726 0.001 (0.632-0.821) 71.4 63.2 1.94 PTE 3.5 0.740 0.002 (0.624-0.855) 73.3 62.4 1.95 MI 3.5 0.750 0.01 (0.630-0.870) 77.8 61.7 2 D-dimer (pg/mL)* Any thrombosis 16.75 0.804 <0.001 (0.710-0.898) 61.9 84.8 4 PTE 14.97 0.867 <0.001 (0.774-0.960) 86.7 83.5 5.3 MI 5.83 0.736 0.016 (0.585-0.887) 66.7 66.7 2 C-reactive protein (mg/L)* Any thrombosis 171.2 0.780 <0.001 (0.684-0.875) 76.5 72.3 2.8 PTE 201 0.800 <0.001 (0.694-0.905) 71.4 78.4 3.3 MI 145.3 0.743 0.043 (0.629-0.857) 100 54.7 2.2 Lactate dehydrogenase (U/L)* Any thrombosis 496 0.676 0.008 (0.551-0.801) 66.7 53.4 1.4 PTE NS NS NS NS NS NS MI 649.5 0.802 0.002 (0.675-0.928) 77.8 75.5 3.2 Ferritin (pg/mL)* Any thrombosis NS NS NS NS NS NS PTE NS NS NS NS NS NS MI NS NS NS NS NS NS Neutrophil-lymphocyte ratio Any thrombosis NS NS NS NS NS NS PTE NS NS NS NS NS NS MI NS NS NS NS NS NS *Peak levels of value, PTE: Pulmonary thromboembolism, MI: Myocardial infarction, CI: Confidence interval Additional Declarations No competing interests reported. Supplementary Files supplementarydataanakinrathrombosis.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 08 Apr, 2024 Reviews received at journal 08 Mar, 2024 Reviewers agreed at journal 07 Mar, 2024 Reviewers invited by journal 07 Mar, 2024 Editor assigned by journal 07 Mar, 2024 Editor invited by journal 07 Mar, 2024 Submission checks completed at journal 07 Mar, 2024 First submitted to journal 27 Feb, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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-3994466","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":277839317,"identity":"924a0a82-3869-4c89-8484-bf8fe79bac1b","order_by":0,"name":"Ramazan Çakmak","email":"","orcid":"","institution":"Istinye University","correspondingAuthor":false,"prefix":"","firstName":"Ramazan","middleName":"","lastName":"Çakmak","suffix":""},{"id":277839318,"identity":"01b256de-f07d-4e0f-bb43-4fe40bde6924","order_by":1,"name":"Servet Yüce","email":"","orcid":"","institution":"Aksaray University, Aksaray Training and Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Servet","middleName":"","lastName":"Yüce","suffix":""},{"id":277839319,"identity":"5a17a6e0-b272-4358-a191-37aabbd6ecad","order_by":2,"name":"Mustafa Ay","email":"","orcid":"","institution":"Aksaray University, Aksaray Training and Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mustafa","middleName":"","lastName":"Ay","suffix":""},{"id":277839320,"identity":"da862efc-f0e5-4f18-a617-d80041ed512b","order_by":3,"name":"Muhammed Hamdi Uyar","email":"","orcid":"","institution":"Aksaray University, Aksaray Training and Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Muhammed","middleName":"Hamdi","lastName":"Uyar","suffix":""},{"id":277839321,"identity":"775b9c66-ae55-420d-8f03-9f9a81ca4a0d","order_by":4,"name":"Muhammed İkbal Kılıç","email":"","orcid":"","institution":"Aksaray University, Aksaray Training and Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Muhammed","middleName":"İkbal","lastName":"Kılıç","suffix":""},{"id":277839322,"identity":"eefdf938-6740-4559-9006-36bb13d8d5b5","order_by":5,"name":"Murat Bektaş","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1klEQVRIiWNgGAWjYPCCA3L87D1gFg8fcRoYDhhL9pwBMRh42IjVkrjhRg5YCwNBLbozch9+/sBwx1hy5tuDjz/m2MmwMTA/fHQDjxazG+nGEgcYnsnxS+clGxzclgx0GJuxcQ5eLWkMQC2HjSVn55hJHNzGDNTCwyZNQAvzD6CWxA03z4C01BOlhU0CrOUGD0jLYSK0nHnGZnHG4BkwkHOMDc5uO87DxkzIL8fTmG9UVNwBRuUZwweV26rt+dmbHz7GpwUCDJA5zASVj4JRMApGwSggBAA510rRjMg+ywAAAABJRU5ErkJggg==","orcid":"","institution":"Istanbul Aydın University","correspondingAuthor":true,"prefix":"","firstName":"Murat","middleName":"","lastName":"Bektaş","suffix":""}],"badges":[],"createdAt":"2024-02-27 17:10:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3994466/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3994466/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52451119,"identity":"e498dcec-ef20-4f9d-8e9b-9583705a1d6c","added_by":"auto","created_at":"2024-03-11 19:11:40","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":212016,"visible":true,"origin":"","legend":"\u003cp\u003eDevelopment of any thromboembolic event in patients with COVID-19 according to the treatment groups (Kaplan-Meier survival analysis)\u003c/p\u003e\n\u003cp\u003eLog-Rank; p=0.003\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3994466/v1/7039d1477b659837232f44fd.jpeg"},{"id":52451121,"identity":"1c1e2c9d-fb01-40d9-ae54-9356521c6c1b","added_by":"auto","created_at":"2024-03-11 19:11:40","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":197979,"visible":true,"origin":"","legend":"\u003cp\u003eThe survival rate of patients with COVID-19 according to the presence of any thromboembolic event (Kaplan-Meier survival analysis)\u003c/p\u003e\n\u003cp\u003eLog-Rank; p=0.03\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3994466/v1/9c7345cc7cdb9e14512c50e2.jpeg"},{"id":52451151,"identity":"ba6a2a34-d814-41af-a1a5-419c8dab3761","added_by":"auto","created_at":"2024-03-11 19:11:40","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":195043,"visible":true,"origin":"","legend":"\u003cp\u003eThe survival rate of patients with COVID-19 according to the presence of myocardial infarction (Kaplan-Meier survival analysis)\u003c/p\u003e\n\u003cp\u003eLog-Rank; p\u0026lt;0.001\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3994466/v1/a0f87bd76d5b442d84c1a009.jpeg"},{"id":52451189,"identity":"8e0b3d3a-1535-4b5e-86c6-1997350cb14a","added_by":"auto","created_at":"2024-03-11 19:11:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1547763,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3994466/v1/6a52ac28-44ce-45e0-9000-71ee9346ce28.pdf"},{"id":52451153,"identity":"f2e69980-fb86-4c76-8ca9-3ef8bd6e2e79","added_by":"auto","created_at":"2024-03-11 19:11:40","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":396126,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarydataanakinrathrombosis.docx","url":"https://assets-eu.researchsquare.com/files/rs-3994466/v1/3e19f9f9fa938fefad52f562.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Intravenous High-dose Anakinra Drops Venous Thrombosis and Myocardial Infarction in Severe and Critical COVID-19 Patients: A Propensity Score Matched Study","fulltext":[{"header":"Bullet points","content":"\u003col\u003e\n \u003cli\u003eAn important proportion of COVID-19 patients experienced venous and/or arterial thrombotic events despite anticoagulant prophylaxis in patients with COVID-19.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eIn our study, the development of thrombosis was associated with hyperinflammation as well as disease severity in patients with severe and critical COVID-19.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eIntravenous high-dose anakinra treatment decreases both pulmonary thrombosis and myocardial infarction compared to standard of care in patients with COVID-19.\u0026nbsp;\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Introduction","content":"\u003cp\u003eCoronavirus-19 (COVID-19) is an emerging infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and affects many organs mainly upper and lower respiratory tracts. Disease severity of COVID-19 ranges from asymptomatic and/or mild symptoms to potential life-threatening disease including acute respiratory distress syndrome (ARDS), multi-organ failure, and even death. Several risk factors such as male gender, advanced age, some comorbidities including diabetes mellitus (DM), hypertension (HT) and coronary heart disease (CHD), and immunosuppressive treatment were described for the development of poor prognosis as well as severe course in COVID-19 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHyperinflammation (cytokine storm) is one of the main features of severe disease in COVID-19 and is also closely associated with poor outcomes including ARDS, the need for oxygen therapy, and higher mortality [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Several immunomodulatory treatments such as corticosteroids, baricitinib, anakinra, and tocilizumab were found to be effective in COVID-19 patients with signs of hyperinflammation [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition to cytokine storm, some patients suffer from thrombotic events including myocardial infarction (MI), cerebrovascular accident (CVA), and venous thromboembolism (VTE) such as deep vein thrombosis (DVT) and pulmonary thromboembolism (PTE) during the course of COVID-19 [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Thereby, prophylactic use of anticoagulant and/or antiaggregant therapies were applied especially in hospitalized COVID-19 patients in daily practice [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, some studies have shown that reduced mortality with prophylactic use of anticoagulant therapy reduces mortality [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] and also the development of thromboembolic events [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], there are conflicting results with the benefit of anticoagulant therapy in terms of mortality and/or thrombosis [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Moreover, it is not known whether immunomodulatory therapy reduces thromboembolic events in patients with severe COVID-19.\u003c/p\u003e \u003cp\u003eIn our study, we aimed to evaluate the effect of high-dose intravenous anakinra treatment on the development of thrombotic events in severe and critical COVID-19 patients.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients and data:\u003c/h2\u003e \u003cp\u003eThis retrospective observational study, which includes secondary analysis of our previous study [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], was conducted at a tertiary referral center in Aksaray, Turkey. Diagnosis of COVID-19 was performed by typical computer tomography (CT) findings in addition to clinical signs and symptoms and confirmed with positive polymerase chain reaction (PCR).\u003c/p\u003e \u003cp\u003eThe study population consisted of two groups as follows; the patients receiving high-dose intravenous anakinra (anakinra group) added to background therapy between 01.09.2021 and 01.02.2022 and the patients treated with standard of care (SoC) as historical control group who were hospitalized between 01.07.2021 and 01.09.2021. COVID-19 disease severity was evaluated according to the National Institute of Health (NIH) severity scale and only severe and critically ill patients who followed up in the ward were included in the study [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e The study has been performed in accordance with the Declaration of Helsinki and the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule. An informed consent was obtained for the study. Institutional Review Board approval was also obtained from the Aksaray University Ethics Committee (date/number: 24.02.2022, 2022/04\u0026ndash;09).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eLaboratory evaluation\u003c/h2\u003e \u003cp\u003eLaboratory values such as hemogram, liver enzymes, troponin levels, C-reactive protein (CRP) (mg/dL), ferritin (pg/mL), d-dimer (pg/mL), lactate dehydrogenase (LDH) (U/L), procalcitonin (pg/dL) at the admission and consecutive days (procalcitonin was every other day but others were once in a day); the peak levels of CRP, ferritin, d-dimer and LDH levels were recorded. The inflammatory state of the patients was evaluated and derived based on the COVID hyperinflammatory syndrome score (cHIS) and it was calculated according to the combination of neutrophil and lymphocyte counts at the admission and the peak levels of CRP, ferritin, D-dimer, and LDH during to the follow-up [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The item of fever was removed due to its lower frequency (\u0026lt;%10) in both arms. Therefore, the maximum score of the new version of the cHIS score was 5 points (modified cHIS [mcHIS] score) was calculated in both groups [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eTreatment protocol and outcome\u003c/h2\u003e \u003cp\u003eAll patients received background corticosteroid therapy with 80 mg/day methylprednisolone (or its equivalent) and enoxaparin 0.4 mg/day at the admission and continued consecutive days (SoC). Anakinra was added to the background treatment in patients who did not respond to initial treatment for at least two days or concomitantly with steroids in patients with higher risk and/or critical illness at admission and continued until discharge or death. The average starting dose of anakinra was 400 mg/day intravenously and increased gradually to a maximum of 1600 mg/day if necessary (10 mg/kg/day). Anakinra dose adjustment was performed by the same experienced physician in COVID-19 (MB) according to daily clinical (respiratory symptoms, degree of oxygen supply, presence of fever) and laboratory findings.\u003c/p\u003e \u003cp\u003eDiagnosis of PTE was confirmed by thorax CT-angiography in patients with prominent d-dimer increase despite a decrease in acute phase reactants (APR) such as CRP and ferritin and/or increase in need of oxygen therapy and respiratory distress despite the decrease in levels of APRs. Diagnosis of MI was made according to the Thygesen et al. study [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Severe infection was defined as the development of opportunistic infection, need for intravenous antibiotics, sepsis, or requirement of intensive care unit (ICU) admission or development of death due to secondary infection.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eIn our study, the 22.0 version (IBM, Armonk, NY, USA) of the SPSS (Statistical Package for the Social Sciences) program was used for statistical analysis of data. In descriptive statistics, discrete​ ​and continuous numerical variables were expressed as mean, \u0026plusmn; standard deviation, or median (minimum-maximum). Categorical variables were expressed as number of cases (%). Cross-table statistics were used to compare categorical variables (Chi-Square, Fisher\u0026rsquo;s exact test). Normally distributed parametric data were compared with Student's t-test and non-parametric data that did not meet normal distribution were compared with Mann Whitney U and Kruskal Wallis tests. Correlation analysis was performed by Pearson or Spearman method according to normality distribution. ​Kaplan-Meier and log-rank methods were used for survival analysis. Multivariate analysis was performed by using logistic regression. Sensitivity and specificity calculations were performed by Receiver operating characteristic (ROC) analysis. p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 value was considered statistically significant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003ePropensity score matching\u003c/h2\u003e \u003cp\u003eThe first step in Propensity Score Matching (PSM) is to identify the covariates from which to calculate propensity scores (PS). Age, gender, mcHIS scores, and comorbidities such as DM, HT, and CHD of the patients were determined as the variables to be matched. The PS matching was done as 1:1 with the nearest neighbor method. The caliper value was 0.2. When matching, we performed this analysis by assigning values ​​according to the averages of the parameters with missing data. PSM was performed with the SPSS package program 28.0.1 using the R package program and an auxiliary plugin (PS matching 3.0 SPE). Dot-plot of standardized mean differences for all covariates before and after PS matching was shown in supplementary Fig.\u0026nbsp;1. Jitter plots for trend scores and line plots of standardized differences were described in supplemental Figs.\u0026nbsp;2 and 3, respectively.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eAnalysis Before PS Matching\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe included 114 patients in SoC and 139 patients in the Anakinra group in the study. The baseline clinical and laboratory features of the patients are described in Table 1. Frequency of male gender (51.8% vs 39.5%, p=0.05; Odds ratio [OR]: 3.8), chronic renal failure (CRF) (20% vs 5.3%, p=0.001; OR: 11.9), critical illness (61.2% vs 40.4%, p=0.001, OR:10.9) were higher in Anakinra group than SoC. Additionally, median (IQR) duration of hospitalization (11 [12] vs 9 [7.3] days; p=0.03), mcHIS scores (p\u0026lt;0.001), baseline NLR (p=0.002) and d-dimer levels (p=0.04), peak levels of CRP (p=0.012), ferritin (p\u0026lt;0.001), d-dimer (p=0.002), LDH (p\u0026lt;0.001) levels were higher in Anakinra receiving patients than SoC. \u003c/p\u003e\n\u003cp\u003eDevelopment of any thromboembolic event (5% vs 12.3%, p=0.038; OR:4.3) and PTE (2.9% vs 9.6%, p=0.023; OR:5.1) were lower in the Anakinra group than SoC. No patient experienced CVA and/or clinically evident DVT both in two arms. Although severe infection, pneumothorax, and MI were not different between the two arms (p=0.1, p=0.1, and p=0.2, respectively); ICU admission (39.6% vs 22%, p=0.003; OR:9) and mortality (36.7% vs 27%, p=0.026; OR:) were higher in Anakinra group compared to SoC before PS matching analysis (table 1). \u003c/p\u003e\n\u003cp\u003ePatients experienced any thromboembolic event had longer duration of hospitalization (p=0.03), higher vaccination counts (p=0.028), more frequent CHD (p=0.001; OR:11.8), critical disease (p=0.001; OR:10.6), higher mcHIS scores (p\u0026lt;0.001), lower NLR (p=0.002) and higher baseline d-dimer levels (p=0.04), higher peak levels of CRP (p=0.012), ferritin (p\u0026lt;0.001), d-dimer (p=0.002), and LDH (p\u0026lt;0.001). Development of thrombosis was also higher in patients who had mortality (62% vs 28%, p=0.001; OR:10.4) in univariate analysis (table 2). Patients developed PTE had longer duration of hospitalization (p=0.03), higher vaccination counts (p=0.03), critical disease (p=0.005; OR:7.8), higher mcHIS scores (p\u0026lt;0.001), and higher baseline d-dimer levels (p=0.04), higher peak levels of CRP (p=0.012), ferritin (p\u0026lt;0.001), d-dimer (p=0.002), and LDH (p\u0026lt;0.001). Development of PTE was also higher in patients who had severe infection (p=0.028; OR:4.8), pneumothorax (p=0.046; OR:4), MI (p\u0026lt;0.001; OR:12.6), and SoC (p=0.023; OR: 5.1) in univariate analysis (table 3). In multivariate analysis, peak d-dimer levels (p\u0026lt;0.001, OR:1.1, 95% Confidence interval [CI]: 1.05-1.16), critical illness (p=0.044, OR:9.5, 95% CI: 1.06-85.5), and SoC (compared to Anakinra) (p=0.002, OR:11.2, 95% CI: 2.47-51.1) were associated with development of any thromboembolic event (supplementary table). \u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAnalysis After PS Matching\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter 1:1 PS matching, 88 patients in SoC and 88 patients in the Anakinra group were matched and included in the analysis. The baseline clinical and laboratory features of the patients are described in Table 1. After adjustment of potential confounders age, gender, presence of comorbidities (DM, HT, CHD, CRF, chronic lung disease, and malignancy), disease severity, vaccination history, and mcHIS scores were not different between the two groups (table 1). Only baseline d-dimer and peak levels of LDH were higher in the Anakinra arm compared to SoC (p=0.05 and p\u0026lt;0.001). Severe infection (28.4% vs 16%, p=0.05; OR:3.9), development of any thromboembolic event (15.9% vs 3.4%, p=0.005; OR:7.9), PTE (12.5% vs 3.4%, p=0.026; OR:5), MI (6.8% vs 0, p=0.013; OR:6.2) were higher in SoC arm compared to Anakinra. ICU requirement and mortality did not differ between the two arms (p=0.2 and p=0.4, respectively). \u003c/p\u003e\n\u003cp\u003ePatients who experienced any thromboembolic event had more frequent CHD (p=0.04; OR:4.1), critical illness (p\u0026lt;0.001; OR:12.5), lower hemoglobin and baseline ferritin levels (p=0.03 and p=0.04, respectively), higher mcHIS scores (p=0.001), higher peak levels of CRP (p\u0026lt;0.001), d-dimer (p\u0026lt;0.001), LDH (p=0.038). Furthermore, severe infection (41% vs 20.3%, p=0.05; OR:3.9) and mortality (64.7% vs 27.7%, p=0.002; OR:9.8) were higher in patients who had any thromboembolic event than those had not (table 2). Similarly, PTE was higher in patients who had critical illness (p=0.002; OR:9.5), lower hemoglobin and ferritin levels (p=0.02 and p=0.04, respectively), higher mcHIS score (p=0.002), peak levels of CRP (p\u0026lt;0.001), d-dimer (p\u0026lt;0.001), pneumothorax (p=0.03; OR:4.8), MI (p\u0026lt;0.001; OR:15), and mortality (p=0.03; OR:4.7) (table 3). PTE development was associated with peak levels of d-dimer levels (p=0.02, OR:1.08, 95% CI: 1.01-1.15) in multivariate analysis. \u003c/p\u003e\n\u003cp\u003eDevelopment of MI was higher in patients who had history of CHD and malignancy (p=0.007; OR:7.3 and p=0.02; OR:5.5, respectively), critical illness (p=0.02; OR:5.4), higher mcHIS scores (p=0.02), peak levels of CRP (p=0.043), d-dimer (p=0.03), LDH (p=0.004) (table 4). MI was also higher in SoC (P=0.016; OR:6.2) and patients had mortality (p\u0026lt;0.001; OR:13.7) in univariate analysis. MI development was associated with the history of CHD (p=0.038, OR:6.9, 95% CI:1.1-42.3) and PTE (p=0.008, OR:11.5, 95% CI:1.9-69.5) in multivariate analysis. \u003c/p\u003e\n\u003cp\u003eIn survival analysis, development of any thromboembolic event, PTE, and MI were higher in SoC compared to Anakinra (Log-Rank; p=0.003 [figure 1], p=0.003 [supplementary figure 4], and p=0.007 [supplementary figure 5], respectively). Survival rate was also lower in patients with the SoC arm than Anakinra in patients who had any thromboembolic event as well as MI (Log-Rank; p=0.03 [figure 2] and p\u0026lt;0.001 [figure 3], respectively). The survival rate of patients with and without PTE did not differ in patients with COVID-19 (supplementary figure 6). \u003c/p\u003e\n\u003cp\u003eROC analysis revealed a cut-off value of d-dimer for the development of any thromboembolic event 16.75 (Area under curve [AUC]: 0.804, p\u0026lt;0.001 [95% CI: 0.710-0.898]) with 61.9% sensitivity and 84.8% specificity (likelihood ratio [LR]:4), for the development of PTE 14.97 (AUC: 0.867, p\u0026lt;0.001 [95% CI: 0.774-0.960]) with 86.7% sensitivity and 83.5% specificity (LR:5.3), for the development of MI 5.83 (AUC: 0.736, p\u0026lt;0.016 [95% CI: 0.585-0.887]) with 66.7% sensitivity and 66.7% specificity (LR:2) (Supplementary figure 7,8, and 9, respectively). Cut-off value of mcHIS score for the development of any thromboembolic event 3.5 (AUC: 0.726, p=0.001 [95% CI: 0.632-0.821]) with 71.4% sensitivity and 63.2% specificity (LR:1.94), for the development of PTE 3.5 (AUC: 0.740, p=0.002 [95% CI: 0.624-0.855]) with 73.3% sensitivity and 62.4% specificity (LR:1.95), for the development of MI 3.5 (AUC: 0.750, p=0.01 [95% CI: 0.630-0.870]) with 77.8% sensitivity and 61.7% specificity (LR:2) (Supplementary figure 10,11, and 12, respectively). A cut-off value of peak levels of CRP for the development of any thromboembolic event 171.2 mg/L (AUC: 0.780, p\u0026lt;0.001 [95% CI: 0.684-0.875]) with 76.5% sensitivity and 72.3% specificity (LR:2.8), for the development of PTE 201 mg/L (AUC: 0.800, p\u0026lt;0.001 [95% CI: 0.694-0.905]) with 71.4% sensitivity and 78.4% specificity (LR:3.3), for the development of MI 145.3 mg/L (AUC: 0.743, p=0.043 [95% CI: 0.629-0.857]) with 100% sensitivity and 54.7% specificity (LR:2.2) (Supplementary figure 13,14, and 15, respectively). Other results of ROC analysis are shown in Table 5 and supplementary figures 16 and 17).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIt is well known that higher mortality rates and poor outcomes are mainly associated with the development of cytokine storms in patients with COVID-19 [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Cytokine storm is a hyperinflammatory state that is seen in several conditions such as hematological malignancies, infectious diseases, and rheumatological conditions including adult-onset still disease (AOSD), and systemic lupus erythematosus [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Development of cytokine storm depends on the excessive production of several cytokines including interleukin-1 (IL-1), IL-6, tumor necrosis factor-alpha (TNF-α), and type 1 interferon (IFN) triggered by SARS-CoV-2 in COVID-19 [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Recent studies revealed the importance of pulmonary macrophages’ activation secondary to SARS-CoV-2 (23), which results in inflammasome activation in COVID-19 [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Inflammasomes are essential in the host defense against microorganisms including viruses that are present in various innate immune cells such as neutrophils, macrophages, and dendritic cells. Activation of inflammasomes leads to the cleavage of pro-IL-1β to produce active IL-1β [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], and is responsible for the development of various immune-mediated diseases such as Familial Mediterranean Fever (FMF), gout, and AOSD [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Furthermore, the safety and efficacy of IL-1 blockade in these diseases were established in these conditions [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAnakinra is an IL-1 receptor antagonist which is widely used in several rheumatological diseases such as FMF, AOSD, and gout [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] and also several hyperinflammatory conditions such as cancer-related hemophagocytic syndrome, chimeric antigen receptor-modified (CAR) T cell-associated cytokine storm, and macrophage activation syndrome [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Safety and efficacy of Anakinra was also established in COVID-19-associated cytokine storm [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Intravenous and high-dose anakinra is an emerging therapeutic option both in rheumatology, other hyperinflammatory conditions, and COVID-19 [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Intravenous administration of anakinra ensures higher and faster maximum plasma concentration compared to the subcutaneous form [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Daily dose adjustment of anakinra may allow early intervention of the cytokine storm according to daily clinical status, as well as withdrawing the drug in case of infection or other complications. Additionally, intravenous high-dose anakinra treatment reduced mortality in our previous study [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThromboembolic events are common in COVID-19 which is a remarkable finding from the beginning of the pandemic [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In the Middeldorp et al. study overall VTE frequency was 20% which was higher in patients in ICU (47%) than ward (3.3%). In the former study, ICU admission, increased d-dimer, and NLR levels were associated with the development of VTE which were similar to our results. In another observational study with 3334 patients, 16% of patients experienced a thrombotic event which 6.2% of them were VTE and 11.1% were arterial events (1.6% stroke and 8.9% MI) [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The former study also revealed an association between the development of thrombosis and a prior history of CHD and increased d-dimer levels which were consistent with our results. In the former study, thrombotic events were also higher in patients who had critical disease and/or deceased compared to those who had not. In a study with COVID-19-related deceased patients, although 9% of the patients had macroscopic thrombosis, most of the patients (87%) had microscopic evidence of thrombosis accompanying intense inflammation in autopsy specimens [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The authors also concluded a pathologic link between inflammation and thrombosis in the former study. In our study, higher mcHIS score and its components such as d-dimer and CRP levels in patients who experienced thrombosis suggest that hyperinflammation is one of the key factors for the development of thrombotic events in patients with COVID-19. Moreover, the fact that higher values of peak levels of CRP, d-dimer, LDH, and ferritin than those baseline levels emphasize the crucial role of hyperinflammation in the development of thrombotic events. This finding was also consistent with our previous results regarding the close association between peak levels of these laboratory tests and poor outcomes [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn our study, the lower frequency of PTE in the anakinra group was a remarkable finding even though the anakinra group had more severe disease before propensity score matching [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. This finding persists after the PS matching procedure. As already known, endothelial dysfunction, thrombophilia, and stasis are the main contributors to the development of venous thrombosis according to Virchow’s triad. In COVID-19, endothelial dysfunction appears to be a more prominent factor in the development of thrombosis [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In our study, none of the patients with PTE had clinically evident DVT which suggests COVID-19-related pulmonary thrombosis is an in-situ thrombosis rather than embolism which was claimed by Gabrielli et. al. study [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. In our study, all patients received background anticoagulant prophylaxis in two arms but could not prevent thrombotic events. This situation is recently called ‘inflammothrombosis’ which is similar to Behçet’s disease (BD) associated venous thrombosis. While DVT and PT (in situ thrombosis, not embolism) may develop in BD separately, DVT is not expected to cause embolism due to its inflammatory nature (firmly attached to the vascular wall). Therefore, the definition of pulmonary thrombosis may be more accurate than pulmonary embolism in patients with COVID-19 similar to BD. Furthermore, while anticoagulant therapy does not prevent vascular thrombosis in BD patients, anti-inflammatory treatment improves vascular outcomes such as recanalization and prevention of relapses [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In light of these data, pulmonary thrombosis in COVID-19 may be mainly associated with pulmonary inflammatory environment rather than stasis or other components of Virchow’s triad and develops in situ thrombosis rather than embolism. Therefore, anti-inflammatory treatment may reduce thrombosis risk beyond the anticoagulant treatment in patients with severe COVID-19 which was shown in our study. However, it should be kept in mind that limited data is showing the efficacy of anti-inflammatory therapy as an anticoagulant effect in patients with COVID-19.\u003c/p\u003e\u003cp\u003eInflammation is an important contributor to the development of cardiovascular disease including acute coronary syndromes (ACS). During the pandemic arterial thrombotic events such as CVA and MI were increased in patients with COVID-19 [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The NLRP3 (NOD [nucleotide oligomerization domain]-, LRR [leucine-rich repeat]-, and PYD [pyrin domain]-containing protein 3) [NLRP3] inflammasome, an innate immune signaling complex, is the key mediator of IL-1 family cytokine production. Recent evidence has shown that NLRP3 inflammasome activation has a crucial role in leading higher IL-1 production for the development of ACS [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Furthermore, colchicine, an inflammasome inhibitor was found to be effective for the prevention of MI in patients before ACS history [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Similarly, canakinumab is an IL-1β monoclonal antibody that decreases composite cardiovascular events including MI, stroke, coronary revascularization, and cardiovascular death in the CANTOS study [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. In our study, the decreased incidence of MI with Anakinra was consistent with previous studies. Additionally, higher mcHIS scores in patients who had MI compared with had not emphasized the crucial role of hyperinflammation in the development of arterial events.\u003c/p\u003e\u003cp\u003eThis study has some strengths and limitations. The retrospective design of the study was the main limitation although the controlled design of the study adjusting potential confounders by PS matching was important to prevent bias. We could not perform Doppler USG screening in patients who had PTE since it did not cause a change in treatment and critical situation of the patients. Diagnosis of MI could not be confirmed with cardiac catheterization. Having missing data is also a limitation of the study. On the other hand, the fact that the study is conducted in a single center enables homogeneity in terms of patient population and treatment decisions that are made by a single physician.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThromboembolic events were seen despite the anticoagulant prophylaxis in our study. Development of thrombosis was associated with hyperinflammation in patients with severe and critical COVID-19. Intravenous high-dose anakinra treatment decreases both venous and arterial events in patients with COVID-19.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eNo specific funding was received from any bodies in the public, commercial, or not-for-profit sectors to carry out the work described in this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u0026nbsp;\u003c/strong\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material:\u0026nbsp;\u003c/strong\u003eThe Dataset of the study is available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u003c/strong\u003e MB and R\u0026Ccedil; designed and planned the study, R\u0026Ccedil;, SY, MA, MHU, and MİK collected the data, SY and MB carried out the data evaluation and basic analyses, all authors contributed to the follow-up of the patients and interpretation of results. R\u0026Ccedil; and MB wrote the first draft, and all authors provided critical feedback for the last version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e: Individual informed written patient consent and Institutional Review Board approval was obtained from Aksaray University Ethics Committee (date/number: 24.02.2022, 2022/04-09). \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e Many thanks to Prof. Ahmet G\u0026uuml;l for shedding light of our way.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eVerity R, Okell LC, Dorigatti I, Winskill P, Whittaker C, Imai N, Cuomo-Dannenburg G, Thompson H, Walker PGT, Fu H, et al: Estimates of the severity of coronavirus disease 2019: a model-based analysis. Lancet Infect Dis 2020, 20:669\u0026ndash;677.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTufan A, Avanoğlu G\u0026uuml;ler A, Matucci-Cerinic M: COVID-19, immune system response, hyperinflammation and repurposing antirheumatic drugs. Turk J Med Sci 2020, 50:620\u0026ndash;632.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKyriazopoulou E, Poulakou G, Milionis H, Metallidis S, Adamis G, Tsiakos K, Fragkou A, Rapti A, Damoulari C, Fantoni M, et al: Early treatment of COVID-19 with anakinra guided by soluble urokinase plasminogen receptor plasma levels: a double-blind, randomized controlled phase 3 trial. Nat Med 2021, 27:1752\u0026ndash;1760.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarconi VC, Ramanan AV, de Bono S, Kartman CE, Krishnan V, Liao R, Piruzeli MLB, Goldman JD, Alatorre-Alexander J, de Cassia Pellegrini R, et al: Efficacy and safety of baricitinib for the treatment of hospitalised adults with COVID-19 (COV-BARRIER): a randomised, double-blind, parallel-group, placebo-controlled phase 3 trial. Lancet Respir Med 2021, 9:1407\u0026ndash;1418.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHorby P, Lim WS, Emberson JR, Mafham M, Bell JL, Linsell L, Staplin N, Brightling C, Ustianowski A, Elmahi E, et al: Dexamethasone in Hospitalized Patients with Covid-19. N Engl J Med 2021, 384:693\u0026ndash;704.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTocilizumab in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial. Lancet 2021, 397:1637\u0026ndash;1645.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAsakura H, Ogawa H: COVID-19-associated coagulopathy and disseminated intravascular coagulation. Int J Hematol 2021, 113:45\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiddeldorp S, Coppens M, van Haaps TF, Foppen M, Vlaar AP, M\u0026uuml;ller MCA, Bouman CCS, Beenen LFM, Kootte RS, Heijmans J, et al: Incidence of venous thromboembolism in hospitalized patients with COVID-19. J Thromb Haemost 2020, 18:1995\u0026ndash;2002.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTang N, Bai H, Chen X, Gong J, Li D, Sun Z: Anticoagulant treatment is associated with decreased mortality in severe coronavirus disease 2019 patients with coagulopathy. J Thromb Haemost 2020, 18:1094\u0026ndash;1099.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlbani F, Sepe L, Fusina F, Prezioso C, Baronio M, Caminiti F, Di Maio A, Faggian B, Franceschetti ME, Massari M, et al: Thromboprophylaxis with enoxaparin is associated with a lower death rate in patients hospitalized with SARS-CoV-2 infection. A cohort study. EClinicalMedicine 2020, 27:100562.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLachant DJ, Lachant NA, Kouides P, Rappaport S, Prasad P, White RJ: Chronic therapeutic anticoagulation is associated with decreased thrombotic complications in SARS-CoV-2 infection. J Thromb Haemost 2020, 18:2640\u0026ndash;2645.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSadeghipour P, Talasaz AH, Rashidi F, Sharif-Kashani B, Beigmohammadi MT, Farrokhpour M, Sezavar SH, Payandemehr P, Dabbagh A, Moghadam KG, et al: Effect of Intermediate-Dose vs Standard-Dose Prophylactic Anticoagulation on Thrombotic Events, Extracorporeal Membrane Oxygenation Treatment, or Mortality Among Patients With COVID-19 Admitted to the Intensive Care Unit: The INSPIRATION Randomized Clinical Trial. Jama 2021, 325:1620\u0026ndash;1630.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBektaş M, Y\u0026uuml;ce S, Ay M, Uyar MH, \u0026Ouml;nder ME, Kılı\u0026ccedil; M: High-dose intravenous anakinra treatment is safe and effective in severe and critical COVID-19 patients: a propensity score-matched study in a single center. Inflammopharmacology 2023, 31:787\u0026ndash;797.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCOVID-19 Treatment Guidelines Panel. Coronavirus Disease 2019 (COVID-19) Treatment Guidelines. [ \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.covid19treatmentguidelines.nih.gov/\u003c/span\u003e\u003cspan address=\"https://www.covid19treatmentguidelines.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. ]\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWebb BJ, Peltan ID, Jensen P, Hoda D, Hunter B, Silver A, Starr N, Buckel W, Grisel N, Hummel E, et al: Clinical criteria for COVID-19-associated hyperinflammatory syndrome: a cohort study. Lancet Rheumatol 2020, 2:e754-e763.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThygesen K, Alpert JS, Jaffe AS, Chaitman BR, Bax JJ, Morrow DA, White HD: Fourth Universal Definition of Myocardial Infarction (2018). J Am Coll Cardiol 2018, 72:2231\u0026ndash;2264.\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\u003eJarczak D, Nierhaus A: Cytokine Storm-Definition, Causes, and Implications. Int J Mol Sci 2022, 23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen G, Wu D, Guo W, Cao Y, Huang D, Wang H, Wang T, Zhang X, Chen H, Yu H, et al: Clinical and immunological features of severe and moderate coronavirus disease 2019. J Clin Invest 2020, 130:2620\u0026ndash;2629.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJunqueira C, Crespo \u0026Acirc;, Ranjbar S, de Lacerda LB, Lewandrowski M, Ingber J, Parry B, Ravid S, Clark S, Schrimpf MR, et al: FcγR-mediated SARS-CoV-2 infection of monocytes activates inflammation. Nature 2022, 606:576\u0026ndash;584.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSefik E, Qu R, Junqueira C, Kaffe E, Mirza H, Zhao J, Brewer JR, Han A, Steach HR, Israelow B, et al: Inflammasome activation in infected macrophages drives COVID-19 pathology. Nature 2022, 606:585\u0026ndash;593.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVora SM, Lieberman J, Wu H: Inflammasome activation at the crux of severe COVID-19. Nat Rev Immunol 2021, 21:694\u0026ndash;703.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGabay C, Lamacchia C, Palmer G: IL-1 pathways in inflammation and human diseases. Nat Rev Rheumatol 2010, 6:232\u0026ndash;241.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDinarello CA: Interleukin-1 in the pathogenesis and treatment of inflammatory diseases. Blood 2011, 117:3720\u0026ndash;3732.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarko L, Shemer A, Lidar M, Grossman C, Druyan A, Livneh A, Kivity S: Anakinra for colchicine refractory familial Mediterranean fever: a cohort of 44 patients. Rheumatology (Oxford) 2021, 60:2878\u0026ndash;2883.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGiacomelli R, Sota J, Ruscitti P, Campochiaro C, Colafrancesco S, Dagna L, Iacono D, Iannone F, Lopalco G, Sfriso P, Cantarini L: The treatment of adult-onset Still's disease with anakinra, a recombinant human IL-1 receptor antagonist: a systematic review of literature. Clin Exp Rheumatol 2021, 39:187\u0026ndash;195.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaag KG, Khanna PP, Keenan RT, Ohlman S, Osterling Koskinen L, Sparve E, \u0026Aring;kerblad AC, Wik\u0026eacute;n M, So A, Pillinger MH, Terkeltaub R: A Randomized, Phase II Study Evaluating the Efficacy and Safety of Anakinra in the Treatment of Gout Flares. Arthritis Rheumatol 2021, 73:1533\u0026ndash;1542.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBami S, Vagrecha A, Soberman D, Badawi M, Cannone D, Lipton JM, Cron RQ, Levy CF: The use of anakinra in the treatment of secondary hemophagocytic lymphohistiocytosis. Pediatr Blood Cancer 2020, 67:e28581.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStrati P, Ahmed S, Kebriaei P, Nastoupil LJ, Claussen CM, Watson G, Horowitz SB, Brown ART, Do B, Rodriguez MA, et al: Clinical efficacy of anakinra to mitigate CAR T-cell therapy-associated toxicity in large B-cell lymphoma. Blood Adv 2020, 4:3123\u0026ndash;3127.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrom AA, Horne A, De Benedetti F: Macrophage activation syndrome in the era of biologic therapy. Nat Rev Rheumatol 2016, 12:259\u0026ndash;268.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNigrovic PA, Mannion M, Prince FH, Zeft A, Rabinovich CE, van Rossum MA, Cortis E, Pardeo M, Miettunen PM, Janow G, et al: Anakinra as first-line disease-modifying therapy in systemic juvenile idiopathic arthritis: report of forty-six patients from an international multicenter series. Arthritis Rheum 2011, 63:545\u0026ndash;555.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMehta P, Cron RQ, Hartwell J, Manson JJ, Tattersall RS: Silencing the cytokine storm: the use of intravenous anakinra in haemophagocytic lymphohistiocytosis or macrophage activation syndrome. Lancet Rheumatol 2020, 2:e358-e367.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePhadke O, Rouster-Stevens K, Giannopoulos H, Chandrakasan S, Prahalad S: Intravenous administration of anakinra in children with macrophage activation syndrome. Pediatr Rheumatol Online J 2021, 19:98.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaunders BN, Kuijpers MV, Sloan JJ, Gertner E: Continuous IV infusion of anakinra. Front Pharmacol 2023, 14:1162742.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBilaloglu S, Aphinyanaphongs Y, Jones S, Iturrate E, Hochman J, Berger JS: Thrombosis in Hospitalized Patients With COVID-19 in a New York City Health System. Jama 2020, 324:799\u0026ndash;801.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhismatullin RR, Ponomareva AA, Nagaswami C, Ivaeva RA, Montone KT, Weisel JW, Litvinov RI: Pathology of lung-specific thrombosis and inflammation in COVID-19. J Thromb Haemost 2021, 19:3062\u0026ndash;3072.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBektaş M, Y\u0026uuml;ce S, Ay M, Uyar MH, \u0026Ouml;nder ME, Kılı\u0026ccedil; M: High-dose intravenous anakinra treatment is safe and effective in severe and critical COVID-19 patients: a propensity score-matched study in a single center. Inflammopharmacology 2023:1\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAhmed S, Zimba O, Gasparyan AY: Thrombosis in Coronavirus disease 2019 (COVID-19) through the prism of Virchow's triad. Clin Rheumatol 2020, 39:2529\u0026ndash;2543.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGabrielli M, Lamendola P, Esperide A, Valletta F, Franceschi F: COVID-19 and thrombotic complications: Pulmonary thrombosis rather than embolism? Thromb Res 2020, 193:98.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBettiol A, Alibaz-Oner F, Direskeneli H, Hatemi G, Saadoun D, Seyahi E, Prisco D, Emmi G: Vascular Beh\u0026ccedil;et syndrome: from pathogenesis to treatment. Nat Rev Rheumatol 2023, 19:111\u0026ndash;126.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStein LK, Mayman NA, Dhamoon MS, Fifi JT: The emerging association between COVID-19 and acute stroke. Trends Neurosci 2021, 44:527\u0026ndash;537.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKnight R, Walker V, Ip S, Cooper JA, Bolton T, Keene S, Denholm R, Akbari A, Abbasizanjani H, Torabi F, et al: Association of COVID-19 With Major Arterial and Venous Thrombotic Diseases: A Population-Wide Cohort Study of 48 Million Adults in England and Wales. Circulation 2022, 146:892\u0026ndash;906.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAfrasyab A, Qu P, Zhao Y, Peng K, Wang H, Lou D, Niu N, Yuan D: Correlation of NLRP3 with severity and prognosis of coronary atherosclerosis in acute coronary syndrome patients. Heart Vessels 2016, 31:1218\u0026ndash;1229.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTardif JC, Kouz S, Waters DD, Bertrand OF, Diaz R, Maggioni AP, Pinto FJ, Ibrahim R, Gamra H, Kiwan GS, et al: Efficacy and Safety of Low-Dose Colchicine after Myocardial Infarction. N Engl J Med 2019, 381:2497\u0026ndash;2505.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEverett BM, MacFadyen JG, Thuren T, Libby P, Glynn RJ, Ridker PM: Inhibition of Interleukin-1β and Reduction in Atherothrombotic Cardiovascular Events in the CANTOS Trial. J Am Coll Cardiol 2020, 76:1660\u0026ndash;1670.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e: Baseline clinical and laboratory features and outcomes of the patients before and after Propensity-score (PS) Matching\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.727969348659006%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBefore PS Matching\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.37547892720306%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAfter PS Matching\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnakinra (n=139)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSoC (n=114)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value (OR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnakinra (n=88)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSoC (n=88)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value (OR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, years, median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e71 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e65.5 (23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e70 (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e66.5 (24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender, male, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e72 (51.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e45 (39.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.05 (3.8)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e40 (45.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e41 (46.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDuration of hospitalization (days), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e11 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e9 (7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.03\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e10 (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e10 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes mellitus\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e36/137 (26.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e39 (34.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e27 (30.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e29 (33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertension\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e79/135 (58.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e64 (56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e49/86 (57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e53 (60.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoronary heart disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e24/135 (17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e24 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e19/86 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e19 (21.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eChronic renal failure\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e28 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e6 (5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.001 (11.9)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e15/75 (19.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e22 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eChronic obstructive lung disease\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e22/136 (16.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e19 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e14/86 (16.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e14 (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMalignancy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e16/138 (11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e8 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e6 (6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e8 (9.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVaccination history\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e44/86 (51.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e26/63 (41.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e31/58 (53.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e18/48 (37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisease severity, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNIH score 3 (severe)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e54 (38.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e68 (59.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.001 (10.9)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e36 (41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e46 (52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.411764705882355%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNIH score 4 (Critical)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.882352941176471%\" valign=\"top\"\u003e\n \u003cp\u003e85 (61.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.058823529411764%\" valign=\"top\"\u003e\n \u003cp\u003e46 (40.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.372549019607842%\" valign=\"top\"\u003e\n \u003cp\u003e52 (59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.274509803921568%\" valign=\"top\"\u003e\n \u003cp\u003e42 (48)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVaccination history, median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e2 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e2 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e3 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e2 (1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003emcHIS score, median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e3 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e3 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e3 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e3 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLaboratory \u0026nbsp;results\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNeutrophil to lymphocyte ratio, median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e6.8 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e4.4 (4.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.002\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e6.9 (8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e4.6 (5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHemoglobin (g/L), mean\u0026plusmn;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e13.2\u0026plusmn;2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e13.2\u0026plusmn;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e13.3\u0026plusmn;2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e13.2\u0026plusmn;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCreatinine (mg/dL), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e0.9 (0.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e0.83 (0.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e0.84 (0.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e0.9 (0.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eProkalsitonin (pg/dL), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e0.2 (0.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e0.16 (0.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e0.18 (0.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e0.18 (0.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eC-reactive protein (mg/L), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e116 (113)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e100.3 (100.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e115 (133)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e107 (107)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e148 (120)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e126 (88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.012\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e141 (152)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e141.2 (90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e11.4 (64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e13.1 (91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e10.4 (58.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e14.5 (101)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFerritin (pg/mL), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e393 (592)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e322 (423)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e334.5 (590.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e302 (371)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e714 (969)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e378 (660)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e630 (811)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e495 (873)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e392 (590)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e268 (480)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.007\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e379 (427)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e313 (630)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eD-dimer (pg/mL), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e1.2 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e0.85 (1.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.04\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e1.24 (1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e1 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.05\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e4.1 (12.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e2.25 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.002\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e2.75 (14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e2.7 (6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e1.4 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e1.14 (2.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e1.37 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e1.2 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLactate dehydrogenase (U/L), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e404 (220)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e414 (229)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e398.5 (219)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e399.5 (210)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e559 (266)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e408 (237)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e570 (259)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e425 (269)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e357 (231)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e334 (170)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.03\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e366.5 (204)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e345.5 (195)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutcomes, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSevere infection\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e19/128 (14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e26 (22.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e13/82 (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e25 (28.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.05 (3.9)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePneumothorax\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e3/134 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e2/86 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e0,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDevelopment of any thrombotic event\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e7 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e14 (12.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.038 (4.3)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e3 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e14 (15.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.005 (7.9)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePulmonary thromboembolism\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e4 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e11 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.023 (5.1)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e3 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e11 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.026 (5)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMyocardial infarction\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e3 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e6 (5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e6 (6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.013 (6.2)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eICU requirement\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e55 (39.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e25 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.003 (9)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e33 (37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e24 (27.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMortality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.413793103448276%\" valign=\"top\"\u003e\n \u003cp\u003e51 (36.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.425287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e27 (23.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.026 (5)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.704980842911876%\" valign=\"top\"\u003e\n \u003cp\u003e30 (34.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.720306513409962%\" valign=\"top\"\u003e\n \u003cp\u003e25 (28.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.950191570881225%\" valign=\"top\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;PS: Propensity score, SoC: Standard of care, OR: Odds ratio, IQR: Interquartile range, ICU: Intensive care unit, 1: Baseline levels, 2: Peak levels, 3: Last levels\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u003c/strong\u003e Univariate analysis of the patients who had any thromboembolic event before and after Propensity-score (PS) Matching\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.727969348659006%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients with thrombosis before PSM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.37547892720306%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients with thrombosis after PSM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes (n=21)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo (n=232)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value (OR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes (n=17)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo (n=159)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value (OR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, years, median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e71 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e68 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e71 (26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e69 (26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender, male, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e13 (62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e104(45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e10 (58.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e71 (44.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDuration of hospitalization (days), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e11 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e9.5 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.03\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e11 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e10 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes mellitus\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e7 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e68/230 (29.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e5 (29.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e51 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertension\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e13 (62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e130/228 (57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e10 (58.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e92 (58.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoronary heart disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e10 (47.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e38/228 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.001 (11.8)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e7 (41.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e31 (19.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.04 (4.1)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eChronic renal failure\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e4 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e30 (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e4 (23.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e33 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eChronic obstructive lung disease\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e4 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e37/229 (16.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e4 (23.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e24 (15.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMalignancy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e3 (14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e21/231 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e3 (17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e11 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVaccination history\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e5/13 (38.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e65/136 (48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e4/10 (40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e45/96 (47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisease severity, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNIH score 3 (severe)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e3 (14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e119 (51.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.001 (10.6)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e1 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e81 (61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001 (12.5)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.85291113381001%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNIH score 4 (Critical)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.461695607763023%\" valign=\"top\"\u003e\n \u003cp\u003e18 (85.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.811031664964249%\" valign=\"top\"\u003e\n \u003cp\u003e113 (48.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.853932584269664%\" valign=\"top\"\u003e\n \u003cp\u003e16 (94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.020429009193055%\" valign=\"top\"\u003e\n \u003cp\u003e78 (49)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVaccination counts, median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e3 (1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e2 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.028\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e2.5 (1.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e2 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003emcHIS score, median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e4 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e3 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e4 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e3 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.001\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLaboratory \u0026nbsp;results\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNeutrophil to lymphocyte ratio, median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e5.6 (10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e5.6 (5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.002\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e4 (10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e5.9 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHemoglobin (g/L), mean\u0026plusmn;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e12.6\u0026plusmn;1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e13.3\u0026plusmn;2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e12.4\u0026plusmn;1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e13.3\u0026plusmn;2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.03\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCreatinine (mg/dL), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e0.94 (0.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e0.84 (0.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e0.94 (0.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e0.85 (0.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eProkalsitonin (pg/dL), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e0.2 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e0.2 (0.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e0.12 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e0.2 (0.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eC-reactive protein (mg/L), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e118 (123)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e108 (107)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e110 (106)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e107 (119)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e212.5 (121)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e137.5 (95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.012\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e212.5 (113)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e135 (98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e87.4 (144)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e11.5 (64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e121 (152)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e11.4 (75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.014\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFerritin (pg/mL), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e204.5 (603)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e371 (545)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e172 (223)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e336 (544)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.04\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e714 (735)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e546 (867)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e694 (735)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e532 (853)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e551.4 (695)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e331.5 (483)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.007\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e551 (680)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e331.5 (483)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.044\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eD-dimer (pg/mL), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e1.44 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e1.15 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.04\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e0.75 (1.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e1.2 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e21 (28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e2.7 (7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.002\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e23.8 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e2.56 (6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e5.6 (32.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e1.2 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e19.7 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e1.18 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLactate dehydrogenase (U/L), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e418 (268)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e409 (215)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e418 (154)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e398 (207)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e655 (487)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e476 (271)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e663 (540)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e490 (277)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.038\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e482 (518)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e348 (169)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.03\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e482 (506)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e351 (164)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.012\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutcomes, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSevere infection\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e7 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e38/221 (17.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e7 (41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e31/153 (20.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.05 (3.9)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePneumothorax\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e1 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e2/227 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e1 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e1/157 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnakinra\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e7 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e132 (95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.038 (4.3)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e3 (17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e85 (53.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.005 (7.9)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.85291113381001%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSoC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.461695607763023%\" valign=\"top\"\u003e\n \u003cp\u003e14 (12.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.811031664964249%\" valign=\"top\"\u003e\n \u003cp\u003e100 (87.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.853932584269664%\" valign=\"top\"\u003e\n \u003cp\u003e14 (82.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.020429009193055%\" valign=\"top\"\u003e\n \u003cp\u003e74 (46.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eICU requirement\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e10 (47.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e70 (30.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e8 (47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e49 (31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.875957120980093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMortality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.341500765696784%\" valign=\"top\"\u003e\n \u003cp\u003e13 (62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.10260336906585%\" valign=\"top\"\u003e\n \u003cp\u003e65 (28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.260336906584993%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.001 (10.4)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.633996937212864%\" valign=\"top\"\u003e\n \u003cp\u003e11 (64.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007656967840735%\" valign=\"top\"\u003e\n \u003cp\u003e44 (27.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.777947932618684%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.002 (9.8)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;PSM: Propensity score-matching, SoC: Standard of care, OR: Odds ratio, IQR: Interquartile range, ICU: Intensive care unit, 1: Baseline levels, 2: Peak levels, 3: Last levels\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e: Univariate analysis of the patients who had pulmonary thromboembolism before and after Propensity-score (PS) Matching\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.727969348659006%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients with pulmonary thromboembolism before PSM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.37547892720306%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients with pulmonary thromboembolism after PSM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes (n=15)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo (n=238)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value (OR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes (n=14)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo (n=162)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value (OR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, years, median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e71 (23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e68.5 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e68.5 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e69.5 (27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender, male, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e8 (53.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e109 (45.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e8 (57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e73 (45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDuration of hospitalization (days), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e10 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e10 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.03\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e10.5 (5.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e10 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes mellitus\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e3 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e72/236 (30.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e3 (21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e53 (32.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertension\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e8 (53.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e135/234 (57.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e8 (57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e94/160 (58.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoronary heart disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e5 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e43/234 (18.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e5 (35.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e33/160 (20.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eChronic renal failure\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e3 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e31 (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e3 (21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e21 (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eChronic obstructive lung disease\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e3 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e38/235 (16.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e3 (21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e25/160 (15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMalignancy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e2 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e22/237 (9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e2 (14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e12 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVaccination history\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e4/10 (40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e66/139 (47.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e4/9 (44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e45/97 (46.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisease severity, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNIH score 3 (severe)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e2 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e120 (50.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.005 (7.8)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e1 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e81 (50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.002 (9.5)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.63451776649746%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNIH score 4 (Critical)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.776649746192893%\" valign=\"top\"\u003e\n \u003cp\u003e13 (86.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.228426395939087%\" valign=\"top\"\u003e\n \u003cp\u003e118 (49.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.055837563451778%\" valign=\"top\"\u003e\n \u003cp\u003e13 (93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.304568527918782%\" valign=\"top\"\u003e\n \u003cp\u003e81 (50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVaccination history, median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e2.5 (1.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e2 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.03\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e2.5 (1.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e2 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003emcHIS score, median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e4 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e3 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e4.5 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e3 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.002\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLaboratory \u0026nbsp;results\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNeutrophil to lymphocyte ratio, median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e7.6 (12.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e5.6 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e7.5 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e5.8 (6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHemoglobin (g/L), mean\u0026plusmn;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e12.6\u0026plusmn;1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e13.3\u0026plusmn;2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e12.2\u0026plusmn;1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e13.6\u0026plusmn;2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.02\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCreatinine (mg/dL), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.94 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e0.84 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e1 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e0.85 (0.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eProkalsitonin (pg/dL), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e0.13 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e0.2 (0.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e0.1 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e0.2 (0.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eC-reactive protein (mg/L), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e110 (110)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e108 (105)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e114 (120)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e107 (118)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e212.5 (122)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e138.6 (96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.012\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e216 (119)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e136.5 (97.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e87.4 (158)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e11.6 (68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e91 (160)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e11.6 (80.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFerritin (pg/mL), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e203 (413)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e379 (543.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e172.4 (223)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e336 (544)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.04\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e693.6 (739)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e552 (863)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e633 (800)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e545.7 (853)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e551.4 (614)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e335.5 (487)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.007\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e533.7 (699)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e333 (486)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eD-dimer (pg/mL), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e1.1 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e1.17 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.04\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e0.75 (1.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e1.2 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e31.8 (18.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e2.7 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.002\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e33.4 (18.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e2.6 (6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e22.3 (31.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e1.2 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e27 (31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e1.2 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLactate dehydrogenase (U/L), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e428.5 (207)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e409 (219)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e418 (154)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e398 (207)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e633 (426)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e477 (282)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e615.5 (468)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e496 (282)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e482 (495)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e348 (171)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.03\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e472 (517)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e355 (166)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.044\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutcomes, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSevere infection\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e6 (40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e39/227 (17.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.028 (4.8)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e6 (43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e32/156 (20.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePneumothorax\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e1 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e2/233 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.046 (4)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e1 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e1/160 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.03 (4.8)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMyocardial infarction\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e3 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e6 (2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001 (12.6)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e3 (21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e3 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001 (15)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnakinra\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e4 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e135 (97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.023 (5.1)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e3 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e85 (96.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.026 (5)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.63451776649746%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSoC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.776649746192893%\" valign=\"top\"\u003e\n \u003cp\u003e11 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.228426395939087%\" valign=\"top\"\u003e\n \u003cp\u003e103 (90.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.055837563451778%\" valign=\"top\"\u003e\n \u003cp\u003e11 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.304568527918782%\" valign=\"top\"\u003e\n \u003cp\u003e77 (87.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eICU requirement\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e5 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e75 (31.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e5 (35.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e52 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.896551724137932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMortality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e8 (53.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.494252873563218%\" valign=\"top\"\u003e\n \u003cp\u003e70 (29.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.344827586206897%\" valign=\"top\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.873563218390805%\" valign=\"top\"\u003e\n \u003cp\u003e8 (57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.32567049808429%\" valign=\"top\"\u003e\n \u003cp\u003e47 (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17624521072797%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.03 (4.7)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;PSM: Propensity score-matching, SoC: Standard of care, OR: Odds ratio, IQR: Interquartile range, ICU: Intensive care unit, 1: Baseline levels, 2: Peak levels, 3: Last levels\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4:\u0026nbsp;\u003c/strong\u003eUnivariate analysis of the patients who had myocardial infarction after Propensity-score (PS) Matching\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.897893030794165%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"61.102106969205835%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients with MI after PSM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes (n=6)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo (n=170)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value (OR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, years, median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e77.5 (33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e69 (26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender, male, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e5 (83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e76 (44.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDuration of hospitalization (days), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e9 (14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e10 (9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes mellitus\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e2 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e54 (31.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertension\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e3 (50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e99/168 (59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoronary heart disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e4 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e34/168 (20.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.007 (7.3)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eChronic renal failure\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e1 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e23 (13.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eChronic obstructive lung disease\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e2 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e26/168 (15.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMalignancy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e2 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e12 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.02 (5.5)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVaccination history\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e1/4 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e48/102 (47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisease severity, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNIH score 3 (severe)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e82 (48.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.02 (5.4)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.281314168377826%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNIH score 4 (Critical)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.408624229979466%\" valign=\"top\"\u003e\n \u003cp\u003e6 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.310061601642712%\" valign=\"top\"\u003e\n \u003cp\u003e88 (51.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVaccination history, median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e2 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003emcHIS score, median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e4.5 (1.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e3 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.02\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLaboratory results\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNeutrophil to lymphocyte ratio, median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e4 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e5.9 (6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHemoglobin (g/L), mean\u0026plusmn;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e12.8\u0026plusmn;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e13.3\u0026plusmn;2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCreatinine (mg/dL), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e1 (0.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e0.87 (0.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eProkalsitonin (pg/dL), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e0.18 (0.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eC-reactive protein (mg/L), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e129 (164)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e107 (117)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e144.8 (74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e138.6 (110)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.043\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e207.6 (80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e11.5 (80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.003\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFerritin (pg/mL), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e331 (545)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e1001 (761)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e542 (848)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e1001 (687)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e333 (483)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.009\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eD-dimer (pg/mL), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e1.2 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e27.3 (32.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e2.7 (8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.03\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e27.3 (33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e1.2 (2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.005\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLactate dehydrogenase (U/L), median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e390 (97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e399 (206)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e998 (759)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e488 (278)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.004\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e582.5 (684)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e355 (172)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.016\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutcomes, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSevere infection\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e3 (50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e35/164 (21.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePneumothorax\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e2/168 (1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnakinra\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e88 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.013 (6.2)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.281314168377826%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSoC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.408624229979466%\" valign=\"top\"\u003e\n \u003cp\u003e6 (6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.310061601642712%\" valign=\"top\"\u003e\n \u003cp\u003e82 (93.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eICU requirement\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e4 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e53 (31.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.83495145631068%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMortality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.446601941747574%\" valign=\"top\"\u003e\n \u003cp\u003e6 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.521035598705502%\" valign=\"top\"\u003e\n \u003cp\u003e49 (28.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.197411003236247%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001 (13.7)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ePSM: Propensity score-matching, SoC: Standard of care, OR: Odds ratio, IQR: Interquartile range, ICU: Intensive care unit, 1: Baseline levels, 2: Peak levels, 3: Last levels\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5\u003c/strong\u003e: ROC analysis of laboratory features of the patients for development of thromboembolic events in patients with COVID-19\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"669\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCut-off value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eArea under curve\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSensitivity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecificity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLikelihood ratio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003emcHIS score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAny thrombosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\n \u003cp\u003e0.726\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\n \u003cp\u003e0.001 (0.632-0.821)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\n \u003cp\u003e71.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\n \u003cp\u003e63.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\n \u003cp\u003e1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePTE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\n \u003cp\u003e0.740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\n \u003cp\u003e0.002 (0.624-0.855)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\n \u003cp\u003e73.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\n \u003cp\u003e62.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\n \u003cp\u003e1.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\n \u003cp\u003e0.750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\n \u003cp\u003e0.01 (0.630-0.870)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\n \u003cp\u003e77.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\n \u003cp\u003e61.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eD-dimer (pg/mL)*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAny thrombosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\n \u003cp\u003e16.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\n \u003cp\u003e0.804\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001 (0.710-0.898)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\n \u003cp\u003e61.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\n \u003cp\u003e84.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePTE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\n \u003cp\u003e14.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\n \u003cp\u003e0.867\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001 (0.774-0.960)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\n \u003cp\u003e86.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\n \u003cp\u003e83.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\n \u003cp\u003e5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\n \u003cp\u003e5.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\n \u003cp\u003e0.736\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\n \u003cp\u003e0.016 (0.585-0.887)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\n \u003cp\u003e66.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\n \u003cp\u003e66.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eC-reactive protein (mg/L)*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAny thrombosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\n \u003cp\u003e171.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\n \u003cp\u003e0.780\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001 (0.684-0.875)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\n \u003cp\u003e76.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\n \u003cp\u003e72.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePTE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\n \u003cp\u003e201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\n \u003cp\u003e0.800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001 (0.694-0.905)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\n \u003cp\u003e71.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\n \u003cp\u003e78.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\n \u003cp\u003e145.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\n \u003cp\u003e0.743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\n \u003cp\u003e0.043 (0.629-0.857)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\n \u003cp\u003e54.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\n \u003cp\u003e2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLactate dehydrogenase (U/L)*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAny thrombosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\n \u003cp\u003e496\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\n \u003cp\u003e0.676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\n \u003cp\u003e0.008 (0.551-0.801)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\n \u003cp\u003e66.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\n \u003cp\u003e53.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePTE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\n \u003cp\u003e649.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\n \u003cp\u003e0.802\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\n \u003cp\u003e0.002 (0.675-0.928)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\n \u003cp\u003e77.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\n \u003cp\u003e75.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\n \u003cp\u003e3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFerritin (pg/mL)*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAny thrombosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePTE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNeutrophil-lymphocyte ratio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAny thrombosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePTE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.850299401197606%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.431137724550899%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.634730538922156%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.095808383233532%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.083832335329342%\" valign=\"top\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;*Peak levels of value, PTE: Pulmonary thromboembolism, MI: Myocardial infarction, CI: Confidence interval\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Anakinra, COVID-19, thrombosis, inflammasome, hyperinflammation","lastPublishedDoi":"10.21203/rs.3.rs-3994466/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3994466/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cb\u003eIntroduction\u003c/b\u003e: In our study, we aimed to evaluate the effect of high-dose intravenous anakinra treatment on the development of thrombotic events in severe and critical COVID-19 patients.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMaterial and methods\u003c/b\u003e: This retrospective observational study was conducted at a tertiary referral center in Aksaray, Turkey. The study population consisted of two groups as follows; the patients receiving high-dose intravenous anakinra (anakinra group) added to background therapy and the patients treated with standard of care (SoC) as a historical control group. Age, gender, mcHIS scores, and comorbidities such as DM, HT, and CHD of the patients were determined as the variables to be matched.\u003c/p\u003e \u003cp\u003e \u003cb\u003eResults\u003c/b\u003e: We included 114 patients in SoC and 139 patients in the Anakinra group in the study. Development of any thromboembolic event (5% vs 12.3%, p\u0026thinsp;=\u0026thinsp;0.038; OR:4.3) and PTE (2.9% vs 9.6%, p\u0026thinsp;=\u0026thinsp;0.023; OR:5.1) were lower in the Anakinra group than SoC. No patient experienced CVA and/or clinically evident DVT both in two arms.\u003c/p\u003e \u003cp\u003eAfter 1:1 PS matching, 88 patients in SoC and 88 patients in the Anakinra group were matched and included in the analysis. In survival analysis, the development of any thromboembolic event, PTE, and MI were higher in SoC compared to Anakinra. Survival rate was also lower in patients with SoC arm than Anakinra in patients who had any thromboembolic event as well as MI.\u003c/p\u003e \u003cp\u003e \u003cb\u003eConclusion\u003c/b\u003e: In our study, the development of thrombosis was associated with hyperinflammation in patients with severe and critical COVID-19. Intravenous high-dose anakinra treatment decreases both venous and arterial events in patients with COVID-19.\u003c/p\u003e","manuscriptTitle":"Intravenous High-dose Anakinra Drops Venous Thrombosis and Myocardial Infarction in Severe and Critical COVID-19 Patients: A Propensity Score Matched Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-11 19:11:34","doi":"10.21203/rs.3.rs-3994466/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-04-08T08:41:25+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-03-08T19:21:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"572ea250-84c1-4aab-b63a-725c92ea97a2","date":"2024-03-07T20:18:10+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-07T11:21:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-07T11:08:48+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-03-07T09:22:10+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-07T09:17:20+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-02-27T17:07:15+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f359f9f4-d6cf-41c7-b715-bc76109bd6a0","owner":[],"postedDate":"March 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":29270764,"name":"Biological sciences/Immunology"},{"id":29270765,"name":"Biological sciences/Microbiology"},{"id":29270766,"name":"Health sciences/Rheumatology"}],"tags":[],"updatedAt":"2024-05-13T11:54:44+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-11 19:11:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3994466","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3994466","identity":"rs-3994466","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}