Clinical characteristics associated with ARDS and mortality in patients with COVID-19 who received corticosteroid therapy

Clinical characteristics associated with ARDS and mortality in patients with COVID-19 who received corticosteroid therapy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Clinical characteristics associated with ARDS and mortality in patients with COVID-19 who received corticosteroid therapy Madeleine Anthonisen, Elliot Fortin, Simon Rousseau, Karine Tremblay This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6384044/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Background Corticosteroids are commonly used to manage severe Coronavirus disease 2019 (COVID-19) to prevent complications such as acute respiratory distress syndrome (ARDS) and mortality. However, their effectiveness varies. We assessed the clinical outcomes and risk factors associated with ARDS and mortality among patients with severe COVID-19 treated with corticosteroids. Methods We conducted a multi-center retrospective observational cohort study of 317 patients with severe COVID-19 who received corticosteroid therapy at hospitals in Quebec, Canada, from August 2020 to September 2022. Patient comparisons included: ARDS vs non-ARDS cases, survivors vs non-survivors, and survival profiles within ARDS/non-ARDS subgroups. Clinical characteristics, laboratory values, and outcomes were analyzed using chi-squared or Fisher's exact tests for categorical variables and t-tests or Mann-Whitney-Wilcoxon tests for continuous variables. Independent predictors of ARDS development and mortality were identified through multivariate logistic regression analysis. Results Logistic regression identified prior myocardial infarction as the only clinical comorbidity associated with ARDS development (OR = 3.64, 95% CI [1.11-11.94]). Notably, basophil counts showed a strong inverse relationship with ARDS development (OR = 5E-09, 95% CI [2.16E-15-0.012]). Age emerged as a significant predictor of mortality (OR = 1.07 per year, 95% CI [1.05-1.10]), along with previous lung disease (OR = 3.88, 95% CI [1.04-5.74]). Mortality was significantly higher in ARDS patients (40.6 % vs. 19.0 %, P < 0.0001). Surprisingly, obesity was associated with increased survival, particularly in ARDS patients (32.1 % vs. 9.6 %, P = 0.037). Conclusion The inverse relationship between basophil counts and ARDS development suggests a potential role for these cells in COVID-19 immune response. These findings reveal complex relationships between COVID-19, ARDS, and corticosteroids, generating new hypotheses for investigation. Acute respiratory distress syndrome Coronavirus disease 2019 Corticosteroids Mortality Figures Figure 1 Background COVID-19 has caused more than 7 million deaths worldwide ( 1 ), with severe and critical cases at the greatest risk of mortality ( 2 ). Although the World Health Organization (WHO) declared that the outbreak no longer constituted a public health emergency of international concern as of May 5th, 2023 ( 3 ), risks of viral exposure, disease severity and adverse outcomes remain significant among certain populations. Effective treatments for patients with severe and critical COVID-19 are thus essential. The link between corticosteroid therapy and reduced mortality in patients with severe COVID-19 has been established in the literature ( 4 – 7 ). The WHO recommends the administration of systemic corticosteroid therapy to patients with severe and critical COVID-19 ( 7 ). The National Institute for Excellence in Health and Social Services (INESSS, Quebec, Canada) guidelines also advocate for the utilization of corticosteroid therapy to manage COVID-19 and COVID-19-associated ARDS ( 8 , 9 ). Moreover, corticosteroid therapy has been shown to reduce mortality in patients with COVID-19-associated ARDS ( 10 – 12 ) as well as to reduce the risk of ARDS development in patients with COVID-19 ( 13 ). Despite substantial evidence of an association between systemic corticosteroid therapy and reduced mortality in patients with severe and critical COVID-19, the use of corticosteroids to treat infections has been controversial ( 5 , 14 ). Some studies show that systemic corticosteroid therapy failed to prevent the negative outcomes of severe or critical COVID-19, namely mortality ( 2 , 15 ), ARDS ( 15 ), and mortality following COVID-19-related ARDS ( 14 ), in certain patients. Understanding which factors, including those relating to patient demographics, disease progression, and medical interventions, are associated with negative outcomes of COVID-19 is thus imperative to diminishing mortality and ARDS in all patient populations. Using data from a multi-center retrospective cohort study encompassing 317 patients afflicted with severe COVID-19, who underwent hospitalization and received corticosteroid treatment in Quebec, Canada, spanning August 3rd, 2020, to September 24th, 2022 ( 16 ), we delved into the intricate relationships between diverse risk factors, clinical attributes, and critical outcomes, such as ARDS and mortality. This study compares the profiles of patients who did and did not develop ARDS as well as the profiles of patients who did and did not survive. This study also examines the progression to mortality in groups that did and did not experience ARDS. We present patient demographics, comorbidities, laboratory results at hospital admission, as well as details concerning hospitalization. We identified risk factors associated with ARDS and with mortality. Since all patients in this study received corticosteroid therapy, our results reflect factors that may be responsible for adverse outcomes despite the indicated therapy, as well as the interplay of these factors and corticosteroids. Materials and Methods Study Population This retrospective observational study includes data from 317 patients diagnosed with COVID-19 and hospitalized in Quebec, Canada between 3 rd August 2020 and 24 th September 2022. Data, including biological samples and clinical information, were obtained from the Biobanque québécoise de la COVID-19 (BQC19, https://www.quebeccovidbiobank.ca), a multi-center initiative composed of 10 hospitals and 5 academic institutions in Quebec (16). COVID-19 status was determined by a PCR test and only positive cases were considered in this study. The New Global Definition was used to diagnose ARDS (17). Criteria for patient inclusion are summarized in Figure 1. From a total of 6120 patients in the BQC19 cohort, those under 18 or with missing information were removed from consideration. Patients who were taking corticosteroids prior to hospitalization were also removed from consideration, as one of the aims of this study was to investigate the impact of corticosteroids on patients with COVID-19. Also, to this end, patients considered were diagnosed after 3 rd August, 2020. This is the date new guidelines were issued by the INESSS, recommending the administration of corticosteroids to critically ill patients with COVID-19 in the province of Quebec (8,9). Only severe COVID-19 cases, as classified by the WHO Working Group on Clinical Characterization and Management of COVID-19 infection (18), were retained in this study, and all of them received corticosteroid therapy during hospitalization. Statistical Analysis Significance tests Baseline characteristics, medical history elements, physiological parameters, complications and treatments received during hospitalization were compared between patients who did and did not develop ARDS (see Table 1); separately these variables were compared between patients who died and patients who survived (Table 1). Furthermore, the groups of patients who did and did not develop ARDS were stratified by those who did and did not die (see Table 2). The full list of variables studied is presented in Table A.1 (supplemental material), while the most relevant variables are presented in Tables 1 and 2. Categorical variables are reported as percentage and continuous variables are reported as mean plus or minus standard deviation. Parametric Pearson’s chi-squared or non-parametric Fisher’s exact tests were used to compare categorical variables appropriately. Either the Two sample t-test, Welch’s two sample t-test or the Mann-Whitney-Wilcoxon test were used to compare continuous data. To control the false discovery rate, P-values were adjusted using the Benjamini-Hochberg method, with adjusted P < 0.05 considered statistically significant (19). Regression analysis Multivariable logistic regression models were developed to assess predictors of ARDS and mortality, with results expressed as odds ratios (OR) with 95% confidence intervals (CI). For each outcome, two models were constructed. The first models included clinically relevant variables available at hospital admission: demographic characteristics, comorbidities, and initial laboratory results (see Tables A.3, A.4, supplemental material for a complete list). The second models, built to validate the stability of initial findings, included demographic data and significant predictors identified in the first models (see Tables 3 & 4). All analyses were performed using Python and R statistical software. Results Demographics and clinical characteristics Among 317 patients (70.0 % male, mean age 63.6 ± 16.0 years), 138 (43.5 %) developed ARDS (see Table 1). While ARDS development was not associated with age or sex, mortality was significantly higher in older patients (73.2 ± 12.7 vs. 59.8 ± 15.5 years, adj. P-value = 0.0005). Logistic regression analysis confirmed age as a significant predictor of mortality (OR = 1.07, 95% CI [1.05-1.10], P-value < 0.001, Table 4), indicating a 7 % increase in mortality risk per year of age. Patients with ARDS had higher mortality (40.6 % vs. 19.0 %, adj. P-value < 0.0001) compared to patients without ARDS. Table 1 shows that patients who died had more comorbidities than survivors (5.4 ± 3.3 vs. 3.5 ± 2.7, adj. P-value = 0.0018), with significantly higher rates of cancer, chronic kidney disease, COPD, coronary artery disease, dementia, hypertension, hematological disease, prior myocardial infarction, and prior stroke (all adj. P-value < 0.04). Notably, obesity was more prevalent among survivors (23.2 % vs. 9.5 %, adj. P-value = 0.0223, Table 1), particularly in the ARDS group (32.1 % vs. 9.6 %, adj. P-value = 0.0373, Table 2). In multivariate analysis, prior myocardial infarction emerged as the only clinical comorbidity significantly associated with ARDS development (OR = 3.64, 95% CI [1.11-11.94], P-value = 0.033, Table 3), while previous lung disease was independently associated with mortality (OR = 2.44, 95% CI [1.04-5.74], P-value = 0.041, Table 4). No significant differences were found in medication use between groups (supplementary Table A.1). Laboratory results Laboratory values at hospital admission showed white blood cell counts elevated within normal limits across all groups (20), with ARDS patients having significantly higher neutrophil counts (8.3 ± 4.7 vs. 7.0 ± 4.4 x 10 9 /L, adj. P-value = 0.0455) but lower basophil counts (0.007 vs. 0.02 x10 9 /L, adj. P-value = 0.0096) compared to non-ARDS patients (Table 1). Logistic regression analysis confirmed the significance of basophil counts in ARDS development (OR = 5E-09, 95% CI [2.16E-15-0.012], P = 0.011), suggesting a strong inverse relationship. ARDS patients also exhibited higher glucose levels (10.2 ± 4.9 vs. 8.4 ± 4.1 mmol/L, adj. P-value = 0.0018). Creatinine levels were elevated above normal range in all groups, with higher levels observed in non-survivors compared to survivors (142.3 ± 107.6 vs. 118.1 ± 167.8 umol/L, adj. P-value = 0.0198, Table 1), particularly in the non-ARDS subgroup (154.8 ± 91.6 vs. 110.5 ± 161.4 umol/L, adj. P-value = 0.0036, Table 2). Complications during hospitalization ARDS patients experienced longer hospitalizations (34.8 ± 35.3 vs. 19.4 ± 22.1 days, adj. P-value = 0.0001) and intensive care unit (ICU) stays (25.2 ± 30.2 vs. 12.3 ± 16.8 days, adj. P-value = 0.0001) compared to non-ARDS patients, Table 1. While total hospital length was similar between survivors and non-survivors, ICU duration was significantly longer among non-survivors (27.5 ± 28.8 vs. 15.7 ± 23.4 days, adj. P-value = 0.0005), particularly in the non-ARDS subgroup (22.3 ± 24.0 vs. 10.0 ± 13.9 days, adj. P-value = 0.0009, Table 2). ARDS patients experienced more complications, notably acute kidney injury (AKI) (49.6 % vs. 20.2 %, adj. P-value = 0.0004). Non-survivors had higher rates of AKI (55.6 % vs. 24.0 %, adj. P-value < 0.0014) and cardiac arrest (9.0 % vs. 0.4 %, adj. P-value < 0.0014) compared to survivors. In subgroup analyses, among non-ARDS patients, AKI was more frequent in non-survivors compared to survivors (47.1 % vs. 13.9 %, adj. P-value = 0.0031), while among ARDS patients, cardiac arrest was more common in non-survivors compared to survivors (14.5 % vs. 1.2 %, adj. P-value = 0.0273). Treatments received during hospitalization All patients received oxygen therapy, with invasive mechanical ventilation (IMV) required more frequently in ARDS patients compared to non-ARDS patients (63.0 % vs. 20.7 %, adj. P-value = 0.0002, Table 1). IMV use was higher among non-survivors versus survivors (65.6 % vs. 28.6 %, adj. P-value = 0.0002, Table 1) in both non-ARDS (44.1 % vs. 15.2 %, adj. P-value ≤ 0.0182, Table 2) and ARDS subgroups (78.6 % vs. 52.4 %, adj. P-value ≤ 0.0182, Table 2). Discussion This retrospective study examined risk factors and clinical features associated with ARDS and mortality in COVID-19 patients treated with corticosteroids. Despite corticosteroid therapy, ARDS patients had more than double the mortality rate of non-ARDS patients, contributing to ongoing debates about optimal therapeutic approaches in COVID-19-associated ARDS ( 11 , 12 , 14 , 15 ). Notably, while previous studies identified age as a risk factor for both ARDS development and mortality ( 21 – 23 ), our analysis found age was not associated with ARDS development but was a powerful independent predictor of mortality (OR = 1.07 per year, 95% CI [1.05–1.10]). This suggests a 7% increase in mortality risk per year of age, highlighting age as a crucial prognostic factor in COVID-19 outcomes regardless of ARDS status. Our multivariate analysis also revealed that prior myocardial infarction was the sole clinical comorbidity significantly associated with ARDS development (OR = 3.64, 95% CI [1.11–11.94]), while previous lung disease emerged as an independent predictor of mortality (OR = 2.44, 95% CI [1.04–5.74]). While no other single comorbidity predicted ARDS development, aligning with meta-analysis findings by Tsai et al. ( 22 ), the total number of comorbidities was consistently higher among non-survivors. Notably, pre-admission obesity showed a protective association with survival, particularly in ARDS patients, potentially due to earlier respiratory support intervention ( 24 ). Disease-related weight loss during hospitalization, regardless of initial obesity status, may explain this finding, as acute weight loss in critical illness is independently associated with increased mortality ( 25 ). We note however the lack of body mass index (BMI) measurements during or after hospitalization in our study. Striking findings emerged when examining laboratory results upon hospitalization. Several significant associations with ARDS development were found in the differential white blood cell count. The presence of neutrophilia has been previously recognized as a risk factor for ARDS, with neutrophils being implicated in cytokine and chemokine production, as well as triggering cytokine storms that can lead to ARDS ( 23 ). Logistic regression analysis also identified basophil counts as significantly associated with ARDS development (OR = 5E-09, 95% CI [2.16E-15-0.012]), demonstrating a strong inverse relationship. This finding might initially appear counterintuitive, given that basophils are implicated in allergic reactions and immune responses. However, emerging evidence indicates that basophils play a specific role in amplifying the adaptive immune response to COVID-19 ( 26 – 28 ). A relatively elevated presence of basophils among patients who do not develop ARDS could indicate a balanced and appropriate immune response characterized by a reduction of excessive inflammation. Elevated admission glucose levels were significantly associated with ARDS development, consistent with previous cohort findings by Reiterer et al. ( 29 ). While hyperglycemia is common in critical illness ( 30 , 31 ), its presence in COVID-19 may reflect underlying pathological processes rather than treatment effects ( 32 ), as these measurements preceded corticosteroid administration. Although our study found no significant association between glucose levels and mortality in ARDS patients, others have reported hyperglycemia as a predictor of fatality in COVID-19-ARDS cases ( 33 ). Elevated creatinine levels on admission were uniquely predictive of mortality, particularly in non-ARDS patients. This finding, coupled with higher rates of acute kidney injury (AKI) during hospitalization in both ARDS and non-survivor groups, underscores the prognostic importance of renal function in COVID-19 outcomes ( 34 – 36 ). Clinical trajectories were notably worse for ARDS patients, characterized by longer hospital and ICU stays, with non-survivors showing extended ICU durations and higher complication rates. Finally, this study presents a few limitations that warrant consideration. First, the retrospective design and relatively modest subgroup sizes limit causal inference and generalizability. Second, we lack granular data regarding corticosteroid administration, including dosage, duration, and specific types used. Third, our study period spans roughly two years, during which viral strains likely varied. However, by focusing exclusively on severe cases requiring hospitalization, we maintained some uniformity in disease presentation. Despite these limitations, our findings, particularly regarding the role of basophils and the differential impact of comorbidities on ARDS versus mortality, generate important hypotheses for future investigation into COVID-19 pathogenesis and treatment optimization. Conclusions In conclusion, our study reveals important risk factors for adverse outcomes in COVID-19 patients receiving corticosteroid therapy. The identification of prior myocardial infarction as a predictor of ARDS development, and the strong inverse relationship between basophil counts and ARDS, suggest potential mechanisms in disease progression. While age was not associated with ARDS development, it emerged as a powerful predictor of mortality, along with previous lung disease. These findings may help clinicians identify high-risk patients and guide therapeutic decisions. Our results also highlight the complex interplay between baseline characteristics and COVID-19 outcomes despite standardized corticosteroid therapy. The differential impact of comorbidities on ARDS versus mortality could suggest distinct pathophysiological pathways that might require targeted therapeutic approaches. Particularly intriguing is the relationship between basophil counts and ARDS development, which could indicate a novel mechanism in COVID-19 immune response and potentially inform future therapeutic strategies. Abbreviations Adj. = Adjusted AKI = Acute kidney injury ARDS = Acute respiratory distress syndrome BMI = Body mass index (BMI) BQC19 = Biobanque québécoise de la COVID-19 CI = Confidence interval COPD = Chronic obstructive pulmonary disease (COPD) COVID-19 = Coronavirus disease 2019 ICU = Intensive care unit INESSS = National Institute for Excellence in Health and Social Services IMV = Invasive mechanical ventilation OR = Odds ratio WHO = World Health Organization Declarations Ethics approval and consent to participate Ethical approval for this work was obtained from the Research Ethics Committee of Centre intégré universitaire de santé et de services sociaux du Saguenay—Lac Saint-Jean (CIUSSS-SLSJ) (#2021-015). Consent for publication Not applicable. Availability of data and materials All data generated or analysed during this study are included in this published article [and its supplementary information files]. Competing interests The authors declare that they have no competing interests Funding This study was supported by the Programme de financement de projets équipes du Réseau de recherche en santé respiratoire du Québec (RSRQ) and a Team grant from the Funding Programs of the Quebec Respiratory Health Research Network (QRNH). Author contributions MA: Methodology, Software, Validation, Formal analysis, Data curation, Writing – Original Draft, Visualization; EF: Software, Formal analysis, Data curation, Writing – Review & Editing; SR : Conceptualization, Methodology, Validation, Data Curation, Writing – Review & Editing, Supervision, Project administration, Funding acquisition ; KT : Conceptualization, Methodology, Validation, Data Curation, Writing – Review & Editing, Supervision, Project administration, Funding acquisition. Acknowledgements This work was made possible through open sharing of data and sample from the Biobanque Québécoise COVID-19 (https://www.quebeccovidbiobank.ca), funded by the Fonds de recherche du Québec - Santé, Génome Québec and the Publich Health Agency of Canada. We thank all participants to BQC19 for their contribution. References Mathieu E, Ritchie H, Rodés-Guirao L, Appel C, Giattino C, Hasell J et al. Coronavirus Pandemic (COVID-19). Our World Data [Internet]. 2020 Mar 5 [cited 2024 Jun 27]; Available from: https://ourworldindata.org/coronavirus Wu J, Huang J, Zhu G, Liu Y, Xiao H, Zhou Q et al. Systemic corticosteroids and mortality in severe and critical COVID-19 patients in Wuhan, China. J Clin Endocrinol Metab. 2020;dgaa627. Rigby J, Satija B, Rigby J, Satija B. WHO declares end to COVID global health emergency. 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Hyperglycemia in acute COVID-19 is characterized by insulin resistance and adipose tissue infectivity by SARS-CoV-2. Cell Metab. 2021;33(11):2174–e21885. Marik PE, Bellomo R. Stress hyperglycemia: an essential survival response! Crit Care Lond Engl. 2013;17(2):305. den Berghe GV, Wouters P, Weekers F, Verwaest C, Bruyninckx F, Schetz M, et al. Intensive Insulin Therapy in Critically Ill Patients. N Engl J Med. 2001;345(19):1359–67. Apicella M, Campopiano MC, Mantuano M, Mazoni L, Coppelli A, Prato SD. COVID-19 in people with diabetes: understanding the reasons for worse outcomes. Lancet Diabetes Endocrinol. 2020;8(9):782–92. Lazzeri C, Bonizzoli M, Batacchi S, Di Valvasone S, Chiostri M, Peris A. The prognostic role of hyperglycemia and glucose variability in covid-related acute respiratory distress Syndrome. Diabetes Res Clin Pract. 2021;175:108789. Park BD, Faubel S. Acute Kidney Injury and Acute Respiratory Distress Syndrome. Crit Care Clin. 2021;37(4):835–49. Cheng Y, Luo R, Wang K, Zhang M, Wang Z, Dong L, et al. Kidney disease is associated with in-hospital death of patients with COVID-19. Kidney Int. 2020;97(5):829–38. Darmon M, Clec’h C, Adrie C, Argaud L, Allaouchiche B, Azoulay E, et al. Acute Respiratory Distress Syndrome and Risk of AKI among Critically Ill Patients. Clin J Am Soc Nephrol CJASN. 2014;9(8):1347–53. Tables Table 1. Patient data stratified by ARDS development and by mortality All ARDS Death Yes No Adj. Yes No Adj. n = 317 n = 138 n = 179 P-value [1] n = 90 n = 227 P-value a Patient characteristics Age, mean years (SD) 63.6 (16.0) 63.4 (15.4) 63.8 (16.4) 1.0000 73.2 (12.7) 59.8 (15.5) 0.0005 Sex, number of males (%) 222 (70.0) 99 (71.7) 123 (68.7) 0.7687 63 (70.0) 159 (70.0) 0.9938 Outcomes (n (%)) Death / ARDS 56 (40.6) 34 (19.0) <0.0001 56 (62.2) 82 (36.1) 0.0012 At hospital admission Comorbidities (n (%)) Total number (mean (SD)) 4.1 (3.0) 4.1 (3.0) 4.0 (3.0) 0.9812 5.4 (3.3) 3.5 (2.7) 0.0018 Cancer 42 (13.5) 15 (10.9) 27 (15.4) 0.8590 21 (23.3) 21 (9.2) 0.0063 CKD 46 (14.8) 21 (15.4) 25 (14.4) 0.9812 25 (27.8) 23 (10.2) 0.0018 COPD 35 (11.3) 14 (10.4) 21 (12.0) 0.9812 18 (20.0) 17 (7.6) 0.0063 CAD 48 (15.4) 22 (16.1) 26 (14.9) 0.9812 23 (25.6) 25 (11.0) 0.0063 Dementia 17 (5.5) 4 (2.9) 13 (7.5) 0.7434 11 (12.2) 6 (2.6) 0.0063 Diabetes 113 (36.5) 51 (37.5) 62 (35.6) 0.9812 40 (44.4) 74 (32.7) 0.0883 Hematological disease 23 (7.4) 10 (7.3) 13 (7.4) 1.0000 12 (13.3) 11 (4.8) 0.0240 Hypertension 167 (53.7) 79 (58.1) 88 (50.3) 0.7838 60 (67.4) 108 (47.4) 0.0063 Lung disease 30 (9.7) 13 (9.6) 17 (9.8) 1.0000 13 (14.9) 18 (7.9) 0.0898 MI 19 (6.1) 12 (8.8) 7 (4.0) 0.7434 10 (11.1) 9 (3.9) 0.0398 Obesity 60 (19.9) 31 (23.5) 29 (17.1) 0.7838 8 (9.5) 52 (23.2) 0.0223 Stroke 16 (5.2) 8 (5.9) 8 (4.6) 0.9812 10 (11.4) 6 (2.6) 0.0117 Lab results (mean (SD)) WBC count [x10 9 /L] 9.2 (5.5) 10.0 (5.9) 8.5 (5.0) 0.0731 9.8 (6.6) 8.9 (4.9) 0.6802 Basophile count [x10 9 /L] 0.01 (0.02) 0.007 (0.02) 0.02 (0.03) 0.0096 0.01 (0.03) 0.01 (0.02) 0.9407 Lymphocyte count [x10 9 /L] 0.9 (0.9) 0.9 (1.3) 0.8 (0.5) 0.6757 1.0 (1.6) 0.8 (0.5) 0.6802 Neutrophil count [x10 9 /L] 7.6 (4.5) 8.3 (4.7) 7.0 (4.4) 0.0455 7.9 (4.8) 7.5 (4.4) 0.6802 Creatinine [umol/L] 125.1 (153.2) 132.8 (154.3) 118.8 (152.6) 0.6738 142.3 (107.6) 118.1 (167.8) 0.0198 Glucose [mmol/L] 9.2 (4.5) 10.2 (4.9) 8.4 (4.1) 0.0018 9.7 (4.8) 8.9 (4.4) 0.4291 Sodium [mmol/L] 137.2 (5.1) 137.6 (5.4) 136.9 (4.8) 0.2158 137.6 (5.7) 137.1 (4.8) 0.6802 During hospitalization Hospitalization details Number of days hospitalized (mean (SD)) 26.1 (29.6) 34.8 (35.3) 19.4 (22.1) 0.0001 27.2 (26.8) 25.7 (30.6) 0.1004 ICU stay (n (%)) 238 (75.1) 128 (92.8) 110 (61.5) 0.0001 70 (77.8) 168 (74.0) 0.6225 Number of days in ICU (mean (SD)) 19.2 (25.6) 25.2 (30.2) 12.3 (16.8) 0.0001 27.5 (28.8) 15.7 (23.4) 0.0005 Complications – Other than ARDS (n (%)) AKI 104 (33.0) 68 (49.6) 36 (20.2) 0.0004 50 (55.6) 54 (24.0) 0.0012 Anemia 77 (24.4) 42 (30.7) 35 (19.6) 0.0583 30 (33.7) 47 (20.7) 0.0497 AF 28 (8.9) 20 (14.6) 8 (4.5) 0.0058 9 (10.1) 19 (8.4) 0.8468 Bacteremia 41 (13.0) 32 (23.5) 9 (5.0) 0.0004 17 (19.3) 24 (10.6) 0.0976 Cardiac arrest 9 (2.8) 9 (6.6) 0 (0) 0.0020 8 (9.0) 1 (0.4) 0.0014 Hyperglycemia 90 (28.8) 59 (43.4) 31 (17.5) 0.0004 28 (31.5) 62 (27.7) 0.7966 Hyponatremia 17 (5.4) 14 (10.2) 3 (1.7) 0.0032 6 (6.7) 11 (4.8) 0.8403 Pleural effusion 48 (15.2) 25 (18.2) 23 (12.8) 0.2920 22 (24.7) 26 (11.5) 0.0138 Pneumonia 85 (27.2) 58 (42.6) 27 (15.3) 0.0004 33 (37.5) 52 (23.1) 0.0359 Pneumothorax 21 (6.7) 15 (10.9) 6 (3.4) 0.0222 10 (11.2) 11 (4.9) 0.0977 PE 41 (13.0) 30 (21.9) 11 (6.1) 0.0004 12 (13.5) 29 (12.8) 1.0000 Rhabdomyolysis 7 (2.2) 6 (4.4) 1 (0.6) 0.0895 6 (6.8) 1 (0.4) 0.0127 Stroke 6 (1.9) 3 (2.2) 3 (1.7) 1.0000 5 (5.7) 1 (0.4) 0.0288 VT 9 (2.9) 7 (5.1) 2 (1.1) 0.0895 7 (8.0) 2 (0.9) 0.0127 Non-drug interventions administered O2 therapy (n (%)) 310 (100.0) 137 (100.0) 173 (100.0) N/A 88 (100.0) 222 (100.0) N/A Number of days O2 therapy (mean (SD)) 21.0 (27.7) 30.9 (34.9) 14.0 (18.4) 0.0002 27.5 (29.3) 18.5 (26.7) 0.0002 IMV (n (%)) 124 (39.1) 87 (63.0) 37 (20.7) 0.0002 59 (65.6) 65 (28.6) 0.0002 Table 2. Patient data stratified by ARDS development then by progression to death ARDS No ARDS n = 138 n = 179 Survived Died Adj. Survived Died Adj. n = 82 n = 56 P-value [2] n = 145 n = 34 P-value c Patient characteristics Age, mean years (SD) 58.2 (14.9) 71.1 (12.7) 0.0008 60.7 (15.9) 76.7 (12.0) 0.0009 Sex, number of males (%) 60 (73.2) 39 (69.6) 0.6513 99 (68.3) 24 (70.6) 0.9312 At admission Comorbidities (n (%)) Total number (mean (SD)) 3.4 (2.5) 5.2 (3.3) 0.0373 3.6 (2.8) 5.7 (3.1) 0.0027 Cancer 4 (4.9) 11 (19.6) 0.0434 17 (11.7) 10 (29.4) 0.0366 CKD 8 (9.9) 14 (25.0) 0.0963 14 (9.7) 11 (32.4) 0.0115 COPD 5 (6.3) 9 (16.1) 0.1910 12 (8.3) 9 (26.5) 0.0311 CAD 7 (8.5) 15 (26.8) 0.0373 18 (12.4) 8 (23.5) 0.2448 Dementia 2 (2.4) 2 (3.6) 1.0000 4 (2.8) 9 (26.5) 0.0027 Hypertension 43 (52.4) 36 (65.5) 0.2698 65 (44.8) 24 (70.6) 0.0311 Obesity 26 (32.1) 5 (9.6) 0.0373 26 (18.3) 3 (9.4) 0.3969 Stroke 4 (4.9) 4 (7.3) 0.7992 2 (1.4) 6 (18.2) 0.0054 Lab results (mean (SD)) Creatinine [umol/L] 132.3 (175.6) 135.3 (115.9) 0.9142 110.5 (161.4) 154.8 (91.6) 0.0036 During hospitalization Hospitalization details Number of days (mean (SD)) 37.8 (38.7) 30.5 (29.3) 0.8580 18.8 (22.4) 21.7 (21.3) 0.3404 ICU stay (n (%)) 78 (95.1) 50 (89.3) 0.5865 90 (62.1) 20 (58.8) 0.7264 Number of days in ICU (mean (SD)) 22.4 (29.8) 29.6 (30.5) 0.0527 10.0 (13.9) 22.3 (24.0) 0.0009 Complications (n (%)) AKI 34 (42.0) 34 (60.7) 0.1447 20 (13.9) 16 (47.1) 0.0031 Arrest 1 (1.2) 8 (14.5) 0.0273 0 (0.0) 0 (0.0) NA Pleural effusion 13 (15.9) 12 (21.8) 0.6510 13 (9.0) 10 (29.4) 0.0341 Non-drug interventions administered O2 therapy 82 (100.0) 55 (100.0) NA 140 (100.0) 33 (100.0) NA Number of days O2 therapy (mean (SD)) 30.9 (36.0) 30.8 (33.7) 1.0000 12.3 (17.8) 22.0 (19.3) 0.0072 IMV (n (%)) 43 (52.4) 44 (78.6) 0.0182 22 (15.2) 15 (44.1) 0.0036 Table 3. Multivariate logistic regression results on the association between ARDS development and clinical features Features Odds ratios P-values 95% Confidence intervals Significance Intercept 0.005 0.134 [0 - 5.279] Sex 0.763 0.342 [0.437 - 1.332] Age 0.995 0.533 [0.98 - 1.011] MI 3.636 0.033 [1.108 - 11.936] * Basophil count 0 0.011 [0 - 0.012] * Sodium 1.043 0.113 [0.99 - 1.098] Table 4. Multivariate logistic regression results on the association between mortality and clinical features Features Odds ratio P-value 95% Confidence intervals Significance Intercept 0.003 0 [0.001 - 0.014] *** Sex 1.019 0.951 [0.559 - 1.856] Age 1.074 0 [1.051 - 1.098] *** Lung disease 2.437 0.041 [1.035 - 5.738] * [1] P-values adjusted with the Benjamini-Hochberg method and adjusted P-values of less than 0.05 were considered statistically significant (19). Parametric Pearson’s chi-squared or non-parametric Fisher’s exact tests were used to compare categorical variables appropriately. Either the Two sample t-test, Welch’s two sample t-test or the Mann-Whitney-Wilcoxon test were used to compare continuous data. [2] P-values adjusted with the Benjamini-Hochberg method and adjusted P-values of less than 0.05 were considered statistically significant (19). Parametric Pearson’s chi-squared or non-parametric Fisher’s exact tests were used to compare categorical variables appropriately. Either the Two sample t-test, Welch’s two sample t-test or the Mann-Whitney-Wilcoxon test were used to compare continuous data. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6384044","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":456922507,"identity":"797a5c31-18d4-49fd-8963-aba16de0f5d0","order_by":0,"name":"Madeleine Anthonisen","email":"","orcid":"","institution":"Université de Sherbrooke","correspondingAuthor":false,"prefix":"","firstName":"Madeleine","middleName":"","lastName":"Anthonisen","suffix":""},{"id":456922509,"identity":"a791bd95-ba35-443e-bca0-e6993a244bde","order_by":1,"name":"Elliot Fortin","email":"","orcid":"","institution":"Université de Sherbrooke","correspondingAuthor":false,"prefix":"","firstName":"Elliot","middleName":"","lastName":"Fortin","suffix":""},{"id":456922511,"identity":"a605e5ba-8ea0-4c2c-8d54-ad630f32bb1e","order_by":2,"name":"Simon Rousseau","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Simon","middleName":"","lastName":"Rousseau","suffix":""},{"id":456922513,"identity":"a7d308ab-9a4e-47fa-bb80-e8e3b6ca1a61","order_by":3,"name":"Karine Tremblay","email":"data:image/png;base64,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","orcid":"","institution":"Université de Sherbrooke","correspondingAuthor":true,"prefix":"","firstName":"Karine","middleName":"","lastName":"Tremblay","suffix":""}],"badges":[],"createdAt":"2025-04-05 22:53:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6384044/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6384044/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83041222,"identity":"fcef2a37-60f9-4910-8e91-f02f1dad9e49","added_by":"auto","created_at":"2025-05-19 10:44:42","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":65911,"visible":true,"origin":"","legend":"\u003cp\u003eA flowchart summarizing inclusion criteria of patients in this retrospective observational study. We retained 317 patients and show data segmented by those who developed ARDS (138 patients) and those who did not (179 patients). We further stratified the data by those who survived and those who did not within both groups.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6384044/v1/dbcc60bc3bf1f91af66f9420.jpg"},{"id":83041885,"identity":"316b970a-77d4-4c33-b0e7-2111467322e9","added_by":"auto","created_at":"2025-05-19 10:52:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1415272,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6384044/v1/95084476-30d2-45dd-a3b2-4902367fabcc.pdf"},{"id":83039334,"identity":"61928455-49c5-44f6-98ee-31f93abf8adf","added_by":"auto","created_at":"2025-05-19 10:36:42","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":81481,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarymaterial30032025.docx","url":"https://assets-eu.researchsquare.com/files/rs-6384044/v1/f2295b6c7499b2f186b2f269.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinical characteristics associated with ARDS and mortality in patients with COVID-19 who received corticosteroid therapy","fulltext":[{"header":"Background","content":"\u003cp\u003eCOVID-19 has caused more than 7\u0026nbsp;million deaths worldwide (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), with severe and critical cases at the greatest risk of mortality (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Although the World Health Organization (WHO) declared that the outbreak no longer constituted a public health emergency of international concern as of May 5th, 2023 (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e), risks of viral exposure, disease severity and adverse outcomes remain significant among certain populations. Effective treatments for patients with severe and critical COVID-19 are thus essential.\u003c/p\u003e \u003cp\u003eThe link between corticosteroid therapy and reduced mortality in patients with severe COVID-19 has been established in the literature (\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The WHO recommends the administration of systemic corticosteroid therapy to patients with severe and critical COVID-19 (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The National Institute for Excellence in Health and Social Services (INESSS, Quebec, Canada) guidelines also advocate for the utilization of corticosteroid therapy to manage COVID-19 and COVID-19-associated ARDS (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Moreover, corticosteroid therapy has been shown to reduce mortality in patients with COVID-19-associated ARDS (\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) as well as to reduce the risk of ARDS development in patients with COVID-19 (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite substantial evidence of an association between systemic corticosteroid therapy and reduced mortality in patients with severe and critical COVID-19, the use of corticosteroids to treat infections has been controversial (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Some studies show that systemic corticosteroid therapy failed to prevent the negative outcomes of severe or critical COVID-19, namely mortality (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), ARDS (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), and mortality following COVID-19-related ARDS (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), in certain patients. Understanding which factors, including those relating to patient demographics, disease progression, and medical interventions, are associated with negative outcomes of COVID-19 is thus imperative to diminishing mortality and ARDS in all patient populations.\u003c/p\u003e \u003cp\u003eUsing data from a multi-center retrospective cohort study encompassing 317 patients afflicted with severe COVID-19, who underwent hospitalization and received corticosteroid treatment in Quebec, Canada, spanning August 3rd, 2020, to September 24th, 2022 (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), we delved into the intricate relationships between diverse risk factors, clinical attributes, and critical outcomes, such as ARDS and mortality. This study compares the profiles of patients who did and did not develop ARDS as well as the profiles of patients who did and did not survive. This study also examines the progression to mortality in groups that did and did not experience ARDS. We present patient demographics, comorbidities, laboratory results at hospital admission, as well as details concerning hospitalization. We identified risk factors associated with ARDS and with mortality. Since all patients in this study received corticosteroid therapy, our results reflect factors that may be responsible for adverse outcomes despite the indicated therapy, as well as the interplay of these factors and corticosteroids.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003ch2\u003e\u003cstrong\u003eStudy Population\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThis retrospective observational study includes data from 317 patients diagnosed with COVID-19 and hospitalized in Quebec, Canada between 3\u003csup\u003erd\u003c/sup\u003e August 2020 and 24\u003csup\u003eth\u003c/sup\u003e September 2022. Data, including biological samples and clinical information, were obtained from the \u003cem\u003eBiobanque québécoise de la COVID-19\u003c/em\u003e (BQC19, https://www.quebeccovidbiobank.ca), a multi-center initiative composed of 10 hospitals and 5 academic institutions in Quebec (16). COVID-19 status was determined by a PCR test and only positive cases were considered in this study. The New Global Definition was used to diagnose ARDS (17).\u003c/p\u003e\n\u003cp\u003eCriteria for patient inclusion are summarized in Figure 1. From a total of 6120 patients in the BQC19 cohort, those under 18 or with missing information were removed from consideration. Patients who were taking corticosteroids prior to hospitalization were also removed from consideration, as one of the aims of this study was to investigate the impact of corticosteroids on patients with COVID-19. Also, to this end, patients considered were diagnosed after 3\u003csup\u003erd\u003c/sup\u003e August, 2020. This is the date new guidelines were issued by the INESSS, recommending the administration of corticosteroids to critically ill patients with COVID-19 in the province of Quebec (8,9). Only severe COVID-19 cases, as classified by the WHO Working Group on Clinical Characterization and Management of COVID-19 infection (18), were retained in this study, and all of them received corticosteroid therapy during hospitalization.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003e\u003cem\u003eSignificance tests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eBaseline characteristics, medical history elements, physiological parameters, complications and treatments received during hospitalization were compared between patients who did and did not develop ARDS (see Table 1); separately these variables were compared between patients who died and patients who survived (Table 1). Furthermore, the groups of patients who did and did not develop ARDS were stratified by those who did and did not die (see Table 2). The full list of variables studied is presented in Table A.1 (supplemental material), while the most relevant variables are presented in Tables 1 and 2. Categorical variables are reported as percentage and continuous variables are reported as mean plus or minus standard deviation. Parametric Pearson’s chi-squared or non-parametric Fisher’s exact tests were used to compare categorical variables appropriately. Either the Two sample t-test, Welch’s two sample t-test or the Mann-Whitney-Wilcoxon test were used to compare continuous data. To control the false discovery rate, P-values were adjusted using the Benjamini-Hochberg method, with adjusted P \u0026lt; 0.05 considered statistically significant (19).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eRegression analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMultivariable logistic regression models were developed to assess predictors of ARDS and mortality, with results expressed as odds ratios (OR) with 95% confidence intervals (CI). For each outcome, two models were constructed. The first models included clinically relevant variables available at hospital admission: demographic characteristics, comorbidities, and initial laboratory results (see Tables A.3, A.4, supplemental material for a complete list). The second models, built to validate the stability of initial findings, included demographic data and significant predictors identified in the first models (see Tables 3 \u0026amp; 4). All analyses were performed using Python and R statistical software.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eDemographics and clinical characteristics\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong 317 patients (70.0 % male, mean age 63.6 \u0026plusmn; 16.0 years), 138 (43.5 %) developed ARDS (see Table 1). While ARDS development was not associated with age or sex, mortality was significantly higher in older patients (73.2 \u0026plusmn; 12.7 vs. 59.8 \u0026plusmn; 15.5 years, adj. P-value = 0.0005). Logistic regression analysis confirmed age as a significant predictor of mortality (OR = 1.07, 95% CI [1.05-1.10], P-value \u0026lt; 0.001, Table 4), indicating a 7 % increase in mortality risk per year of age. Patients with ARDS had higher mortality (40.6 % vs. 19.0 %, adj. P-value \u0026lt; 0.0001) compared to patients without ARDS.\u003c/p\u003e\n\u003cp\u003eTable 1 shows that patients who died had more comorbidities than survivors (5.4 \u0026plusmn; 3.3 vs. 3.5 \u0026plusmn; 2.7, adj. P-value = 0.0018), with significantly higher rates of cancer, chronic kidney disease, COPD, coronary artery disease, dementia, hypertension, hematological disease, prior myocardial infarction, and prior stroke (all adj. P-value \u0026lt; 0.04). Notably, obesity was more prevalent among survivors (23.2 % vs. 9.5 %, adj. P-value = 0.0223, Table 1), particularly in the ARDS group (32.1 % vs. 9.6 %, adj. P-value = 0.0373, Table 2). In multivariate analysis, prior myocardial infarction emerged as the only clinical comorbidity significantly associated with ARDS development (OR = 3.64, 95% CI [1.11-11.94], P-value = 0.033, Table 3), while previous lung disease was independently associated with mortality (OR = 2.44, 95% CI [1.04-5.74], P-value = 0.041, Table 4). No significant differences were found in medication use between groups (supplementary Table A.1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLaboratory results\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLaboratory values at hospital admission showed white blood cell counts elevated within normal limits across all groups (20), with ARDS patients having significantly higher neutrophil counts (8.3 \u0026plusmn; 4.7 vs. 7.0 \u0026plusmn; 4.4 x 10\u003csup\u003e9\u003c/sup\u003e/L, adj. P-value = 0.0455) but lower basophil counts (0.007 vs. 0.02 x10\u003csup\u003e9\u003c/sup\u003e/L, adj. P-value = 0.0096) compared to non-ARDS patients (Table 1). Logistic regression analysis confirmed the significance of basophil counts in ARDS development (OR = 5E-09, 95% CI [2.16E-15-0.012], P = 0.011), suggesting a strong inverse relationship. ARDS patients also exhibited higher glucose levels (10.2 \u0026plusmn; 4.9 vs. 8.4 \u0026plusmn; 4.1 mmol/L, adj. P-value = 0.0018). Creatinine levels were elevated above normal range in all groups, with higher levels observed in non-survivors compared to survivors (142.3 \u0026plusmn; 107.6 vs. 118.1 \u0026plusmn; 167.8 umol/L, adj. P-value = 0.0198, Table 1), particularly in the non-ARDS subgroup (154.8 \u0026plusmn; 91.6 vs. 110.5 \u0026plusmn; 161.4 umol/L, adj. P-value = 0.0036, Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComplications during hospitalization\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eARDS patients experienced longer hospitalizations (34.8 \u0026plusmn; 35.3 vs. 19.4 \u0026plusmn; 22.1 days, adj. P-value = 0.0001) and intensive care unit (ICU) stays (25.2 \u0026plusmn; 30.2 vs. 12.3 \u0026plusmn; 16.8 days, adj. P-value = 0.0001) compared to non-ARDS patients, Table 1. While total hospital length was similar between survivors and non-survivors, ICU duration was significantly longer among non-survivors (27.5 \u0026plusmn; 28.8 vs. 15.7 \u0026plusmn; 23.4 days, adj. P-value = 0.0005), particularly in the non-ARDS subgroup (22.3 \u0026plusmn; 24.0 vs. 10.0 \u0026plusmn; 13.9 days, adj. P-value = 0.0009, Table 2).\u003c/p\u003e\n\u003cp\u003eARDS patients experienced more complications, notably acute kidney injury (AKI) (49.6 % vs. 20.2 %, adj. P-value = 0.0004). Non-survivors had higher rates of AKI (55.6 % vs. 24.0 %, adj. P-value \u0026lt; 0.0014) and cardiac arrest (9.0 % vs. 0.4 %, adj. P-value \u0026lt; 0.0014) compared to survivors. In subgroup analyses, among non-ARDS patients, AKI was more frequent in non-survivors compared to survivors (47.1 % vs. 13.9 %, adj. P-value = 0.0031), while among ARDS patients, cardiac arrest was more common in non-survivors compared to survivors (14.5 % vs. 1.2 %, adj. P-value = 0.0273).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTreatments received during hospitalization\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll patients received oxygen therapy, with invasive mechanical ventilation (IMV) required more frequently in ARDS patients compared to non-ARDS patients (63.0 % vs. 20.7 %, adj. P-value = 0.0002, Table 1). IMV use was higher among non-survivors versus survivors (65.6 % vs. 28.6 %, adj. P-value = 0.0002, Table 1) in both non-ARDS (44.1 % vs. 15.2 %, adj. P-value \u0026le; 0.0182, Table 2) and ARDS subgroups (78.6 % vs. 52.4 %, adj. P-value \u0026le; 0.0182, Table 2). \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis retrospective study examined risk factors and clinical features associated with ARDS and mortality in COVID-19 patients treated with corticosteroids. Despite corticosteroid therapy, ARDS patients had more than double the mortality rate of non-ARDS patients, contributing to ongoing debates about optimal therapeutic approaches in COVID-19-associated ARDS (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNotably, while previous studies identified age as a risk factor for both ARDS development and mortality (\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), our analysis found age was not associated with ARDS development but was a powerful independent predictor of mortality (OR\u0026thinsp;=\u0026thinsp;1.07 per year, 95% CI [1.05\u0026ndash;1.10]). This suggests a 7% increase in mortality risk per year of age, highlighting age as a crucial prognostic factor in COVID-19 outcomes regardless of ARDS status. Our multivariate analysis also revealed that prior myocardial infarction was the sole clinical comorbidity significantly associated with ARDS development (OR\u0026thinsp;=\u0026thinsp;3.64, 95% CI [1.11\u0026ndash;11.94]), while previous lung disease emerged as an independent predictor of mortality (OR\u0026thinsp;=\u0026thinsp;2.44, 95% CI [1.04\u0026ndash;5.74]). While no other single comorbidity predicted ARDS development, aligning with meta-analysis findings by Tsai et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), the total number of comorbidities was consistently higher among non-survivors. Notably, pre-admission obesity showed a protective association with survival, particularly in ARDS patients, potentially due to earlier respiratory support intervention (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Disease-related weight loss during hospitalization, regardless of initial obesity status, may explain this finding, as acute weight loss in critical illness is independently associated with increased mortality (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). We note however the lack of body mass index (BMI) measurements during or after hospitalization in our study.\u003c/p\u003e \u003cp\u003eStriking findings emerged when examining laboratory results upon hospitalization. Several significant associations with ARDS development were found in the differential white blood cell count. The presence of neutrophilia has been previously recognized as a risk factor for ARDS, with neutrophils being implicated in cytokine and chemokine production, as well as triggering cytokine storms that can lead to ARDS (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Logistic regression analysis also identified basophil counts as significantly associated with ARDS development (OR\u0026thinsp;=\u0026thinsp;5E-09, 95% CI [2.16E-15-0.012]), demonstrating a strong inverse relationship. This finding might initially appear counterintuitive, given that basophils are implicated in allergic reactions and immune responses. However, emerging evidence indicates that basophils play a specific role in amplifying the adaptive immune response to COVID-19 (\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). A relatively elevated presence of basophils among patients who do not develop ARDS could indicate a balanced and appropriate immune response characterized by a reduction of excessive inflammation.\u003c/p\u003e \u003cp\u003eElevated admission glucose levels were significantly associated with ARDS development, consistent with previous cohort findings by Reiterer et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). While hyperglycemia is common in critical illness (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), its presence in COVID-19 may reflect underlying pathological processes rather than treatment effects (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), as these measurements preceded corticosteroid administration. Although our study found no significant association between glucose levels and mortality in ARDS patients, others have reported hyperglycemia as a predictor of fatality in COVID-19-ARDS cases (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eElevated creatinine levels on admission were uniquely predictive of mortality, particularly in non-ARDS patients. This finding, coupled with higher rates of acute kidney injury (AKI) during hospitalization in both ARDS and non-survivor groups, underscores the prognostic importance of renal function in COVID-19 outcomes (\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Clinical trajectories were notably worse for ARDS patients, characterized by longer hospital and ICU stays, with non-survivors showing extended ICU durations and higher complication rates.\u003c/p\u003e \u003cp\u003eFinally, this study presents a few limitations that warrant consideration. First, the retrospective design and relatively modest subgroup sizes limit causal inference and generalizability. Second, we lack granular data regarding corticosteroid administration, including dosage, duration, and specific types used. Third, our study period spans roughly two years, during which viral strains likely varied. However, by focusing exclusively on severe cases requiring hospitalization, we maintained some uniformity in disease presentation. Despite these limitations, our findings, particularly regarding the role of basophils and the differential impact of comorbidities on ARDS versus mortality, generate important hypotheses for future investigation into COVID-19 pathogenesis and treatment optimization.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, our study reveals important risk factors for adverse outcomes in COVID-19 patients receiving corticosteroid therapy. The identification of prior myocardial infarction as a predictor of ARDS development, and the strong inverse relationship between basophil counts and ARDS, suggest potential mechanisms in disease progression. While age was not associated with ARDS development, it emerged as a powerful predictor of mortality, along with previous lung disease. These findings may help clinicians identify high-risk patients and guide therapeutic decisions.\u003c/p\u003e \u003cp\u003eOur results also highlight the complex interplay between baseline characteristics and COVID-19 outcomes despite standardized corticosteroid therapy. The differential impact of comorbidities on ARDS versus mortality could suggest distinct pathophysiological pathways that might require targeted therapeutic approaches. Particularly intriguing is the relationship between basophil counts and ARDS development, which could indicate a novel mechanism in COVID-19 immune response and potentially inform future therapeutic strategies.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAdj. = Adjusted\u003c/p\u003e\n\u003cp\u003eAKI = Acute kidney injury\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eARDS = Acute respiratory distress syndrome\u003c/p\u003e\n\u003cp\u003eBMI = Body mass index (BMI)\u003c/p\u003e\n\u003cp\u003eBQC19 = \u003cem\u003eBiobanque qu\u0026eacute;b\u0026eacute;coise de la COVID-19\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCI = Confidence interval\u003c/p\u003e\n\u003cp\u003eCOPD = Chronic obstructive pulmonary disease (COPD)\u003c/p\u003e\n\u003cp\u003eCOVID-19 = Coronavirus disease 2019\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eICU = Intensive care unit\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eINESSS = National Institute for Excellence in Health and Social Services\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIMV = Invasive mechanical ventilation\u003c/p\u003e\n\u003cp\u003eOR = Odds ratio\u003c/p\u003e\n\u003cp\u003eWHO = World Health Organization\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eEthical approval for this work was obtained from the Research Ethics Committee of Centre intégré universitaire de santé et de services sociaux du Saguenay—Lac Saint-Jean (CIUSSS-SLSJ) (#2021-015).\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article [and its supplementary information files].\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThis study was supported by the Programme de financement de projets équipes du Réseau de recherche en santé respiratoire du Québec (RSRQ) and a Team grant from the Funding Programs of the Quebec Respiratory Health Research Network (QRNH).\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eMA:\u003c/strong\u003e Methodology, Software, Validation, Formal analysis, Data curation, Writing – Original Draft, Visualization; \u003cstrong\u003eEF:\u0026nbsp;\u003c/strong\u003eSoftware, Formal analysis, Data curation, Writing – Review \u0026amp; Editing;\u003cstrong\u003e\u0026nbsp;SR\u003c/strong\u003e: Conceptualization, Methodology, Validation, Data Curation, Writing – Review \u0026amp; Editing, Supervision, Project administration, Funding acquisition\u003cstrong\u003e; KT\u003c/strong\u003e: Conceptualization, Methodology, Validation, Data Curation, Writing – Review \u0026amp; Editing, Supervision, Project administration, Funding acquisition.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThis work was made possible through open sharing of data and sample from the Biobanque Québécoise COVID-19 (https://www.quebeccovidbiobank.ca), funded by the Fonds de recherche du Québec - Santé, Génome Québec and the Publich Health Agency of Canada. 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Stress hyperglycemia: an essential survival response! Crit Care Lond Engl. 2013;17(2):305.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eden Berghe GV, Wouters P, Weekers F, Verwaest C, Bruyninckx F, Schetz M, et al. Intensive Insulin Therapy in Critically Ill Patients. N Engl J Med. 2001;345(19):1359\u0026ndash;67.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eApicella M, Campopiano MC, Mantuano M, Mazoni L, Coppelli A, Prato SD. COVID-19 in people with diabetes: understanding the reasons for worse outcomes. Lancet Diabetes Endocrinol. 2020;8(9):782\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLazzeri C, Bonizzoli M, Batacchi S, Di Valvasone S, Chiostri M, Peris A. The prognostic role of hyperglycemia and glucose variability in covid-related acute respiratory distress Syndrome. Diabetes Res Clin Pract. 2021;175:108789.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark BD, Faubel S. Acute Kidney Injury and Acute Respiratory Distress Syndrome. Crit Care Clin. 2021;37(4):835\u0026ndash;49.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCheng Y, Luo R, Wang K, Zhang M, Wang Z, Dong L, et al. Kidney disease is associated with in-hospital death of patients with COVID-19. Kidney Int. 2020;97(5):829\u0026ndash;38.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDarmon M, Clec\u0026rsquo;h C, Adrie C, Argaud L, Allaouchiche B, Azoulay E, et al. Acute Respiratory Distress Syndrome and Risk of AKI among Critically Ill Patients. Clin J Am Soc Nephrol CJASN. 2014;9(8):1347\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003ch3\u003e\u003cstrong\u003eTable 1. Patient data stratified by ARDS development and by mortality\u003c/strong\u003e\u003c/h3\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 219px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eARDS\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDeath\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cem\u003eAdj.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cem\u003eAdj.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en = 317\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en = 138\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en = 179\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003cstrong\u003e\u003csup\u003e[1]\u003c/sup\u003e\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en = 90\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en = 227\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003csup\u003ea\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 183px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatient characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eAge, mean years (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e63.6 (16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e63.4 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e63.8 (16.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e73.2 (12.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e59.8 (15.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eSex, number of males (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e222 (70.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e99 (71.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e123 (68.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.7687\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e63 (70.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e159 (70.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.9938\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 183px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutcomes (n (%))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eDeath / ARDS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e56 (40.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e34 (19.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e56 (62.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e82 (36.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 183px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eAt hospital admission\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 183px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities (n (%))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eTotal number (mean (SD))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e4.1 (3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e4.1 (3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e4.0 (3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.9812\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e5.4 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e3.5 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eCancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e42 (13.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e15 (10.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e27 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.8590\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e21 (23.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e21 (9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eCKD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e46 (14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e21 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e25 (14.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.9812\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e25 (27.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e23 (10.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eCOPD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e35 (11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e14 (10.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e21 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.9812\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e18 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e17 (7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eCAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e48 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e22 (16.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e26 (14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.9812\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e23 (25.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e25 (11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eDementia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e17 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e4 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e13 (7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.7434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e11 (12.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e6 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eDiabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e113 (36.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e51 (37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e62 (35.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.9812\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e40 (44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e74 (32.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0883\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eHematological disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e23 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e10 (7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e13 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e12 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e11 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0240\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e167 (53.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e79 (58.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e88 (50.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.7838\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e60 (67.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e108 (47.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eLung disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e30 (9.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e13 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e17 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e13 (14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e18 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0898\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e19 (6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e12 (8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e7 (4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.7434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e10 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e9 (3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0398\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e60 (19.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e31 (23.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e29 (17.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.7838\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e8 (9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e52 (23.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0223\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eStroke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e16 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e8 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e8 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.9812\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e10 (11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e6 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0117\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 183px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLab results (mean (SD))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eWBC count [x10\u003csup\u003e9\u003c/sup\u003e/L]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e9.2 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e10.0 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e8.5 (5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.0731\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e9.8 (6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e8.9 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.6802\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eBasophile count [x10\u003csup\u003e9\u003c/sup\u003e/L]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.01 (0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e0.007 (0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e0.02 (0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.0096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e0.01 (0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e0.01 (0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.9407\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eLymphocyte count [x10\u003csup\u003e9\u003c/sup\u003e/L]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.9 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e0.9 (1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e0.8 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.6757\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e1.0 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e0.8 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.6802\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eNeutrophil count [x10\u003csup\u003e9\u003c/sup\u003e/L]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e7.6 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e8.3 (4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e7.0 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.0455\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e7.9 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e7.5 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.6802\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eCreatinine [umol/L]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e125.1 (153.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e132.8 (154.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e118.8 (152.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.6738\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e142.3 (107.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e118.1 (167.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0198\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eGlucose [mmol/L]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e9.2 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e10.2 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e8.4 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.0018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e9.7 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e8.9 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.4291\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eSodium [mmol/L]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e137.2 (5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e137.6 (5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e136.9 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.2158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e137.6 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e137.1 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.6802\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 183px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eDuring hospitalization\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 183px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospitalization details\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eNumber of days hospitalized (mean (SD))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e26.1 (29.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e34.8 (35.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e19.4 (22.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e27.2 (26.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e25.7 (30.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.1004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eICU stay\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(n (%))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e238 (75.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e128 (92.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e110 (61.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e70 (77.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e168 (74.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.6225\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eNumber of days in ICU\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(mean (SD))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e19.2 (25.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e25.2 (30.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e12.3 (16.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e27.5 (28.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e15.7 (23.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\" style=\"width: 343px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComplications \u0026ndash; Other than ARDS (n (%))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eAKI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e104 (33.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e68 (49.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e36 (20.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.0004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e50 (55.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e54 (24.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eAnemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e77 (24.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e42 (30.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e35 (19.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.0583\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e30 (33.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e47 (20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0497\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eAF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e28 (8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e20 (14.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e8 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.0058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e9 (10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e19 (8.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.8468\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eBacteremia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e41 (13.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e32 (23.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e9 (5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.0004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e17 (19.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e24 (10.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0976\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eCardiac arrest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e9 (2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e9 (6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.0020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e8 (9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e1 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eHyperglycemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e90 (28.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e59 (43.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e31 (17.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.0004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e28 (31.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e62 (27.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.7966\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eHyponatremia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e17 (5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e14 (10.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e3 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.0032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e6 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e11 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.8403\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ePleural effusion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e48 (15.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e25 (18.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e23 (12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.2920\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e22 (24.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e26 (11.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0138\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ePneumonia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e85 (27.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e58 (42.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e27 (15.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.0004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e33 (37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e52 (23.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0359\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ePneumothorax\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e21 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e15 (10.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e6 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.0222\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e10 (11.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e11 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0977\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003ePE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e41 (13.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e30 (21.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e11 (6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.0004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e12 (13.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e29 (12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eRhabdomyolysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e7 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e6 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e1 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.0895\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e6 (6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e1 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0127\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eStroke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e6 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e3 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e3 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e5 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e1 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0288\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eVT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e9 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e7 (5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e2 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.0895\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e7 (8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e2 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0127\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-drug interventions administered\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eO2 therapy\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(n (%))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e310 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e137 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e173 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e88 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e222 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eNumber of days O2 therapy (mean (SD))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e21.0 (27.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e30.9 (34.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e14.0 (18.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.0002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e27.5 (29.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e18.5 (26.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eIMV (n (%))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e124 (39.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e87 (63.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e37 (20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.0002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e59 (65.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e65 (28.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.0002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eTable 2. Patient data stratified by ARDS development then by progression to death\u003c/strong\u003e\u003c/h3\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"600\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 39.8333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eARDS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 39%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo ARDS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 39.8333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003en = 138\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 39%;\"\u003e\n \u003cp\u003e\u003cstrong\u003en = 179\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurvived\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDied\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9%;\"\u003e\n \u003cp\u003e\u003cem\u003eAdj.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurvived\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDied\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cem\u003eAdj.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en = 82\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en = 56\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9%;\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003cstrong\u003e\u003csup\u003e[2]\u003c/sup\u003e\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003en = 145\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en = 34\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cem\u003eP-value\u003csup\u003ec\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 219px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatient characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eAge, mean years (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e58.2 (14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e71.1 (12.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\n \u003cp\u003e0.0008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e60.7 (15.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e76.7 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.0009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eSex, number of males (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e60 (73.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e39 (69.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\n \u003cp\u003e0.6513\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e99 (68.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e24 (70.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.9312\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eAt admission\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 219px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities (n (%))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eTotal number (mean (SD))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e3.4 (2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e5.2 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\n \u003cp\u003e0.0373\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e3.6 (2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e5.7 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.0027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eCancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e4 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e11 (19.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\n \u003cp\u003e0.0434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e17 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e10 (29.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.0366\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eCKD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e8 (9.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e14 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\n \u003cp\u003e0.0963\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e14 (9.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e11 (32.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.0115\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eCOPD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e5 (6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e9 (16.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\n \u003cp\u003e0.1910\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e12 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e9 (26.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.0311\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eCAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e7 (8.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e15 (26.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\n \u003cp\u003e0.0373\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e18 (12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e8 (23.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.2448\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eDementia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e2 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e2 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e4 (2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e9 (26.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.0027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e43 (52.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e36 (65.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\n \u003cp\u003e0.2698\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e65 (44.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e24 (70.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.0311\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e26 (32.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e5 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\n \u003cp\u003e0.0373\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e26 (18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e3 (9.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.3969\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eStroke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e4 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e4 (7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\n \u003cp\u003e0.7992\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e2 (1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e6 (18.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.0054\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 219px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLab results (mean (SD))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eCreatinine [umol/L]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e132.3 (175.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e135.3 (115.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\n \u003cp\u003e0.9142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e110.5 (161.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e154.8 (91.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.0036\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 219px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eDuring hospitalization\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 219px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospitalization details\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eNumber of days (mean (SD))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e37.8 (38.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e30.5 (29.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\n \u003cp\u003e0.8580\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e18.8 (22.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e21.7 (21.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.3404\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eICU stay (n (%))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e78 (95.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e50 (89.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\n \u003cp\u003e0.5865\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e90 (62.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e20 (58.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.7264\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eNumber of days in ICU (mean (SD))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e22.4 (29.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e29.6 (30.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\n \u003cp\u003e0.0527\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e10.0 (13.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e22.3 (24.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.0009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 219px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComplications (n (%))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eAKI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e34 (42.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e34 (60.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\n \u003cp\u003e0.1447\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e20 (13.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e16 (47.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.0031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eArrest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1 (1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e8 (14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\n \u003cp\u003e0.0273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003ePleural effusion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e13 (15.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e12 (21.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\n \u003cp\u003e0.6510\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e13 (9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e10 (29.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.0341\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-drug interventions administered\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eO2 therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e82 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e55 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e140 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e33 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eNumber of days O2 therapy (mean (SD))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e30.9 (36.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e30.8 (33.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e12.3 (17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e22.0 (19.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.0072\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eIMV (n (%))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e43 (52.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e44 (78.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 9%;\"\u003e\n \u003cp\u003e0.0182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003e22 (15.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e15 (44.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.0036\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Multivariate logistic regression results on the association between ARDS development and clinical features\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"517\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFeatures\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOdds\u0026nbsp;\u003cbr\u003e\u0026nbsp;ratios\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-values\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% Confidence\u0026nbsp;\u003cbr\u003e\u0026nbsp;intervals\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSignificance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eIntercept\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 115px;\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 159px;\"\u003e\n \u003cp\u003e[0 - 5.279]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.763\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 115px;\"\u003e\n \u003cp\u003e0.342\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 159px;\"\u003e\n \u003cp\u003e[0.437 - 1.332]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.995\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 115px;\"\u003e\n \u003cp\u003e0.533\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 159px;\"\u003e\n \u003cp\u003e[0.98 - 1.011]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e3.636\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 115px;\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 159px;\"\u003e\n \u003cp\u003e[1.108 - 11.936]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eBasophil count\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 115px;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 159px;\"\u003e\n \u003cp\u003e[0 - 0.012]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eSodium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e1.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 115px;\"\u003e\n \u003cp\u003e0.113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 159px;\"\u003e\n \u003cp\u003e[0.99 - 1.098]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. Multivariate logistic regression results on the association between mortality and clinical features\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"539\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFeatures\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOdds\u0026nbsp;\u003cbr\u003e\u0026nbsp;ratio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% Confidence\u0026nbsp;\u003cbr\u003e\u0026nbsp;intervals\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSignificance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eIntercept\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e[0.001 - 0.014]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 105px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003e1.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.951\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e[0.559 - 1.856]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 105px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003e1.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e[1.051 - 1.098]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 105px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eLung disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003e2.437\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e[1.035 - 5.738]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 105px;\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e[1]\u003c/sup\u003eP-values adjusted with the Benjamini-Hochberg method and adjusted P-values of less than 0.05 were considered statistically significant (19). Parametric Pearson\u0026rsquo;s chi-squared or non-parametric Fisher\u0026rsquo;s exact tests were used to compare categorical variables appropriately. Either the Two sample t-test, Welch\u0026rsquo;s two sample t-test or the Mann-Whitney-Wilcoxon test were used to compare continuous data.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e[2]\u003c/sup\u003eP-values adjusted with the Benjamini-Hochberg method and adjusted P-values of less than 0.05 were considered statistically significant (19). Parametric Pearson\u0026rsquo;s chi-squared or non-parametric Fisher\u0026rsquo;s exact tests were used to compare categorical variables appropriately. Either the Two sample t-test, Welch\u0026rsquo;s two sample t-test or the Mann-Whitney-Wilcoxon test were used to compare continuous data.\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pulmonary-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pulm","sideBox":"Learn more about [BMC Pulmonary Medicine](http://bmcpulmmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pulm/default.aspx","title":"BMC Pulmonary Medicine","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Acute respiratory distress syndrome, Coronavirus disease 2019, Corticosteroids, Mortality","lastPublishedDoi":"10.21203/rs.3.rs-6384044/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6384044/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003cbr\u003e\nCorticosteroids are commonly used to manage severe Coronavirus disease 2019 (COVID-19) to prevent complications such as acute respiratory distress syndrome (ARDS) and mortality. However, their effectiveness varies. We assessed the clinical outcomes and risk factors associated with ARDS and mortality among patients with severe COVID-19 treated with corticosteroids.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003cbr\u003e\nWe conducted a multi-center retrospective observational cohort study of 317 patients with severe COVID-19 who received corticosteroid therapy at hospitals in Quebec, Canada, from August 2020 to September 2022. Patient comparisons included: ARDS vs non-ARDS cases, survivors vs non-survivors, and survival profiles within ARDS/non-ARDS subgroups. Clinical characteristics, laboratory values, and outcomes were analyzed using chi-squared or Fisher's exact tests for categorical variables and t-tests or Mann-Whitney-Wilcoxon tests for continuous variables. Independent predictors of ARDS development and mortality were identified through multivariate logistic regression analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003cbr\u003e\nLogistic regression identified prior myocardial infarction as the only clinical comorbidity associated with ARDS development (OR = 3.64, 95% CI [1.11-11.94]). Notably, basophil counts showed a strong inverse relationship with ARDS development (OR = 5E-09, 95% CI [2.16E-15-0.012]). Age emerged as a significant predictor of mortality (OR = 1.07 per year, 95% CI [1.05-1.10]), along with previous lung disease (OR = 3.88, 95% CI [1.04-5.74]). Mortality was significantly higher in ARDS patients (40.6 % vs. 19.0 %, P \u0026lt; 0.0001). Surprisingly, obesity was associated with increased survival, particularly in ARDS patients (32.1 % vs. 9.6 %, P = 0.037).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003cbr\u003e\nThe inverse relationship between basophil counts and ARDS development suggests a potential role for these cells in COVID-19 immune response. These findings reveal complex relationships between COVID-19, ARDS, and corticosteroids, generating new hypotheses for investigation.\u003c/p\u003e","manuscriptTitle":"Clinical characteristics associated with ARDS and mortality in patients with COVID-19 who received corticosteroid therapy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-19 10:36:37","doi":"10.21203/rs.3.rs-6384044/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-06-17T16:44:40+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-13T17:36:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-04T14:18:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"191966593149796040662869242792016752323","date":"2025-05-27T05:45:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-25T13:07:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"205903574940669056904345396545526401110","date":"2025-05-21T08:43:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"84203372020591331128620551888174444470","date":"2025-05-15T07:34:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-14T15:48:02+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-04-16T19:04:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-15T11:21:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-15T11:20:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pulmonary Medicine","date":"2025-04-05T22:37:01+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pulmonary-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pulm","sideBox":"Learn more about [BMC Pulmonary Medicine](http://bmcpulmmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pulm/default.aspx","title":"BMC Pulmonary Medicine","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"360bb6da-37ed-435f-b800-80a1c0122156","owner":[],"postedDate":"May 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-07-08T23:08:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-19 10:36:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6384044","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6384044","identity":"rs-6384044","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}