Mortality of cancer patients with septic shock: a nation-based cohort analysis in 77,888 patients

Mortality of cancer patients with septic shock: a nation-based cohort analysis in 77,888 patients | 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 Mortality of cancer patients with septic shock: a nation-based cohort analysis in 77,888 patients Antoine Bianchi, Yann Brousse, Ines Lakbar, Vanessa Pauly, Veronica Orleans, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4347653/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose: Septic shock and cancer occur routinely in intensive care unit patients. Our aim was to determine the 90-day mortality rate of patients with septic shock and solid cancer or hematological cancer. Methods: We performed a retrospective cohort study using data from the French national hospitalization database, including adult patients with septic shock from 2017 to 2018. Primary outcomes were the hospital mortality rate at 90 days in patients with solid cancer and hematological cancer. Secondary outcomes were the risk factors associated with mortality in our global cohort. Results: Septic shock was found in 77,888 patients, including 19,329 patients with solid cancer, 6,498 with hematological cancer and 52,061 noncancer patients. Patients with solid cancer (adjusted hazard ratio 1.55 [1.51-1.59]) and hematological cancer (1.59 [1.53-1.65]) had increased risk of 90-day mortality, as compared with noncancer patients. Risk factors for 90-days hospital mortality included hematological cancer and solid cancer. Conclusion: Our study showed that solid cancer and hematological cancer differed in terms of 90-days mortality in septic shock patients. Future investigations are required to assess the interplay between cancer and septic shock. sepsis cancer shock solid hematology Figures Figure 1 Figure 2 Take Home Message In septic shock, cancer patients had increased risk of mortality compared with noncancer patients. Early ICU admission and identification of source infection are crucial in cancer patients. Introduction Septic shock is the most severe form of sepsis, defined as an inappropriate host response to infection, resulting in one or more life-threatening organ dysfunction(s) with a mortality rate around 45% [1]. The management of patients with severe underlying diseases may participate to these poor outcomes. In a previous cohort study based on a national database, we found that 53,206 (28.4%) of 187,587 patients with septic shock had an history of cancer while a diagnosis of “tumor” was reported as the cause of intensive care unit (ICU) admission in 5.9% of patients [2]. In addition, cancer was associated with an increased mortality rate at 90 days. In a large national cohort study from the Netherlands, the one-year mortality of cancer patients with an unplanned ICU admission was also higher than that of patients without cancer [3]. In a systematic review, the ICU mortality rate of cancer patients was 38% but wide variations were round between the studies [4]. The outcome of cancer may differ according to the type of cancer. In a retrospective study describing trends in outcomes of cancer patients requiring an unplanned admission to the ICU, analysis of more than 46,000 patients admitted to ICU between 2009 and 2013 showed that hospital mortality rates of patients with solid tumors and hematological malignancies were 26% and 56%, respectively [5]. A study based on the National Intensive Care Evaluation registry focusing on patients with unplanned ICU admission in the Netherlands between 2008 and 2017 found that one-year mortality rates were 60.1%, 46.2%, and 28.3% in patients with hematological cancer, solid cancer, and those without cancer [3]. These studies tend to show that the mortality is affected by the nature of cancer with an increased risk in patients with hematological cancer. Although several observational studies reported mortality rates of septic patients with solid or hematological cancers, most of them were conducted in specialized centers in low or moderate numbers of patients [6]. Here we aim to describe the effect of solid cancer and hematological cancer on the outcome of patients with septic shock requiring admission to the ICU, based on the French national database over a 2-year period (2017-2018) [2]. Our primary goal was to determine the 90-day mortality of patients with septic shock and solid cancer, hematological cancer and noncancer affection. Secondary objectives were the risk factors of 90-day mortality in the entire cohort. Methods This was a general population cohort study involving all adult patients (over 18 years old) with septic shock, admitted to French intensive care units between January 1, 2017, and December 31, 2018, using data from the French national Program of Medicalization of Systems of Information (PMSI) database, which compiles administrative and medical information (diagnoses and surgical procedures), as described in a previous study [ 2 ]. Briefly, the PMSI is based on patient discharge diagnosis groups coded according to the International Classification of Diseases, 10th revision (ICD-10). Technical and medical procedures performed throughout the stay are also coded daily according to the Common Classification of Medical Procedures (CCAM). The PMSI database is used to determine financial resources and is subject to frequent and thorough checks by both its producer and the payer, with possible financial and legal consequences for those who do not provide data or provide inaccurate data. PMSI data are anonymized and can be reused for research purposes. Due to its accuracy and comprehensive data collection, no patient is lost to follow-up during the study period. This study follows the STROBE guidelines (Strengthening the Reporting of Observational Studies in Epidemiology) and, as it is based on anonymous and retrospective data, did not require approval from an ethics committee or informed consent from patients. Data extraction was performed by the authorized public health service of Public Hospitals of Marseille according to the registered study protocol. Access to the national PMSI database was obtained through a usage agreement signed between the Technical Agency for Information on Hospitalization (ATIH) and the Public Hospitals of Marseille. In accordance with French law, a declaration of compliance with reference methodology 005 (MR005) was registered with the National Commission for Data Protection (CNIL) under number F20220318151239. Study Patients Septic shock was identified using two strategies: either directly from a "septic shock" ICD-10 code (r572) or indirectly with a combination of codes corresponding to a severe infection (sepsis or bacteremia) associated with the use of vasopressors, as described elsewhere [ 2 ]. Cancer patients were defined based on the algorithm of the National Cancer Institute (INCa) searched in all PMSI hospitalizations in conventional wards, follow-up care and rehabilitation, home hospitalization, and psychiatry during the year preceding hospitalization for septic shock, as well as during hospitalization for septic shock. The study was limited to patients aged 18 years or older. By convention, the group of patients with neoplasms will be called the cancer group, while patients without neoplasms serving as controls will be grouped in the non-cancer group. To exclude patients with no severity criteria, suggesting overcoding of septic shock, ICU stays were included only if they lasted at least 48 hours, with the exception of patients who died within the first 48 hours. Data Collected For each ICU stay, the following data were collected: age (raw data) and categorized into 4 classes (18–44 years; 45–64 years; 65–75 years; > 75 years), sex, social disadvantage according to the FDep territorial index of social disadvantage for the French Deprivation Index (calculated at the municipal level from 4 variables: the proportion of workers in the working population aged 15 to 64 years, the proportion of unemployed in the working population aged 15 to 64 years, the proportion of high school graduates (minimum) in the non-school population aged 15 years or older, and the median household income tax), the Charlson score (a comorbidity measurement tool designed to predict one-year mortality and the comorbidities used to calculate it (for the cancer patients, cancer and metastasis items were deliberately excluded from the calculation), presence or absence of neutropenia (neutrophil count in the blood < 500 cells/mm 3 ), reason for ICU admission, time from hospital admission to ICU admission, mode of admission (through the emergency department, medical or surgical services), severity acute physiology score (SAPS) 2, organ failures, site of infection, health care associated or community acquired infection, causative germs and antimicrobial resistance profile, support therapies (cardiopulmonary resuscitation, mechanical ventilation, blood transfusion, renal replacement therapy, type of cancer (solid tumors or hematological), hospital characteristics (academic vs. nonacademic public vs. private), and mode of ICU discharge. End Points The primary outcome was all-cause mortality assessed at day 90 according to the status “solid cancer”, “hematological cancer”, or “noncancer”. Secondary outcomes were the identification of risk factors associated with the 90-day mortality rate. Statistical Analysis Data are presented as mean ± (standard deviation) for parametric distribution data, as median (interquartile range defined as interquartile range (IQR) [25–75]) for non-parametric data. Categorical data are presented as number and %. Standardized differences were used to compare “solid cancer”, “hematological cancer”, or “noncancer” patients. An absolute standardized difference (SD) of ⩽0.20 was chosen to indicate a negligible difference in the mean or prevalence of a variable between groups. The SD helps to understand the magnitude of the differences found, in addition to statistical significance, which examines whether the findings are likely to be due to chance[ 7 , 8 ]. To study the association between each group and outcome, the Kaplan–Meier method and the log-rank statistic were used to estimate and compare the cumulative death rates. Hazard ratios (HRs) and 95% confidence intervals (95% CIs) were estimated using Cox survival models with a robust variance estimator to account for clustering within matched pairs. Two models were developed. Model 1 included the group, age, sex, smoking, alcohol, overweight or obesity, the Charlson comorbidity index (0, 1 to 2, ≥ 3), SAPS II score (modified, without age), organ failures, ICU supportive therapies, site of infection, the source of hospital admission, time between hospital admission and ICU admission, hospital characteristics. The model 2 included the 17 Charlson comorbidities instead of the Charlson comorbidity index. The proportional-hazards assumption for the Cox models was investigated and confirmed graphically through survival functions over time. A p < 0.05 was considered significant. Data management and analyses were performed using the SAS software. Cox regression analyses were performed using the PROC PHREG in SAS. Results Among 77,888 ICU admissions for septic shock from 2017 to 2018, 19,329 patients had solid cancer, 6,498 had hematological cancer and 52,061 had noncancer affections (Fig. 1 ). Almost all differences between solid cancer patients, hematological patients, and noncancer patients reached a significant level (Table 1 ). Patients with solid cancer were slightly older than those with noncancer affection (68.7±11.3 vs. 66.4±15.2 years). The SAPS2 at ICU admission was higher in the hematological cancer patients than in the solid cancer and noncancer patients (Table 1 ). Table 1 Socio-demo graphic, clinical and hospital characteristics between the different groups All Patients with solid cancer (A) Patients with Hematologic cancer (B) Patients without cancer (C) A vs C B vs C A vs B N 77,888 19,329 6,498 52,061 SD† p-value† SD‡ p-value‡ SD⨎ p-value⨎ Age – year Mean ± SD [95% CI] 67.1 ± 14.2 [67.0–67.2] 68.7 ± 11.3 [68.6–68.9] 67.4 ± 13.5 [67.1–67.7] 66.4 ± 15.2 [66.3–66.5] 0.17 < 0.001 0.07 < 0.001 -0.11 < 0.001 Sex (women) –n (%) [95% CI] 27,939 (35.9%) [35.5–36.1] 5,997 (31.0%) [30.4–31.7] 2,204 (33.9%) [32.8–35.1] 19,738 (37.9%) [37.5–38.3] -0.15 < 0.001 -0.08 < 0.001 0.06 < 0.001 Overweight or obese – n (%) [95% CI] 14,289 (18.3%) [18.1–18.6] 3,147 (16.3%) [15.8–16.8] 939 (14.5%) [13.6–15.3] 10,203 (19.6%) [19.3–19.9] -0.09 < 0.001 -0.14 < 0.001 -0.05 < 0.001 Smoking addiction – n (%) [95% CI] 12,529 (16.1%) [15.8–16.3] 3,572 (18.5%) [17.9–19.0] 735 (11.3%) [10.5–12.1] 8,222 (15.8%) [15.5–16.1] 0.07 < 0.001 -0.13 < 0.001 -0.20 < 0.001 Alcohol addiction – n (%) [95% CI] 11,408 (14.6%) [14.4–14.9] 2,552 (13.2%) [12.7–13.7] 449 (6.9%) [6.3–7.5] 8,407 (16.1%) [15.8–16.5] -0.08 < 0.001 -0.29 < 0.001 -0.21 < 0.001 Charlson index – n (%) [95% CI] 0.19 < 0.001 0.13 < 0.001 0.08 < 0.001 0 16,365 (21.0%) [20.7–21.3] 5,001 (25.9%) [25.2–26.5] 1,561 (24.0%) [23.0–25.1] 9,803 (18.8%) [18.5–19.2] 0.17 < 0.001 0.13 < 0.001 -0.04 0.003 1–2 27,900 (35.8%) [35.5–36.1] 7,111 (36.8%) [36.1–37.5] 2,270 (34.9%) [33.8–36.1] 18,519 (35.6%) [35.2–36.0] 0.03 0.002 -0.01 0.310 -0.04 0.007 ≥ 3 33.623 (43.2%) [42.8–43.5] 7,217 (37.3%) [36.6–38.0] 2,667 (41.0%) [39.8–42.2] 23,739 (45.6%) [45.2–46.0] -0.17 < 0.001 -0.09 < 0.001 0.08 < 0.001 SAPS II score at ICU admission (without age), Mean ± SD [95% CI] 43.4 ± 23.1 [43.2–43.6] 43.0 ± 23.5 [42.7–43.3] 47.7 ± 24.6 [47.1–48.3] 43.0 ± 22.6 [42.8–43.2] -0.00 < 0.001 0.20 < 0.001 0.19 < 0.001 SAPS II score at ICU admission (without age, solid and hematologic cancer), Mean ± SD [95% CI] 40.3 ± 23.3 [40.2–40.5] 34.0 ± 23.5 [33.7–34.3] 37.7 ± 24.6 [37.1–38.3] 43.0 ± 22.6 [42.8–43.2] -0.39 < 0.001 -0.23 < 0.001 0.15 < 0.001 Site of infection – n (%) [95% CI] Respiratory 29,358 (37.7%) [37.3–38.0] 6,400 (33.1%) [32.4–33.8] 2,401 (36.9%) [35.8–38.1] 20,557 (39.5%) [39.1–39.9] -0.13 < 0.001 -0.05 < 0.001 0.08 < 0.001 Gastrointestinal 14,499 (18.6%) [18.3–18.9] 5,260 (27.2%) [26.6–27.8] 796 (12.2%) [11.5–13.0] 8,443 (16.2%) [15.9–16.5] 0.27 < 0.001 -0.11 < 0.001 -0.38 < 0.001 Renal 7,319 (9.4%) [9.2–9.6] 1,818 (9.4%) [9.0–9.8] 572 (8.8%) [8.1–9.5] 4,929 (9.5%) [9.2–9.7] -0.00 0.800 -0.02 0.083 -0.02 0.146 Cardiac 7,932 (10.2%) [10.0–10.4] 1,841 (9.5%) [9.1–9.9] 841 (12.9%) [12.1–13.8] 5,250 (10.1%) [9.8–10.3] -0.02 0.026 0.09 < 0.001 0.11 < 0.001 Dermatologic 5,468 (7.0%) [6.8–7.2] 1,291 (6.7%) [6.3–7.0] 459 (7.1%) [6.4–7.7] 3,718 (7.1%) [6.9–7.4] -0.02 0.032 -0.00 0.818 0.02 0.285 Organ failures – n (%) [95% CI] Respiratory 44,400 (57.0%) [56.6–57.3] 10,483 (54.2%) [53.5–54.9] 3,878 (59.7%) [58.5–60.9] 30,039 (57.7%) [57.3–58.1] -0.07 < 0.001 0.04 0.002 0.11 < 0.001 Renal 37,861 (48.6%) [48.2–49.0] 9,001 (46.6%) [45.9–47.3] 3,524 (54.2%) [53.0–55.4] 25,336 (48.7%) [48.2–49.1] -0.04 < 0.001 0.11 < 0.001 0.15 < 0.001 Neurologic 17,900 (23.0%) [22.7–23.3] 3,423 (17.7%) [17.2–18.2] 1,256 (19.3%) [18.4–20.3] 13,221 (25.4%) [25.0–25.8] -0.19 < 0.001 -0.15 < 0.001 0.04 0.003 Cardiovascular 12,873 (16.5%) [16.3–16.8] 2,445 (12.6%) [12.2–13.1] 1,068 (16.4%) [15.5–17.3] 9,360 (18.0%) [17.6–18.3] -0.15 < 0.001 -0.04 0.002 0.11 < 0.001 Hematologic 10,685 (13.7%) [13.5–14.0] 2,303 (11.9%) [11.5–12.4] 1,739 (26.8%) [25.7–27.8] 6,643 (12.8%) [12.5–13.0] -0.03 0.002 0.36 < 0.001 0.38 < 0.001 Metabolic 18,298 (23.5%) [23.2–23.8] 4,274 (22.1%) [21.5–22.7] 1,524 (23.5%) [22.4–24.5] 12,500 (24.0%) [23.6–24.4] -0.05 < 0.001 -0.01 0.321 0.03 0.025 Hepatic 7,964 (10.2%) [10.0–10.4] 1,832 (9.5%) [9.1–9.9] 663 (10.2%) [9.5–10.9] 5,469 (10.5%) [10.2–10.8] -0.03 < 0.001 -0.01 0.453 0.02 0.086 ICU supportive therapies – n (%) [95% CI] Cardiopulmonary resuscitation 3,801 (4.9%) [4.7–5.0] 762 (3.9%) [3.7–4.2] 310 (4.8%) [4.3–5.3] 2,729 (5.2%) [5.1–5.4] -0.06 < 0.001 -0.02 0.106 0.04 0.003 Invasive mechanical ventilation 61,026 (78.3%) [78.1–78.6] 14,553 (75.3%) [74.7–75.9] 4,666 (71.8%) [70.7–72.9] 41,807 (80.3%) [80.0–80.6] -0.12 < 0.001 -0.20 < 0.001 -0.08 < 0.001 Renal replacement therapy 21,584 (27.7%) [27.4–28.0] 4,722 (24.4%) [23.8–25.0] 2,077 (32.0%) [30.8–33.1] 14,785 (28.4%) [28.0–28.8] -0.09 < 0.001 0.08 < 0.001 0.17 < 0.001 Transfusion 24,596 (31.6%) [31.2–31.9] 6,489 (33.6%) [32.9–34.2] 2,857 (44.0%) [42.8–45.2] 15,250 (29.3%) [28.9–29.7] 0.09 < 0.001 0.31 < 0.001 0.21 < 0.001 Positive culture with identification, n (%) [95% CI] 52,533 (67.4%) [67.1–67.8] 13,048 (67.5%) [66.8–68.2] 4,411 (67.9%) [66.7–69.0] 35,074 (67.4%) [67.0–67.8] 0.00 0.734 0.01 0.406 0.01 0.573 Multidrug resistant bacteria, n (%) [95% CI] 13,777 (17.7%) [17.4–17.9] 3,527 (18.2%) [17.7–18.8] 1,218 (18.7%) [17.8–19.7] 9,032 (17.3%) [17.0–17.7] 0.02 0.005 0.04 0.005 0.01 0.370 Enterobacter, n (%) [95% CI] 26,700 (34.3%) [33.9–34.6] 7,258 (37.5%) [36.9–38.2] 2,133 (32.8%) [31.7–34.0] 17,309 (33.2%) [32.8–33.7] 0.09 < 0.001 -0.01 0.495 -0.10 < 0.001 Staphylococcus, n (%) [95% CI] 18,311 (23.5%) [23.2–23.8] 4,120 (21.3%) [20.7–21.9] 1,421 (21.9%) [20.9–22.9] 12,770 (24.5%) [24.2–24.9] -0.08 < 0.001 -0.06 < 0.001 0.01 0.347 Streptococcus, n (%) [95% CI] 16,952 (21.8%) [21.5–22.0] 4,450 (23.0%) [22.4–23.6] 1,178 (18.1%) [17.2–19.1] 11,324 (21.8%) [21.4–22.1] 0.03 < 0.001 -0.09 < 0.001 -0.12 < 0.001 Pseudomonas aeruginosa, n (%) [95% CI] 10,388 (13.3%) [13.1–13.6] 2,683 (13.9%) [13.4–14.4] 998 (15.4%) [14.5–16.2] 6,707 (12.9%) [12.6–13.2] 0.03 < 0.001 0.07 < 0.001 0.04 0.003 Candida, n (%) [95% CI] 9,417 (12.1%) [11.9–12.3] 2,826 (14.6%) [14.1–15.1] 887 (13.6%) [12.8–14.5] 5,704 (11.0%) [10.7–11.2] 0.11 < 0.001 0.08 < 0.001 -0.03 0.053 Hospital-acquired infection, n (%) [95% CI] 21,508 (27.6%) [27.3–27.9] 6,560 (33.9%) [33.3–34.6] 1,755 (27.0%) [25.9–28.1] 13,193 (25.3%) [25.0–25.7] 0.19 < 0.001 0.04 0.003 -0.15 < 0.001 Source of hospital admission – n (%) [95% CI] -0.00 0.747 0.00 0.945 0.00 0.801 Home 74,842 (96.1%) [95.9–96.2] 18,851 (96.1%) [95.9–96.4] 6,242 (96.1%) [95.6–96.5] 50,019 (96.1%) [95.9–96.2] 0.00 0.747 -0.00 0.945 -0.00 0.801 Transfer from other hospital 3,046 (3.9%) [3.8–4.0] 748 (3.9%) [3.6–4.1] 256 (3.9%) [3.5–4.4] 2,042 (3.9%) [3.8–4.1] -0.00 0.747 0.00 0.945 0.00 0.801 Time to ICU admission ≤ 1 day – n (%) [95% CI] 46,297 (59.4%) [59.1–59.8] 9,392 (48.6%) [47.9–49.3] 2,994 (46.1%) [44.9–47.3] 33,911 (65.1%) [64.7–65.5] -0.34 < 0.001 -0.39 < 0.001 -0.05 < 0.001 Hospital characteristics – n (%) [95% CI] 0.27 < 0.001 0.20 < 0.001 0.24 < 0.001 Academic 25,993 (33.4%) [33.0–33.7] 6,518 (33.7%) [31.1–34.4] 2,685 (41.3%) [40.1–42.5] 16,790 (32.2%) [31.8–32.7] 0.03 < 0.001 0.19 < 0.001 0.16 < 0.001 Other public hospital 39,354 (50.5%) [50.2–50.9] 8,247 (42.7%) [42.0–43.4] 2,942 (45.3%) [44.1–46.5] 28,165 (54.1%) [53.7–54.5] -0.23 < 0.001 -0.18 < 0.001 0.05 < 0.001 Private 12,541 (16.1%) [15.8–16.3] 4,564 (23.6%) [23.0–24.2] 871 (13.4%) [12.6–14.2] 7,106 (13.6%) [13.4–13.9] 0.26 < 0.001 -0.01 0.586 -0.27 < 0.001 † Standardized difference and p-value between patients with solid cancer and without cancer; ‡ Standardized difference and p-value between patients with hematologic cancer and without cancer; ⨎ Standardized difference and p-value between patients with solid and hematologic cancer. SD≤|0.10| was chosen to indicate a negligible difference in the mean or prevalence of a variable between groups. SD>|0.10| shown in bold. 95% CI: 95% confidence interval. ICU : Intensive Care Unit SAPS II : Simplified Acute Physiology Score Table 2 90-day mortality in septic shock patients Alive (N = 40,606) Dead (N = 37,282) Crude HR Random effect : Finess [95% CI] p-value Frailty model 1 Random effect : Finess Frailty model 2 Random effect : Finess Adjusted HR (95% CI) p-value Adjusted HR (95% CI) p-value Group of patients < 0.001 < 0.001 < 0.001 Patients without cancer – n (%) 29,007 (71.4%) 23,054 (61.8%) 1 - 1 - 1 - Patients with solid cancer– n (%) 8,943 (22.0%) 10,386 (27.9%) 1.26 [1.24–1.29] < 0.001 1.55 [1.51–1.59] < 0.001 1.55 [1.51–1.59] < 0.001 Patients with Hematologic cancer– n (%) 2,656 (6.5%) 3,842 (10.3%) 1.49 [1.44–1.54] < 0.001 1.59 [1.53–1.65] < 0.001 1.60 [1.55–1.66] < 0.001 Age – year, Mean ± SD 64.3 ± 14.8 70.0 ± 12.9 1.02 [1.02–1.02] < 0.001 1.02 [1.02–1.02] < 0.001 1.02 [1.02–1.02] < 0.001 Sex (women) – n (%) 14,902 (36.7%) 13,037 (35.0%) 0.97 [0.95–0.99] 0.019 1.01 [0.99–1.03] 0.306 1.01 [0.99–1.03] 0.281 Overweight or obese – n (%) 8,254 (20.3%) 6,035 (16.2%) 0.79 [0.77–0.82] < 0.001 0.82 [0.79–0.84] < 0.001 0.83 [0.81–0.85] < 0.001 Smoking addiction – n (%) 7,377 (18.2%) 5,152 (13.8%) 0.77 [0.75–0.79] < 0.001 0.92 [0.89–0.95] < 0.001 0.92 [0.89–0.95] < 0.001 Alcohol addiction – n (%) 6,283 (15.5%) 5,125 (13.7%) 0.88 [0.85–0.91] < 0.001 0.99 [0.96–1.02] 0.662 0.89 [0.86–0.92] < 0.001 Charlson comorbidity index – n (%) 0.001 0.001 0 9,237 (22.7%) 7,128 (19.1%) 1 - 1 - 1–2 15,010 (37.0%) 12,890 (34.6%) 1.02 [0.99–1.05] 0.114 0.93 [0.90–0.96] < 0.001 ≥ 3 16,359 (40.3%) 17,264 (46.3%) 1.14 [1.11–1.17] < 0.001 0.98 [0.95–1.01] 0.197 Charlson comorbidity – n (%) Dementia 1,301 (3.2%) 1,589 (4,3%) 1.18 [1.12–1.24] < 0.001 1.00 [0.95–1.05] 0.821 HIV 411 (1.0%) 286 (0.8%) 0.80 [0.71–0.90] < 0.001 0.88 [0.78–0.99] 0.042 Moderate or severe liver disease 2,009 (4.9%) 3,634 (9.7%) 1.58 [1.53–1.64] < 0.001 1.28 [1.23–1.34] < 0.001 Hemiplegia or paraplegia 4,842 (11.9%) 2,988 (8.0%) 0.67 [0.65–0.70] < 0.001 0.79 [0.76–0.82] < 0.001 Cardio heart failure 13,715 (33.8%) 14,227 (38.2%) 1.10 [1.07–1.12] < 0.001 1.04 [1.01–1.07] 0.003 Chronic obstructive pulmonary disease 8,315 (20.5%) 7,750 (20.8%) 0.96 [0.94–0.99] 0.012 1.00 [0.97–1.03] 0.845 Diabetes with complication 4,247 (10.5%) 4,409 (11.8%) 1.04 [1.01–1.08] 0.003 1.01 [0.98–1.05] 0.302 Diabetes without complications 10,134 (25.0%) 9,129 (24.5%) 0.95 [0.93–0.97] < 0.001 0.89 [0.86–0.91] < 0.001 Myocardial infarction 6,821 (16.8%) 7,007 (18.8%) 1.07 [1.04–1.10] < 0.001 0.98 [0.95–1.02] 0.481 Mild liver disease 4,005 (9.9%) 5,600 (15.0%) 1.38 [1.34–1.42] < 0.001 1.21 [1.17–1.25] < 0.001 Peptic ulcer disease 2,368 (5.8%) 2,216 (5.9%) 0.94 [0.90–0.98] 0.006 0.88 [0.85–0.92] < 0.001 Peripheral vascular disease 6,092 (15.0%) 6,341 (17.0%) 1.08 [1.05–1.11] < 0.001 1.08 [1.05–1.11] < 0.001 Renal disease 7,306 (18.0%) 8,483 (22.7%) 1.17 [1.14–1.20] < 0.001 0.92 [0.89–0.94] < 0.001 SAPS II score at ICU admission (without age), Mean ± SD 37.5 ± 19.2 49.8 ± 25.1 1.02 [1.02–1.02] < 0.001 SAPS II score at ICU admission (without age, solid and hematologic cancer), Mean ± SD 34.9 ± 19.7 46.3 ± 25.5 1.02 [1.02–1.02] < 0.001 1.01 [1.01–1.01] < 0.001 1.01 [1.01–1.01] < 0.001 Site of infection – n (%) Respiratory 15,770 (38.8%) 13,588 (36.4%) 0.83 [0.81–0.85] < 0.001 0.82 [0.80–0.84] < 0.001 0.82 [0.80–0.84] < 0.001 Gastrointestinal 8,199 (20.2%) 6,300 (16.9%) 0.83 [0.81–0.85] < 0.001 0.76 [0.74–0.79] < 0.001 0.77 [0.74–0.79] < 0.001 Renal 5,065 (12.5%) 2,254 (6.0%) 0.52 [0.50–0.55] < 0.001 0.57 [0.55–0.60] < 0.001 0.58 [0.56–0.61] < 0.001 Cardiac 4,896 (12.1%) 3,036 (8.1%) 0.67 [0.65–0.70] < 0.001 0.94 [0.90–0.98] 0.003 0.94 [0.90–0.98] 0.004 Dermatologic 3,581 (8.8%) 1,887 (5.1%) 0.61 [0.58–0.63] < 0.001 0.77 [0.74–0.81] < 0.001 0.77 [0.74–0.81] < 0.001 Organ failures – n (%) Respiratory 21,184 (52.2%) 23,216 (62.3%) 1.29 [1.27–1.32] < 0.001 1.14 [1.12–1.17] < 0.001 1.15 [1.12–1.18] < 0.001 Renal 16,085 (39.6%) 21,776 (58.4%) 1.72 [1.68–1.76] < 0.001 1.22 [1.19–1.25] < 0.001 1.22 [1.19–1.25] < 0.001 Neurologic 7,757 (19.1%) 10,143 (27.2%) 1.35 [1.32–1.38] < 0.001 1.14 [1.11–1.17] < 0.001 1.15 [1.12–1.18] < 0.001 Cardiovascular 7,066 (17.4%) 5,807 (15.6%) 0.86 [0.84–0.89] < 0.001 0.78 [0.76–0.80] < 0.001 0.77 [0.74–0.79] < 0.001 Hematologic 4,876 (12.0%) 5,809 (15.6%) 1.24 [1.20–1.27] < 0.001 1.06 [1.03–1.10] < 0.001 1.04 [1.01–1.07] 0.004 Metabolic 7,845 (19.3%) 10,453 (28.0%) 1.50 [1.47–1.54] < 0.001 1.18 [1.15–1.21] < 0.001 1.18 [1.15–1.21] < 0.001 Hepatic 2,159 (5.3%) 5,805 (15.6%) 2.23 [2.17–2.30] < 0.001 1.72 [1.67–1.78] < 0.001 1.58 [1.53–1.63] < 0.001 ICU supportive therapies – n (%) Cardiopulmonary resuscitation 987 (2.4%) 2,814 (7.5%) 2.20 [2.11–2.28] < 0.001 1.59 [1.52–1.65] < 0.001 1.60 [1.54–1.67] < 0.001 Invasive mechanical ventilation 29,600 (72.9%) 31,426 (84.3%) 1.64 [1.60–1.69] < 0.001 1.33 [1.29–1.37] < 0.001 1.34 [1.30–1.38] < 0.001 Renal replacement therapy 7,616 (18.8%) 13,968 (37.5%) 1.79 [1.75–1.83] < 0.001 1.32 [1.28–1.35] < 0.001 1.34 [1.30–1.37] < 0.001 Transfusion 12,725 (31.3%) 11,871 (31.8%) 0.89 [0.87–0.91] < 0.001 0.78 [0.77–0.80] < 0.001 0.78 [0.76–0.80] < 0.001 Positive culture with identification – n (%) 29,933 (73.7%) 22,600 (60.6%) 0.56 [0.55–0.57] < 0.001 0.88 [0.85–0.91] < 0.001 0.88 [0.85–0.91] < 0.001 Hospital-acquired infection – n (%) 13,601 (33.5%) 7,907 (21.2%) 0.56 [0.55–0.57] < 0.001 0.69 [0.67–0.71] < 0.001 0.70 [0.68–0.72] < 0.001 Source of hospital admission – n (%) < 0.001 < 0.001 < 0.001 Transfer from other hospital 1,444 (3.6%) 1,602 (4.3%) 1 - 1 - 1 - Home 39,162 (96.4%) 35,680 (95.7%) 0.88 [0.84–0.93] < 0.001 0.79 [0.75–0.83] < 0.001 0.78 [0.74–0.82] < 0.001 Time to ICU admission ≤ 1 day – n (%) 25,892 (63.8%) 20,405 (51.7%) 0.79 [0.78–0.81] < 0.001 0.76 [0.74–0.77] < 0.001 0.76 [0.75–0.78] < 0.001 Hospital characteristics – n (%) < 0.001 < 0.001 < 0.001 Academic 14,230 (35.0%) 11,763 (31.5%) 1 - 1 - 1 - Other public hospital 19,872 (48.9%) 19,482 (52.3%) 1.16 [1.09–1.24] < 0.001 1.09 [1.02–1.17] 0.006 1.09 [1.02–1.17] 0.002 Private 6,504 (16.0%) 6,037 (16.2%) 1.07 [0.99–1.15] 0.056 0.97 [0.90–1.04] 0.489 0.97 [0.90–1.04] 0.448 95% CI: 95% confidence interval. HR : Hazard Ratio ICU : Intensive Care Unit SAPS II : Simplified Acute Physiology Score Among 67.4% [95%CI, 67.1 to 67.8] patients with positive culture identification, Enterobacter sp. (34.3% [95%CI, 33.9 to 34.6]), Staphylococcus sp. (23.5% [95%CI, 23.2 to 23.8]), Streptococcus sp. (21.8% [95%CI, 21.5 to 22.0]), Pseudomonas aeruginosa (13.3% [95%CI, 13.1 to 13.6]) and Candida sp. (12.1% [95%CI, 11.9 to 12.3]) were the most frequently isolated. Regarding the sites of infection, the gastrointestinal site was identified in 27.2% [95%CI, 26.6 to 27.8] of solid cancer patients, as compared with 12.2% [95%CI, 11.5 to 13.0] and 16.2% [95%CI, 15.9 to 16.5] of hematological cancer patients and noncancer patients, respectively. The rate of positive culture and that of multidrug resistant bacteria were no significantly different in the three groups. The recourse to invasive mechanical ventilation was slightly increased in the noncancer patients (80.3% [95%CI, 80.0 to 80.6]), as compared with 75.3% [95%CI, 74.7 to 75.9] in solid cancer patients and 71.8% [95%CI, 70.7 to 72.9] in hematological cancer patients. Primary outcome The 90-day mortality rate differed significantly in the three groups with the highest 90-day mortality rate for patients with hematological cancer, an intermediate 90-day mortality rate for those with solid cancer and the lowest mortality rate for the noncancer patients (Fig. 2 ). The mortality rates at day 90 were 53.7%, 59.1% and 44.3% for the solid cancer patients, the hematologic patients and the noncancer patients. Patients with solid cancer (adjusted HR 1.55 [95%CI, 1.51 to 1.59]) and hematological cancer (adjusted HR 1.59 [95%CI, 1.53 to 1.65]) had increased risk of 90-day mortality, as compared with noncancer patients. This difference was confirmed using two different statistical models (Frailty 1 and Frailty 2). Risk factors associated with 90-day mortality Being admitted to ICU with cancer, the type of cancer (solid vs. hematological), an advanced age, an increased severity score, the site of infection (lung, kidney, central nervous system, liver, metabolic), each organ failure, the ICU supportive therapies with the exception of blood transfusion and being admitted to a non-academic public hospital (as compared with other public hospital) were associated with poor outcomes. In contrast, overweigh, Charlson comorbidity index 1–2, known source of infection, cardiovascular failure, hospital-acquired infection, direct admission from home to ICU, and time to ICU below 24 h were found as protective factors. Then we explored the risk factors for 90-day mortality in patients with hematological cancer (Supplemental Tables 1 & 2) and solid cancer (Supplemental Tables 3 & 4). Positive culture, microbiological identification and the time to ICU admission (≤ 1 day) were associated with decreased 90-day mortality in each subgroup. Discussion Our study showed that solid cancer patients represented around 25% of our cohort of patients with septic shock while those with hematological cancer represented around 8% of these patients. The 90-day mortality rate was higher in the cancer patients than in the noncancer patients. Among the cancer patients, those with hematological cancer were at higher risk of 90-day mortality than those with solid cancer. The factors associated with the 90-day mortality in the patients with hematological and solid cancer shared the same profiles. Our data underlined the need for an identification of the source of infection and the pathogen responsible for the infective episode, as well as an early admission to ICU. Our findings are in line with two previous studies based on large cohorts and exploring the effects of solid and hematological cancers on the outcomes of a population with unplanned ICU admission [ 3 , 5 ]. Both these studies found an increased mortality in patients with hematological cancer, but Ostermann et al. found a reduced mortality in patients with solid cancer as compared with the noncancer patients [ 5 ]. In contrast, the patients with hematological cancer had an increased risk of death as compared with the noncancer patients. The survival of patients with hematological cancer was around 40% at day 90. To reflect the interplay between septic shock and cancer, we deliberately chose an early assessment, since long-term outcome may reflect the underlying affection instead of septic shock. However, van der Zee et al. found a one-year mortality rate at 60% in patients with unplanned ICU admission in the Netherlands [ 3 ]. The difference with our study is probably due to our inclusion criteria selecting patients with septic shock instead of all ICU patients, while the Dutch study included all types of patients. In an observational study assessing the mortality rates of septic shock patients with hematological cancer, the mortality rate in specialized ICU declined from 70.4% in 1997 to 52.8% in 2008 [ 9 ]. The risk factors of 90-days mortality suggested the role of cancer in the outcomes. In addition, hematological cancer had a greater impact on outcomes than solid cancer. Other risk factors are in line with previous studies, confirming the deleterious role of advanced age, of increased severity scores, the effects of few comorbidities and those of each organ failure, and the negative impact of receiving supportive therapies as invasive mechanical ventilation and renal replacement therapy. Our results showed a beneficial effect of being admitted to academic hospitals, as compared with public non-academic hospital. This could reflect the case volume, as previously suggested in an observational study that showed an association between improved survival and the case volumes [ 9 ]. Interestingly, protective risk factors confirm the findings of previous studies. Importantly, the determination of the site of infection and that of the pathogens responsible for septic episodes were protective factors, probably associated with an earlier source control and administration of adequate antimicrobial therapy [ 10 – 12 ]. This finding was corroborated with the admission to ICU within the first day, which was also associated with reduced 90-day mortality, confirming previous findings [ 6 ]. In an observational study including 1,611 immunocompromised patients with acute hypoxemic respiratory failure, Azoulay et al. found that failure to identify acute respiratory failure etiology was associated with higher mortality rates [ 6 ]. In the patients with cancer, early management in ICU and efforts to identify the source of infection are repetitively associated with a decreased mortality. Previous observational studies also reported associations between improved survival and administration of antibiotics in the first hour of shock[ 13], as well as between improved survival and early indwelling catheter removal [ 14 ]. Thus, early management of the septic shock patients with cancer should be implemented in routine practices. The strength of our study was to explore a large, national database that included a high number of patients with an exhaustivity of data. However, several limitations have to be acknowledged. First, our results are derived from a large, administrative database which can carry on the limitations of national database extracted from coding. Second, the database precludes several interesting data as the causes of mortality and notably the use of withdrawal or withholding life sustained treatments. Third, previous studies included cancer patients with unplanned ICU admission. In our database, this information was not available but as we selected only patients with septic shock, one can guess that they were likely patients with the pre-requisite to be admitted to ICU. Finally, we provide here crude data and confounding factors may have an undetermined influence on our results. In conclusion, our retrospective analysis of 77,888 patients with septic shock found that there was a declining 90-day mortality between the patients with hematological cancer, those with solid cancer, and the noncancer patients. Our data confirmed previous smaller studies showing the benefit of an early admission to ICU for those patients and the need to identify the source of infection. In addition, our findings encourage the admission of septic shock patients with hematological cancer and solid cancer to ICU. Due to the high number of patients with septic shock and cancer, future investigations should assess the interplay between the two affections. Declarations AUTHOR CONTRIBUTIONS Conception and design: Marc Leone, Ines Lakbar, Laurent Boyer Collection and assembly of data: Antoine Bianchi, Guillaume Fond, Gary Duclos, Laurent Zieleskiewicz Data analysis and interpretation: Antoine Bianchi, Yann Brousse, Ines Lakbar, Vanessa Pauly, Veronica Orleans, Laurent Boyer, Marc Leone, Manuscript writing: All authors Final approval of manuscript: All authors Accountable for all aspects of the work: All authors References Singer M, Deutschman CS, Seymour CW et al (2016) The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA 315:801. https://doi.org/10.1001/jama.2016.0287 Lakbar I, Munoz M, Pauly V et al (2022) Septic shock: incidence, mortality and hospital readmission rates in French intensive care units from 2014 to 2018. Anaesth Crit Care Pain Med 41:101082. https://doi.org/10.1016/j.accpm.2022.101082 Van Der Zee EN, Termorshuizen F, Benoit DD et al (2022) One-year Mortality of Cancer Patients with an Unplanned ICU Admission: A Cohort Analysis Between 2008 and 2017 in the Netherlands. J Intensive Care Med 37:1165–1173. https://doi.org/10.1177/08850666211054369 Nazer LH, Lopez-Olivo MA, Brown AR et al (2022) A Systematic Review and Meta-Analysis Evaluating Geographical Variation in Outcomes of Cancer Patients Treated in ICUs. Crit Care Explor 4:e0757. https://doi.org/10.1097/CCE.0000000000000757 Ostermann M, Ferrando-Vivas P, Gore C et al (2017) Characteristics and Outcome of Cancer Patients Admitted to the ICU in England, Wales, and Northern Ireland and National Trends Between 1997 and 2013*. Crit Care Med 45 Azoulay E, Pickkers P, Soares M et al (2017) Acute hypoxemic respiratory failure in immunocompromised patients: the Efraim multinational prospective cohort study. Intensive Care Med 43:1808–1819. https://doi.org/10.1007/s00134-017-4947-1 Austin P (2009) Using the Standardized Difference to Compare the Prevalence of a Binary Variable Between Two Groups in Observational Research. Peter C Austin 38. https://doi.org/10.1080/03610910902859574 Sullivan GM, Feinn R (2012) Using Effect Size—or Why the P Value Is Not Enough. J Grad Med Educ 4:279–282. https://doi.org/10.4300/JGME-D-12-00156.1 Zuber B, Tran T-C, Aegerter P et al (2012) Impact of case volume on survival of septic shock in patients with malignancies*. Crit Care Med 40:55–62. https://doi.org/10.1097/CCM.0b013e31822d74ba Reitz KM, Kennedy J, Li SR et al (2022) Association Between Time to Source Control in Sepsis and 90-Day Mortality. JAMA Surg 157:817. https://doi.org/10.1001/jamasurg.2022.2761 Martínez ML, Ferrer R, Torrents E et al (2017) Impact of Source Control in Patients With Severe Sepsis and Septic Shock*. Crit Care Med 45 Kollef MH, Shorr AF, Bassetti M et al (2021) Timing of antibiotic therapy in the ICU. Crit Care 25:360. https://doi.org/10.1186/s13054-021-03787-z Mokart D, Saillard C, Sannini A et al (2014) Neutropenic cancer patients with severe sepsis: need for antibiotics in the first hour. Intensive Care Med 40:1173–1174. https://doi.org/10.1007/s00134-014-3374-9 Legrand M, Max A, Peigne V et al (2012) Survival in neutropenic patients with severe sepsis or septic shock*. Crit Care Med 40:43–49. https://doi.org/10.1097/CCM.0b013e31822b50c2 Supplementary Files AppendixICM.docx STROBEchecklistv4cohort.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4347653","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":304180877,"identity":"06dbad30-b8bf-41c1-bad2-84431eb4ae5e","order_by":0,"name":"Antoine Bianchi","email":"","orcid":"","institution":"Aix-Marseille Universite","correspondingAuthor":false,"prefix":"","firstName":"Antoine","middleName":"","lastName":"Bianchi","suffix":""},{"id":304180878,"identity":"336815c5-fbc6-4631-9088-dbc83172085c","order_by":1,"name":"Yann Brousse","email":"","orcid":"","institution":"Aix-Marseille Universite","correspondingAuthor":false,"prefix":"","firstName":"Yann","middleName":"","lastName":"Brousse","suffix":""},{"id":304180879,"identity":"8c1f8178-d51c-4f3b-b996-dc4aa62fe39a","order_by":2,"name":"Ines Lakbar","email":"","orcid":"","institution":"Montpellier University: Universite de Montpellier","correspondingAuthor":false,"prefix":"","firstName":"Ines","middleName":"","lastName":"Lakbar","suffix":""},{"id":304180880,"identity":"840b36ef-2fb9-4c82-b438-3bcf55438060","order_by":3,"name":"Vanessa Pauly","email":"","orcid":"","institution":"Aix-Marseille Universite","correspondingAuthor":false,"prefix":"","firstName":"Vanessa","middleName":"","lastName":"Pauly","suffix":""},{"id":304180881,"identity":"4dd08d30-63b4-4610-84b8-33b18036e01c","order_by":4,"name":"Veronica Orleans","email":"","orcid":"","institution":"Universite Aix-Marseille III: Aix-Marseille Universite","correspondingAuthor":false,"prefix":"","firstName":"Veronica","middleName":"","lastName":"Orleans","suffix":""},{"id":304180882,"identity":"64a27e0a-7f45-4256-8662-6b55272d343a","order_by":5,"name":"Guillaume Fond","email":"","orcid":"","institution":"Aix-Marseille Universite","correspondingAuthor":false,"prefix":"","firstName":"Guillaume","middleName":"","lastName":"Fond","suffix":""},{"id":304180883,"identity":"4f1197b2-21c9-4084-881a-40f6a61e7988","order_by":6,"name":"Gary Duclos","email":"","orcid":"","institution":"Aix-Marseille Universite","correspondingAuthor":false,"prefix":"","firstName":"Gary","middleName":"","lastName":"Duclos","suffix":""},{"id":304180884,"identity":"0a4f5d82-ab5b-41cd-8534-b7e35161bb8d","order_by":7,"name":"Laurent Zieleskiewicz","email":"","orcid":"","institution":"Aix-Marseille Universite","correspondingAuthor":false,"prefix":"","firstName":"Laurent","middleName":"","lastName":"Zieleskiewicz","suffix":""},{"id":304180885,"identity":"32b02a0b-3ceb-40ed-9308-4c7af3fff9dd","order_by":8,"name":"Djamel Mokart","email":"","orcid":"","institution":"Aix-Marseille Universite","correspondingAuthor":false,"prefix":"","firstName":"Djamel","middleName":"","lastName":"Mokart","suffix":""},{"id":304180886,"identity":"4b891a98-2c88-4b59-a508-29cf57c1cc77","order_by":9,"name":"Laurent Boyer","email":"","orcid":"","institution":"Aix-Marseille Universite","correspondingAuthor":false,"prefix":"","firstName":"Laurent","middleName":"","lastName":"Boyer","suffix":""},{"id":304180887,"identity":"a766e799-97d2-4a12-88d6-62ef92d0dfc8","order_by":10,"name":"Marc Leone","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0ElEQVRIiWNgGAWjYNCCAhDBfABIHIDSBIEBiGBLgGgB08Rp4TEgTotu+9mHHxgMbOTM2Xs+fi5guBPNwMb7AK8WszPpxhIMBmnGlj1nN0vPYHiW28DGboBfy4E0NqDDDiduuJG7QZr33+HcBvk2/A4zO/8MpOV/4ob7bx7/5mEAamFjI6DlBtiWA0BbeNikidTyjFkiwSDZ2OBMmpn1DKCWNoJazqcxfvhQYSdncPzw49sFQC39hLSAQQKUZgYRxGhAAGaSVI+CUTAKRsGIAQDSgEEPZHdpGwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-3097-758X","institution":"Aix-Marseille Universite","correspondingAuthor":true,"prefix":"","firstName":"Marc","middleName":"","lastName":"Leone","suffix":""}],"badges":[],"createdAt":"2024-04-30 08:55:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4347653/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4347653/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":57721538,"identity":"5edc12ab-991d-405a-b665-0971e5b8a10e","added_by":"auto","created_at":"2024-06-04 18:58:29","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":152484,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of the patients admitted to the intensive care unit (ICU) with septic shock during the study period 2017-2018\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4347653/v1/5d5161b645d745c3d83b39c6.jpeg"},{"id":57721540,"identity":"4c9b15e7-8b92-4134-ba7b-49b8c10c1ae1","added_by":"auto","created_at":"2024-06-04 18:58:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":59899,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier estimates of overall survival at 90-day after intensive care unit (ICU) admission in septic shock\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4347653/v1/89e3034eabe16f111fcd9786.png"},{"id":59148155,"identity":"391c0752-0cc6-45e6-99fa-50a34476443d","added_by":"auto","created_at":"2024-06-27 01:16:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1738320,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4347653/v1/717be271-ef7e-49b2-aeba-84ffec80ddb4.pdf"},{"id":57721539,"identity":"bdb8c516-37c3-4fc0-83dd-cf00e599fcd1","added_by":"auto","created_at":"2024-06-04 18:58:29","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":28822,"visible":true,"origin":"","legend":"","description":"","filename":"AppendixICM.docx","url":"https://assets-eu.researchsquare.com/files/rs-4347653/v1/862ef25811b406a4c6d841b4.docx"},{"id":57721542,"identity":"59b70738-8c11-4829-9a3a-67f7370657c6","added_by":"auto","created_at":"2024-06-04 18:58:30","extension":"pdf","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":18824,"visible":true,"origin":"","legend":"","description":"","filename":"STROBEchecklistv4cohort.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4347653/v1/806429b0e202ee0665d206a7.pdf"}],"financialInterests":"","formattedTitle":"Mortality of cancer patients with septic shock: a nation-based cohort analysis in 77,888 patients","fulltext":[{"header":"Take Home Message","content":"\u003cp\u003eIn septic shock, cancer patients had increased risk of mortality compared with noncancer patients. Early ICU admission and identification of source infection are crucial in cancer patients.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eSeptic shock is the most severe form of sepsis, defined as an inappropriate host response to infection, resulting in one or more life-threatening organ dysfunction(s) with a mortality rate around 45%\u0026nbsp;[1]. The management of patients with severe underlying diseases may participate to these poor outcomes.\u003c/p\u003e\n\u003cp\u003eIn a previous cohort study based on a national database, we found that\u0026nbsp;53,206 (28.4%) of 187,587\u0026nbsp;patients with septic shock had an history of cancer while a diagnosis of \u0026ldquo;tumor\u0026rdquo; was reported as the cause of intensive care unit (ICU) admission in 5.9% of patients\u0026nbsp;[2]. In addition, cancer was associated with an increased mortality rate at 90 days. In a large national cohort study from the Netherlands, the one-year mortality of cancer patients with an unplanned ICU admission was also higher than that of patients without cancer\u0026nbsp;[3]. In a systematic review, the ICU mortality rate of cancer patients was 38% but wide variations were round between the studies\u0026nbsp;[4].\u003c/p\u003e\n\u003cp\u003eThe outcome of cancer may differ according to the type of cancer. In a retrospective study describing trends in outcomes of cancer patients requiring an unplanned admission to the ICU, analysis of more than 46,000 patients admitted to ICU between 2009 and 2013 showed that hospital mortality rates of patients with solid tumors and hematological malignancies were 26% and 56%, respectively\u0026nbsp;[5]. A study based on the National Intensive Care Evaluation registry focusing on patients with unplanned ICU admission in the Netherlands between 2008 and 2017 found that one-year mortality rates were 60.1%, 46.2%, and 28.3% in patients with hematological cancer, solid cancer, and those without cancer\u0026nbsp;[3]. These studies tend to show that the mortality is affected by the nature of cancer with an increased risk in patients with hematological cancer.\u003c/p\u003e\n\u003cp\u003eAlthough several observational studies reported mortality rates of septic patients with solid or hematological cancers, most of them were conducted in specialized centers in low or moderate numbers of patients [6]. Here we aim to describe the effect of solid cancer and hematological cancer on the outcome of patients with septic shock requiring admission to the ICU, based on the French national database over a 2-year period (2017-2018) [2]. Our primary goal was to determine the 90-day mortality of patients with septic shock and solid cancer, hematological cancer and noncancer affection. Secondary objectives were the risk factors of 90-day mortality in the entire cohort.\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis was a general population cohort study involving all adult patients (over 18 years old) with septic shock, admitted to French intensive care units between January 1, 2017, and December 31, 2018, using data from the French national Program of Medicalization of Systems of Information (PMSI) database, which compiles administrative and medical information (diagnoses and surgical procedures), as described in a previous study [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Briefly, the PMSI is based on patient discharge diagnosis groups coded according to the International Classification of Diseases, 10th revision (ICD-10). Technical and medical procedures performed throughout the stay are also coded daily according to the Common Classification of Medical Procedures (CCAM). The PMSI database is used to determine financial resources and is subject to frequent and thorough checks by both its producer and the payer, with possible financial and legal consequences for those who do not provide data or provide inaccurate data. PMSI data are anonymized and can be reused for research purposes. Due to its accuracy and comprehensive data collection, no patient is lost to follow-up during the study period. This study follows the STROBE guidelines (Strengthening the Reporting of Observational Studies in Epidemiology) and, as it is based on anonymous and retrospective data, did not require approval from an ethics committee or informed consent from patients. Data extraction was performed by the authorized public health service of Public Hospitals of Marseille according to the registered study protocol. Access to the national PMSI database was obtained through a usage agreement signed between the Technical Agency for Information on Hospitalization (ATIH) and the Public Hospitals of Marseille. In accordance with French law, a declaration of compliance with reference methodology 005 (MR005) was registered with the National Commission for Data Protection (CNIL) under number F20220318151239.\u003c/p\u003e \u003cp\u003eStudy Patients\u003c/p\u003e \u003cp\u003eSeptic shock was identified using two strategies: either directly from a \"septic shock\" ICD-10 code (r572) or indirectly with a combination of codes corresponding to a severe infection (sepsis or bacteremia) associated with the use of vasopressors, as described elsewhere [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Cancer patients were defined based on the algorithm of the National Cancer Institute (INCa) searched in all PMSI hospitalizations in conventional wards, follow-up care and rehabilitation, home hospitalization, and psychiatry during the year preceding hospitalization for septic shock, as well as during hospitalization for septic shock. The study was limited to patients aged 18 years or older. By convention, the group of patients with neoplasms will be called the cancer group, while patients without neoplasms serving as controls will be grouped in the non-cancer group. To exclude patients with no severity criteria, suggesting overcoding of septic shock, ICU stays were included only if they lasted at least 48 hours, with the exception of patients who died within the first 48 hours.\u003c/p\u003e \u003cp\u003eData Collected\u003c/p\u003e \u003cp\u003eFor each ICU stay, the following data were collected: age (raw data) and categorized into 4 classes (18\u0026ndash;44 years; 45\u0026ndash;64 years; 65\u0026ndash;75 years; \u0026gt; 75 years), sex, social disadvantage according to the FDep territorial index of social disadvantage for the French Deprivation Index (calculated at the municipal level from 4 variables: the proportion of workers in the working population aged 15 to 64 years, the proportion of unemployed in the working population aged 15 to 64 years, the proportion of high school graduates (minimum) in the non-school population aged 15 years or older, and the median household income tax), the Charlson score (a comorbidity measurement tool designed to predict one-year mortality and the comorbidities used to calculate it (for the cancer patients, cancer and metastasis items were deliberately excluded from the calculation), presence or absence of neutropenia (neutrophil count in the blood\u0026thinsp;\u0026lt;\u0026thinsp;500 cells/mm\u003csup\u003e3\u003c/sup\u003e), reason for ICU admission, time from hospital admission to ICU admission, mode of admission (through the emergency department, medical or surgical services), severity acute physiology score (SAPS) 2, organ failures, site of infection, health care associated or community acquired infection, causative germs and antimicrobial resistance profile, support therapies (cardiopulmonary resuscitation, mechanical ventilation, blood transfusion, renal replacement therapy, type of cancer (solid tumors or hematological), hospital characteristics (academic vs. nonacademic public vs. private), and mode of ICU discharge.\u003c/p\u003e \u003cp\u003eEnd Points\u003c/p\u003e \u003cp\u003eThe primary outcome was all-cause mortality assessed at day 90 according to the status \u0026ldquo;solid cancer\u0026rdquo;, \u0026ldquo;hematological cancer\u0026rdquo;, or \u0026ldquo;noncancer\u0026rdquo;. Secondary outcomes were the identification of risk factors associated with the 90-day mortality rate.\u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eData are presented as mean \u0026plusmn; (standard deviation) for parametric distribution data, as median (interquartile range defined as interquartile range (IQR) [25\u0026ndash;75]) for non-parametric data. Categorical data are presented as number and %.\u003c/p\u003e \u003cp\u003eStandardized differences were used to compare \u0026ldquo;solid cancer\u0026rdquo;, \u0026ldquo;hematological cancer\u0026rdquo;, or \u0026ldquo;noncancer\u0026rdquo; patients. An absolute standardized difference (SD) of ⩽0.20 was chosen to indicate a negligible difference in the mean or prevalence of a variable between groups. The SD helps to understand the magnitude of the differences found, in addition to statistical significance, which examines whether the findings are likely to be due to chance[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo study the association between each group and outcome, the Kaplan\u0026ndash;Meier method and the log-rank statistic were used to estimate and compare the cumulative death rates. Hazard ratios (HRs) and 95% confidence intervals (95% CIs) were estimated using Cox survival models with a robust variance estimator to account for clustering within matched pairs. Two models were developed. Model 1 included the group, age, sex, smoking, alcohol, overweight or obesity, the Charlson comorbidity index (0, 1 to 2, \u0026ge;\u0026thinsp;3), SAPS II score (modified, without age), organ failures, ICU supportive therapies, site of infection, the source of hospital admission, time between hospital admission and ICU admission, hospital characteristics. The model 2 included the 17 Charlson comorbidities instead of the Charlson comorbidity index.\u003c/p\u003e \u003cp\u003eThe proportional-hazards assumption for the Cox models was investigated and confirmed graphically through survival functions over time. A \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered significant. Data management and analyses were performed using the SAS software. Cox regression analyses were performed using the PROC PHREG in SAS.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eAmong 77,888 ICU admissions for septic shock from 2017 to 2018, 19,329 patients had solid cancer, 6,498 had hematological cancer and 52,061 had noncancer affections (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAlmost all differences between solid cancer patients, hematological patients, and noncancer patients reached a significant level (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Patients with solid cancer were slightly older than those with noncancer affection (68.7\u0026plusmn;11.3 vs. 66.4\u0026plusmn;15.2 years). The SAPS2 at ICU admission was higher in the hematological cancer patients than in the solid cancer and noncancer patients (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demo graphic, clinical and hospital characteristics between the different groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatients with solid cancer\u003c/p\u003e \u003cp\u003e(A)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePatients with Hematologic cancer\u003c/p\u003e \u003cp\u003e(B)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePatients without cancer\u003c/p\u003e \u003cp\u003e(C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eA vs C\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eB vs C\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003eA vs B\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77,888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19,329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6,498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52,061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSD\u0026dagger;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u0026dagger;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSD\u0026Dagger;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep-value\u0026Dagger;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSD⨎\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ep-value⨎\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge \u0026ndash; year\u003c/p\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e67.1\u0026thinsp;\u0026plusmn;\u0026thinsp;14.2\u003c/p\u003e \u003cp\u003e[67.0\u0026ndash;67.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e68.7\u0026thinsp;\u0026plusmn;\u0026thinsp;11.3\u003c/p\u003e \u003cp\u003e[68.6\u0026ndash;68.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e67.4\u0026thinsp;\u0026plusmn;\u0026thinsp;13.5\u003c/p\u003e \u003cp\u003e[67.1\u0026ndash;67.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e66.4\u0026thinsp;\u0026plusmn;\u0026thinsp;15.2\u003c/p\u003e \u003cp\u003e[66.3\u0026ndash;66.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (women)\u003c/p\u003e \u003cp\u003e\u0026ndash;n (%)\u003c/p\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27,939\u003c/p\u003e \u003cp\u003e(35.9%)\u003c/p\u003e \u003cp\u003e[35.5\u0026ndash;36.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,997 (31.0%)\u003c/p\u003e \u003cp\u003e[30.4\u0026ndash;31.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,204 (33.9%)\u003c/p\u003e \u003cp\u003e[32.8\u0026ndash;35.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19,738 (37.9%)\u003c/p\u003e \u003cp\u003e[37.5\u0026ndash;38.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight or obese \u0026ndash; n (%)\u003c/p\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14,289 (18.3%)\u003c/p\u003e \u003cp\u003e[18.1\u0026ndash;18.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,147 (16.3%)\u003c/p\u003e \u003cp\u003e[15.8\u0026ndash;16.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e939 (14.5%)\u003c/p\u003e \u003cp\u003e[13.6\u0026ndash;15.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10,203 (19.6%)\u003c/p\u003e \u003cp\u003e[19.3\u0026ndash;19.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking addiction \u0026ndash; n (%)\u003c/p\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12,529 (16.1%)\u003c/p\u003e \u003cp\u003e[15.8\u0026ndash;16.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,572 (18.5%)\u003c/p\u003e \u003cp\u003e[17.9\u0026ndash;19.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e735 (11.3%)\u003c/p\u003e \u003cp\u003e[10.5\u0026ndash;12.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8,222 (15.8%)\u003c/p\u003e \u003cp\u003e[15.5\u0026ndash;16.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol addiction \u0026ndash; n (%)\u003c/p\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11,408 (14.6%)\u003c/p\u003e \u003cp\u003e[14.4\u0026ndash;14.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,552 (13.2%)\u003c/p\u003e \u003cp\u003e[12.7\u0026ndash;13.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e449 (6.9%)\u003c/p\u003e \u003cp\u003e[6.3\u0026ndash;7.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8,407 (16.1%)\u003c/p\u003e \u003cp\u003e[15.8\u0026ndash;16.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharlson index \u0026ndash; n (%)\u003c/p\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16,365 (21.0%)\u003c/p\u003e \u003cp\u003e[20.7\u0026ndash;21.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,001 (25.9%)\u003c/p\u003e \u003cp\u003e[25.2\u0026ndash;26.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,561 (24.0%)\u003c/p\u003e \u003cp\u003e[23.0\u0026ndash;25.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9,803 (18.8%)\u003c/p\u003e \u003cp\u003e[18.5\u0026ndash;19.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27,900 (35.8%)\u003c/p\u003e \u003cp\u003e[35.5\u0026ndash;36.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,111 (36.8%)\u003c/p\u003e \u003cp\u003e[36.1\u0026ndash;37.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,270 (34.9%)\u003c/p\u003e \u003cp\u003e[33.8\u0026ndash;36.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18,519 (35.6%)\u003c/p\u003e \u003cp\u003e[35.2\u0026ndash;36.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.623 (43.2%)\u003c/p\u003e \u003cp\u003e[42.8\u0026ndash;43.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,217 (37.3%)\u003c/p\u003e \u003cp\u003e[36.6\u0026ndash;38.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,667 (41.0%)\u003c/p\u003e \u003cp\u003e[39.8\u0026ndash;42.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23,739 (45.6%)\u003c/p\u003e \u003cp\u003e[45.2\u0026ndash;46.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSAPS II score at ICU admission (without age), Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.4\u0026thinsp;\u0026plusmn;\u0026thinsp;23.1\u003c/p\u003e \u003cp\u003e[43.2\u0026ndash;43.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.0\u0026thinsp;\u0026plusmn;\u0026thinsp;23.5\u003c/p\u003e \u003cp\u003e[42.7\u0026ndash;43.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.7\u0026thinsp;\u0026plusmn;\u0026thinsp;24.6\u003c/p\u003e \u003cp\u003e[47.1\u0026ndash;48.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43.0\u0026thinsp;\u0026plusmn;\u0026thinsp;22.6\u003c/p\u003e \u003cp\u003e[42.8\u0026ndash;43.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSAPS II score at ICU admission (without age, solid and hematologic cancer), Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.3\u0026thinsp;\u0026plusmn;\u0026thinsp;23.3\u003c/p\u003e \u003cp\u003e[40.2\u0026ndash;40.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.0\u0026thinsp;\u0026plusmn;\u0026thinsp;23.5\u003c/p\u003e \u003cp\u003e[33.7\u0026ndash;34.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.7\u0026thinsp;\u0026plusmn;\u0026thinsp;24.6\u003c/p\u003e \u003cp\u003e[37.1\u0026ndash;38.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43.0\u0026thinsp;\u0026plusmn;\u0026thinsp;22.6\u003c/p\u003e \u003cp\u003e[42.8\u0026ndash;43.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite of infection \u0026ndash; n (%)\u003c/p\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29,358 (37.7%)\u003c/p\u003e \u003cp\u003e[37.3\u0026ndash;38.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,400 (33.1%)\u003c/p\u003e \u003cp\u003e[32.4\u0026ndash;33.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,401 (36.9%)\u003c/p\u003e \u003cp\u003e[35.8\u0026ndash;38.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20,557 (39.5%)\u003c/p\u003e \u003cp\u003e[39.1\u0026ndash;39.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastrointestinal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14,499 (18.6%)\u003c/p\u003e \u003cp\u003e[18.3\u0026ndash;18.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,260 (27.2%)\u003c/p\u003e \u003cp\u003e[26.6\u0026ndash;27.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e796 (12.2%)\u003c/p\u003e \u003cp\u003e[11.5\u0026ndash;13.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8,443 (16.2%)\u003c/p\u003e \u003cp\u003e[15.9\u0026ndash;16.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,319 (9.4%)\u003c/p\u003e \u003cp\u003e[9.2\u0026ndash;9.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,818 (9.4%)\u003c/p\u003e \u003cp\u003e[9.0\u0026ndash;9.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e572 (8.8%)\u003c/p\u003e \u003cp\u003e[8.1\u0026ndash;9.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4,929 (9.5%)\u003c/p\u003e \u003cp\u003e[9.2\u0026ndash;9.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.146\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiac\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,932 (10.2%)\u003c/p\u003e \u003cp\u003e[10.0\u0026ndash;10.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,841 (9.5%)\u003c/p\u003e \u003cp\u003e[9.1\u0026ndash;9.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e841 (12.9%)\u003c/p\u003e \u003cp\u003e[12.1\u0026ndash;13.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5,250 (10.1%)\u003c/p\u003e \u003cp\u003e[9.8\u0026ndash;10.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDermatologic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,468 (7.0%)\u003c/p\u003e \u003cp\u003e[6.8\u0026ndash;7.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,291 (6.7%)\u003c/p\u003e \u003cp\u003e[6.3\u0026ndash;7.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e459 (7.1%)\u003c/p\u003e \u003cp\u003e[6.4\u0026ndash;7.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,718 (7.1%)\u003c/p\u003e \u003cp\u003e[6.9\u0026ndash;7.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.818\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.285\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrgan failures \u0026ndash; n (%)\u003c/p\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44,400 (57.0%)\u003c/p\u003e \u003cp\u003e[56.6\u0026ndash;57.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10,483 (54.2%)\u003c/p\u003e \u003cp\u003e[53.5\u0026ndash;54.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,878 (59.7%)\u003c/p\u003e \u003cp\u003e[58.5\u0026ndash;60.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30,039 (57.7%)\u003c/p\u003e \u003cp\u003e[57.3\u0026ndash;58.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37,861 (48.6%)\u003c/p\u003e \u003cp\u003e[48.2\u0026ndash;49.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9,001 (46.6%)\u003c/p\u003e \u003cp\u003e[45.9\u0026ndash;47.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,524 (54.2%)\u003c/p\u003e \u003cp\u003e[53.0\u0026ndash;55.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25,336 (48.7%)\u003c/p\u003e \u003cp\u003e[48.2\u0026ndash;49.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeurologic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17,900 (23.0%)\u003c/p\u003e \u003cp\u003e[22.7\u0026ndash;23.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,423 (17.7%)\u003c/p\u003e \u003cp\u003e[17.2\u0026ndash;18.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,256 (19.3%)\u003c/p\u003e \u003cp\u003e[18.4\u0026ndash;20.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13,221 (25.4%)\u003c/p\u003e \u003cp\u003e[25.0\u0026ndash;25.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiovascular\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12,873 (16.5%)\u003c/p\u003e \u003cp\u003e[16.3\u0026ndash;16.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,445 (12.6%)\u003c/p\u003e \u003cp\u003e[12.2\u0026ndash;13.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,068 (16.4%)\u003c/p\u003e \u003cp\u003e[15.5\u0026ndash;17.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9,360 (18.0%)\u003c/p\u003e \u003cp\u003e[17.6\u0026ndash;18.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHematologic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10,685 (13.7%)\u003c/p\u003e \u003cp\u003e[13.5\u0026ndash;14.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,303 (11.9%)\u003c/p\u003e \u003cp\u003e[11.5\u0026ndash;12.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,739 (26.8%)\u003c/p\u003e \u003cp\u003e[25.7\u0026ndash;27.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6,643 (12.8%)\u003c/p\u003e \u003cp\u003e[12.5\u0026ndash;13.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetabolic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18,298 (23.5%)\u003c/p\u003e \u003cp\u003e[23.2\u0026ndash;23.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,274 (22.1%)\u003c/p\u003e \u003cp\u003e[21.5\u0026ndash;22.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,524 (23.5%)\u003c/p\u003e \u003cp\u003e[22.4\u0026ndash;24.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12,500 (24.0%)\u003c/p\u003e \u003cp\u003e[23.6\u0026ndash;24.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,964 (10.2%)\u003c/p\u003e \u003cp\u003e[10.0\u0026ndash;10.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,832 (9.5%)\u003c/p\u003e \u003cp\u003e[9.1\u0026ndash;9.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e663 (10.2%)\u003c/p\u003e \u003cp\u003e[9.5\u0026ndash;10.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5,469 (10.5%)\u003c/p\u003e \u003cp\u003e[10.2\u0026ndash;10.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICU supportive therapies \u0026ndash; n (%)\u003c/p\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiopulmonary resuscitation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,801 (4.9%)\u003c/p\u003e \u003cp\u003e[4.7\u0026ndash;5.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e762 (3.9%)\u003c/p\u003e \u003cp\u003e[3.7\u0026ndash;4.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e310 (4.8%)\u003c/p\u003e \u003cp\u003e[4.3\u0026ndash;5.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,729 (5.2%)\u003c/p\u003e \u003cp\u003e[5.1\u0026ndash;5.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInvasive mechanical ventilation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61,026 (78.3%)\u003c/p\u003e \u003cp\u003e[78.1\u0026ndash;78.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14,553 (75.3%)\u003c/p\u003e \u003cp\u003e[74.7\u0026ndash;75.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,666 (71.8%)\u003c/p\u003e \u003cp\u003e[70.7\u0026ndash;72.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41,807 (80.3%)\u003c/p\u003e \u003cp\u003e[80.0\u0026ndash;80.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal replacement therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21,584 (27.7%)\u003c/p\u003e \u003cp\u003e[27.4\u0026ndash;28.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,722 (24.4%)\u003c/p\u003e \u003cp\u003e[23.8\u0026ndash;25.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,077 (32.0%)\u003c/p\u003e \u003cp\u003e[30.8\u0026ndash;33.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14,785 (28.4%)\u003c/p\u003e \u003cp\u003e[28.0\u0026ndash;28.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransfusion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24,596 (31.6%)\u003c/p\u003e \u003cp\u003e[31.2\u0026ndash;31.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,489 (33.6%)\u003c/p\u003e \u003cp\u003e[32.9\u0026ndash;34.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,857 (44.0%)\u003c/p\u003e \u003cp\u003e[42.8\u0026ndash;45.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15,250 (29.3%)\u003c/p\u003e \u003cp\u003e[28.9\u0026ndash;29.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive culture with identification, n (%)\u003c/p\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52,533 (67.4%)\u003c/p\u003e \u003cp\u003e[67.1\u0026ndash;67.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13,048 (67.5%)\u003c/p\u003e \u003cp\u003e[66.8\u0026ndash;68.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,411 (67.9%)\u003c/p\u003e \u003cp\u003e[66.7\u0026ndash;69.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35,074 (67.4%)\u003c/p\u003e \u003cp\u003e[67.0\u0026ndash;67.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.734\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.573\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultidrug resistant bacteria, n (%)\u003c/p\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13,777 (17.7%)\u003c/p\u003e \u003cp\u003e[17.4\u0026ndash;17.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,527 (18.2%)\u003c/p\u003e \u003cp\u003e[17.7\u0026ndash;18.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,218 (18.7%)\u003c/p\u003e \u003cp\u003e[17.8\u0026ndash;19.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9,032 (17.3%)\u003c/p\u003e \u003cp\u003e[17.0\u0026ndash;17.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.370\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnterobacter, n (%)\u003c/p\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26,700 (34.3%)\u003c/p\u003e \u003cp\u003e[33.9\u0026ndash;34.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,258 (37.5%)\u003c/p\u003e \u003cp\u003e[36.9\u0026ndash;38.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,133 (32.8%)\u003c/p\u003e \u003cp\u003e[31.7\u0026ndash;34.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17,309 (33.2%)\u003c/p\u003e \u003cp\u003e[32.8\u0026ndash;33.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStaphylococcus, n (%)\u003c/p\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18,311 (23.5%)\u003c/p\u003e \u003cp\u003e[23.2\u0026ndash;23.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,120 (21.3%)\u003c/p\u003e \u003cp\u003e[20.7\u0026ndash;21.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,421 (21.9%)\u003c/p\u003e \u003cp\u003e[20.9\u0026ndash;22.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12,770 (24.5%)\u003c/p\u003e \u003cp\u003e[24.2\u0026ndash;24.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.347\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStreptococcus, n (%)\u003c/p\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16,952 (21.8%)\u003c/p\u003e \u003cp\u003e[21.5\u0026ndash;22.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,450 (23.0%)\u003c/p\u003e \u003cp\u003e[22.4\u0026ndash;23.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,178 (18.1%)\u003c/p\u003e \u003cp\u003e[17.2\u0026ndash;19.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11,324 (21.8%)\u003c/p\u003e \u003cp\u003e[21.4\u0026ndash;22.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePseudomonas aeruginosa, n (%)\u003c/p\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10,388 (13.3%)\u003c/p\u003e \u003cp\u003e[13.1\u0026ndash;13.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,683 (13.9%)\u003c/p\u003e \u003cp\u003e[13.4\u0026ndash;14.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e998 (15.4%)\u003c/p\u003e \u003cp\u003e[14.5\u0026ndash;16.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6,707 (12.9%)\u003c/p\u003e \u003cp\u003e[12.6\u0026ndash;13.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCandida, n (%)\u003c/p\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9,417 (12.1%)\u003c/p\u003e \u003cp\u003e[11.9\u0026ndash;12.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,826 (14.6%)\u003c/p\u003e \u003cp\u003e[14.1\u0026ndash;15.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e887 (13.6%)\u003c/p\u003e \u003cp\u003e[12.8\u0026ndash;14.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5,704 (11.0%)\u003c/p\u003e \u003cp\u003e[10.7\u0026ndash;11.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital-acquired infection, n (%)\u003c/p\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21,508 (27.6%)\u003c/p\u003e \u003cp\u003e[27.3\u0026ndash;27.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,560 (33.9%)\u003c/p\u003e \u003cp\u003e[33.3\u0026ndash;34.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,755 (27.0%)\u003c/p\u003e \u003cp\u003e[25.9\u0026ndash;28.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13,193 (25.3%)\u003c/p\u003e \u003cp\u003e[25.0\u0026ndash;25.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource of hospital admission \u0026ndash; n (%)\u003c/p\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.747\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.801\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74,842 (96.1%)\u003c/p\u003e \u003cp\u003e[95.9\u0026ndash;96.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18,851 (96.1%)\u003c/p\u003e \u003cp\u003e[95.9\u0026ndash;96.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6,242 (96.1%)\u003c/p\u003e \u003cp\u003e[95.6\u0026ndash;96.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50,019 (96.1%)\u003c/p\u003e \u003cp\u003e[95.9\u0026ndash;96.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.747\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.801\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransfer from other hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,046 (3.9%)\u003c/p\u003e \u003cp\u003e[3.8\u0026ndash;4.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e748 (3.9%)\u003c/p\u003e \u003cp\u003e[3.6\u0026ndash;4.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e256 (3.9%)\u003c/p\u003e \u003cp\u003e[3.5\u0026ndash;4.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,042 (3.9%)\u003c/p\u003e \u003cp\u003e[3.8\u0026ndash;4.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.747\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.801\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime to ICU admission\u0026thinsp;\u0026le;\u0026thinsp;1 day \u0026ndash; n (%)\u003c/p\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46,297 (59.4%)\u003c/p\u003e \u003cp\u003e[59.1\u0026ndash;59.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9,392 (48.6%)\u003c/p\u003e \u003cp\u003e[47.9\u0026ndash;49.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,994 (46.1%)\u003c/p\u003e \u003cp\u003e[44.9\u0026ndash;47.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33,911 (65.1%)\u003c/p\u003e \u003cp\u003e[64.7\u0026ndash;65.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital characteristics \u0026ndash; n (%) [95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcademic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25,993 (33.4%)\u003c/p\u003e \u003cp\u003e[33.0\u0026ndash;33.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,518 (33.7%)\u003c/p\u003e \u003cp\u003e[31.1\u0026ndash;34.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,685 (41.3%)\u003c/p\u003e \u003cp\u003e[40.1\u0026ndash;42.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16,790 (32.2%)\u003c/p\u003e \u003cp\u003e[31.8\u0026ndash;32.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther public hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39,354 (50.5%)\u003c/p\u003e \u003cp\u003e[50.2\u0026ndash;50.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8,247 (42.7%)\u003c/p\u003e \u003cp\u003e[42.0\u0026ndash;43.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,942 (45.3%)\u003c/p\u003e \u003cp\u003e[44.1\u0026ndash;46.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28,165 (54.1%)\u003c/p\u003e \u003cp\u003e[53.7\u0026ndash;54.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12,541 (16.1%)\u003c/p\u003e \u003cp\u003e[15.8\u0026ndash;16.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,564 (23.6%)\u003c/p\u003e \u003cp\u003e[23.0\u0026ndash;24.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e871 (13.4%)\u003c/p\u003e \u003cp\u003e[12.6\u0026ndash;14.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7,106 (13.6%)\u003c/p\u003e \u003cp\u003e[13.4\u0026ndash;13.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u0026dagger; \u003cem\u003eStandardized difference and p-value between patients with solid cancer and without cancer;\u003c/em\u003e \u0026Dagger; \u003cem\u003eStandardized difference and p-value between patients with hematologic cancer and without cancer;\u003c/em\u003e ⨎ \u003cem\u003eStandardized difference and p-value between patients with solid and hematologic cancer.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003cem\u003eSD\u0026le;|0.10| was chosen to indicate a negligible difference in the mean or prevalence of a variable between groups. SD\u0026gt;|0.10| shown in bold.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003cem\u003e95% CI: 95% confidence interval.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003cem\u003eICU : Intensive Care Unit\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003cem\u003eSAPS II : Simplified Acute Physiology Score\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e90-day mortality in septic shock patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAlive\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;40,606)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDead\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;37,282)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCrude HR\u003c/p\u003e \u003cp\u003eRandom effect : Finess\u003c/p\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eFrailty model 1\u003c/p\u003e \u003cp\u003eRandom effect : Finess\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eFrailty model 2\u003c/p\u003e \u003cp\u003eRandom effect : Finess\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAdjusted HR\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAdjusted HR\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup of patients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatients without cancer \u0026ndash; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29,007 (71.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23,054 (61.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatients with solid cancer\u0026ndash; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8,943 (22.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10,386 (27.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.26 [1.24\u0026ndash;1.29]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.55 [1.51\u0026ndash;1.59]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.55 [1.51\u0026ndash;1.59]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatients with Hematologic cancer\u0026ndash; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,656 (6.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,842 (10.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.49 [1.44\u0026ndash;1.54]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.59 [1.53\u0026ndash;1.65]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.60 [1.55\u0026ndash;1.66]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge \u0026ndash; year, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64.3\u0026thinsp;\u0026plusmn;\u0026thinsp;14.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.0\u0026thinsp;\u0026plusmn;\u0026thinsp;12.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.02 [1.02\u0026ndash;1.02]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.02 [1.02\u0026ndash;1.02]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.02 [1.02\u0026ndash;1.02]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (women) \u0026ndash; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14,902 (36.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13,037 (35.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.97 [0.95\u0026ndash;0.99]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.019\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.01 [0.99\u0026ndash;1.03]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.306\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.01 [0.99\u0026ndash;1.03]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.281\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight or obese \u0026ndash; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8,254 (20.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,035 (16.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79 [0.77\u0026ndash;0.82]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.82 [0.79\u0026ndash;0.84]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.83 [0.81\u0026ndash;0.85]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking addiction \u0026ndash; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,377 (18.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,152 (13.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77 [0.75\u0026ndash;0.79]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.92 [0.89\u0026ndash;0.95]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.92 [0.89\u0026ndash;0.95]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol addiction \u0026ndash; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6,283 (15.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,125 (13.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.88 [0.85\u0026ndash;0.91]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.99 [0.96\u0026ndash;1.02]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.662\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.89 [0.86\u0026ndash;0.92]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharlson comorbidity index \u0026ndash; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9,237 (22.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,128 (19.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15,010 (37.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12,890 (34.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.02 [0.99\u0026ndash;1.05]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.93 [0.90\u0026ndash;0.96]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16,359 (40.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17,264 (46.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.14 [1.11\u0026ndash;1.17]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.98 [0.95\u0026ndash;1.01]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharlson comorbidity \u0026ndash; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDementia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,301 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,589 (4,3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.18 [1.12\u0026ndash;1.24]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.00 [0.95\u0026ndash;1.05]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.821\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e411 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e286 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.80 [0.71\u0026ndash;0.90]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.88 [0.78\u0026ndash;0.99]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.042\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate or severe liver disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,009 (4.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,634 (9.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.58 [1.53\u0026ndash;1.64]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.28 [1.23\u0026ndash;1.34]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemiplegia or paraplegia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,842 (11.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,988 (8.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.67 [0.65\u0026ndash;0.70]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.79 [0.76\u0026ndash;0.82]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardio heart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13,715 (33.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14,227 (38.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.10 [1.07\u0026ndash;1.12]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.04 [1.01\u0026ndash;1.07]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic obstructive pulmonary disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8,315 (20.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,750 (20.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.96 [0.94\u0026ndash;0.99]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.012\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.00 [0.97\u0026ndash;1.03]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.845\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes with complication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,247 (10.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,409 (11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.04 [1.01\u0026ndash;1.08]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.01 [0.98\u0026ndash;1.05]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes without complications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10,134 (25.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9,129 (24.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.95 [0.93\u0026ndash;0.97]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.89 [0.86\u0026ndash;0.91]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyocardial infarction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6,821 (16.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,007 (18.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.07 [1.04\u0026ndash;1.10]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.98 [0.95\u0026ndash;1.02]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.481\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMild liver disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,005 (9.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,600 (15.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.38 [1.34\u0026ndash;1.42]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.21 [1.17\u0026ndash;1.25]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeptic ulcer disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,368 (5.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,216 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.94 [0.90\u0026ndash;0.98]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.88 [0.85\u0026ndash;0.92]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeripheral vascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6,092 (15.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,341 (17.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.08 [1.05\u0026ndash;1.11]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.08 [1.05\u0026ndash;1.11]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,306 (18.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8,483 (22.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.17 [1.14\u0026ndash;1.20]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.92 [0.89\u0026ndash;0.94]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSAPS II score at ICU admission (without age), Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37.5\u0026thinsp;\u0026plusmn;\u0026thinsp;19.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.8\u0026thinsp;\u0026plusmn;\u0026thinsp;25.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.02 [1.02\u0026ndash;1.02]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSAPS II score at ICU admission (without age, solid and hematologic cancer), Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e34.9\u0026thinsp;\u0026plusmn;\u0026thinsp;19.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.3\u0026thinsp;\u0026plusmn;\u0026thinsp;25.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.02 [1.02\u0026ndash;1.02]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.01 [1.01\u0026ndash;1.01]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.01 [1.01\u0026ndash;1.01]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite of infection \u0026ndash; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15,770 (38.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13,588 (36.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83 [0.81\u0026ndash;0.85]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.82 [0.80\u0026ndash;0.84]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.82 [0.80\u0026ndash;0.84]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastrointestinal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8,199 (20.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,300 (16.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83 [0.81\u0026ndash;0.85]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.76 [0.74\u0026ndash;0.79]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.77 [0.74\u0026ndash;0.79]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,065 (12.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,254 (6.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.52 [0.50\u0026ndash;0.55]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.57 [0.55\u0026ndash;0.60]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.58 [0.56\u0026ndash;0.61]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiac\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,896 (12.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,036 (8.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.67 [0.65\u0026ndash;0.70]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.94 [0.90\u0026ndash;0.98]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.94 [0.90\u0026ndash;0.98]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDermatologic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,581 (8.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,887 (5.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.61 [0.58\u0026ndash;0.63]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.77 [0.74\u0026ndash;0.81]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.77 [0.74\u0026ndash;0.81]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrgan failures \u0026ndash; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21,184 (52.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23,216 (62.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.29 [1.27\u0026ndash;1.32]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.14 [1.12\u0026ndash;1.17]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.15 [1.12\u0026ndash;1.18]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16,085 (39.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21,776 (58.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.72 [1.68\u0026ndash;1.76]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.22 [1.19\u0026ndash;1.25]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.22 [1.19\u0026ndash;1.25]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeurologic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,757 (19.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10,143 (27.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.35 [1.32\u0026ndash;1.38]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.14 [1.11\u0026ndash;1.17]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.15 [1.12\u0026ndash;1.18]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiovascular\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,066 (17.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,807 (15.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.86 [0.84\u0026ndash;0.89]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.78 [0.76\u0026ndash;0.80]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.77 [0.74\u0026ndash;0.79]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHematologic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,876 (12.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,809 (15.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.24 [1.20\u0026ndash;1.27]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.06 [1.03\u0026ndash;1.10]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.04 [1.01\u0026ndash;1.07]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetabolic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,845 (19.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10,453 (28.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.50 [1.47\u0026ndash;1.54]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.18 [1.15\u0026ndash;1.21]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.18 [1.15\u0026ndash;1.21]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,159 (5.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,805 (15.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.23 [2.17\u0026ndash;2.30]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.72 [1.67\u0026ndash;1.78]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.58 [1.53\u0026ndash;1.63]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICU supportive therapies \u0026ndash; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiopulmonary resuscitation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e987 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,814 (7.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.20 [2.11\u0026ndash;2.28]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.59 [1.52\u0026ndash;1.65]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.60 [1.54\u0026ndash;1.67]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInvasive mechanical ventilation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29,600 (72.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31,426 (84.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.64 [1.60\u0026ndash;1.69]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.33 [1.29\u0026ndash;1.37]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.34 [1.30\u0026ndash;1.38]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal replacement therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,616 (18.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13,968 (37.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.79 [1.75\u0026ndash;1.83]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.32 [1.28\u0026ndash;1.35]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.34 [1.30\u0026ndash;1.37]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransfusion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12,725 (31.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11,871 (31.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.89 [0.87\u0026ndash;0.91]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.78 [0.77\u0026ndash;0.80]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.78 [0.76\u0026ndash;0.80]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive culture with identification \u0026ndash; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29,933 (73.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22,600 (60.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.56 [0.55\u0026ndash;0.57]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.88 [0.85\u0026ndash;0.91]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.88 [0.85\u0026ndash;0.91]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital-acquired infection \u0026ndash; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13,601 (33.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,907 (21.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.56 [0.55\u0026ndash;0.57]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.69 [0.67\u0026ndash;0.71]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.70 [0.68\u0026ndash;0.72]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource of hospital admission \u0026ndash; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransfer from other hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,444 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,602 (4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39,162 (96.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35,680 (95.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.88 [0.84\u0026ndash;0.93]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.79 [0.75\u0026ndash;0.83]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.78 [0.74\u0026ndash;0.82]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime to ICU admission\u0026thinsp;\u0026le;\u0026thinsp;1 day \u0026ndash; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25,892 (63.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20,405 (51.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79 [0.78\u0026ndash;0.81]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.76 [0.74\u0026ndash;0.77]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.76 [0.75\u0026ndash;0.78]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital characteristics \u0026ndash; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcademic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14,230 (35.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11,763 (31.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther public hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19,872 (48.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19,482 (52.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.16 [1.09\u0026ndash;1.24]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.09 [1.02\u0026ndash;1.17]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.09 [1.02\u0026ndash;1.17]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6,504 (16.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,037 (16.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.07 [0.99\u0026ndash;1.15]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.97 [0.90\u0026ndash;1.04]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.97 [0.90\u0026ndash;1.04]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.448\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003cem\u003e95% CI: 95% confidence interval.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003cem\u003eHR : Hazard Ratio\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003cem\u003eICU : Intensive Care Unit\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003cem\u003eSAPS II : Simplified Acute Physiology Score\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAmong 67.4% [95%CI, 67.1 to 67.8] patients with positive culture identification, \u003cem\u003eEnterobacter\u003c/em\u003e sp. (34.3% [95%CI, 33.9 to 34.6]), \u003cem\u003eStaphylococcus\u003c/em\u003e sp. (23.5% [95%CI, 23.2 to 23.8]), \u003cem\u003eStreptococcus\u003c/em\u003e sp. (21.8% [95%CI, 21.5 to 22.0]), \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e (13.3% [95%CI, 13.1 to 13.6]) and \u003cem\u003eCandida\u003c/em\u003e sp. (12.1% [95%CI, 11.9 to 12.3]) were the most frequently isolated. Regarding the sites of infection, the gastrointestinal site was identified in 27.2% [95%CI, 26.6 to 27.8] of solid cancer patients, as compared with 12.2% [95%CI, 11.5 to 13.0] and 16.2% [95%CI, 15.9 to 16.5] of hematological cancer patients and noncancer patients, respectively. The rate of positive culture and that of multidrug resistant bacteria were no significantly different in the three groups. The recourse to invasive mechanical ventilation was slightly increased in the noncancer patients (80.3% [95%CI, 80.0 to 80.6]), as compared with 75.3% [95%CI, 74.7 to 75.9] in solid cancer patients and 71.8% [95%CI, 70.7 to 72.9] in hematological cancer patients.\u003c/p\u003e \u003cp\u003ePrimary outcome\u003c/p\u003e \u003cp\u003eThe 90-day mortality rate differed significantly in the three groups with the highest 90-day mortality rate for patients with hematological cancer, an intermediate 90-day mortality rate for those with solid cancer and the lowest mortality rate for the noncancer patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The mortality rates at day 90 were 53.7%, 59.1% and 44.3% for the solid cancer patients, the hematologic patients and the noncancer patients.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePatients with solid cancer (adjusted HR 1.55 [95%CI, 1.51 to 1.59]) and hematological cancer (adjusted HR 1.59 [95%CI, 1.53 to 1.65]) had increased risk of 90-day mortality, as compared with noncancer patients. This difference was confirmed using two different statistical models (Frailty 1 and Frailty 2).\u003c/p\u003e \u003cp\u003eRisk factors associated with 90-day mortality\u003c/p\u003e \u003cp\u003eBeing admitted to ICU with cancer, the type of cancer (solid vs. hematological), an advanced age, an increased severity score, the site of infection (lung, kidney, central nervous system, liver, metabolic), each organ failure, the ICU supportive therapies with the exception of blood transfusion and being admitted to a non-academic public hospital (as compared with other public hospital) were associated with poor outcomes.\u003c/p\u003e \u003cp\u003eIn contrast, overweigh, Charlson comorbidity index 1\u0026ndash;2, known source of infection, cardiovascular failure, hospital-acquired infection, direct admission from home to ICU, and time to ICU below 24 h were found as protective factors.\u003c/p\u003e \u003cp\u003eThen we explored the risk factors for 90-day mortality in patients with hematological cancer (Supplemental Tables\u0026nbsp;1 \u0026amp; 2) and solid cancer (Supplemental Tables\u0026nbsp;3 \u0026amp; 4). Positive culture, microbiological identification and the time to ICU admission (\u0026le;\u0026thinsp;1 day) were associated with decreased 90-day mortality in each subgroup.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study showed that solid cancer patients represented around 25% of our cohort of patients with septic shock while those with hematological cancer represented around 8% of these patients. The 90-day mortality rate was higher in the cancer patients than in the noncancer patients. Among the cancer patients, those with hematological cancer were at higher risk of 90-day mortality than those with solid cancer. The factors associated with the 90-day mortality in the patients with hematological and solid cancer shared the same profiles. Our data underlined the need for an identification of the source of infection and the pathogen responsible for the infective episode, as well as an early admission to ICU.\u003c/p\u003e \u003cp\u003eOur findings are in line with two previous studies based on large cohorts and exploring the effects of solid and hematological cancers on the outcomes of a population with unplanned ICU admission [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Both these studies found an increased mortality in patients with hematological cancer, but Ostermann et al. found a reduced mortality in patients with solid cancer as compared with the noncancer patients [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In contrast, the patients with hematological cancer had an increased risk of death as compared with the noncancer patients.\u003c/p\u003e \u003cp\u003eThe survival of patients with hematological cancer was around 40% at day 90. To reflect the interplay between septic shock and cancer, we deliberately chose an early assessment, since long-term outcome may reflect the underlying affection instead of septic shock. However, van der Zee et al. found a one-year mortality rate at 60% in patients with unplanned ICU admission in the Netherlands [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The difference with our study is probably due to our inclusion criteria selecting patients with septic shock instead of all ICU patients, while the Dutch study included all types of patients. In an observational study assessing the mortality rates of septic shock patients with hematological cancer, the mortality rate in specialized ICU declined from 70.4% in 1997 to 52.8% in 2008 [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe risk factors of 90-days mortality suggested the role of cancer in the outcomes. In addition, hematological cancer had a greater impact on outcomes than solid cancer. Other risk factors are in line with previous studies, confirming the deleterious role of advanced age, of increased severity scores, the effects of few comorbidities and those of each organ failure, and the negative impact of receiving supportive therapies as invasive mechanical ventilation and renal replacement therapy. Our results showed a beneficial effect of being admitted to academic hospitals, as compared with public non-academic hospital. This could reflect the case volume, as previously suggested in an observational study that showed an association between improved survival and the case volumes [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eInterestingly, protective risk factors confirm the findings of previous studies. Importantly, the determination of the site of infection and that of the pathogens responsible for septic episodes were protective factors, probably associated with an earlier source control and administration of adequate antimicrobial therapy [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This finding was corroborated with the admission to ICU within the first day, which was also associated with reduced 90-day mortality, confirming previous findings [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In an observational study including 1,611 immunocompromised patients with acute hypoxemic respiratory failure, Azoulay et al. found that failure to identify acute respiratory failure etiology was associated with higher mortality rates [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In the patients with cancer, early management in ICU and efforts to identify the source of infection are repetitively associated with a decreased mortality. Previous observational studies also reported associations between improved survival and administration of antibiotics in the first hour of shock[ 13], as well as between improved survival and early indwelling catheter removal [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Thus, early management of the septic shock patients with cancer should be implemented in routine practices.\u003c/p\u003e \u003cp\u003eThe strength of our study was to explore a large, national database that included a high number of patients with an exhaustivity of data. However, several limitations have to be acknowledged. First, our results are derived from a large, administrative database which can carry on the limitations of national database extracted from coding. Second, the database precludes several interesting data as the causes of mortality and notably the use of withdrawal or withholding life sustained treatments. Third, previous studies included cancer patients with unplanned ICU admission. In our database, this information was not available but as we selected only patients with septic shock, one can guess that they were likely patients with the pre-requisite to be admitted to ICU. Finally, we provide here crude data and confounding factors may have an undetermined influence on our results.\u003c/p\u003e \u003cp\u003eIn conclusion, our retrospective analysis of 77,888 patients with septic shock found that there was a declining 90-day mortality between the patients with hematological cancer, those with solid cancer, and the noncancer patients. Our data confirmed previous smaller studies showing the benefit of an early admission to ICU for those patients and the need to identify the source of infection. In addition, our findings encourage the admission of septic shock patients with hematological cancer and solid cancer to ICU. Due to the high number of patients with septic shock and cancer, future investigations should assess the interplay between the two affections.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAUTHOR CONTRIBUTIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConception and design: Marc Leone, Ines Lakbar, Laurent Boyer\u003c/p\u003e\n\u003cp\u003eCollection and assembly of data: Antoine Bianchi,\u0026nbsp;Guillaume Fond, Gary Duclos, Laurent Zieleskiewicz\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData analysis and interpretation: Antoine Bianchi, Yann Brousse, Ines Lakbar, Vanessa Pauly, Veronica Orleans, Laurent Boyer, Marc Leone,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eManuscript writing: All authors\u003c/p\u003e\n\u003cp\u003eFinal approval of manuscript: All authors\u003c/p\u003e\n\u003cp\u003eAccountable for all aspects of the work: All authors\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSinger M, Deutschman CS, Seymour CW et al (2016) The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA 315:801. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1001/jama.2016.0287\u003c/span\u003e\u003cspan address=\"10.1001/jama.2016.0287\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLakbar I, Munoz M, Pauly V et al (2022) Septic shock: incidence, mortality and hospital readmission rates in French intensive care units from 2014 to 2018. Anaesth Crit Care Pain Med 41:101082. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.accpm.2022.101082\u003c/span\u003e\u003cspan address=\"10.1016/j.accpm.2022.101082\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan Der Zee EN, Termorshuizen F, Benoit DD et al (2022) One-year Mortality of Cancer Patients with an Unplanned ICU Admission: A Cohort Analysis Between 2008 and 2017 in the Netherlands. J Intensive Care Med 37:1165\u0026ndash;1173. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/08850666211054369\u003c/span\u003e\u003cspan address=\"10.1177/08850666211054369\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNazer LH, Lopez-Olivo MA, Brown AR et al (2022) A Systematic Review and Meta-Analysis Evaluating Geographical Variation in Outcomes of Cancer Patients Treated in ICUs. Crit Care Explor 4:e0757. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/CCE.0000000000000757\u003c/span\u003e\u003cspan address=\"10.1097/CCE.0000000000000757\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOstermann M, Ferrando-Vivas P, Gore C et al (2017) Characteristics and Outcome of Cancer Patients Admitted to the ICU in England, Wales, and Northern Ireland and National Trends Between 1997 and 2013*. Crit Care Med 45\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAzoulay E, Pickkers P, Soares M et al (2017) Acute hypoxemic respiratory failure in immunocompromised patients: the Efraim multinational prospective cohort study. Intensive Care Med 43:1808\u0026ndash;1819. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00134-017-4947-1\u003c/span\u003e\u003cspan address=\"10.1007/s00134-017-4947-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAustin P (2009) Using the Standardized Difference to Compare the Prevalence of a Binary Variable Between Two Groups in Observational Research. Peter C Austin 38. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/03610910902859574\u003c/span\u003e\u003cspan address=\"10.1080/03610910902859574\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSullivan GM, Feinn R (2012) Using Effect Size\u0026mdash;or Why the \u003cem\u003eP\u003c/em\u003e Value Is Not Enough. J Grad Med Educ 4:279\u0026ndash;282. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4300/JGME-D-12-00156.1\u003c/span\u003e\u003cspan address=\"10.4300/JGME-D-12-00156.1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZuber B, Tran T-C, Aegerter P et al (2012) Impact of case volume on survival of septic shock in patients with malignancies*. Crit Care Med 40:55\u0026ndash;62. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/CCM.0b013e31822d74ba\u003c/span\u003e\u003cspan address=\"10.1097/CCM.0b013e31822d74ba\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReitz KM, Kennedy J, Li SR et al (2022) Association Between Time to Source Control in Sepsis and 90-Day Mortality. JAMA Surg 157:817. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1001/jamasurg.2022.2761\u003c/span\u003e\u003cspan address=\"10.1001/jamasurg.2022.2761\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMart\u0026iacute;nez ML, Ferrer R, Torrents E et al (2017) Impact of Source Control in Patients With Severe Sepsis and Septic Shock*. Crit Care Med 45\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKollef MH, Shorr AF, Bassetti M et al (2021) Timing of antibiotic therapy in the ICU. Crit Care 25:360. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s13054-021-03787-z\u003c/span\u003e\u003cspan address=\"10.1186/s13054-021-03787-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMokart D, Saillard C, Sannini A et al (2014) Neutropenic cancer patients with severe sepsis: need for antibiotics in the first hour. Intensive Care Med 40:1173\u0026ndash;1174. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00134-014-3374-9\u003c/span\u003e\u003cspan address=\"10.1007/s00134-014-3374-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLegrand M, Max A, Peigne V et al (2012) Survival in neutropenic patients with severe sepsis or septic shock*. Crit Care Med 40:43\u0026ndash;49. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/CCM.0b013e31822b50c2\u003c/span\u003e\u003cspan address=\"10.1097/CCM.0b013e31822b50c2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"sepsis, cancer, shock, solid, hematology","lastPublishedDoi":"10.21203/rs.3.rs-4347653/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4347653/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose:\u003c/strong\u003e Septic shock and cancer occur routinely in intensive care unit patients. Our aim was to determine the 90-day mortality rate of patients with septic shock and solid cancer or hematological cancer.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We performed a retrospective cohort study using data from the French national hospitalization database, including adult patients with septic shock from 2017 to 2018. Primary outcomes were the hospital mortality rate at 90 days in patients with solid cancer and hematological cancer. Secondary outcomes were the risk factors associated with mortality in our global cohort.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Septic shock was found in 77,888 patients, including 19,329 patients with solid cancer, 6,498 with hematological cancer and 52,061 noncancer patients. Patients with solid cancer (adjusted hazard ratio 1.55 [1.51-1.59]) and hematological cancer (1.59 [1.53-1.65]) had increased risk of 90-day mortality, as compared with noncancer patients. Risk factors for 90-days hospital mortality included hematological cancer and solid cancer.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Our study showed that solid cancer and hematological cancer differed in terms of 90-days mortality in septic shock patients. Future investigations are required to assess the interplay between cancer and septic shock.\u003c/p\u003e","manuscriptTitle":"Mortality of cancer patients with septic shock: a nation-based cohort analysis in 77,888 patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-04 18:58:23","doi":"10.21203/rs.3.rs-4347653/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ebb307e3-ad12-403d-9383-237bfdf674a0","owner":[],"postedDate":"June 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-27T01:08:02+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-04 18:58:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4347653","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4347653","identity":"rs-4347653","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}