Albumin in patients with ARDS in ICU: a retrospective study from eICU and MIMIC-III database

Albumin in patients with ARDS in ICU: a retrospective study from eICU and MIMIC-III database | 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 Albumin in patients with ARDS in ICU: a retrospective study from eICU and MIMIC-III database Ming He, You Wu, Xiaojun Pan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6948848/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 Although early administration of albumin has been shown to improve oxygenation and maintain hemodynamic stability in patients with acute respiratory distress syndrome (ARDS), whether the addition therapy of albumin can improve the outcome of ARDS patient was still unknow. Therefore, this study aims to evaluate the efficacy of early albumin therapy in ARDS patients diagnosed according to the Berlin definition. We conducted a multicenter, retrospective study utilizing data from the eICU Collaborative Research Database and the MIMIC-III Database. Inverse probability of treatment weighting (IPTW) and propensity score matching were implemented to further adjust for confounding variables between the groups. Cox proportional hazards models were applied to estimate the association between albumin administration within 48 hours of admission and 28-day mortality in patients with ARDS. Kaplan–Meier survival curves were constructed, and the log-rank test was employed to assess the association between 28-day mortality and albumin therapy in the two groups. Following a review of over 200,000 subjects from the eICU database, 3,371 eligible patients with ARDS were identified according to the inclusion and exclusion criteria. The albumin therapy was not associated with 28-day mortality (HR, 1.12; 95% CI, 0.76–1.67; P = 0.6) in the IPTW cohort and was also not associated with 28-day mortality (HR, 0.88; 95% CI, 0.62–1.24; P = 0.5) in the PSM cohort in eICU database. Moreover, the albumin therapy was not associated with 28-day mortality (HR, 1.12; 95% CI, 0.76–1.67; P = 0.6) in the IPTW cohort and was not associated with 28-day mortality (HR, 0.95; 95% CI, 0.65–1.38; P = 0.8) in the PSM cohort in MIMIC-III database. In conclusion, our findings suggested that ARDS patients receiving albumin therapy did not improve the outcomes. Using albumin treatment may lead to albumin leakage when the damaged endothelial cells cause severe leakage of capillaries may even aggravate tissue edema and thus prolong the hospital stay, ICU stay, and mechanical ventilation duration. Albumin Acute respiratory distress syndrome eICU MIMIC-III Database 28-day mortality Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Acute Respiratory Distress Syndrome (ARDS) is a severe, life-threatening condition affecting over 3 million patients globally, accounting for approximately 10% of admissions to intensive care units (ICUs). In the United States alone, ARDS impacts around 200,000 individuals annually and is responsible for nearly 75,000 deaths each year[ 1 ]. Despite advancements in therapeutic strategies that have led to a reduction in mortality rates, the condition's mortality remains significantly high, ranging from 35–46%[ 2 ]. ARDS can result from various pulmonary or non-pulmonary pathophysiological insults and is characterized by pulmonary endothelial dysfunction and increased alveolocapillary permeability. These changes can exacerbate pulmonary edema, impairing oxygen delivery and leading to refractory hypoxemia. Human serum albumin, synthesized by the liver and constituting 40–60% of total plasma protein, plays a crucial role in maintaining plasma colloid osmotic pressure, supporting vascular endothelial integrity, and exhibiting antioxidant and anti-inflammatory properties[ 3 ]. Additionally, albumin remains within the intravascular compartment, contributing to restoring effective volume and maintaining colloidal osmotic pressure[ 4 ]. Experimental and clinical evidence indicates that colloids confer several pulmonary benefits over crystalloids, such as reduced alveolar-capillary permeability[ 5 ], diminished histological damage[ 6 ], and more rapid hemodynamic stabilization[ 7 ]. Conversely, colloid administration may exacerbate tissue edema due to the extravasation of colloid molecules in conditions of heightened capillary leakage[ 8 ]. Early administration of albumin has been shown to enhance oxygenation and maintain hemodynamic stability in patients with ARDS and hypoproteinemia[ 9 , 10 ]. Nevertheless, albumin therapy did not result in a significant reduction in all-cause mortality at 28 days[ 11 ]. Notably, albumin infusion was associated with improved 28-day survival in patients experiencing acute kidney injury and septic shock[ 12 ]. Additional studies have demonstrated a direct correlation between decreased albumin levels and increased 14-day, 28-day, and 90-day mortality rates in patients with congestive heart failure in intensive care settings[ 13 ]. However, the impact of albumin infusion on the outcomes of ARDS patients remains inconclusive. This study aimed to evaluate the efficacy of early albumin therapy in patients with ARDS according to Berlin definition. Methods Data source The data utilized in the present study were derived from the eICU Collaborative Research Database (version 2.0) and the MIMIC-III Database (Medical Information Mart for Intensive Care, version 1.4). The eICU database is a comprehensive, multi-center resource encompassing over 200,000 ICU admissions across the United States during the period of 2014 to 2015. It contains detailed information on critically ill patients, including vital signs, diagnoses, illness severity, laboratory results, and treatments. In contrast, the MIMIC-III database comprises patient data from the Beth Israel Deaconess Medical Center, spanning from June 2001 to October 2012. This database is organized into tables in CSV format for research purposes, encompassing nearly all patient data during ICU treatment. This includes demographic information, hourly vital signs, surgical records, drug administration details (timing and dosage), fluid balance, microbiological examination results, care records, and patient outcomes (including inpatient and out-of-hospital deaths, as well as discharges). Both databases have received approval from the Institutional Review Boards (IRB) of the Massachusetts Institute of Technology (MIT). Ethical approval was obtained following the completion of all required National Institutes of Health web-based training courses and the Protecting Human Research Participants certification (Record ID 35209874). Study cohort: We conducted a multicenter, retrospective study involving patients with ARDS as defined by the Berlin criteria[ 1 ]. Data collection was limited to the first admission, and all data were extracted from the database by using Structured Query Language following the methodology established by Johnson et al[ 14 ]. The inclusion criteria for the study were: (1) patients diagnosed with ARDS; (2) patients admitted to the Intensive Care Unit (ICU) for the first time; and (3) patients aged 16 years or older. The exclusion criteria included: (1) patients who succumbed within the first 48 hours; (2) readmissions to the hospital or ICU; (3) ARDS diagnosis occurring more than 48 hours post-admission; and (4) cases with missing critical data. Data extraction was performed using Structured Query Language (SQL) from the MIMIC database. On the first day of ICU admission, the following data were collected: weight, gender, age, type of admission, ethnicity (categorized as White, Hispanic, Black, or Other), use of mechanical ventilation, renal replacement therapy (RRT), ARDS severity, Simplified Acute Physiology Score II (SAPS II), Sequential Organ Failure Assessment (SOFA) score, heart rate, P/F ratio, respiratory rate, albumin levels, and comorbidities. Data collection and definitions Structured Query Language (SQL) was utilized to extract the necessary data. Demographic information, including age, gender, ethnicity, and admission source, as well as Acute Physiology and Chronic Health Evaluation (APACHE IVa) scores, Sequential Organ Failure Assessment (SOFA) scores, Simplified Acute Physiology Score (SAPS II), and comorbidities, were retrieved from the database. Additionally, data on urine output, heart rate, mean arterial pressure, respiration rate, P/F ratio, and serum albumin levels on the first and seventh day post-admission were reviewed. In cases where the fraction of inspired oxygen (FiO2) data was missing, adjacent two-hour FiO2 values were substituted. The severity of ARDS was assessed according to the Berlin definition. Continuous variables were presented as medians with interquartile ranges (IQR), and the Wilcoxon rank-sum test was employed to compare differences between groups. Endpoint events The primary endpoint was 28-day mortality, while secondary endpoints included ICU mortality, hospital mortality, length of hospital and ICU stay, duration of ventilation, and measurements of urine output, heart rate, respiration rate, mean arterial pressure, P/F ratio, and SOFA score on day 7. Statistical analysis Continuous variables were presented as medians with interquartile ranges (IQR), and the Wilcoxon rank-sum test was employed to compare differences between groups. Categorical variables were summarized using frequencies and percentages, and differences between groups were assessed using either the χ² test or Fisher's exact test, as appropriate. To address potential confounding factors between the two groups, propensity score matching (PSM) was employed. A univariate Cox regression model was utilized to examine the association between potential confounding variables and mortality; variables with a p-value less than 0.05 or those identified through clinical expertise were included in the PSM process. The matching was conducted using a greedy nearest neighbor approach at a 1:1 ratio, with a caliper width of 0.2 standard deviations. Prior to PSM, missing values in selected confounding variables were addressed using random forest imputation. Additionally, an inverse probability of treatment weighting (IPTW) model was implemented to further adjust for confounding variables between the groups. Cox proportional hazards models were applied to estimate the association between albumin administration within 48 hours of admission and patient outcomes in those with acute respiratory distress syndrome (ARDS) across pre-matched, matched, and IPTW cohorts. The hazard ratios (HR) and 95% confidence intervals (CI) for the variables of interest were reported for comparisons between the two groups. Kaplan–Meier survival curves were constructed, and the log-rank test was employed to assess the association between 28-day mortality and albumin therapy in both pre-matched and matched cohorts across the two groups. Stratified analyses based on age, Sequential Organ Failure Assessment (SOFA) and Acute Physiology and Chronic Health Evaluation IVa (APACHE IVa) scores, severity of ARDS, heart rate, mean arterial pressure, urine output, respiratory rate, and serum albumin levels were conducted to evaluate the impact of albumin infusion between the groups. All statistical analyses were executed using RStudio (version 4.0.5). Results Basic characteristics Following a review of over 200,000 subjects from the eICU database, 3,371 eligible patients with ARDS were identified according to the specified inclusion and exclusion criteria. Of these, 209 patients (6.2%) received albumin therapy, while 3,162 (93.8%) did not, as detailed in Figure 1 and Table 1a. From the MIMIC-III database, 61,532 subjects were reviewed, resulting in the enrollment of 1,137 patients with ARDS according to the Berlin definition. Among these, 189 patients (16.62%) received albumin therapy, whereas 948 (83.38%) did not, as presented in Figure 1 and Table 1b. In the eICU cohort 1670 (49.54%) patients were female and 1701 (50.46%) were male, the median age and median weight in the study cohort was 67.00 (56.00, 78.00) and 81.10 (65.75, 100.73) respectively. Medical (87.04%) was the main admission source and white was the main ethnicity (75.23%) in the present study. 2348 (69.65%) patients received mechanical ventilation on the first day admitted to ICU. The median SOFA score and APACHE IVa score was 6.00 (4.00, 9.00) and 62.00 (47.00, 82.00) respectively. The median PaO2/FiO2 (P/F) ratio on the first day was 138.33 (94.00, 208.00). The median heart rate, respiratory rate and mean arterial pressure of the first day was 90.10 (78.72, 102.05), 21.41 (18.45, 24.85), 82.16 (75.10, 91.40) respectively. The median of first day serum albumin was 3.00 (2.55, 3.50), the median urine output of the first day was 1550.00 (775.00, 2800.00). The main severity of ARDS in the study population was moderate (44.62%). There was no significant difference in age, gender, first day mechanical ventilation, respiratory rate, chronic heart failure, renal disease, malignant cancer between the two groups in the eICU database. However, in the MIMIC-III cohort 660 (58.05%) patients were female, the median age and median weight in the study cohort was 60.80 (48.43, 74.50) and 80.00 (67.15, 94.85) respectively. Medical (86.63%) was the main admission source and white was the main ethnicity (68.34%) in the present study. 993 (87.34%) patients received mechanical ventilation on the first day admitted to ICU. The median SOFA score and SAPS II score was 7.00 (5.00, 9.00) and 42.00 (33.00, 52.00) respectively. The median P/F ratio on the first day was 123.33 (82.00, 178.00). The median heart rate, respiratory rate and mean arterial pressure of the first day was 92.53 (80.91, 104.35), 20.85 (17.87, 24.65), 75.58 (70.10, 82.88) respectively. The median of first day serum albumin was 2.80 (2.40, 3.32), the median urine output of the first day was 1669.50 (960.00, 264.00). The main severity of ARDS in the study population was moderate (46.35%). There was no significant difference in age, gender, weight, first day mechanical ventilation, respiratory rate, RRT on the first day, chronic heart failure, renal disease, malignant cancer between the two groups in the MIMIC-III database. After implementing Inverse Probability of Treatment Weighting (IPTW) and Propensity Score Matching (PSM), the baseline characteristics of the patients were well-balanced between the two groups, as shown in Figure 1 and Tables S1a, S1b, S1c, and S1d. Table 1a: Baseline Characteristics between the study cohort from eICU database. Variables Overall(n=3371) non-albumin (n=3162) Albumin (n=209) p Age (median (IQR)) 67.00 (56.00, 78.00) 67.00 (56.00, 79.00) 66.00 (54.00, 77.00) 0.36 Gender (female, %) 1670 (49.54) 1570 (49.65) 100 (47.85) 0.66 Admission source (%) <0.01 Medical 2934 (87.04) 2771 (87.63) 163 (77.99) Surgical urgent 220 (6.53) 193 (6.10) 27 (12.92) Surgical elective 217 (6.44) 198 (6.26) 19 (9.09) Ethnicity (%) <0.01 White 2536 (75.23) 2391 (75.62) 145 (69.38) Black 412 (12.22) 393 (12.43) 19 (9.09) Hispanic 193 (5.73) 159 (5.03) 34 (16.27) Other 182 (5.40) 230 (6.82) 174 (5.50) 219 (6.92) 8 (3.83) 11 (5.27) Weight (median (IQR)) 81.10 (65.75, 100.73) 81.50 (65.80, 101.00) 76.20 (64.77, 96.08) 0.03 ARDS severity (%) <0.01 Mild 904 (26.82) 867 (27.42) 37 (17.70) Moderate 1504 (44.62) 1432 (45.29) 72 (34.45) Severe 963 (28.57) 863 (27.29) 100 (47.85) Mechanical ventilation (%) 2348 (69.65) 2190 (69.26) 158 (75.60) 0.06 SOFA (median (IQR)) 6.00 (4.00, 9.00) 6.00 (4.00, 9.00) 9.00 (6.00, 12.00) <0.01 APACHE-IVa (median (IQR)) 62.00 (47.00, 82.00) 61.00 (46.00, 81.00) 80.00 (58.00, 105.00) <0.01 P/F (median (IQR)) 138.33 (94.00, 208.00) 140.00 (96.00, 210.00) 103.52 (66.00, 174.00) <0.01 Urine output (median (IQR)) 1550.00 (775.00, 2800.00) 1570.00 (800.00, 2835.50) 1127.50 (400.00, 2077.25) <0.01 Heart rate (median (IQR)) 90.10 (78.72, 102.05) 89.93 (78.51, 101.45) 92.71 (82.73, 106.75) <0.01 Respiratory rate (median (IQR)) 21.41 (18.45, 24.85) 21.35 (18.44, 24.82) 21.74 (18.77, 25.37) 0.25 Mean arterial pressure (median (IQR)) 82.16 (75.10, 91.40) 82.69 (75.58, 91.98) 76.49 (70.80, 83.34) <0.01 Albumin (median (IQR)) 3.00 (2.55, 3.50) 3.07 (2.60, 3.50) 2.69 (2.22, 3.05) <0.01 Co-morbidities, n (%) Chronic heart failure 649 (19.25) 618 (19.54) 31 (14.83) 0.11 Liver disease 100 (2.97) 86 (2.72) 14 (6.70) 0.99 Malignant cancer 115 (3.41) 107 (3.38) 8 (3.83) 0.88 Table 1b: Baseline Characteristics between the study cohort from MIMIC-III database. Overall (1137) non-albumin (948) Albumin (189) p Age (median [IQR]) 60.80 [48.43, 74.50] 60.78 [47.66, 74.95] 61.30 [49.70, 72.04] 0.71 Gender (female, %) 660 (58.05) 556 (58.65) 104 (55.03) 0.4 Admission source (%) <0.01 Medical 985 (86.63) 832 (87.76) 153 (80.95) Surgical urgent 38 (3.34) 34 (3.59) 4 (2.12) Surgical elective 114 (10.03) 82 (8.65) 32 (16.93) Ethnicity (%) 0.02 Black 85 (7.48) 76 (8.02) 9 (4.76) Hispanic 37 (3.25) 28 (2.95) 9 (4.76) White 777 (68.34) 634 (66.88) 143 (75.66) Other 238 (20.93) 210 (22.15) 28 (14.81) Weight (median [IQR]) 80.00 [67.15, 94.85] 80.00 [67.75, 95.00] 75.40 [66.00, 92.00] 0.07 ARDS severity (%) <0.01 Mild 196 (17.24) 168 (17.72) 28 (14.81) Moderate 527 (46.35) 455 (48.00) 72 (38.10) Severe 414 (36.41) 325 (34.28) 89 (47.09) Mechanical ventilation (%) 993 (87.34) 836 (88.19) 157 (83.07) 0.07 SOFA (median [IQR]) 7.00 [5.00, 9.00] 6.00 [4.00, 9.00] 8.00 [5.00, 11.00] <0.01 SAPS II (median [IQR]) 42.00 [33.00, 52.00] 42.00 [32.00, 51.00] 46.00 [36.00, 55.00] <0.01 P/F (median [IQR]) 123.33 [82.00, 178.00] 125.00 [83.94, 180.00] 103.33 [74.00, 157.50] <0.01 PEEP (median [IQR]) 5.30 [5.00, 10.00] 5.00 [5.00, 10.00] 8.00 [5.00, 10.00] 0.01 Heart rate (median [IQR]) 92.53 [80.91, 104.35] 91.76 [80.34, 103.19] 97.85 [84.93, 108.96] <0.01 Mean arterial pressure (median [IQR]) 75.58 [70.10, 82.88] 76.04 [70.50, 83.52] 73.81 [68.05, 78.77] <0.01 Respiratory rate (median [IQR]) 20.85 [17.87, 24.65] 20.76 [17.88, 24.61] 21.18 [17.65, 24.73] 0.69 Albumin (median [IQR]) 2.80 [2.40, 3.32] 2.90 [2.40, 3.40] 2.50 [2.20, 2.90] <0.01 Urine Output (median [IQR]) 1669.50 [960.00, 2640.00] 1759.50 [1013.75, 2736.25] 1177.00 [653.25, 2091.00] <0.01 RRT (%) 62 (5.45) 51 (5.38) 11 (5.82) 0.95 Co-morbidities, n (%) Chronic heart failure 470 (41.34) 414 (43.67) 56 (29.63) <0.01 Liver disease 136 (11.96) 114 (12.03) 22 (11.64) 0.98 Renal disease 91 (8.00) 50 (5.27) 41 (21.69) <0.01 Malignant cancer 209 (18.38) 168 (17.72) 41 (21.69) 0.24 Abbreviations: ARDS, acute respiratory distress syndrome. SOFA, sequential organ failure assessment. SAPSII, simplified acute physiology score II. P/F：PaO2/FiO2 ratio. RRT, renal replacement therapy. CHF, chronic heart failure. a. All covariates were reported as mean (standard deviation) and median [IQR]. b.Mechanical ventilation and RRT were received the therapy on the first day ICU admission. c. All data is extracted in the first 24 h of ICU admission Relationship between furosemide and outcomes In the eICU cohort, the 28-day mortality (HR=2.10; 95% CI: 1.62-2.74; P<0.01), ICU mortality (HR=1.82; 95% CI: 1.36-2.43; P<0.01), hospital mortality (HR=1.53; 95% CI: 1.18-1.98; P=0.001) were associated with albumin therapy in the original cohort. After being adjusted for the confounders (including gender, age, admission source, weight, and ethnicity), the addition therapy of albumin was associated with the 28-day (HR=1.98; 95% CI: 1.5-2.6; P<0.01), ICU (HR=1.86; 95% CI: 1.39-2.5; P<0.01), or hospital mortality (HR=1.46; 95% CI: 1.12-1.91; P=0.005). Albumin was only associated with the ICU (HR=1.44; 95% CI: 1.06-1.94; P=0.02) mortality after adjusted for the confounders including gender, age, ethnicity, admit source, weight, SOFA, APACHE IVa score, first day mechanical ventilation, ARDS severity, chronic heart failure, liver, disease, renal disease, and malignant cancer. After PSM matching, 206 patients who received albumin therapy were matched with 206 patients who did not. The albumin therapy was not associated with 28-day mortality (HR, 0.88; 95% CI, 0.62-1.24; P=0.5), the ICU mortality (HR, 0.95; 95% CI, 0.65-1.4; P=0.8), hospital mortality (HR, 0.78; 95% CI, 0.56-1.1; P=0.2). After adjusted with gender, age, admission source, weight, and ethnicity, the 28-day mortality (HR, 0.86; 95% CI, 0.61-1.23; P=0.41), the ICU mortality (HR, 0.91; 95% CI, 0.62-1.35; P＜0.65), hospital mortality (HR, 0.76; 95% CI, 0.54-1.08; P=0.13) were not associated with albumin infusion. After adjusted with gender, age, ethnicity, admit source, weight, SOFA, APACHE IVa score, first day mechanical ventilation, ARDS severity, chronic heart failure, liver, disease, renal disease, and malignant cancer, the 28-day mortality (HR, 0.92; 95% CI, 0.64-1.3; P=0.63), the ICU mortality (HR, 0.94; 95% CI, 0.63-1.4; P=0.77), hospital mortality (HR, 0.79; 95% CI, 0.56-1.13; P=0.2) were not associated with albumin infusion in the matched cohort. The albumin therapy was not associated with 28-day mortality (HR, 1.12; 95% CI, 0.76-1.67; P=0.6), the ICU mortality (HR, 0.92; 95% CI, 0.77-1.11; P=0.4), hospital mortality (HR, 1.02; 95% CI, 0.69-1.5; P=0.9) in the IPTW cohort. After adjusted with gender, age, admission source, weight, and ethnicity, the 28-day mortality (HR, 1.18; 95% CI, 0.79-1.77; P=0.41), the ICU mortality (HR, 0.96; 95% CI, 0.8-1.15; P=0.62), hospital mortality (HR, 1.07; 95% CI, 0.73-1.57; P=0.73) were not associated with albumin infusion in the IPTW cohort. After adjusted with gender, age, ethnicity, admit source, weight, SOFA, APACHE IVa score, first day mechanical ventilation, ARDS severity, chronic heart failure, liver, disease, renal disease, and malignant cancer, the 28-day mortality (HR, 1.11; 95% CI, 0.74-1.66; P=0.61), the ICU mortality (HR, 1.06; 95% CI, 0.88-1.3; P=0.5), hospital mortality (HR, 1.02; 95% CI, 0.69-1.51; P=0.91) were not associated with albumin infusion in the IPTW cohort.. In the MIMIC-III cohort, 178 patients who received albumin therapy were matched with 178 patients who did not after PSM. The albumin was both not association with the 28-day, hospital, 90-day, and 365-day mortality in the three COX model in pre-matched cohort. However, the albumin therapy was not association with ICU mortality in the COX1 and COX2 model and was association with ICU mortality in the COX3 model before PSM. The addition therapy was not association with 28-day, ICU, hospital, 90-day, and 365-day mortality in both three model after PSM. The albumin infusion was not association with 28-day, hospital, 90-day, and 365-day mortality in the IPTW cohort. However, the albumin therapy decreased the ICU mortality in the IPTW. The median length of hospital and ICU stays were 7.61 and 2.96 days, respectively. The median duration of ventilation was 29.5 hours in the matched of eICU database. The 28-day, ICU and hospital mortality were no significant difference in the two groups (P=0.6, P=0.91 and P=0.75, respectively). Moreover, the length of ICU and ventilation duration were no significant difference in the two groups (P=0.51 and P=0.29, respectively). However, the hospital was longer in the albumin group than non-albumin group (8.98 vs. 8.25, P=0.02). The median length of hospital, ICU stays, and the duration of mechanical ventilation were 17.34, 9.28 and 5.63 days in the matched cohort of MIMIC-III database, respectively. The 28-day, ICU, hospital, 90-day, and 365-day mortality were no significant difference in the two groups after PSM. However, the length of ICU and hospital stays were longer in the albumin therapy group (P<0.01). Moreover, the duration of mechanical ventilation was longer in the albumin therapy group than control group in the matched cohort (P<0.01). The univariate COX analysis of eICU and MIMIC-III cohort were performed and the results were showed in the Table S3a and S3b. Kaplan–Meier survival curves were plotted and log-rank test were performed to compare the difference of 28-day mortality between the two groups, and the results were shown in Figure 2 and Table 2. There was no significant difference in 28-day mortality between the two groups after PSM (P=0.45) in the eICU cohort. In the MIMIC-III cohort, the 28-day, 90-day, and one-year mortality were higher in the albumin group (P=0.17, P=0.0016, P=0.0012) in the original cohort. However, there is no difference in 28-day, 90-day, and one-year mortality between the groups in the matched cohort (P=0.8, P=0.24, P=0.41). There is no difference in 28-day between the groups in the IPTW cohort (P=0.17). However, the 90-day and one-year mortality were higher in the non-albumin group than the albumin groups (P=0.0016, P=0.0012) in the IPTW cohort (Figure 3). The comparison of the urine output, heart rate, respiratory rate, mean arterial pressure, P/F ratio, SOFA score, or albumin on day 1 and day 7 were compared between the albumin therapy and non-albumin group. The mean arterial pressure was higher and the P/F ratio was lower in the non-albumin group than the albumin group in the eICU cohort. The mean arterial pressure was higher in the non-albumin group than the albumin group in the MIMIC-III database (shown in Table 3a and 3b). Subgroup analysis The results of the subgroup analysis of 28-day mortality were shown in Figure 4. There were no differences in the albumin treatment in subgroups in the eICU cohort Figure 4A) and in the MIMIC-III group (Figure 4B). Table 2a: Outcomes of Albumin and non-Albumin patients and sensitivity analysis from eICU database. Pre-matched Matched IPTW HR 95%CI P-value HR 95%CI P-value HR 95%CI P-value 28-day Mortality Model 1 2.1 （1.62-2.74） <0.01 0.88 （0.62-1.24） 0.5 1.12 （0.76-1.67） 0.6 Model 2 1.98 （1.5-2.6） <0.01 0.86 （0.61-1.23） 0.41 1.18 （0.79-1.77） 0.41 Model 3 1.28 （0.97-1.69） 0.07 0.92 （0.64-1.3） 0.63 1.11 （0.74-1.66） 0.61 ICU Mortality Model 1 1.82 （1.362-2.431） <0.01 0.95 （0.65-1.4） 0.8 0.92 （0.77-1.11） 0.4 Model 2 1.86 （1.388-2.5） <0.01 0.91 （0.62-1.35） 0.65 0.96 （0.8-1.15） 0.62 Model 3 1.44 （1.06-1.94） 0.02 0.94 （0.63-1.4） 0.77 1.06 （0.88-1.3） 0.5 Hospital Mortality Model 1 1.53 （1.18-1.98） 0.001 0.78 （0.56-1.1） 0.2 1.02 （0.69-1.5） 0.9 Model 2 1.46 （1.12-1.91） 0.005 0.76 （0.54-1.08） 0.13 1.07 （0.73-1.57） 0.73 Model 3 1.1 （0.84-1.45） 0.48 0.79 （0.56-1.13） 0.2 1.02 （0.69-1.51） 0.91 Table 2b: Outcomes of Albumin and non-Albumin patients and sensitivity analysis from MIMIC-III database. Pre-matched Matched IPTW HR 95%CI P-value HR 95%CI P-value HR 95%CI P-value 28-day Mortality Model 1 0.95 0.65-1.38 0.8 0.95 0.65-1.38 0.8 0.96 0.63-1.45 0.8 Model 2 0.98 0.67-1.43 0.92 0.91 0.62-1.32 0.61 0.91 0.58-1.42 0.67 Model 3 0.98 0.67-1.44 0.91 0.95 0.65-1.39 0.81 0.95 0.6-1.49 0.81 ICU Mortality Model 1 0.72 0.49-1.05 0.09 0.72 0.49-1.05 0.09 0.58 0.45-0.75 <0.01 Model 2 0.73 0.49-1.08 0.12 0.68 0.46-1.00 0.3 0.61 0.48-0.77 <0.01 Model 3 0.65 0.44-0.98 0.04 0.64 0.43-0.96 0.03 0.63 0.5-0.78 <0.01 Hospital Mortality Model 1 0.88 0.61-1.27 0.5 0.88 0.61-1.27 0.5 0.89 0.61-1.29 0.5 Model 2 0.87 0.59-1.27 0.48 0.79 0.54-1.15 0.22 0.84 0.56-1.27 0.41 Model 3 0.84 0.57-1.23 0.37 0.79 0.54-1.16 0.24 0.84 0.54-1.3 0.43 90-day Mortality Model 1 1.21 0.87-1.69 0.3 1.21 0.87-1.69 0.3 1.19 0.85-1.67 0.3 Model 2 1.26 0.9-1.77 0.18 1.15 0.82-1.61 0.41 1.14 0.79-1.64 0.49 Model 3 1.31 0.93-1.85 0.13 1.24 0.89-1.74 0.20 1.24 0.88-1.75 0.23 365-day Mortality Model 1 1.13 0.84-1.53 0.4 1.13 0.84-1.53 0.4 1.13 0.82-1.55 0.5 Model 2 1.16 0.85-1.57 0.36 1.08 0.8-1.47 0.6 1.07 0.76-1.51 0.69 Model 3 1.23 0.9-1.68 0.20 1.19 0.87-162 0.27 1.2 0.87-1.64 0.26 Abbreviation: CI, confidence interval. HR, hazard ratio. All models were performed by Cox proportional hazards model analysis the relationship between NMBAs therapy and all cause mortality. Model 1 Cox regression was used for estimating the impact of albumin use on mortality outcomes 0.05 in univariate analysis Model 2 Cox regression was adjusted by gender, age, admission type and ethnicity. Model 3 Cox regression was adjusted by gender, age, SOFA, SAPSII, ethnicity, ARDS severity, chronic disease of liver, malignancy, respiratory rate. Table 3a: Comparison of the dynamic indicator in eICU database. Overall (n=412) non-albumin (n=206) Albumin (n=206) p Day 1 Urine Output (median [IQR]) 1187.50 [575.00, 2177.50] 1275.00 [707.50, 2455.00] 1135.00 [400.00, 2090.00] 0.09 Heart rate (median [IQR]) 93.37 [82.77, 105.90] 93.98 [82.92, 105.16] 92.64 [82.66, 106.39] 0.82 Respiratory rate (median [IQR]) 21.66 [18.45, 25.47] 21.30 [18.25, 25.58] 21.73 [18.57, 25.39] 0.46 Mean arterial pressure (median [IQR]) 76.32 [71.36, 82.77] 76.02 [72.12, 80.57] 76.61 [70.87, 83.37] 0.49 P/F (median [IQR]) 121.00 [70.00, 216.50] 120.00 [72.00, 204.50] 121.00 [69.75, 221.00] 0.95 SOFA (median [IQR]) 9.00 [6.00, 12.00] 9.00 [6.00, 12.00] 9.00 [6.00, 12.00] 0.85 Albumin (median [IQR]) 2.70 [2.25, 3.10] 2.65 [2.26, 3.10] 2.70 [2.25, 3.05] 0.99 Day 7 Urine Output (median [IQR]) 1400.00 [500.00, 2490.00] 1450.00 [741.25, 2648.25] 1375.00 [425.00, 2475.00] 0.29 Heart rate (median [IQR]) 89.07 (14.89) 90.03 (15.07) 88.35 (14.79) 0.48 Respiratory rate (median [IQR]) 19.97 [18.00, 24.36] 19.99 [18.00, 24.37] 19.93 [17.90, 24.36] 0.93 Mean arterial pressure (median [IQR]) 84.91 [77.06, 95.15] 90.13 [79.96, 98.59] 82.19 [74.56, 90.94] 0.01 P/F (median [IQR]) 7.00 [4.00, 10.00] 5.50 [2.75, 8.25] 7.00 [4.00, 11.50] 0.01 SOFA (median [IQR]) 168.00 [108.50, 257.00] 160.00 [107.00, 212.00] 170.00 [109.50, 268.50] 0.39 Albumin (median [IQR]) 2.41 (0.64) 2.34 (0.44) 2.45 (0.73) 0.48 Table 3b: Comparison of the dynamic indicator in the MIMIC-III database. Overall (n=356) 0 (n=178) 1 (n=178) p Day 1 Urine Output (median [IQR]) 1278.50 [748.75, 2267.50] 1325.00 [752.50, 2362.50] 1198.00 [756.00, 2200.00] 0.67 Heart rate (mean (SD)) 96.74 (17.55) 96.50 (17.38) 96.98 (17.77) 0.79 Respiratory rate (median [IQR]) 21.00 [17.86, 24.87] 20.86 [17.99, 25.17] 21.19 [17.48, 24.77] 0.97 Mean arterial pressure (median [IQR]) 73.41 [67.72, 79.12] 72.93 [67.31, 79.79] 73.95 [68.40, 79.00] 0.37 P/F (median [IQR]) 108.45 [75.00, 165.25] 111.83 [75.00, 169.64] 104.50 [77.12, 160.00] 0.71 Albumin (median [IQR]) 2.60 [2.20, 2.92] 2.60 [2.11, 2.94] 2.57 [2.20, 2.90] 0.65 Day 7 Urine Output (median [IQR]) 2254.50 [937.75, 3462.50] 2460.00 [1090.00, 3470.00] 2207.00 [658.00, 3440.00] 0.22 Albumin (median [IQR]) 2.60 [2.20, 3.01] 2.60 [2.20, 2.96] 2.66 [2.20, 3.08] 0.52 Respiratory rate (median [IQR]) 21.50 [18.46, 25.71] 21.43 [17.86, 24.89] 21.70 [18.69, 26.16] 0.48 Mean arterial pressure (median [IQR]) 78.00 [71.42, 88.60] 80.54 [72.77, 91.70] 75.52 [70.59, 85.07] 0.01 Heart rate (mean (SD)) 90.26 (15.46) 90.09 (15.98) 90.39 (15.11) 0.88 P/F (median [IQR]) 206.40 [170.15, 282.50] 206.40 [166.15, 285.17] 207.14 [170.54, 272.53] 0.69 Discussion Our research indicated that albumin treatment did not enhance the 28-day, hospital, 90-day, or one-year mortality rates among patients with ARDS. Notably, within the MIMIC-III cohort, after adjusting for confounding variables in the propensity score-matched (PSM) cohort, albumin treatment was associated with a reduction in ICU mortality rates. This finding was corroborated by results from the inverse probability weighted cohort. However, it was observed that in the MIMIC-III cohort, albumin treatment was linked to an increased duration of hospital stay, ICU stay, and mechanical ventilation. In contrast, within the eICU cohort, while albumin treatment did not extend ICU stay or mechanical ventilation duration, it did result in a prolonged hospital stay. Subgroup analyses revealed no therapeutic benefit of albumin treatment across any subgroup. Furthermore, data analysis on the seventh day post-treatment showed that the mean arterial pressure was lower in the albumin group compared to the control group. In the eICU cohort, the P/F ratio of ARDS patients improved on the seventh day following albumin administration. In the MIMIC-III cohort, following inverse probability weighting, the administration of albumin to patients with ARDS was associated with a reduction in ICU mortality rates. Similarly, in the matched cohort of Model 3, after adjusting for confounding variables, albumin treatment was also found to potentially decrease ICU mortality rates among patients. This observation may be attributed to a reduction in sample size post-matching, which could diminish statistical power and increase the likelihood of type II errors. However, analysis of the eICU multicenter data revealed that albumin treatment did not significantly reduce the 28-day mortality rate for ARDS patients. This discrepancy may be explained by the larger sample size from multiple centers, which mitigates bias. The use of inverse probability weighting (IPW) allowed for the inclusion of all samples and addressed covariate imbalances by calculating appropriate weights. However, the presence of extreme propensity scores can result in disproportionately high weights for certain individuals, potentially skewing the results and amplifying the influence of sparse data, such as isolated extreme cases that might drive positive outcomes[15]. Consequently, the negative findings from propensity score matching (PSM) could reflect the effects observed in matched subgroups[16], whereas the positive findings from IPW might be influenced by samples with extreme weights, leading to discrepancies between the two analytical methods under specific conditions. To enhance the robustness of our findings, sensitivity analyses were conducted. It is noteworthy that albumin is commonly employed in the management of septic shock and may offer beneficial effects in fluid management for sepsis. Previous studies have demonstrated a direct correlation between decreased albumin levels and increased mortality rates at 14, 28, and 90 days in patients with sepsis[13]. Albumin infusion has been linked to improved 28-day mortality rates in patients suffering from acute kidney injury and septic shock[12]. Nonetheless, there remains a considerable paucity of evidence concerning the therapeutic efficacy of albumin in patients with ARDS. Some researchers argue that albumin infusion in these patients may not only fail to ameliorate relative hypovolemia but could also exacerbate extravascular fluid accumulation, potentially impairing the function of vital organs in individuals with advanced cirrhosis, diabetes mellitus, and sepsis[17]. Furthermore, while colloid therapy with albumin has been shown to enhance oxygenation, it does not appear to influence mortality rates[11]. This outcome may be attributed to the addition of albumin to furosemide therapy, which has been found to significantly improve oxygenation, achieve a greater net negative fluid balance, and maintain hemodynamic stability in hypoproteinemic patients with acute lung injury/ARDS[9]. Another study corroborates these findings, demonstrating that albumin and furosemide therapy enhances fluid balance, oxygenation, and hemodynamics in hypoproteinemic patients with acute lung injury[10]. The primary pathophysiological characteristic of ARDS is the increased permeability of the alveolar-capillary barrier, resulting in non-cardiogenic pulmonary edema. In a healthy state, the pulmonary endothelium effectively suppresses inflammation and coagulation. However, epithelial injury can be directly triggered by microbial pathogens, acid injury (such as aspiration of gastric contents), hyperoxia, or mechanical stretch (for instance, due to mechanical ventilation)[18,19]. These insults may induce epithelial apoptosis or necrosis, while others may disrupt intercellular junctions, thereby increasing epithelial permeability[18,20]. Circulating factors such as damage-associated molecular patterns (DAMPs), cell-free hemoglobin, microbial products, toxins, and circulating immune cells and inflammatory mediators can inflict damage on the epithelium, causing cells to detach from one another and facilitating endothelial gap formation[21,22]. When the typically well-regulated endothelial barrier is compromised, plasma and inflammatory cells infiltrate the interstitial space, resulting in interstitial edema[2]. Breach of the normally tight alveolar epithelial barrier leads to alveolar edema, which is exacerbated by a reduction in alveolar fluid clearance, culminating in alveolar flooding and impaired gas exchange. Furthermore, the systemic inflammation and subsequent endothelial permeability observed in many patients with ARDS contribute to third spacing and relative intravascular volume depletion, often resulting in hypotension[23,24]. Human albumin, a small globular protein synthesized in the liver at a rate of 10-15 g/day and released into the intravascular space, accounts for 75% of the plasma oncotic pressure[25]. Of the total body albumin pool, 30%-40% remains within the intravascular compartment, while the remainder transitions to the interstitial space via capillaries and returns to systemic circulation through the lymphatic system[25]. More than 50% of total body albumin is located in the extravascular compartment, where it may directly affect vascular integrity and permeability through interactions with the extracellular matrix[26]. The thiol group of albumin constitutes approximately 80% of extracellular thiols, rendering it the most significant extracellular antioxidant. Additionally, albumin mitigates oxidative stress by neutralizing free copper (Cu2+) and iron ions, which catalyze reactions that generate free radicals[27]. Albumin has been shown to inhibit TNF (tumor necrosis factor) α-induced upregulation of vascular cell adhesion molecule-1 and NF-KB activation in human aortic endothelial cells, indicating its role in enhancing intracellular protection against inflammatory and oxidative stress damage[28]. Experimental findings have demonstrated that albumin infusion can improve endothelial function in patients with septic shock[29]. This may explain the observed improvement in oxygenation among ARDS patients in our study following albumin treatment on the seventh day. However, similar results were not replicated in the single-center MIMIC-III dataset. In the early stages of ARDS, the inflammatory response leads to increased vascular permeability. Albumin administration can replenish blood volume and enhance blood flow in the pulmonary microvasculature. Nonetheless, due to capillary leakage, volume expansion at this stage may not result in increased blood pressure. The findings of this study indicated a significant decrease in mean arterial pressure on the seventh day post-albumin treatment. The administration of albumin has been shown not to reduce capillary leakage[30], with a portion of the albumin escaping into the interstitial fluid. Consequently, albumin infusion in such patients may not only fail to ameliorate relative hypovolemia but could also exacerbate extravascular fluid accumulation, potentially impairing the function of several vital organs[31]. This raises concerns regarding the relative inefficacy of albumin in conditions characterized by significant capillary leakage[32]. In the context of ARDS, these factors may contribute to the observation that patients' blood pressure does not increase, but rather decreases by the seventh day following albumin treatment in the current study. Furthermore, these factors might also account for the prolonged hospital stays, intensive care unit (ICU) stays, and extended durations of mechanical ventilation observed in ARDS patients following albumin administration. Conclusion In conclusion, our findings suggested that ARDS patients receiving albumin therapy did not improve the outcomes. Using albumin treatment may lead to albumin leakage when the damaged endothelial cells cause severe leakage of capillaries may even aggravate tissue edema and thus prolong the hospital stay, ICU stay, and mechanical ventilation duration. Limitations Most notably, the MIMIC III database used in our study only contains the data of critically ill patients admitted between 2001 and 2012. Secondly, different treatment strategies for critically ill patients, including ventilation strategies, nutritional support, and fluid management, may influence the outcomes of ARDS patients. Thirdly, our study it was had a single-center, retrospective design; thus, so the results of the present study still required further validation by using external datasets. Despite our careful propensity score matching, residual confounding factors cannot be fully excluded. Therefore, the risk of confounding factors should be taken into account for when interpreting the results interpreting. Conclusion The use of NMBAs was not associated with reduced 28-day and or 90-day mortality and may prolong the duration of ventilation duration and length of ICU stay. Due to their many side effects, we should use NMBAs with caution. Declarations Authors’ contributions: Ming He and Xiaojun Pan designed the study, collected and analyzed the data, and contributed to the writing of this manuscript. You Wu and Xiaojun Pan designed and supervised the study and drafted the manuscript. All authors have read and approved the final manuscript. Funding : This work was supported by the National Natural Science Foundation of China (Grant grant No. 82302477, 82302423) Availability of data and materials : The datasets used in the present study are available from the first author and corresponding authors upon reasonable request. Ethics approval and consent to participate : The MIMIC III database used in the present study was approved by the Institutional Review Boards (IRB) of the Massachusetts Institute of Technology and does not contain protected health information. Consent for publication : Not applicable. Competing interests : The authors declare that they have no competing interests. References Fan E, Brodie D, Slutsky AS. Acute Respiratory Distress Syndrome: Advances in Diagnosis and Treatment. JAMA. 2018;319(7):698-710. Bellani G, Laffey JG, Pham T, Fan E, Brochard L, Esteban A, et al. Epidemiology, Patterns of Care, and Mortality for Patients With Acute Respiratory Distress Syndrome in Intensive Care Units in 50 Countries. JAMA. 2016;315(8):788-800. Wang Z, Zhang L, Li S, Xu F, Han D, Wang H, et al. The relationship between hematocrit and serum albumin levels difference and mortality in elderly sepsis patients in intensive care units-a retrospective study based on two large database. BMC Infect Dis. 2022;22(1):629. From the American Association of Neurological Surgeons ASoNC, Interventional Radiology Society of Europe CIRACoNSESoMINTESoNESOSfCA, Interventions SoIRSoNS, World Stroke O, Sacks D, Baxter B, et al. Multisociety Consensus Quality Improvement Revised Consensus Statement for Endovascular Therapy of Acute Ischemic Stroke. Int J Stroke. 2018;13(6):612-632. Verheij J, van Lingen A, Raijmakers PG, Rijnsburger ER, Veerman DP, Wisselink W, et al. 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A randomized, controlled trial of furosemide with or without albumin in hypoproteinemic patients with acute lung injury. Crit Care Med. 2005;33(8):1681-7. Martin GS, Mangialardi RJ, Wheeler AP, Dupont WD, Morris JA, Bernard GR. Albumin and furosemide therapy in hypoproteinemic patients with acute lung injury. Crit Care Med. 2002;30(10):2175-82. Uhlig C, Silva PL, Deckert S, Schmitt J, de Abreu MG. Albumin versus crystalloid solutions in patients with the acute respiratory distress syndrome: a systematic review and meta-analysis. Crit Care. 2014;18(1):R10. Ge C, Peng Q, Chen W, Li W, Zhang L, Ai Y. Association between albumin infusion and outcomes in patients with acute kidney injury and septic shock. Sci Rep. 2021;11(1):24083. Chao P, Cui X, Wang S, Zhang L, Ma Q, Zhang X. Serum albumin and the short-term mortality in individuals with congestive heart failure in intensive care unit: an analysis of MIMIC. Sci Rep. 2022;12(1):16251. Serpa Neto A, Deliberato RO, Johnson AEW, Bos LD, Amorim P, Pereira SM, et al. Mechanical power of ventilation is associated with mortality in critically ill patients: an analysis of patients in two observational cohorts. Intensive care medicine. 2018;44(11):1914-1922. Cole SR, Hernan MA. Constructing inverse probability weights for marginal structural models. Am J Epidemiol. 2008;168(6):656-64. Austin PC. An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies. Multivariate Behav Res. 2011;46(3):399-424. Kumar R, Kumar S, Lata S. Albumin infusion may deleteriously promote extracellular fluid overload without improving circulating hypovolemia in patients of advanced cirrhosis with diabetes mellitus and sepsis. Med Hypotheses. 2013;80(4):452-5. Short KR, Kasper J, van der Aa S, Andeweg AC, Zaaraoui-Boutahar F, Goeijenbier M, et al. Influenza virus damages the alveolar barrier by disrupting epithelial cell tight junctions. 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Resolved versus confirmed ARDS after 24 h: insights from the LUNG SAFE study. Intensive Care Med. 2018;44(5):564-577. Garcia-Martinez R, Caraceni P, Bernardi M, Gines P, Arroyo V, Jalan R. Albumin: pathophysiologic basis of its role in the treatment of cirrhosis and its complications. Hepatology. 2013;58(5):1836-46. Qiao R, Siflinger-Birnboim A, Lum H, Tiruppathi C, Malik AB. Albumin and Ricinus communis agglutinin decrease endothelial permeability via interactions with matrix. Am J Physiol. 1993;265(2 Pt 1):C439-46. Loban A, Kime R, Powers H. Iron-binding antioxidant potential of plasma albumin. Clin Sci (Lond). 1997;93(5):445-51. Cantin AM, Paquette B, Richter M, Larivee P. Albumin-mediated regulation of cellular glutathione and nuclear factor kappa B activation. Am J Respir Crit Care Med. 2000;162(4 Pt 1):1539-46. Lang JD, Jr., Figueroa M, Chumley P, Aslan M, Hurt J, Tarpey MM, et al. Albumin and hydroxyethyl starch modulate oxidative inflammatory injury to vascular endothelium. Anesthesiology. 2004;100(1):51-8. Margarson MP, Soni NC. Effects of albumin supplementation on microvascular permeability in septic patients. J Appl Physiol (1985). 2002;92(5):2139-45. Finfer S, Bellomo R, Boyce N, French J, Myburgh J, Norton R, et al. A comparison of albumin and saline for fluid resuscitation in the intensive care unit. N Engl J Med. 2004;350(22):2247-56. Awad S, Dharmavaram S, Wearn CS, Dube MG, Lobo DN. Effects of an intraoperative infusion of 4% succinylated gelatine (Gelofusine(R)) and 6% hydroxyethyl starch (Voluven(R)) on blood volume. Br J Anaesth. 2012;109(2):168-76. Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6948848","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":490136487,"identity":"34045a6c-be41-4726-9884-dbc969253a32","order_by":0,"name":"Ming He","email":"","orcid":"","institution":"The First People’s Hospital of Linping District","correspondingAuthor":false,"prefix":"","firstName":"Ming","middleName":"","lastName":"He","suffix":""},{"id":490136488,"identity":"c47d1712-cb52-44e5-b7e4-9218ad379214","order_by":1,"name":"You Wu","email":"","orcid":"","institution":"Xijing Hospital","correspondingAuthor":false,"prefix":"","firstName":"You","middleName":"","lastName":"Wu","suffix":""},{"id":490136489,"identity":"da4bbaf0-453e-4db3-a878-db8cb2db1461","order_by":2,"name":"Xiaojun Pan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAt0lEQVRIiWNgGAWjYBAC++MNiQ8SKtjkSNBz5sBjgwdn+IxJ0HIj8Znkwxa5xAaidTDOSE6TSGwwS+87nsD44WMOEVqYeZ4lWyTuSMudeeYBs+TMbURoYWPPSbyReOZY7oYbCWzMvMRo4WHI/yCR2PY/3YBoLRIcCUlALWwJxGsx4DmQbJBwhs1w5pmHzcT5xYC9IfHhjwo2eb7jyQc/fCRGCwIcICFqYFoSSNUxCkbBKBgFIwUAAO/HPlqtbZUHAAAAAElFTkSuQmCC","orcid":"","institution":"Ruijin Hospital","correspondingAuthor":true,"prefix":"","firstName":"Xiaojun","middleName":"","lastName":"Pan","suffix":""}],"badges":[],"createdAt":"2025-06-22 09:53:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6948848/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6948848/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87705166,"identity":"9413190f-3c10-4ec9-b5ee-3ca4e881ae20","added_by":"auto","created_at":"2025-07-28 07:54:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":231100,"visible":true,"origin":"","legend":"\u003cp\u003eStandardized mean difference (SMD) of variables before and after propensity score matching. A was the eICU database, B represented the MIMIC-III database.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6948848/v1/d82053317e3c4d6be1a0e134.png"},{"id":87705192,"identity":"2f260ad7-0247-4f36-a04e-48e61cf8019a","added_by":"auto","created_at":"2025-07-28 07:54:37","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":147920,"visible":true,"origin":"","legend":"\u003cp\u003eSurvival analysis between Albumin and non-albumin therapy group. Kaplan–Meier curve of 28-day mortality in the pre-PSM cohort (A) and PSM cohort in eICU database.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6948848/v1/aa12ba1977e6874521ba1e93.png"},{"id":87706136,"identity":"33c2944e-73ce-4911-9511-d635350ba35e","added_by":"auto","created_at":"2025-07-28 08:02:33","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":439442,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSurvival analysis between Albumin and non-albumin therapy group. Kaplan–Meier curve of 28 days in the pre-PSM cohort(A), PSM cohort (B) and IPTW cohort (C) of the MIMIC-III database. Kaplan–Meier curve of 90 days in the pre-PSM cohort(D), PSM cohort (E) and IPTW cohort (F) of the MIMIC-III database. Kaplan–Meier curve of 365 days in the pre-PSM cohort(G), PSM cohort (H) and IPTW cohort (I) of the MIMIC-III database.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6948848/v1/3c7002d008a9acdd8e22285d.png"},{"id":87705172,"identity":"829d29cf-ed00-49fa-b1b1-da76685ccf00","added_by":"auto","created_at":"2025-07-28 07:54:34","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":558713,"visible":true,"origin":"","legend":"\u003cp\u003eThe association between Albumin administration and 28-day mortality in subgroups of eICU database (A) and MIMIC-III database (B).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6948848/v1/398a590403d723a6b735eb55.png"},{"id":91618311,"identity":"c8b32e84-693d-4aa2-b483-e41c464e149c","added_by":"auto","created_at":"2025-09-18 11:02:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2562014,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6948848/v1/81e85023-3c06-4ec6-be2c-e11cf8f4e2e4.pdf"},{"id":87706145,"identity":"0fb92c82-35e1-4a32-baea-c117873161a6","added_by":"auto","created_at":"2025-07-28 08:02:38","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":53319,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-6948848/v1/222e1030f3c07e1ddf65c180.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Albumin in patients with ARDS in ICU: a retrospective study from eICU and MIMIC-III database","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAcute Respiratory Distress Syndrome (ARDS) is a severe, life-threatening condition affecting over 3\u0026nbsp;million patients globally, accounting for approximately 10% of admissions to intensive care units (ICUs). In the United States alone, ARDS impacts around 200,000 individuals annually and is responsible for nearly 75,000 deaths each year[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Despite advancements in therapeutic strategies that have led to a reduction in mortality rates, the condition's mortality remains significantly high, ranging from 35\u0026ndash;46%[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. ARDS can result from various pulmonary or non-pulmonary pathophysiological insults and is characterized by pulmonary endothelial dysfunction and increased alveolocapillary permeability. These changes can exacerbate pulmonary edema, impairing oxygen delivery and leading to refractory hypoxemia.\u003c/p\u003e\u003cp\u003eHuman serum albumin, synthesized by the liver and constituting 40\u0026ndash;60% of total plasma protein, plays a crucial role in maintaining plasma colloid osmotic pressure, supporting vascular endothelial integrity, and exhibiting antioxidant and anti-inflammatory properties[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Additionally, albumin remains within the intravascular compartment, contributing to restoring effective volume and maintaining colloidal osmotic pressure[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Experimental and clinical evidence indicates that colloids confer several pulmonary benefits over crystalloids, such as reduced alveolar-capillary permeability[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], diminished histological damage[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], and more rapid hemodynamic stabilization[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Conversely, colloid administration may exacerbate tissue edema due to the extravasation of colloid molecules in conditions of heightened capillary leakage[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eEarly administration of albumin has been shown to enhance oxygenation and maintain hemodynamic stability in patients with ARDS and hypoproteinemia[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Nevertheless, albumin therapy did not result in a significant reduction in all-cause mortality at 28 days[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Notably, albumin infusion was associated with improved 28-day survival in patients experiencing acute kidney injury and septic shock[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Additional studies have demonstrated a direct correlation between decreased albumin levels and increased 14-day, 28-day, and 90-day mortality rates in patients with congestive heart failure in intensive care settings[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, the impact of albumin infusion on the outcomes of ARDS patients remains inconclusive. This study aimed to evaluate the efficacy of early albumin therapy in patients with ARDS according to Berlin definition.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData source\u003c/h2\u003e\u003cp\u003e The data utilized in the present study were derived from the eICU Collaborative Research Database (version 2.0) and the MIMIC-III Database (Medical Information Mart for Intensive Care, version 1.4). The eICU database is a comprehensive, multi-center resource encompassing over 200,000 ICU admissions across the United States during the period of 2014 to 2015. It contains detailed information on critically ill patients, including vital signs, diagnoses, illness severity, laboratory results, and treatments. In contrast, the MIMIC-III database comprises patient data from the Beth Israel Deaconess Medical Center, spanning from June 2001 to October 2012. This database is organized into tables in CSV format for research purposes, encompassing nearly all patient data during ICU treatment. This includes demographic information, hourly vital signs, surgical records, drug administration details (timing and dosage), fluid balance, microbiological examination results, care records, and patient outcomes (including inpatient and out-of-hospital deaths, as well as discharges). Both databases have received approval from the Institutional Review Boards (IRB) of the Massachusetts Institute of Technology (MIT). Ethical approval was obtained following the completion of all required National Institutes of Health web-based training courses and the Protecting Human Research Participants certification (Record ID 35209874).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStudy cohort:\u003c/h3\u003e\n\u003cp\u003eWe conducted a multicenter, retrospective study involving patients with ARDS as defined by the Berlin criteria[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Data collection was limited to the first admission, and all data were extracted from the database by using Structured Query Language following the methodology established by Johnson et al[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The inclusion criteria for the study were: (1) patients diagnosed with ARDS; (2) patients admitted to the Intensive Care Unit (ICU) for the first time; and (3) patients aged 16 years or older. The exclusion criteria included: (1) patients who succumbed within the first 48 hours; (2) readmissions to the hospital or ICU; (3) ARDS diagnosis occurring more than 48 hours post-admission; and (4) cases with missing critical data. Data extraction was performed using Structured Query Language (SQL) from the MIMIC database. On the first day of ICU admission, the following data were collected: weight, gender, age, type of admission, ethnicity (categorized as White, Hispanic, Black, or Other), use of mechanical ventilation, renal replacement therapy (RRT), ARDS severity, Simplified Acute Physiology Score II (SAPS II), Sequential Organ Failure Assessment (SOFA) score, heart rate, P/F ratio, respiratory rate, albumin levels, and comorbidities.\u003c/p\u003e\n\u003ch3\u003eData collection and definitions\u003c/h3\u003e\n\u003cp\u003eStructured Query Language (SQL) was utilized to extract the necessary data. Demographic information, including age, gender, ethnicity, and admission source, as well as Acute Physiology and Chronic Health Evaluation (APACHE IVa) scores, Sequential Organ Failure Assessment (SOFA) scores, Simplified Acute Physiology Score (SAPS II), and comorbidities, were retrieved from the database. Additionally, data on urine output, heart rate, mean arterial pressure, respiration rate, P/F ratio, and serum albumin levels on the first and seventh day post-admission were reviewed. In cases where the fraction of inspired oxygen (FiO2) data was missing, adjacent two-hour FiO2 values were substituted. The severity of ARDS was assessed according to the Berlin definition. Continuous variables were presented as medians with interquartile ranges (IQR), and the Wilcoxon rank-sum test was employed to compare differences between groups.\u003c/p\u003e\n\u003ch3\u003eEndpoint events\u003c/h3\u003e\n\u003cp\u003eThe primary endpoint was 28-day mortality, while secondary endpoints included ICU mortality, hospital mortality, length of hospital and ICU stay, duration of ventilation, and measurements of urine output, heart rate, respiration rate, mean arterial pressure, P/F ratio, and SOFA score on day 7.\u003c/p\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eContinuous variables were presented as medians with interquartile ranges (IQR), and the Wilcoxon rank-sum test was employed to compare differences between groups. Categorical variables were summarized using frequencies and percentages, and differences between groups were assessed using either the χ\u0026sup2; test or Fisher's exact test, as appropriate. To address potential confounding factors between the two groups, propensity score matching (PSM) was employed. A univariate Cox regression model was utilized to examine the association between potential confounding variables and mortality; variables with a p-value less than 0.05 or those identified through clinical expertise were included in the PSM process. The matching was conducted using a greedy nearest neighbor approach at a 1:1 ratio, with a caliper width of 0.2 standard deviations. Prior to PSM, missing values in selected confounding variables were addressed using random forest imputation.\u003c/p\u003e\u003cp\u003eAdditionally, an inverse probability of treatment weighting (IPTW) model was implemented to further adjust for confounding variables between the groups. Cox proportional hazards models were applied to estimate the association between albumin administration within 48 hours of admission and patient outcomes in those with acute respiratory distress syndrome (ARDS) across pre-matched, matched, and IPTW cohorts. The hazard ratios (HR) and 95% confidence intervals (CI) for the variables of interest were reported for comparisons between the two groups. Kaplan\u0026ndash;Meier survival curves were constructed, and the log-rank test was employed to assess the association between 28-day mortality and albumin therapy in both pre-matched and matched cohorts across the two groups. Stratified analyses based on age, Sequential Organ Failure Assessment (SOFA) and Acute Physiology and Chronic Health Evaluation IVa (APACHE IVa) scores, severity of ARDS, heart rate, mean arterial pressure, urine output, respiratory rate, and serum albumin levels were conducted to evaluate the impact of albumin infusion between the groups. All statistical analyses were executed using RStudio (version 4.0.5).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eBasic characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFollowing a review of over 200,000 subjects from the eICU database, 3,371 eligible patients with ARDS were identified according to the specified inclusion and exclusion criteria. Of these, 209 patients (6.2%) received albumin therapy, while 3,162 (93.8%) did not, as detailed in Figure 1 and Table 1a. From the MIMIC-III database, 61,532 subjects were reviewed, resulting in the enrollment of 1,137 patients with ARDS according to the Berlin definition. Among these, 189 patients (16.62%) received albumin therapy, whereas 948 (83.38%) did not, as presented in Figure 1 and Table 1b.\u003c/p\u003e\n\u003cp\u003eIn the eICU cohort 1670 (49.54%) patients were female and 1701 (50.46%) were male, the median age and median weight in the study cohort was 67.00 (56.00, 78.00) and 81.10 (65.75, 100.73) respectively. Medical (87.04%) was the main admission source and white was the main ethnicity (75.23%) in the present study. 2348 (69.65%) patients received mechanical ventilation on the first day admitted to ICU. The median SOFA score and APACHE IVa score was 6.00 (4.00, 9.00) and 62.00 (47.00, 82.00) respectively. The median PaO2/FiO2 (P/F) ratio on the first day was 138.33 (94.00, 208.00). The median heart rate, respiratory rate and mean arterial pressure of the first day was 90.10 (78.72, 102.05), 21.41 (18.45, 24.85), 82.16 (75.10, 91.40) respectively. The median of first day serum albumin was 3.00 (2.55, 3.50), the median urine output of the first day was 1550.00 (775.00, 2800.00). The main severity of ARDS in the study population was moderate (44.62%). There was no significant difference in age, gender, first day mechanical ventilation, respiratory rate, chronic heart failure, renal disease, malignant cancer between the two groups in the eICU database. However, in the MIMIC-III cohort 660 (58.05%) patients were female, the median age and median weight in the study cohort was 60.80 (48.43, 74.50) and 80.00 (67.15, 94.85) respectively. Medical (86.63%) was the main admission source and white was the main ethnicity (68.34%) in the present study. 993 (87.34%) patients received mechanical ventilation on the first day admitted to ICU. The median SOFA score and SAPS II score was 7.00 (5.00, 9.00) and 42.00 (33.00, 52.00) respectively. The median P/F ratio on the first day was 123.33 (82.00, 178.00). The median heart rate, respiratory rate and mean arterial pressure of the first day was 92.53 (80.91, 104.35), 20.85 (17.87, 24.65), 75.58 (70.10, 82.88) respectively. The median of first day serum albumin was 2.80 (2.40, 3.32), the median urine output of the first day was 1669.50 (960.00, 264.00). The main severity of ARDS in the study population was moderate (46.35%). There was no significant difference in age, gender, weight, first day mechanical ventilation, respiratory rate, RRT on the first day, chronic heart failure, renal disease, malignant cancer between the two groups in the MIMIC-III database. After implementing Inverse Probability of Treatment Weighting (IPTW) and Propensity Score Matching (PSM), the baseline characteristics of the patients were well-balanced between the two groups, as shown in Figure 1 and Tables S1a, S1b, S1c, and S1d.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1a: Baseline Characteristics between the study cohort from eICU database.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"910\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall(n=3371)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003enon-albumin (n=3162)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlbumin (n=209)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (median (IQR))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e67.00 (56.00, 78.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e67.00 (56.00, 79.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e66.00 (54.00, 77.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eGender (female, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e1670 (49.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e1570 (49.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e100 (47.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdmission source (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eMedical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e2934 (87.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e2771 (87.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e163 (77.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eSurgical urgent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e220 (6.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e193 (6.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e27 (12.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eSurgical elective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e217 (6.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e198 (6.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e19 (9.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e2536 (75.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e2391 (75.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e145 (69.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e412 (12.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e393 (12.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e19 (9.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003e\u0026nbsp; Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e193 (5.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e159 (5.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e34 (16.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e182 (5.40) 230 (6.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e174 (5.50) 219 (6.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e8 (3.83) 11 (5.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eWeight (median (IQR))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e81.10 (65.75, 100.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e81.50 (65.80, 101.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e76.20 (64.77, 96.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eARDS severity (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eMild\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e904 (26.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e867 (27.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e37 (17.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e1504 (44.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e1432 (45.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e72 (34.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eSevere\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e963 (28.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e863 (27.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e100 (47.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eMechanical ventilation (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e2348 (69.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e2190 (69.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e158 (75.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eSOFA (median (IQR))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e6.00 (4.00, 9.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e6.00 (4.00, 9.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e9.00 (6.00, 12.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eAPACHE-IVa \u0026nbsp;(median (IQR))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e62.00 (47.00, 82.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e61.00 (46.00, 81.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e80.00 (58.00, 105.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eP/F (median (IQR))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e138.33 (94.00, 208.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e140.00 (96.00, 210.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e103.52 (66.00, 174.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eUrine output (median (IQR))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e1550.00 (775.00, 2800.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e1570.00 (800.00, 2835.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e1127.50 (400.00, 2077.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eHeart rate (median (IQR))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e90.10 (78.72, 102.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e89.93 (78.51, 101.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e92.71 (82.73, 106.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eRespiratory rate (median (IQR))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e21.41 (18.45, 24.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e21.35 (18.44, 24.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e21.74 (18.77, 25.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eMean arterial pressure (median (IQR))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e82.16 (75.10, 91.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e82.69 (75.58, 91.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e76.49 (70.80, 83.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eAlbumin (median (IQR))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e3.00 (2.55, 3.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e3.07 (2.60, 3.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e2.69 (2.22, 3.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCo-morbidities, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eChronic heart failure\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e649 (19.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e618 (19.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e31 (14.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eLiver disease\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e100 (2.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e86 (2.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e14 (6.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eRenal disease\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e294 (8.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e276 (8.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e18 (8.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026gt;0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 243px;\"\u003e\n \u003cp\u003eMalignant cancer\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e115 (3.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e107 (3.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 205px;\"\u003e\n \u003cp\u003e8 (3.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1b: Baseline Characteristics between the study cohort from MIMIC-III database.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eOverall (1137)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e\u003cstrong\u003enon-albumin\u003c/strong\u003e (948)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlbumin\u003c/strong\u003e (189)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eAge (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e60.80 [48.43, 74.50]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e60.78 [47.66, 74.95]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e61.30 [49.70, 72.04]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eGender (female, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e660 (58.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e556 (58.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e104 (55.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eAdmission source (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eMedical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e985 (86.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e832 (87.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e153 (80.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eSurgical urgent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e38 (3.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e34 (3.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e4 (2.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eSurgical elective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e114 (10.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e82 (8.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e32 (16.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e85 (7.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e76 (8.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e9 (4.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e37 (3.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e28 (2.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e9 (4.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e777 (68.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e634 (66.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e143 (75.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e238 (20.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e210 (22.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e28 (14.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eWeight (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e80.00 [67.15, 94.85]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e80.00 [67.75, 95.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e75.40 [66.00, 92.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eARDS severity (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eMild\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e196 (17.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e168 (17.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e28 (14.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e527 (46.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e455 (48.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e72 (38.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eSevere\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e414 (36.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e325 (34.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e89 (47.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eMechanical ventilation (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e993 (87.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e836 (88.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e157 (83.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eSOFA (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e7.00 [5.00, 9.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e6.00 [4.00, 9.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e8.00 [5.00, 11.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eSAPS II (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e42.00 [33.00, 52.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e42.00 [32.00, 51.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e46.00 [36.00, 55.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eP/F (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e123.33 [82.00, 178.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e125.00 [83.94, 180.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e103.33 [74.00, 157.50]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003ePEEP (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e5.30 [5.00, 10.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e5.00 [5.00, 10.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e8.00 [5.00, 10.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eHeart rate (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e92.53 [80.91, 104.35]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e91.76 [80.34, 103.19]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e97.85 [84.93, 108.96]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eMean arterial pressure (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e75.58 [70.10, 82.88]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e76.04 [70.50, 83.52]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e73.81 [68.05, 78.77]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eRespiratory rate (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e20.85 [17.87, 24.65]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e20.76 [17.88, 24.61]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e21.18 [17.65, 24.73]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eAlbumin (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e2.80 [2.40, 3.32]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e2.90 [2.40, 3.40]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e2.50 [2.20, 2.90]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eUrine Output (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e1669.50 [960.00, 2640.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e1759.50 [1013.75, 2736.25]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e1177.00 [653.25, 2091.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003eRRT (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e62 (5.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e51 (5.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e11 (5.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCo-morbidities, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 242px;\"\u003e\n \u003cp\u003eChronic heart failure\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e470 (41.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e414 (43.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e56 (29.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 242px;\"\u003e\n \u003cp\u003eLiver disease\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e136 (11.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e114 (12.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e22 (11.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 242px;\"\u003e\n \u003cp\u003eRenal disease\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e91 (8.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e50 (5.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e41 (21.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 242px;\"\u003e\n \u003cp\u003eMalignant cancer\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e209 (18.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e168 (17.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e41 (21.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: ARDS, acute respiratory distress syndrome. SOFA, sequential organ failure assessment. SAPSII, simplified acute physiology score II. P/F：PaO2/FiO2 ratio. RRT, renal replacement therapy. CHF, chronic heart failure.\u003c/p\u003e\n\u003cp\u003ea. All covariates were reported as mean (standard deviation) and median [IQR].\u003c/p\u003e\n\u003cp\u003eb.Mechanical ventilation and RRT were received the therapy on the first day ICU admission.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ec. All data is extracted in the first 24 h of ICU admission\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRelationship between furosemide and outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the eICU cohort, the 28-day mortality (HR=2.10; 95% CI: 1.62-2.74; P\u0026lt;0.01), ICU mortality (HR=1.82; 95% CI: 1.36-2.43; P\u0026lt;0.01), hospital mortality (HR=1.53; 95% CI: 1.18-1.98; P=0.001) were associated with albumin therapy in the original cohort. After being adjusted for the confounders (including gender, age, admission source, weight, and ethnicity), the addition therapy of albumin was associated with the 28-day (HR=1.98; 95% CI: 1.5-2.6; P\u0026lt;0.01), ICU (HR=1.86; 95% CI: 1.39-2.5; P\u0026lt;0.01), or hospital mortality (HR=1.46; 95% CI: 1.12-1.91; P=0.005).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eAlbumin was only associated with the ICU (HR=1.44; 95% CI: 1.06-1.94; P=0.02) mortality after adjusted for the confounders including gender, age, ethnicity, admit source, weight, SOFA, APACHE IVa score, first day mechanical ventilation, ARDS severity, chronic heart failure, liver, disease, renal disease, and malignant cancer.\u003c/p\u003e\n\u003cp\u003eAfter PSM matching, 206 patients who received albumin therapy were matched with 206 patients who did not. The albumin therapy was not associated with 28-day mortality (HR, 0.88; 95% CI, 0.62-1.24; P=0.5), the ICU mortality (HR, 0.95; 95% CI, 0.65-1.4; P=0.8), hospital mortality (HR, 0.78; 95% CI, 0.56-1.1; P=0.2). After adjusted with gender, age, admission source, weight, and ethnicity, the 28-day mortality (HR, 0.86; 95% CI, 0.61-1.23; P=0.41), the ICU mortality (HR, 0.91; 95% CI, 0.62-1.35; P＜0.65), hospital mortality (HR, 0.76; 95% CI, 0.54-1.08; P=0.13) were not associated with albumin infusion. After adjusted with gender, age, ethnicity, admit source, weight, SOFA, APACHE IVa score, first day mechanical ventilation, ARDS severity, chronic heart failure, liver, disease, renal disease, and malignant cancer, the 28-day mortality (HR, 0.92; 95% CI, 0.64-1.3; P=0.63), the ICU mortality (HR, 0.94; 95% CI, 0.63-1.4; P=0.77), hospital mortality (HR, 0.79; 95% CI, 0.56-1.13; P=0.2) were not associated with albumin infusion in the matched cohort.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe albumin therapy was not associated with 28-day mortality (HR, 1.12; 95% CI, 0.76-1.67; P=0.6), the ICU mortality (HR, 0.92; 95% CI, 0.77-1.11; P=0.4), hospital mortality (HR, 1.02; 95% CI, 0.69-1.5; P=0.9) in the IPTW cohort. After adjusted with gender, age, admission source, weight, and ethnicity, the 28-day mortality (HR, 1.18; 95% CI, 0.79-1.77; P=0.41), the ICU mortality (HR, 0.96; 95% CI, 0.8-1.15; P=0.62), hospital mortality (HR, 1.07; 95% CI, 0.73-1.57; P=0.73) were not associated with albumin infusion in the IPTW cohort. After adjusted with gender, age, ethnicity, admit source, weight, SOFA, APACHE IVa score, first day mechanical ventilation, ARDS severity, chronic heart failure, liver, disease, renal disease, and malignant cancer, the 28-day mortality (HR, 1.11; 95% CI, 0.74-1.66; P=0.61), the ICU mortality (HR, 1.06; 95% CI, 0.88-1.3; P=0.5), hospital mortality (HR, 1.02; 95% CI, 0.69-1.51; P=0.91) were not associated with albumin infusion in the IPTW cohort..\u003c/p\u003e\n\u003cp\u003eIn the MIMIC-III cohort, 178 patients who received albumin therapy were matched with 178 patients who did not after PSM. The albumin was both not association with the 28-day, hospital, 90-day, and 365-day mortality in the three COX model in pre-matched cohort. However, the albumin therapy was not association with ICU mortality in the COX1 and COX2 model and was association with ICU mortality in the COX3 model before PSM. The addition therapy was not association with 28-day, ICU, hospital, 90-day, and 365-day mortality in both three model after PSM. The albumin infusion was not association with 28-day, hospital, 90-day, and 365-day mortality in the IPTW cohort. However, the albumin therapy decreased the ICU mortality in the IPTW. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe median length of hospital and ICU stays were 7.61 and 2.96 days, respectively. The median duration of ventilation was 29.5 hours in the matched of eICU database. The 28-day, ICU and hospital mortality were no significant difference in the two groups (P=0.6, P=0.91 and P=0.75, respectively). Moreover, the length of ICU and ventilation duration were no significant difference in the two groups (P=0.51 and P=0.29, respectively). However, the hospital was longer in the albumin group than non-albumin group (8.98 vs. 8.25, P=0.02). The median length of hospital, ICU stays, and the duration of mechanical ventilation were 17.34, 9.28 and 5.63 days in the matched cohort of MIMIC-III database, respectively. The 28-day, ICU, hospital, 90-day, and 365-day mortality were no significant difference in the two groups after PSM. However, the length of ICU and hospital stays were longer in the albumin therapy group (P\u0026lt;0.01). Moreover, the duration of mechanical ventilation was longer in the albumin therapy group than control group in the matched cohort (P\u0026lt;0.01). The univariate COX analysis of eICU and MIMIC-III cohort were performed and the results were showed in the Table S3a and S3b.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eKaplan\u0026ndash;Meier survival curves were plotted and log-rank test were performed to compare the difference of 28-day mortality between the two groups, and the results were shown in Figure 2 and Table 2. There was no significant difference in 28-day mortality between the two groups after PSM (P=0.45) in the eICU cohort. In the MIMIC-III cohort, the 28-day, 90-day, and one-year mortality were higher in the albumin group (P=0.17, P=0.0016, P=0.0012) in the original cohort. However, there is no difference in 28-day, 90-day, and one-year mortality between the groups in the matched cohort (P=0.8, P=0.24, P=0.41). There is no difference in 28-day between the groups in the IPTW cohort (P=0.17). However, the 90-day and one-year mortality were higher in the non-albumin group than the albumin groups (P=0.0016, P=0.0012) in the IPTW cohort (Figure 3).\u003c/p\u003e\n\u003cp\u003eThe comparison of the urine output, heart rate, respiratory rate, mean arterial pressure, P/F ratio, SOFA score, or albumin on day 1 and day 7 were compared between the albumin therapy and non-albumin group. The mean arterial pressure was higher and the P/F ratio was lower in the non-albumin group than the albumin group in the eICU cohort. The mean arterial pressure was higher in the non-albumin group than the albumin group in the MIMIC-III database (shown in Table 3a and 3b).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSubgroup analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of the subgroup analysis of 28-day mortality were shown in Figure 4. There were no differences in the albumin treatment in subgroups in the eICU cohort Figure 4A) and in the MIMIC-III group (Figure 4B).\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"938\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\" style=\"width: 938px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003cstrong\u003eTable 2a: Outcomes of Albumin and non-Albumin patients and sensitivity analysis from eICU database.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003ePre-matched\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003eMatched\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003eIPTW\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e28-day Mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eModel 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（1.62-2.74）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（0.62-1.24）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（0.76-1.67）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（1.5-2.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（0.61-1.23）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（0.79-1.77）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eModel 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（0.97-1.69）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（0.64-1.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（0.74-1.66）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eICU Mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eModel 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（1.362-2.431）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（0.65-1.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（0.77-1.11）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（1.388-2.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（0.62-1.35）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（0.8-1.15）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eModel 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（1.06-1.94）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（0.63-1.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（0.88-1.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHospital Mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eModel 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（1.18-1.98）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（0.56-1.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（0.69-1.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（1.12-1.91）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（0.54-1.08）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（0.73-1.57）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eModel 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（0.84-1.45）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（0.56-1.13）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e（0.69-1.51）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2b: Outcomes of Albumin and non-Albumin patients and sensitivity analysis from MIMIC-III database.\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"938\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 291px;\"\u003e\n \u003cp\u003ePre-matched\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 239px;\"\u003e\n \u003cp\u003eMatched\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 238px;\"\u003e\n \u003cp\u003eIPTW\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e28-day Mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eModel 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.65-1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.65-1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.63-1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.67-1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.62-1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.58-1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eModel 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.67-1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.65-1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.6-1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eICU Mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eModel 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.49-1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.49-1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.45-0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.49-1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.46-1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.48-0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eModel 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.44-0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.43-0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.5-0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eHospital Mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eModel 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.61-1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.61-1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.61-1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.59-1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.54-1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.56-1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eModel 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.57-1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.54-1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.54-1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e90-day Mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eModel 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.87-1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.87-1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.85-1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.9-1.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.82-1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.79-1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eModel 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.93-1.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.89-1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.88-1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e365-day Mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eModel 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.84-1.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.84-1.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.82-1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.85-1.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.8-1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.76-1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eModel 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.9-1.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0.87-162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e0.87-1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAbbreviation: CI, confidence interval. HR, hazard ratio.\u003c/p\u003e\n\u003cp\u003eAll models were performed by Cox proportional hazards model analysis the relationship between NMBAs therapy and all cause mortality.\u003c/p\u003e\n\u003cp\u003eModel 1 Cox regression was used for estimating the impact of albumin use on mortality outcomes\u003c/p\u003e\n\u003cp\u003e0.05 in univariate analysis\u003c/p\u003e\n\u003cp\u003eModel 2 Cox regression was adjusted by gender, age, admission type and ethnicity.\u003c/p\u003e\n\u003cp\u003eModel 3 Cox regression was adjusted by gender, age, SOFA, SAPSII, ethnicity, ARDS severity, chronic disease of liver, malignancy, respiratory rate.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3a: Comparison of the dynamic indicator in eICU database.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"909\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOverall (n=412)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003enon-albumin (n=206)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAlbumin (n=206)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDay 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eUrine Output (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1187.50 [575.00, 2177.50]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1275.00 [707.50, 2455.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1135.00 [400.00, 2090.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHeart rate (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e93.37 [82.77, 105.90]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e93.98 [82.92, 105.16]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e92.64 [82.66, 106.39]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRespiratory rate (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.66 [18.45, 25.47]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.30 [18.25, 25.58]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.73 [18.57, 25.39]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMean arterial pressure (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e76.32 [71.36, 82.77]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e76.02 [72.12, 80.57]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e76.61 [70.87, 83.37]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eP/F (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e121.00 [70.00, 216.50]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e120.00 [72.00, 204.50]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e121.00 [69.75, 221.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSOFA (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.00 [6.00, 12.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.00 [6.00, 12.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.00 [6.00, 12.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAlbumin (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.70 [2.25, 3.10]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.65 [2.26, 3.10]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.70 [2.25, 3.05]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDay 7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eUrine Output (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1400.00 [500.00, 2490.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1450.00 [741.25, 2648.25]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1375.00 [425.00, 2475.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHeart rate (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e89.07 (14.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e90.03 (15.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e88.35 (14.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRespiratory rate (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e19.97 [18.00, 24.36]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e19.99 [18.00, 24.37]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e19.93 [17.90, 24.36]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMean arterial pressure (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e84.91 [77.06, 95.15]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e90.13 [79.96, 98.59]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e82.19 [74.56, 90.94]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eP/F (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.00 [4.00, 10.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.50 [2.75, 8.25]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.00 [4.00, 11.50]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSOFA (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e168.00 [108.50, 257.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e160.00 [107.00, 212.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e170.00 [109.50, 268.50]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAlbumin (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.41 (0.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.34 (0.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.45 (0.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3b: Comparison of the dynamic indicator in the MIMIC-III database.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 283px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003eOverall (n=356)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e0 (n=178)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e1 (n=178)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 283px;\"\u003e\n \u003cp\u003eDay 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 283px;\"\u003e\n \u003cp\u003eUrine Output (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e1278.50 [748.75, 2267.50]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e1325.00 [752.50, 2362.50]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e1198.00 [756.00, 2200.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 283px;\"\u003e\n \u003cp\u003eHeart rate (mean (SD))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e96.74 (17.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e96.50 (17.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e96.98 (17.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 283px;\"\u003e\n \u003cp\u003eRespiratory rate (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e21.00 [17.86, 24.87]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e20.86 [17.99, 25.17]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e21.19 [17.48, 24.77]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 283px;\"\u003e\n \u003cp\u003eMean arterial pressure (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e73.41 [67.72, 79.12]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e72.93 [67.31, 79.79]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e73.95 [68.40, 79.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 283px;\"\u003e\n \u003cp\u003eP/F (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e108.45 [75.00, 165.25]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e111.83 [75.00, 169.64]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e104.50 [77.12, 160.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 283px;\"\u003e\n \u003cp\u003eAlbumin (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e2.60 [2.20, 2.92]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e2.60 [2.11, 2.94]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e2.57 [2.20, 2.90]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 283px;\"\u003e\n \u003cp\u003eDay 7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 283px;\"\u003e\n \u003cp\u003eUrine Output (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e2254.50 [937.75, 3462.50]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e2460.00 [1090.00, 3470.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e2207.00 [658.00, 3440.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 283px;\"\u003e\n \u003cp\u003eAlbumin (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e2.60 [2.20, 3.01]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e2.60 [2.20, 2.96]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e2.66 [2.20, 3.08]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 283px;\"\u003e\n \u003cp\u003eRespiratory rate (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e21.50 [18.46, 25.71]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e21.43 [17.86, 24.89]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e21.70 [18.69, 26.16]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 283px;\"\u003e\n \u003cp\u003eMean arterial pressure (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e78.00 [71.42, 88.60]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e80.54 [72.77, 91.70]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e75.52 [70.59, 85.07]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 283px;\"\u003e\n \u003cp\u003eHeart rate (mean (SD))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e90.26 (15.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e90.09 (15.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e90.39 (15.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 283px;\"\u003e\n \u003cp\u003eP/F (median [IQR])\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e206.40 [170.15, 282.50]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e206.40 [166.15, 285.17]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e207.14 [170.54, 272.53]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur research indicated that albumin treatment did not enhance the 28-day, hospital, 90-day, or one-year mortality rates among patients with ARDS. Notably, within the MIMIC-III cohort, after adjusting for confounding variables in the propensity score-matched (PSM) cohort, albumin treatment was associated with a reduction in ICU mortality rates. This finding was corroborated by results from the inverse probability weighted cohort. However, it was observed that in the MIMIC-III cohort, albumin treatment was linked to an increased duration of hospital stay, ICU stay, and mechanical ventilation. In contrast, within the eICU cohort, while albumin treatment did not extend ICU stay or mechanical ventilation duration, it did result in a prolonged hospital stay. Subgroup analyses revealed no therapeutic benefit of albumin treatment across any subgroup. Furthermore, data analysis on the seventh day post-treatment showed that the mean arterial pressure was lower in the albumin group compared to the control group. In the eICU cohort, the P/F ratio of ARDS patients improved on the seventh day following albumin administration.\u003c/p\u003e\n\u003cp\u003eIn the MIMIC-III cohort, following inverse probability weighting, the administration of albumin to patients with ARDS was associated with a reduction in ICU mortality rates. Similarly, in the matched cohort of Model 3, after adjusting for confounding variables, albumin treatment was also found to potentially decrease ICU mortality rates among patients. This observation may be attributed to a reduction in sample size post-matching, which could diminish statistical power and increase the likelihood of type II errors. However, analysis of the eICU multicenter data revealed that albumin treatment did not significantly reduce the 28-day mortality rate for ARDS patients. This discrepancy may be explained by the larger sample size from multiple centers, which mitigates bias. The use of inverse probability weighting (IPW) allowed for the inclusion of all samples and addressed covariate imbalances by calculating appropriate weights. However, the presence of extreme propensity scores can result in disproportionately high weights for certain individuals, potentially skewing the results and amplifying the influence of sparse data, such as isolated extreme cases that might drive positive outcomes[15]. Consequently, the negative findings from propensity score matching (PSM) could reflect the effects observed in matched subgroups[16], whereas the positive findings from IPW might be influenced by samples with extreme weights, leading to discrepancies between the two analytical methods under specific conditions. To enhance the robustness of our findings, sensitivity analyses were conducted.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIt is noteworthy that albumin is commonly employed in the management of septic shock and may offer beneficial effects in fluid management for sepsis. Previous studies have demonstrated a direct correlation between decreased albumin levels and increased mortality rates at 14, 28, and 90 days in patients with sepsis[13].\u0026nbsp;Albumin infusion has been linked to improved 28-day mortality rates in patients suffering from acute kidney injury and septic shock[12]. Nonetheless, there remains a considerable paucity of evidence concerning the therapeutic efficacy of albumin in patients with ARDS. Some researchers argue that albumin infusion in these patients may not only fail to ameliorate relative hypovolemia but could also exacerbate extravascular fluid accumulation, potentially impairing the function of vital organs in individuals with advanced cirrhosis, diabetes mellitus, and sepsis[17]. Furthermore, while colloid therapy with albumin has been shown to enhance oxygenation, it does not appear to influence mortality rates[11]. This outcome may be attributed to the addition of albumin to furosemide therapy, which has been found to significantly improve oxygenation, achieve a greater net negative fluid balance, and maintain hemodynamic stability in hypoproteinemic patients with acute lung injury/ARDS[9]. Another study corroborates these findings, demonstrating that albumin and furosemide therapy enhances fluid balance, oxygenation, and hemodynamics in hypoproteinemic patients with acute lung injury[10].\u003c/p\u003e\n\u003cp\u003eThe primary pathophysiological characteristic of ARDS is the increased permeability of the alveolar-capillary barrier, resulting in non-cardiogenic pulmonary edema. In a healthy state, the pulmonary endothelium effectively suppresses inflammation and coagulation. However, epithelial injury can be directly triggered by microbial pathogens, acid injury (such as aspiration of gastric contents), hyperoxia, or mechanical stretch (for instance, due to mechanical ventilation)[18,19]. These insults may induce epithelial apoptosis or necrosis, while others may disrupt intercellular junctions, thereby increasing epithelial permeability[18,20]. Circulating factors such as damage-associated molecular patterns (DAMPs), cell-free hemoglobin, microbial products, toxins, and circulating immune cells and inflammatory mediators can inflict damage on the epithelium, causing cells to detach from one another and facilitating endothelial gap formation[21,22]. When the typically well-regulated endothelial barrier is compromised, plasma and inflammatory cells infiltrate the interstitial space, resulting in interstitial edema[2]. Breach of the normally tight alveolar epithelial barrier leads to alveolar edema, which is exacerbated by a reduction in alveolar fluid clearance, culminating in alveolar flooding and impaired gas exchange. Furthermore, the systemic inflammation and subsequent endothelial permeability observed in many patients with ARDS contribute to third spacing and relative intravascular volume depletion, often resulting in hypotension[23,24].\u003c/p\u003e\n\u003cp\u003eHuman albumin, a small globular protein synthesized in the liver at a rate of 10-15 g/day and released into the intravascular space, accounts for 75% of the plasma oncotic pressure[25]. Of the total body albumin pool, 30%-40% remains within the intravascular compartment, while the remainder transitions to the interstitial space via capillaries and returns to systemic circulation through the lymphatic system[25]. More than 50% of total body albumin is located in the extravascular compartment, where it may directly affect vascular integrity and permeability through interactions with the extracellular matrix[26]. The thiol group of albumin constitutes approximately 80% of extracellular thiols, rendering it the most significant extracellular antioxidant. Additionally, albumin mitigates oxidative stress by neutralizing free copper (Cu2+) and iron ions, which catalyze reactions that generate free radicals[27]. Albumin has been shown to inhibit TNF (tumor necrosis factor) \u0026alpha;-induced upregulation of vascular cell adhesion molecule-1 and NF-KB activation in human aortic endothelial cells, indicating its role in enhancing intracellular protection against inflammatory and oxidative stress damage[28]. Experimental findings have demonstrated that albumin infusion can improve endothelial function in patients with septic shock[29]. This may explain the observed improvement in oxygenation among ARDS patients in our study following albumin treatment on the seventh day. However, similar results were not replicated in the single-center MIMIC-III dataset.\u003c/p\u003e\n\u003cp\u003eIn the early stages of ARDS, the inflammatory response leads to increased vascular permeability. Albumin administration can replenish blood volume and enhance blood flow in the pulmonary microvasculature. Nonetheless, due to capillary leakage, volume expansion at this stage may not result in increased blood pressure. The findings of this study indicated a significant decrease in mean arterial pressure on the seventh day post-albumin treatment. The administration of albumin has been shown not to reduce capillary leakage[30], with a portion of the albumin escaping into the interstitial fluid. Consequently, albumin infusion in such patients may not only fail to ameliorate relative hypovolemia but could also exacerbate extravascular fluid accumulation, potentially impairing the function of several vital organs[31]. This raises concerns regarding the relative inefficacy of albumin in conditions characterized by significant capillary leakage[32]. In the context of ARDS, these factors may contribute to the observation that patients\u0026apos; blood pressure does not increase, but rather decreases by the seventh day following albumin treatment in the current study. Furthermore, these factors might also account for the prolonged hospital stays, intensive care unit (ICU) stays, and extended durations of mechanical ventilation observed in ARDS patients following albumin administration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn conclusion, our findings suggested that ARDS patients receiving albumin therapy did not improve the outcomes. Using albumin treatment may lead to albumin leakage when the damaged endothelial cells cause severe leakage of capillaries may even aggravate tissue edema and thus prolong the hospital stay, ICU stay, and mechanical ventilation duration.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMost notably, the MIMIC III database used in our study only contains the data of critically ill patients admitted between 2001 and 2012. Secondly, different treatment strategies for critically ill patients, including ventilation strategies, nutritional support, and fluid management, may influence the outcomes of ARDS patients. Thirdly, our study it was had a single-center, retrospective design; thus, so the results of the present study still required further validation by using external datasets. Despite our careful propensity score matching, residual confounding factors cannot be fully excluded. Therefore, the risk of confounding factors should be taken into account for when interpreting the results interpreting.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe use of NMBAs was not associated with reduced 28-day and or 90-day mortality and may prolong the duration of ventilation duration and length of ICU stay. Due to their many side effects, we should use NMBAs with caution.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMing He and Xiaojun Pan designed the study, collected and analyzed the data, and contributed to the writing of this manuscript. You Wu and Xiaojun Pan designed and supervised the study and drafted the manuscript. All authors have read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: This work was supported by the National Natural Science Foundation of China (Grant grant No. 82302477, 82302423)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e: The datasets used in the present study are available from the first author and corresponding authors upon reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e: The MIMIC III database used in the present study was approved by the Institutional Review Boards (IRB) of the Massachusetts Institute of Technology and does not contain protected health information.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e: Not applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e: The authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFan E, Brodie D, Slutsky AS. 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Multisociety Consensus Quality Improvement Revised Consensus Statement for Endovascular Therapy of Acute Ischemic Stroke. Int J Stroke. 2018;13(6):612-632. \u003c/li\u003e\n\u003cli\u003eVerheij J, van Lingen A, Raijmakers PG, Rijnsburger ER, Veerman DP, Wisselink W, et al. Effect of fluid loading with saline or colloids on pulmonary permeability, oedema and lung injury score after cardiac and major vascular surgery. Br J Anaesth. 2006;96(1):21-30. \u003c/li\u003e\n\u003cli\u003eMargarido CB, Margarido NF, Otsuki DA, Fantoni DT, Marumo CK, Kitahara FR, et al. Pulmonary function is better preserved in pigs when acute normovolemic hemodilution is achieved with hydroxyethyl starch versus lactated Ringer\u0026apos;s solution. Shock. 2007;27(4):390-6. \u003c/li\u003e\n\u003cli\u003eHuang CC, Kao KC, Hsu KH, Ko HW, Li LF, Hsieh MJ, et al. Effects of hydroxyethyl starch resuscitation on extravascular lung water and pulmonary permeability in sepsis-related acute respiratory distress syndrome. 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J Clin Invest. 2018;128(3):1074-1086. \u003c/li\u003e\n\u003cli\u003eAlbertine KH, Soulier MF, Wang Z, Ishizaka A, Hashimoto S, Zimmerman GA, et al. Fas and fas ligand are up-regulated in pulmonary edema fluid and lung tissue of patients with acute lung injury and the acute respiratory distress syndrome. Am J Pathol. 2002;161(5):1783-96. \u003c/li\u003e\n\u003cli\u003eMatthay MA, Ware LB, Zimmerman GA. The acute respiratory distress syndrome. J Clin Invest. 2012;122(8):2731-40. \u003c/li\u003e\n\u003cli\u003eMillar FR, Summers C, Griffiths MJ, Toshner MR, Proudfoot AG. The pulmonary endothelium in acute respiratory distress syndrome: insights and therapeutic opportunities. Thorax. 2016;71(5):462-73. \u003c/li\u003e\n\u003cli\u003eVillar J, Schultz MJ, Kacmarek RM. The LUNG SAFE: a biased presentation of the prevalence of ARDS! Crit Care. 2016;20(1):108. \u003c/li\u003e\n\u003cli\u003eMadotto F, Pham T, Bellani G, Bos LD, Simonis FD, Fan E, et al. Resolved versus confirmed ARDS after 24 h: insights from the LUNG SAFE study. Intensive Care Med. 2018;44(5):564-577. \u003c/li\u003e\n\u003cli\u003eGarcia-Martinez R, Caraceni P, Bernardi M, Gines P, Arroyo V, Jalan R. Albumin: pathophysiologic basis of its role in the treatment of cirrhosis and its complications. Hepatology. 2013;58(5):1836-46. \u003c/li\u003e\n\u003cli\u003eQiao R, Siflinger-Birnboim A, Lum H, Tiruppathi C, Malik AB. Albumin and Ricinus communis agglutinin decrease endothelial permeability via interactions with matrix. Am J Physiol. 1993;265(2 Pt 1):C439-46. \u003c/li\u003e\n\u003cli\u003eLoban A, Kime R, Powers H. Iron-binding antioxidant potential of plasma albumin. Clin Sci (Lond). 1997;93(5):445-51. \u003c/li\u003e\n\u003cli\u003eCantin AM, Paquette B, Richter M, Larivee P. Albumin-mediated regulation of cellular glutathione and nuclear factor kappa B activation. Am J Respir Crit Care Med. 2000;162(4 Pt 1):1539-46. \u003c/li\u003e\n\u003cli\u003eLang JD, Jr., Figueroa M, Chumley P, Aslan M, Hurt J, Tarpey MM, et al. Albumin and hydroxyethyl starch modulate oxidative inflammatory injury to vascular endothelium. Anesthesiology. 2004;100(1):51-8. \u003c/li\u003e\n\u003cli\u003eMargarson MP, Soni NC. Effects of albumin supplementation on microvascular permeability in septic patients. J Appl Physiol (1985). 2002;92(5):2139-45. \u003c/li\u003e\n\u003cli\u003eFinfer S, Bellomo R, Boyce N, French J, Myburgh J, Norton R, et al. A comparison of albumin and saline for fluid resuscitation in the intensive care unit. N Engl J Med. 2004;350(22):2247-56. \u003c/li\u003e\n\u003cli\u003eAwad S, Dharmavaram S, Wearn CS, Dube MG, Lobo DN. Effects of an intraoperative infusion of 4% succinylated gelatine (Gelofusine(R)) and 6% hydroxyethyl starch (Voluven(R)) on blood volume. Br J Anaesth. 2012;109(2):168-76. \u003c/li\u003e\n\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":"Albumin, Acute respiratory distress syndrome, eICU, MIMIC-III Database, 28-day mortality","lastPublishedDoi":"10.21203/rs.3.rs-6948848/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6948848/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAlthough early administration of albumin has been shown to improve oxygenation and maintain hemodynamic stability in patients with acute respiratory distress syndrome (ARDS), whether the addition therapy of albumin can improve the outcome of ARDS patient was still unknow. Therefore, this study aims to evaluate the efficacy of early albumin therapy in ARDS patients diagnosed according to the Berlin definition. We conducted a multicenter, retrospective study utilizing data from the eICU Collaborative Research Database and the MIMIC-III Database. Inverse probability of treatment weighting (IPTW) and propensity score matching were implemented to further adjust for confounding variables between the groups. Cox proportional hazards models were applied to estimate the association between albumin administration within 48 hours of admission and 28-day mortality in patients with ARDS. Kaplan\u0026ndash;Meier survival curves were constructed, and the log-rank test was employed to assess the association between 28-day mortality and albumin therapy in the two groups. Following a review of over 200,000 subjects from the eICU database, 3,371 eligible patients with ARDS were identified according to the inclusion and exclusion criteria. The albumin therapy was not associated with 28-day mortality (HR, 1.12; 95% CI, 0.76\u0026ndash;1.67; P\u0026thinsp;=\u0026thinsp;0.6) in the IPTW cohort and was also not associated with 28-day mortality (HR, 0.88; 95% CI, 0.62\u0026ndash;1.24; P\u0026thinsp;=\u0026thinsp;0.5) in the PSM cohort in eICU database. Moreover, the albumin therapy was not associated with 28-day mortality (HR, 1.12; 95% CI, 0.76\u0026ndash;1.67; P\u0026thinsp;=\u0026thinsp;0.6) in the IPTW cohort and was not associated with 28-day mortality (HR, 0.95; 95% CI, 0.65\u0026ndash;1.38; P\u0026thinsp;=\u0026thinsp;0.8) in the PSM cohort in MIMIC-III database. In conclusion, our findings suggested that ARDS patients receiving albumin therapy did not improve the outcomes. Using albumin treatment may lead to albumin leakage when the damaged endothelial cells cause severe leakage of capillaries may even aggravate tissue edema and thus prolong the hospital stay, ICU stay, and mechanical ventilation duration.\u003c/p\u003e","manuscriptTitle":"Albumin in patients with ARDS in ICU: a retrospective study from eICU and MIMIC-III database","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-28 07:54:17","doi":"10.21203/rs.3.rs-6948848/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":"16de404b-40c1-469d-bbc4-fffe031e3278","owner":[],"postedDate":"July 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-18T10:54:21+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-28 07:54:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6948848","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6948848","identity":"rs-6948848","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}