Prognostic Value of Statins in Critically Ill Patients with Acute Myocardial Infarction-Related Acute Kidney Injury: A Retrospective Cohort Study Based on the MIMIC-IV Database

Prognostic Value of Statins in Critically Ill Patients with Acute Myocardial Infarction-Related Acute Kidney Injury: A Retrospective Cohort Study Based on the MIMIC-IV 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 Prognostic Value of Statins in Critically Ill Patients with Acute Myocardial Infarction-Related Acute Kidney Injury: A Retrospective Cohort Study Based on the MIMIC-IV Database Liying Luo, Mingliu Li, Jiahui Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9118734/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background: Acute Kidney Injury (AKI) is a common complication in critically ill patients with Acute Myocardial Infarction (AMI) and is strongly associated with poor prognosis. Statins are widely used for cardiovascular protection, but their effect on AKI remains uncertain. This study aims to investigate the association between statin therapy and the prognosis of critically ill patients with myocardial infarction-related acute kidney injury (AMI-AKI), providing evidence-based support for clinical decision-making. Methods: AMI-AKI patients were extracted from the MIMIC-IV database and divided into a statin group and a non-statin group based on statin use during their intensive care unit (ICU) stay. The primary outcome was 28-day mortality, and secondary outcomes included 90-day mortality, in-hospital mortality, and ICU mortality. Propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) were used to balance baseline differences between groups. Cox proportional hazards models and logistic regression models assessed the association of statin use, statin type, and statin dosage with clinical outcomes. Survival analysis was performed using Kaplan-Meier curves and Log-rank tests, and subgroup analyses were conducted to explore effect heterogeneity. Results: A total of 3,844 AMI-AKI patients were included, of whom 72.6% received statin therapy during their ICU stay. Multivariable model results showed that statin use was significantly associated with reduced risks of 28-day mortality (HR = 0.621, 95% CI : 0.529-0.729), 90-day mortality (HR = 0.710, 95% CI : 0.617-0.816), in-hospital mortality (OR = 0.612, 95% CI : 0.489-0.767), and ICU mortality (OR = 0.535, 95% CI : 0.414-0.691). These associations remained significant after PSM and IPTW adjustments. Patients receiving simvastatin and standard-dose therapy showed the greatest reduction in mortality. Subgroup analysis revealed that the protective effect of statins was particularly pronounced in patients with AKI stage 3, age ≤65 years, those not using antiplatelet drugs, those without concomitant chronic heart failure (CHF), those undergoing coronary artery bypass grafting (CABG), or those receiving beta-blockers. Conclusion: Statin therapy is significantly associated with lower mortality risk in AMI-AKI patients, particularly with simvastatin and standard-dose strategies. This study supports integrating statins into the comprehensive treatment for critically ill AMI-AKI patients to improve clinical outcomes. Acute myocardial infarction Acute kidney injury Statins Propensity score matching Inverse probability of treatment weighting Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Acute myocardial infarction (AMI) is a critical condition resulting from thrombotic occlusion due to coronary plaque rupture or erosion, leading to myocardial ischemic hypoxia injury and necrosis. It can be classified into ST-segment elevation myocardial infarction (STEMI), caused by complete coronary artery occlusion, and non-ST-segment elevation myocardial infarction (NSTEMI), caused by partial or intermittent occlusion. Epidemiological data indicate that the prevalence of AMI is as high as 23.3%, with a mortality rate ranging from 7% to 10%, making it a significant cause of death among patients in intensive care unit (ICU) [ 1 ] . Acute kidney injury (AKI), a common complication in hospitalized patients with AMI, occurs in 12.1% to 55.6% of cases [ 2 ] . Its pathogenesis involves multiple pathophysiological processes, including ischemia-reperfusion injury, oxidative stress, inflammation, and nephrotoxicity [ 3 – 6 ] . AKI is an independent risk factor affecting both short-term and long-term prognosis in AMI patients, and mortality in patients with concomitant AKI is more than 10 times higher than in those without [ 7 ] . Therefore, strengthening clinical intervention for AKI following AMI is particularly urgent. Statins, or 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors, are widely used for the primary and secondary prevention of cardiovascular events due to their established lipid-lowering efficacy [ 8 ] . Their pleiotropic effects, including anti-inflammatory, immunomodulatory, and antioxidant activities, have expanded their potential applications in other diseases [ 9 – 11 ] . Studies have shown that statins significantly reduce cardiac and all-cause mortality in patients with AMI [ 12 ] , and multiple studies have also suggested their ability to lower the risk of developing AKI [ 13 – 15 ] . Furthermore, a retrospective study by Tang et al. involving 5,376 patients with chronic kidney disease (CKD) reported that statin users had a 55% lower risk of in-hospital mortality compared with non-users [ 16 ] . A retrospective study by Zheng et al. involving 2,034 patients with AKI also confirmed that statin use was significantly associated with reduced in-hospital mortality, although this association was only statistically significant in the atorvastatin subgroup [ 17 ] . However, conflicting findings exist: a large cohort study of 43,438 patients reported that statin users had a 30% increased risk of developing AKI compared to non-users [ 18 ] . Similarly,a study by Wang et al. observed no significant improvement in prognosis with statin use in patients with severe AKI associated with sepsis [ 19 ] . Currently, research on the impact of statins on short-term and long-term outcomes in AMI patients complicated by AKI remains limited. Given the contradictory nature of the existing evidence and the lack of specific clinical guidelines for statin therapy in this particular patient population, this study utilized real-world data to systematically evaluate the association between statin therapy and clinical outcomes in AMI patients with concomitant AKI, aiming to provide refined, evidence-based support for clinical pharmacotherapy in this group. 2. Methods 2.1Data Source Data for this study were obtained from the publicly available Medical Information Mart for Intensive Care IV (MIMIC-Ⅳ-2.2) database, which contains clinical information on critically ill patients admitted to the Beth Israel Deaconess Medical Center between 2008 and 2019. All patient information in the database has been de-identified to protect privacy; therefore, this study was granted an exemption for ethical approval and the requirement for informed consent was waived. One of the authors (Jiahui Li) completed the Collaborative Institutional Training Initiative (CITI) program and passed the relevant examinations (Certification No.: 10125720) to obtain access to the database. 2.2 Inclusion and Exclusion Criteria Patients diagnosed with AMI were identified using the International Classification of Diseases (ICD) code 9/10 (see Supplementary Table 1). Among these patients, those who developed AKI during their ICU stay were included. AKI was defined according to the Kidney Disease Improving Global Outcomes (KDIGO) criteria [ 20 ] : an increase in serum creatinine (SCr) by ≥ 0.3 mg/dL (26.5 µmol/L) within 48 hours, or an increase in SCr to ≥ 1.5 times baseline within 7 days, or urine output ≤ 0.5 mL/(kg·h) for 6 hours. Exclusion criteria were as follows: (1) patients with multiple ICU admissions, only the first ICU admission was included; (2) patients aged < 18 years; and(3) ICU stay duration < 24 h (discharged or death). 2.3 Data Extraction Clinical data during hospitalization were extracted from the MIMIC-IV-2.2 database using the database management tool Navicat Premium (version 16.3.7) via Structured Query Language (SQL). The extracted variables included: (1) Demographic information: age, sex, race, weight, height, insurance type, smoking history, and alcohol consumption history; (2) Vital signs measured within the first 24 hours of ICU admission: heart rate, respiratory rate, systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), peripheral oxygen saturation (SpO₂), and urine output; (3) Laboratory parameters measured within the first 24 hours of ICU admission: white blood cell (WBC) count, platelet count, blood glucose, hemoglobin, blood urea nitrogen (BUN), creatinine, red cell distribution width (RDW), anion gap, lactate, international normalized ratio (INR), activated partial thromboplastin time (APTT), potassium, sodium, calcium, and troponin T (TNT); (4) Comorbidities: hypertension, congestive heart failure (CHF), peripheral vascular disease (PVD), cerebrovascular disease (CVD), chronic pulmonary disease, chronic kidney disease (CKD), malignancy, liver disease, diabetes, obesity, and hyperlipidemia; (5) Disease severity scores: Sequential Organ Failure Assessment (SOFA), Simplified Acute Physiology Score II (SAPS II), Oxford Acute Severity of Illness Score (OASIS), and Charlson Comorbidity Index (CCI); (6) Therapeutic interventions within 48 hours of ICU admission: mechanical ventilation, vasopressors, coronary artery bypass grafting (CABG), percutaneous coronary intervention (PCI), and continuous renal replacement therapy (CRRT); (7) Medications administered within 48 hours of ICU admission: beta-blockers, antiplatelet agents, angiotensin-converting enzyme inhibitors (ACEI), and angiotensin II receptor blockers (ARB); and(8) Outcome variables: 28-day mortality, 90-day mortality, in-hospital mortality, and ICU mortality. For missing data (covariate missingness is illustrated in Supplementary Fig. 1), variables with a missing rate exceeding 20% were excluded. Variables with a missing rate below 20% were imputed using Multiple Imputation by Chained Equations (MICE), generating five imputed datasets. After imputation, estimates from the five datasets were pooled according to Rubin's rules to account for the uncertainty associated with missing data. This process was performed using the "mice" package in R software. 2.4 Statin Use Patterns Patients were divided into a non-statin group and a statin group based on their receipt of statin therapy during the ICU stay. Furthermore, the association between different types of statins and mortality was evaluated by examining four commonly used statins: simvastatin, rosuvastatin, pravastatin, and atorvastatin. To further explore the impact of statin dosage on patient mortality, patients were categorized into a standard-dose group and a high-dose group according to the administered statin dose. High-dose statin therapy was defined as a daily dose exceeding the following thresholds: simvastatin 40 mg, rosuvastatin 20 mg, pravastatin 40 mg, and atorvastatin 80 mg [ 21 ] .Patients receiving multiple types of statins or varying doses were excluded to ensure consistency in exposure assessment. 2.5 Clinical Outcomes The primary outcome was 28-day mortality. Secondary outcomes included 90-day mortality, in-hospital mortality, and ICU mortality. 2.6 Statistical Analysis The Shapiro-Wilk test was used to assess the normality of continuous variables. Normally distributed data are presented as mean ± standard deviation (SD) and were compared using the independent samples t-test. Non-normally distributed data are expressed as median (interquartile range, IQR) and were analyzed with the Mann-Whitney U test. Categorical variables, presented as frequencies (percentages), were compared using the chi-square or Fisher's exact test, as appropriate. Based on a directed acyclic graph (DAG), confounding variables requiring adjustment were identified. Only baseline variables influencing both exposure and outcome were included, while post-exposure variables or mediating variables were avoided. To mitigate imbalances in baseline characteristics between the two groups, propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) were employed. Specifically, propensity scores (PS) were calculated using a multivariate logistic regression model incorporating all baseline covariates. A 1:1 nearest neighbor matching algorithm with a caliper width of 0.05 and without replacement was applied to generate a matched cohort with comparable baseline characteristics. Simultaneously, stabilized inverse probability weights based on the PS were used to construct two pseudo-populations, with weights truncated at the 1st and 99th percentiles to control extreme values. The balance of covariates after PSM and IPTW was assessed using standardized mean differences (SMD), with |SMD| < 0.1 indicating adequate balance, and visualized using density plots. Cox proportional hazards regression and logistic regression models were constructed in the original, matched, and weighted cohorts to evaluate the association between statin use and patient mortality. The multivariate model incorporates confounding variables including: demographic information (insurance type, race, sex, age, weight, smoking history, alcohol consumption history), vital signs (heart rate, respiratory rate, MAP, SBP, blood oxygen saturation, urine output), laboratory parameters (WBC, platelet count, hemoglobin, BUN, creatinine, RDW, anion gap, INR, APTT, potassium, sodium, calcium), comorbidities (hypertension, CHF, CVD, chronic pulmonary disease, CKD, malignancy, liver disease, diabetes, obesity, hyperlipidemia),severity scores of the disease(CCI, SOFA, OASIS, SAPS II), therapeutic interventions (mechanical ventilation, vasopressor use, CRRT), and medications (beta-blockers, antiplatelet agents, ACEI, ARB). Multicollinearity among variables was assessed using the variance inflation factor (VIF), and variables with VIF > 10 were excluded. All variables included in the multivariate Cox regression models had VIF < 10 (see Supplementary Fig. 5). Kaplan-Meier survival curves were estimated for 28-day and 90-day survival in the non-statin and statin groups within the original, matched, and weighted cohorts, with differences between groups compared using the log-rank test. In the original cohort, multivariate Cox and logistic regression models were constructed to assess the association between statin type and dosage with mortality, adjusting for the same variables as described above. Finally, subgroup analyses were performed to evaluate the consistency of the association between statin use and 28-day and 90-day mortality across different patient populations. Stratification was based on age (> 65 years or ≤ 65 years), sex (male or female), weight (> 80 kg or ≤ 80 kg), AKI stage (1, 2, or 3), comorbidities (CVD, CKD, CHF, diabetes, hyperlipidemia), therapeutic interventions (mechanical ventilation, vasopressors, CRRT, CABG), and medications (beta-blockers and antiplatelet agents), with interaction terms introduced for testing. All statistical analyses were performed using R software (version 4.5.1). All tests were two-sided, and P < 0.05 was considered statistically significant. 3. Results 3.1 Baseline Characteristics The patient selection process is illustrated in Fig. 1 . A total of 3,844 patients with AMI-AKI meeting the inclusion criteria were enrolled in this study. Among them, 2,792 patients (72.6%) received statin therapy after ICU admission, while 1,052 patients (27.4%) did not receive statins during this period. After PSM adjustment, 899 patients in the statin group and 899 patients in the non-statin group were included. Baseline characteristics of the original cohort are presented in Table 1 . Significant differences in multiple baseline characteristics were observed between the two groups (SMD > 0.1). Specifically, compared to the non-statin group, patients in the statin group had a higher proportion of males and greater body weight. Regarding vital signs, patients receiving statins exhibited relatively higher oxygen saturation and urine output, but lower heart rate and respiratory rate. Laboratory parameters showed that the statin group had relatively higher white blood cell count, hemoglobin, and calcium levels, but lower BUN, creatinine, anion gap and INR. Disease severity scores (including SOFA, OASIS, SAPS II, and CCI) were lower in the statin group compared to the non-statin group. Regarding comorbidities, the statin group had higher proportions of hypertension, chronic pulmonary disease, diabetes, obesity, and hyperlipidemia, but lower proportions of CHF, malignancy, and liver disease. In terms of therapeutic interventions, the number of patients receiving mechanical ventilation on the first day of ICU admission was higher in the statin group, while vasopressor use and CRRT were more common in the non-statin group. Patients in the statin group were more likely to undergo PCI and CABG. Furthermore, the proportion of patients receiving beta-blockers, antiplatelet agents, and ACEI was higher in the statin group. Table 1 Baseline characteristics of patients in the non-statin and statin groups in the original cohort Variable Non-statin (N = 1052) Statin (N = 2792) P SMD Demographics Insurance, n(%) 0.121 0.075 Medicare 622 (59.1%) 1554 (55.7%) Medicaid 38 (3.6%) 96 (3.4%) Other 392 (37.3%) 1142 (40.9%) Race, n(%) 0.007 0.125 White 701 (66.6%) 1812 (64.9%) Asian 19 (1.8%) 52 (1.9%) Black 102 (9.7%) 200 (7.2%) Other/Unknown 230 (21.9%) 728 (26.1%) Gender, n(%) < 0.001 0.186 Male 588 (55.9%) 1813 (64.9%) Female 464 (44.1%) 979 (35.1%) AKI stage, n(%) < 0.001 0.199 1 207 (19.7%) 729 (26.1%) 2 487 (46.3%) 1333 (47.7%) 3 358 (34%) 730 (26.1%) Age (years) 74.9 (64.6, 83.9) 72.6 (64.0, 80.9) < 0.001 0.069 Weight (kg) 79.1(66.6, 91.4) 82.5 (69.7, 97.0) < 0.001 0.166 Smoke, n(%) 296 (28.1%) 904 (32.4%) 0.013 0.092 Alcohol, n(%) 38 (3.6%) 73 (2.6%) 0.124 0.057 Vital signs Heart Rate(bpm) 87 (74, 103) 84 (75, 96) < 0.001 0.147 Respiratory Rate (beats/min) 19 (16, 24) 18 (15, 22) < 0.001 0.207 MBP (mmHg) 78 (67, 91) 79 (69, 91) 0.119 0.032 SBP (mmHg) 118 (102, 136) 117 (104, 133) 0.978 0.003 DBP (mmHg) 65 (54, 78) 66 (56, 78) 0.146 0.015 Spo2 (%) 97 (94, 100) 98 (95, 100) < 0.001 0.215 Urine output (ml) 1155 (675, 1905) 1455 (900, 2158) < 0.001 0.183 Laboratory test WBC (K/uL) 11.3 (8.3, 15.7) 12.3 (9, 16.5) < 0.001 0.021 Platelet (K/uL) 194 (137, 265) 190 (141, 248) 0.339 0.043 Glucose (mg/dL) 140 (111, 188) 136 (112, 184) 0.507 0.018 Hemoglobin (g/dL) 10.2 (8.7, 11.9) 10.5 (8.8, 12.3) 0.003 0.114 BUN (mg/dL) 28 (18, 49) 23 (16, 37) < 0.001 0.265 Creatinine (mg/dL) 1.4 (0.9, 2.4) 1.1 (0.9, 1.8) < 0.001 0.153 RDW (%) 15 (13.8, 16.9) 14.2 (13.3, 15.4) < 0.001 0.399 Anion gap (mEq/L) 16 (13, 19) 15 (12, 18) < 0.001 0.255 INR 1.3 (1.2, 1.7) 1.3 (1.1, 1.5) 0.001 0.154 APTT (second) 33.8 (28.2, 49.95) 34.2 (28.8, 52.32) 0.105 0.052 Potassium (mmol/L) 4.3 (3.8, 4.8) 4.3 (3.9, 4.7) 0.462 0.01 Sodium (mmol/L) 138 (135, 141) 138 (136, 141) 0.496 0.025 Cacium (mmol/L) 8.3 (7.8, 8.8) 8.4 (7.9, 8.8) < 0.001 0.118 Comorbidities, n(%) Hypertension 798 (75.9%) 2246 (80.4%) 0.002 0.111 CHF 635 (60.4%) 1578 (56.5%) 0.035 0.078 PVD 185 (17.6%) 479 (17.2%) 0.79 0.011 CVD 177 (16.8%) 435 (15.6%) 0.373 0.034 Chronic pulmonary disease 314 (29.8%) 741 (26.5%) 0.045 0.074 CKD 382 (36.3%) 961 (34.4%) 0.290 0.040 Malignant Cancer 123 (11.7%) 193 (6.9%) < 0.001 0.165 Liver Disease 136 (12.9%) 194 (6.9%) < 0.001 0.201 Diabetes 435 (41.3%) 1289 (46.2%) 0.008 0.097 Obesity 119 (11.3%) 385 (13.8%) 0.048 0.075 Hyperlipidemia 506 (48.1%) 1688 (60.5%) < 0.001 0.250 Clinical scores SOFA score 6 (3, 9) 5 (3, 8) < 0.001 0.178 OASIS score 34 (28, 41) 33 (28, 39) 0.006 0.115 SAPS II score 41 (32, 52) 39 (31, 48) < 0.001 0.205 CCI 7 (5, 9) 7 (5, 8) < 0.001 0.207 Treatment, n(%) Mechanical ventilation 855(81.3%) 2405 (86.1%) < 0.001 0.132 Vasopressin 127 (12.1%) 232 (8.3%) < 0.001 0.125 CRRT 172 (16.3%) 330 (11.8%) < 0.001 0.131 PCI 43(4.1%) 240 (8.6%) < 0.001 0.186 CABG 13(1.2%) 499 (17.9%) < 0.001 0.590 Medications, n(%) Beta-blockers 514 (48.9%) 1799 (64.4%) < 0.001 0.318 Antiplatelet 421 (40%) 2244 (80.4%) < 0.001 0.905 ACEI 117 (11.1%) 424 (15.2%) 0.001 0.120 ARB 27 (2.6%) 89 (3.2%) 0.369 0.037 Abbreviations : AKI, Acute Kidney Injury; SBP, Systolic Blood Pressure; DBP, Diastolic Blood Pressure; MBP, Mean Blood Pressure; Spo2, Peripheral Capillary Oxygen Saturation; WBC, White Blood Cell; BUN, Blood Urea Nitrogen; RDW, Red Blood Cell Distribution Width; INR,International Normalized Ratio; APTT, Activated Partial Thromboplastin Time; CHF, Congestive Heart Failure; PVD, Peripheral Vascular Disease; CVD, Cerebrovascular Disease; CKD, Chronic Kidney Disease; SOFA score, Sequential Organ Failure Assessment score; OASIS score, Oxford Acute Severity of Illness Score; SAPS II score, Simplified Acute Physiology Score II; CCI, Charlson Comorbidity Index; CRRT, Continuous Renal Replacement Therapy; PCI, Percutaneous Coronary Intervention; CABG, Coronary Artery Bypass Grafting; ACEI, Angiotensin-Converting Enzyme Inhibitor; ARB, Angiotensin II Receptor Blocker; HR, hazard ratio; OR, Odds Ratio; CI, confidence interval; SMD, Standardized Mean Difference. After PSM and IPTW adjustments(baseline characteristics of the two groups are shown in Table 2 ),in the matched cohort, baseline characteristics were well-balanced between the groups (all P > 0.05 and SMD 0.05 and SMD < 0.1), with the exception of CABG (P < 0.001; SMD = 0.340). Therefore, CABG was included as a confounding variable in the Cox and logistic regression models for the weighted cohort. Table 2 Baseline characteristics and SMD of patients after PSM and IPTW Variable PSM IPTW Non-statin (N = 899) Statin (N = 899) P SMD Non-statin (N = 729.6) Statin (N = 2499.6) P SMD Demographics Insurance, n(%) 0.869 0.009 0.868 0.0 23 Medicare 531 (59.7%) 520 (58.5%) 421 (57.7%) 1419 (56.8%) Medicaid 30 (3.4%) 31 (3.5%) 25 (3.5%) 84 (3.4%) Other 328 (36.9%) 338 (38%) 283 (38.8%) 997 (39.9%) Race, n(%) 0.530 0.009 0.448 0.0 38 White 582 (65.5%) 580 (65.2%) 490 (67.1%) 1642 (65.7%) Asian 16 (1.8%) 10 (1.1%) 11 (1.5%) 43 (1.7%) Black 88 (9.9%) 81 (9.1%) 64 (8.7%) 192 (7.7%) Other/Unknown 203 (22.8%) 218 (24.5%) 165 (22.7%) 623 (24.9%) Gender, n(%) 0.596 0.017 0.170 0.0 58 Male 515 (57.9%) 527 (59.3%) 435 (59.6%) 1560 (62.4%) Female 374 (42.1%) 362 (40.7%) 295 (40.4%) 940 (37.6%) AKI stage, n(%) 0.281 0.021 0.103 0.0 61 1 179 (20.1%) 199 (22.4%) 152 (20.9%) 614 (24.6%) 2 433 (48.7%) 401 (45.1%) 364 (49.8%) 1168 (46.7%) 3 277 (31.2%) 289 (32.5%) 214 (29.3%) 717 (28.7%) Age (years) 75.1 (64.9, 83.5) 73.1 (64.6, 82.2) 0.116 0.000 75.1 (65.9, 83.5) 72.8 (64.3, 81.4) 0.14 0.0 62 Weight (kg) 79.6 (67.6, 92.0) 80.4 (68.0, 95.0) 0.242 0.025 80.4 (68.9, 94.0) 81.7 (68.5, 96.2) 0.355 0.0 41 Smoke, n(%) 275 (30.9%) 253 (28.5%) 0.276 0.012 230 (31.5%) 783 (31.3%) 0.931 0.0 03 Alcohol, n(%) 29 (3.3%) 24 (2.7%) 0.577 0.007 21 (2.9%) 70 (2.8%) 0.83 0.0 09 Vital signs Heart Rate (bpm) 87 (73, 102) 86 (75, 100) 0.935 0.003 86 (73, 100) 85 (75, 97) 0.676 0.0 17 Respiratory Rate (beats/min) 19 (16, 23) 19 (15, 24) 0.869 0.011 19 (15, 23) 18 (15, 23) 0.211 0.0 50 MBP (mmHg) 79 (67, 91) 79 (69, 91) 0.787 0.005 79 (68, 92) 79 (69, 91) 0.562 0.0 21 SBP (mmHg) 119 (103, 136) 118 (104, 135) 0.875 0.003 119 (103, 136) 117 (104, 134) 0.326 0.0 39 DBP (mmHg) 65 (54, 78) 66 (56, 78) 0.47 0.005 66 (55, 80) 66 (56, 78) 0.498 0.0 26 Spo2 (%) 98 (95, 100) 98 (95, 100) 0.113 0.038 98 (95, 100) 98 (95, 100) 0.323 0.0 37 Urineoutput (ml) 1285 (740, 2045) 1315 (785, 2125) 0.184 0.038 1330 (780, 2075) 1400 (845, 2122) 0.495 0.0 33 Laboratory test WBC (K/uL) 11.3 (8.4, 15.5) 12.2 (8.8, 16.8) 0.006 0.036 11.3 (8.6, 15.8) 12.2 (8.8, 16.5) 0.8 0.0 09 Platelet (K/uL) 198 (142, 263) 199 (144, 259) 0.916 0.012 197 (144, 261) 192 (142, 252) 0.21 0.0 49 Glucose (mg/dL) 140 (113, 190) 140 (112, 192) 0.889 0.007 140 (114, 189) 137 (111, 185) 0.375 0.0 38 Hemoglobin (g/dL) 10.3 (8.7, 12) 10.3 (8.7, 12.1) 0.684 0.006 10.5 (8.9, 12.3) 10.5 (8.8, 12.3) 0.767 0.011 BUN (mg/dL) 27 (18, 48) 26 (18, 43) 0.169 0.032 25 (18, 44) 24 (17, 40) 0.245 0.0 45 Creatinine (mg/dL) 1.4 (0.9, 2.3) 1.3 (0.9, 2) 0.028 0.026 1.2 (0.9, 2.1) 1.2 (0.9, 1.9) 0.661 0.0 21 RDW (%) 14.8 (13.7, 16.5) 14.6 (13.6, 16.0) 0.042 0.033 14.6 (13.5, 16.1) 14.3 (13.4, 15.7) 0.076 0.0 72 Anion gap (mEq/L) 16 (13, 19) 15 (13, 19) 0.316 0.024 15 (13, 18) 15 (12, 18) 0.141 0.0 63 INR 1.3 (1.1, 1.6) 1.3 (1.1, 1.6) 0.888 0.028 1.3 (1.1, 1.6) 1.3 (1.1, 1.5) 0.545 0.0 21 APTT (second) 33.9 (28, 51.6) 34 (28.3, 52.1) 0.602 0.011 34.4 (28.2, 53.5) 34 (28.6, 50.9) 0.632 0.0 19 Potassium (mmol/L) 4.3 (3.8, 4.7) 4.2 (3.8, 4.7) 0.856 0.015 4.3 (3.9, 4.7) 4.3 (3.9, 4.7) 0.576 0.0 20 Sodium (mmol/L) 138 (135, 141) 139 (136, 141) 0.556 0.012 138 (135, 141) 138 (136, 141) 0.717 0.0 10 Calcium (mmol/L) 8.3 (7.8, 8.8) 8.4 (7.8, 8.8) 0.959 0.000 8.4 (7.9, 8.8) 8.4 (7.9, 8.8) 0.687 0.0 10 Comorbidities, n(%) Hypertension 697 (78.4%) 680 (76.5%) 0.364 0.015 575 (78.8%) 1988 (79.5%) 0.660 0.0 19 CHF 536 (60.3%) 531 (59.7%) 0.846 0.007 439 (60.1%) 1443 (57.7%) 0.247 0.0 49 PVD 158 (17.8%) 162 (18.2%) 0.853 0.002 134 (18.4%) 430 (17.2%) 0.448 0.0 31 CVD 158 (17.8%) 152 (17.1%) 0.755 0.016 128 (17.5%) 405 (16.2%) 0.410 0.035 Chronic Pulmonary Disease 255 (28.7%) 249 (28%) 0.792 0.004 211 (28.9%) 685 (27.4%) 0.418 0.0 34 CKD 332 (37.3%) 323 (36.3%) 0.694 0.024 256 (35.1%) 873 (34.9%) 0.941 0.0 04 Malignant Cancer 87 (9.8%) 90 (10.1%) 0.874 0.000 64 (8.8%) 204 (8.1%) 0.549 0.0 23 Liver Disease 92 (10.3%) 86 (9.7%) 0.693 0.004 65 (8.9%) 209 (8.4%) 0.638 0.0 19 Diabetes 377 (42.4%) 388 (43.6%) 0.632 0.002 320 (43.9%) 1121 (44.8%) 0.658 0.0 19 Obesity 98 (11%) 107 (12%) 0.552 0.009 87 (11.9%) 324 (13.0%) 0.472 0.0 32 Hyperlipidemia 460 (51.7%) 466 (52.4%) 0.812 0.018 399 (54.7%) 1437 (57.5%) 0.172 0.0 59 Clinical scores SOFA score 5 (3, 8) 5 (3, 8) 0.487 0.012 5 (3, 8) 5 (3, 8) 0.888 0.0 03 OASIS score 34 (27, 40) 35 (28, 40) 0.168 0.006 34 (27, 40) 34 (28, 39) 0.751 0.0 15 SAPS II score 40 (31, 51) 41 (33, 51) 0.383 0.008 40 (31, 50) 40 (32, 49) 0.448 0.0 34 CCI 7 (5, 9) 7 (5, 9) 0.926 0.008 7 (5, 9) 7 (5, 9) 0.078 0.0 73 Treatment, n(%) Mechanical Ventilation 729 (82%) 733 (82.5%) 0.852 0.001 612 (83.8%) 2121 (84.9%) 0.476 0.0 29 Vasopressin 88 (9.9%) 84 (9.4%) 0.810 0.017 69 (9.5%) 229 (9.2%) 0.801 0.0 11 CRRT 133 (15%) 124 (13.9%) 0.590 0.017 94 (12.8%) 321 (12.8%) 0.996 0.0 03 PCI 43 (4.8%) 42 (4.7%) 1.000 0.014 53 (7.2%) 184 (7.4%) 0.908 0.0 06 CABG 13 (1.5%) 15 (1.7%) 0.849 0.011 28 (3.9%) 334 (13.4%) < 0.001 0.3 40 Medications, n(%) Beta-blockers 472 (53.1%) 481 (54.1%) 0.704 0.032 414 (56.8%) 1509 (60.4%) 0.080 0.0 76 Antiplatelet 421 (47.4%) 425 (47.8%) 0.887 0.015 479 (65.7%) 1741 (69.7%) 0.029 0.0 91 ACEI 111 (12.5%) 108 (12.1%) 0.885 0.007 108 (14.7%) 355 (14.2%) 0.734 0.0 15 ARB 25 (2.8%) 17 (1.9%) 0.274 0.033 18 (2.4%) 72 (2.9%) 0.487 0.0 28 Abbreviations : AKI, Acute Kidney Injury; SBP, Systolic Blood Pressure; DBP, Diastolic Blood Pressure; MBP, Mean Blood Pressure; Spo2, Peripheral Capillary Oxygen Saturation; WBC, White Blood Cell; BUN, Blood Urea Nitrogen; RDW, Red Blood Cell Distribution Width; INR,International Normalized Ratio; APTT, Activated Partial Thromboplastin Time; CHF, Congestive Heart Failure; PVD, Peripheral Vascular Disease; CVD, Cerebrovascular Disease; CKD, Chronic Kidney Disease; SOFA score, Sequential Organ Failure Assessment score; OASIS score, Oxford Acute Severity of Illness Score; SAPS II score, Simplified Acute Physiology Score II; CCI, Charlson Comorbidity Index; CRRT, Continuous Renal Replacement Therapy; PCI, Percutaneous Coronary Intervention; CABG, Coronary Artery Bypass Grafting; ACEI, Angiotensin-Converting Enzyme Inhibitor; ARB, Angiotensin II Receptor Blocker; HR, hazard ratio; OR, Odds Ratio; CI, confidence interval; SMD, Standardized Mean Difference. 3.2 Directed Acyclic Graph Analysis Results DAG was constructed to identify confounders and mediators in the association between statin use and mortality (see Fig. 2 ). Confounders identified included: age, alcohol consumption history, smoking history, comorbidities (hypertension, CHF, PVD, CVD, chronic pulmonary disease, CKD, malignancy, diabetes, liver disease, obesity, and hyperlipidemia), and disease severity scores (SOFA, SAPS II, OASIS, and CCI). Relevant variables included: vital signs (heart rate, respiratory rate, SBP, DBP, MAP, oxygen saturation, urine output), laboratory parameters (WBC, platelet count, blood glucose, hemoglobin, BUN, creatinine, RDW, anion gap, INR, APTT, potassium, sodium, calcium), therapeutic interventions (mechanical ventilation, vasopressors, CRRT, PCI, CABG), and medications (beta-blockers, antiplatelet agents, ACEI, ARB). No mediators were identified. Confounders were required to be included in the regression models. Furthermore, as relevant variables may also act as confounders, they were considered for inclusion in the models. 3.3 Association Between Statin Use and Patient Mortality In unadjusted models, statin use was significantly associated with a reduced risk of 28-day mortality (HR = 0.446, 95% CI : 0.387–0.514, P < 0.001), 90-day mortality (HR = 0.491, 95% CI : 0.433–0.556, P < 0.001), in-hospital mortality (OR = 0.407, 95% CI : 0.342–0.484, P < 0.001), and ICU mortality (OR = 0.388, 95% CI : 0.319–0.471, P < 0.001). In multivariable-adjusted models, compared to the non-statin group, patients in the statin group exhibited a 37.9% reduction in 28-day mortality, a 29.0% reduction in 90-day mortality, a 38.8% reduction in in-hospital mortality, and a 46.5% reduction in ICU mortality. The significant protective effect of statins was consistently observed in both the matched and weighted cohorts (see Fig. 3 ). 3.4 Kaplan-Meier Survival Curves In the original cohort, patients with AMI-AKI in the statin group demonstrated significantly higher 28-day and 90-day survival rates compared to those in the non-statin group (P < 0.001; Fig. 4 A, B). The survival curves for the matched cohort (Fig. 4 C, D) and the weighted cohort (Fig. 4 E, F) were consistent with those of the original cohort (all P < 0.05). 3.5 Association of Statin Type and Dosage with Patient Mortality After applying the exclusion criteria, 2,593 patients were identified as having received a single type and dosage of statin therapy. The distribution of statin use was as follows: simvastatin (n = 247), rosuvastatin (n = 163), pravastatin (n = 91), and atorvastatin (n = 2,092). Table 3 shows the association between different types of statins and mortality. Compared with the non-statin group, the use of simvastatin and atorvastatin was significantly associated with lower mortality among patients with AMI-AKI. Specifically, patients receiving simvastatin exhibited a 54.5% reduction in 28-day mortality (HR = 0.455, 95% CI : 0.315–0.658, P < 0.001), a 42.7% reduction in 90-day mortality (HR = 0.573, 95% CI : 0.425–0.772, P < 0.001), a 60.5% reduction in in-hospital mortality (OR = 0.395, 95% CI : 0.242–0.645, P < 0.001), and a 71.1% reduction in ICU mortality (OR = 0.289, 95% CI : 0.157–0.534, P < 0.001). Atorvastatin also demonstrated a significant protective effect, with reductions of 36.1%, 27.6%, 39.1%, and 35.4% in 28-day, 90-day, ICU, and in-hospital mortality, respectively. However, no significant association with reduced mortality was observed for rosuvastatin or pravastatin (all P > 0.05). Table 3 Association of different statin types with patient mortality 28-day mortality 90-day mortality In-Hospital mortality ICU mortality HR (95%Cl) P HR (95%Cl) P OR (95%Cl) P OR (95%Cl) OR (95%Cl) No statin Reference Reference Reference Reference Simvastatin HR 0.455 (0.315, 0.658) < 0.001 HR 0.573 (0.425, 0.772) < 0.001 OR 0.395 ( 0.242, 0.645) < 0.001 OR 0.289 (0.157, 0.534) < 0.001 Rosuvastatin HR 0.734 (0.489, 1.102) 0.136 HR 0.803 (0.562, 1.146) 0.226 OR 0.701 (0.400, 1.226) 0.213 OR 0.397 (0.192, 0.817) 0.012 Pravastatin HR 0.864 (0.525, 1.422) 0.566 HR 0.975 (0.640, 1.486) 0.905 OR 0.941 (0.493, 1.795) 0.853 OR 0.540 (0.230, 1.265) 0.156 Atorvastatin HR 0.639 (0.538, 0.760) < 0.001 HR 0.724 (0.623, 0.842) < 0.001 OR 0.646 (0.507, 0.822) < 0.001 OR 0.609 (0.465, 0.800) < 0.001 Abbreviations : HR, hazard ratio; OR,Odds Ratio; CI, confidence interval. Regarding dosage stratification, 819 patients received standard-dose statin therapy, and 1,774 patients received high-dose statin therapy. As shown in Table 4 , compared to patients in the non-statin group, those receiving standard-dose statin therapy had significantly reduced 28-day (HR = 0.497, 95% CI : 0.397–0.622, P < 0.001), 90-day (HR = 0.612, 95% CI : 0.508–0.736, P < 0.001), in-hospital (OR = 0.457, 95% CI : 0.338–0.618, P < 0.001), and ICU mortality (OR = 0.348, 95% CI : 0.241–0.501, P < 0.001). Similarly, patients receiving high-dose statin therapy also showed significantly reduced risks of 28-day (P < 0.001), 90-day (P = 0.004), in-hospital (P = 0.025), and ICU mortality (P = 0.011). Furthermore, patients with AMI-AKI treated with simvastatin and standard-dose statin therapy exhibited the greatest risk reduction in mortality. Table 4 Association of different statin dosages with patient mortality 28-day mortality 90-day mortality In-hospital mortality ICU mortality HR (95%Cl) P HR (95%Cl) P OR (95%Cl) P OR (95%Cl) P No statin Reference Reference Reference Reference Standard dose HR 0.497 (0.397, 0.622) < 0.001 HR 0.612 (0.508, 0.736) < 0.001 OR 0.457 (0.338, 0.618) < 0.001 OR 0.348 (0.241, 0.501) < 0.001 High dose HR 0.715 (0.597, 0.856) < 0.001 HR 0.795 (0.679, 0.930) 0.004 OR 0.751 (0.584, 0.965) 0.025 OR 0.693 (0.523, 0.920) 0.011 Abbreviations : HR, hazard ratio; OR,Odds Ratio; CI, confidence interval. 3.6 Subgroup Analysis Results In the subgroup analysis, the protective effect of statins remained consistent across most subgroups. Additionally, we evaluated potential effect modification by stratified variables on the association between statin use and mortality. Significant interactions were observed between antiplatelet agents and statin use, as well as between CHF and statin use (P for interaction < 0.05), suggesting that the use of antiplatelet agents attenuated the protective effect of statins, and that the protective effect of statins was more pronounced in patients without CHF. In the analysis of 28-day mortality, significant interactions were found between CABG and statin use, and between beta-blockers and statin use, indicating that patients undergoing CABG or receiving beta-blockers derived greater benefit from statin therapy. For 90-day mortality, a significant interaction was identified between age and statin use (P for interaction < 0.05), suggesting a stronger protective effect of statins in AMI-AKI patients aged ≤ 65 years. Furthermore, although no significant interaction was detected between AKI stage and statin use, a consistently observed pattern across mortality endpoints was that statins did not demonstrate significant benefit in AMI patients with AKI stages 1 or 2; however, the protective effect was more pronounced in patients with AKI stage 3(see Fig. 5 ). 4. Discussion In this large retrospective cohort study utilizing the MIMIC-IV database, we observed that patients with acute myocardial infarction complicated by acute kidney injury (AMI-AKI) who received statin therapy had a significantly reduced risk of mortality. This protective effect remained statistically significant after multivariable adjustment, propensity score matching (PSM), and inverse probability of treatment weighting (IPTW), and was further corroborated by Kaplan-Meier survival curves. Notably, this association was most pronounced in the simvastatin and atorvastatin subgroups, with the greatest reduction in mortality observed in the standard-dose treatment group. Subgroup analyses revealed that the protective effect of statins was more prominent in AMI patients with stage 3 AKI. Furthermore, patients aged ≤ 65 years, those not receiving antiplatelet agents, those without concurrent chronic heart failure (CHF), those undergoing coronary artery bypass grafting (CABG), or those receiving beta-blocker therapy derived greater benefit from statin treatment. 4.1 Potential Mechanisms Underlying the Reduction in Mortality Associated with Statin Use in AMI-AKI Prior to the present study, the association between statin use and prognosis in patients with AMI-AKI had not been investigated. Our study is the first to reveal that statin therapy is significantly associated with reduced mortality risk in this population. The potential protective mechanisms may involve: (1) activation of endothelial nitric oxide synthase (eNOS) in endothelial cells, increasing nitric oxide (NO) production, thereby ameliorating endothelial dysfunction, promoting vasodilation, and improving renal blood flow [ 22 ] ; (2) inhibition of reactive oxygen species (ROS)-generating enzymes (e.g., NADPH oxidase) and upregulation of the expression and activity of ROS-scavenging enzymes (e.g., catalase and superoxide dismutase), consequently reducing ROS generation and mitigating oxidative stress-induced direct damage to renal vascular endothelial cells and tubular epithelial cells [ 23 ] ; (3) synergistic inhibition of NF-κB activation and NLRP3 inflammasome assembly/activation, thereby reducing the production of key inflammatory cytokines such as interleukins (IL-6, IL-1β) and tumor necrosis factor-alpha (TNF-α), and attenuating renal tubular epithelial cell apoptosis, necrosis, and interstitial fibrosis [ 24 ] ; and (4) upregulation of angiotensin-converting enzyme-2(ACE2) expression within the renin-angiotensin-aldosterone system (RAAS), leading to decreased angiotensin II (Ang II) levels and subsequent inhibition of cell proliferation and renal fibrosis [ 25 ] . 4.2 Differential Efficacy of Statin Types and Dosages in Patients with AMI-AKI This study revealed differential protective effects of various statins in patients with AMI-AKI: simvastatin and atorvastatin were associated with significantly reduced mortality, whereas no such benefit was observed for rosuvastatin or pravastatin. These findings are consistent with previous research:A meta-analysis encompassing 143,888 patients with chronic kidney disease (CKD) demonstrated that atorvastatin, simvastatin, and lovastatin reduced the risk of renal failure, while other statins did not exhibit this effect [ 26 ] . A retrospective study by Li et al. involving 5,376 hospitalized patients with CKD also supported that atorvastatin was particularly effective in improving survival and reducing the risk of AKI [ 27 ] . Furthermore, an animal study confirmed that simvastatin promoted renal functional recovery in mice with sepsis-associated AKI (SA-AKI) by regulating anti-apoptotic molecules [ 28 ] . Conversely, rosuvastatin failed to prevent new-onset AKI or slow the progression of mild kidney injury in critically ill patients with acute respiratory distress syndrome (ARDS) and sepsis [ 29 ] .These discrepancies may be attributable to molecular structural differences: lipophilic statins (e.g., atorvastatin, simvastatin) more easily enter into the tissues by passive diffusion, exhibiting enhanc ed "renophilic" and demonstrating superiority over hydrophilic statins in ameliorating renal pathological damage and restoring renal function [ 30 – 31 ] . Dosage stratification analysis indicated that the risk of mortality was significantly reduced in patients receiving either standard-dose or high-dose statin therapy; however, the magnitude of risk reduction was greatest in those receiving standard-dose statins. This finding suggests that, in the maintenance phase of treatment, standard-dose statins may provide adequate protection while being safer, whereas high-dose regimens, though similarly effective, could potentially increase the risk of dose-related adverse effects. 4.3 Subgroup Analysis Subgroup analysis revealed that the protective effect of statins was more pronounced in patients aged ≤ 65 years, those without concurrent CHF, those not receiving antiplatelet agents, and those undergoing CABG or receiving beta-blocker therapy. Specifically, the age-stratified results are consistent with the research of Xiong et al. [ 14 ] , who found that the risk reduction for AKI associated with statin use was more prominent in obese patients with sepsis under 60 years of age, a finding potentially attributable to better baseline organ function and a lower burden of comorbidities in younger patients. Perioperative aspirin use has been shown to increase bleeding risk without reducing the risk of AKI in patients undergoing major non-cardiac surgery [ 32 ] , which may explain why the protective effect of statins in AMI-AKI patients could be attenuated by concomitant antiplatelet therapy. Statins may also trigger the systemic inflammatory response in patients with CHF [ 33 ] , so AMI-AKI patients without CHF may account for more pronounced benefit from statins.Conversely, the protective effect of statins was particularly prominent in patients undergoing CABG or receiving beta-blocker therapy. This finding may be related to the preoperative use of statins improving postoperative renal function following cardiac surgery [ 31 ] and the potential synergistic effects of beta-blockers with statins in conferring renal protection in patients with AMI [ 34 ] . 4.4 Strengths and Limitations This study was based on the publicly available and comprehensive MIMIC database, ensuring relatively high data reliability and integrity. As the first investigation to explore the association between statin therapy and prognosis in patients with AMI-AKI, we provide clear evidence that statin treatment is associated with a significantly reduced risk of mortality in this population, and further evaluate the impact of different statin types and dosages. These findings offer important insights for optimizing treatment strategies in critically ill patients with AMI-AKI and provide practical evidence for clinical decision-making in the ICU. However, this study has several limitations. First, the MIMIC-IV database predominantly comprises a White population; therefore, extrapolation of these findings to other racial or ethnic groups requires caution. Although the sample size was adequate and relatively representative, multicenter prospective studies are warranted to validate the generalizability of these results. Second, as a single-center retrospective study, despite the use of multivariable adjustment, PSM, and IPTW to control for confounding, potential biases cannot be entirely excluded. Prospective studies are needed to further validate the causal relationship and to comprehensively assess the benefits and risks associated with statin therapy in the future. 5. Conclusion Statin therapy was associated with a significantly reduced risk of mortality in patients with AMI-AKI, with more pronounced benefits observed for simvastatin and standard-dose strategies. This study supports the incorporation of statins into the comprehensive therapeutic management of critically ill patients with AMI-AKI to improve clinical outcomes. Abbreviations AKI Acute Kidney Injury AMI Acute Myocardial Infarction PSM Propensity Score Matching IPTW Inverse Probability of Treatment Weighting CABG Coronary Artery Bypass Grafting CHF Congestive Heart Failure STEMI ST-segment elevation myocardial infarction NSTEMI non-ST-segment elevation myocardial infarction HMG-CoA 3-hydroxy-3-methylglutaryl coenzyme A SBP Systolic Blood Pressure DBP Diastolic Blood Pressure MBP Mean Blood Pressure SpO₂ Peripheral Capillary Oxygen Saturation WBC White Blood Cell BUN Blood Urea Nitrogen RDW Red Blood Cell Distribution Width INR International Normalized Ratio APTT Activated Partial Thromboplastin Time TNT Troponin T PVD Peripheral Vascular Disease CVD Cardiovascular Disease CKD Chronic Kidney Disease SOFA Sequential Organ Failure Assessment SAPS II Simplified Acute Physiology Score II OASIS Oxford Acute Severity of Illness Score CCI Charlson Comorbidity Index PCI Percutaneous Coronary Intervention CRRT Continuous Renal Replacement Therapy ACEI Angiotensin-Converting Enzyme Inhibitors ARB Angiotensin II Receptor Blockers HR Hazard Ratio OR Odds Ratio CI Confidence Interval SMD Standardized Mean Difference Declarations Acknowledgements None Author contributions ML: Designed the study, and performed the statistical analysis. LL: Drafted the original manuscript. JL: Conducted data collection, and reviewed-edited the manuscript. All authors approved the final manuscript and are responsible for the content. Funding This research was funded by the National Natural Science Foundation of China (82003609), the Guangdong Basic and Applied Basic Research Foundation (2020A1515110453), Science and Technology Planning Project of Guangzhou (2024A04J4022 ). Clinical trial number Not applicable D ata a vailability The datasets presented in the current study are available in the MIMIC-IV database (https://physionet.org/content/mimiciv/2.2/). All the data generated or analyzed during this study are available upon the corresponding author on reasonable request. Ethics approval and consent to participate This research was conducted in compliance with the Helsinki Declaration’s guidelines. Approval for using the MIMIC-IV database was obtained from the IRBs of both MIT and BIDMC. 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Int J Mol Sci, 2020, 21(19). Hsu RK, Truwit JD, Matthay MA, Levitt JE, Thompson BT, Liu KD. Effect of Rosuvastatin on Acute Kidney Injury in Sepsis-Associated Acute Respiratory Distress Syndrome [J]. Can J Kidney Health Dis. 2018;5:2054358118789158. Jabarpour M, Rashtchizadeh N, Ghorbani Haghjo A, Argani H, Nemati M, Dastmalchi S, et al. Protection of renal damage by HMG-CoA inhibitors: A comparative study between atorvastatin and rosuvastatin [J]. Iran J Basic Med Sci. 2020;23(2):206–13. Wang J, Gu C, Gao M, Yu W, Yu Y. Preoperative Statin Therapy and Renal Outcomes After Cardiac Surgery: A Meta-analysis and Meta-regression of 59,771 Patients [J]. Can J Cardiol. 2015;31(8):1051–60. Garg AX, Kurz A, Sessler DI, Cuerden M, Robinson A, Mrkobrada M, et al. Perioperative aspirin and clonidine and risk of acute kidney injury: a randomized clinical trial [J]. JAMA. 2014;312(21):2254–64. Ahmad F, Karim A, Khan J, Qaisar R. Statin Therapy Induces Gut Leakage and Neuromuscular Disjunction in Patients With Chronic Heart Failure [J]. J Cardiovasc Pharmacol. 2023;82(3):189–95. Queiroz RE, de Oliveira LS, de Albuquerque CA, Santana Cde A, Brasil PM, Carneiro LL, et al. Acute kidney injury risk in patients with ST-segment elevation myocardial infarction at presentation to the ED [J]. Am J Emerg Med. 2012;30(9):1921–7. Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterials.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 23 Apr, 2026 Reviews received at journal 20 Apr, 2026 Reviewers agreed at journal 16 Apr, 2026 Reviewers invited by journal 16 Apr, 2026 Editor invited by journal 16 Mar, 2026 Editor assigned by journal 14 Mar, 2026 Submission checks completed at journal 14 Mar, 2026 First submitted to journal 13 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-9118734","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":627386730,"identity":"ce0af3e5-ece1-4af0-a2f0-5a3b6fce1047","order_by":0,"name":"Liying Luo","email":"","orcid":"","institution":"The First Affiliated Hospital of Jinan University","correspondingAuthor":false,"prefix":"","firstName":"Liying","middleName":"","lastName":"Luo","suffix":""},{"id":627386731,"identity":"79976c77-6d70-4b24-9dbe-e2dad18f1765","order_by":1,"name":"Mingliu Li","email":"","orcid":"","institution":"The First Affiliated Hospital of Jinan University","correspondingAuthor":false,"prefix":"","firstName":"Mingliu","middleName":"","lastName":"Li","suffix":""},{"id":627386732,"identity":"a714c2ea-c7da-4635-9915-08d41c12c2a2","order_by":2,"name":"Jiahui Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYBACPoYzjI9/GPyTk2dvbHz4gRgtbAxnmI0ZKg4YG/YcbjaWIE4LD5s0w5kDiQ030tsEeIjSwnj2mHRh2x3GxpkP2xgkGOzkdBsI2nIu2Xpm2zNmdunEtgcFDMnGZgcI+8XwBm8bMxvj7MR2AwmGA4nbiNBiIAHUwsNw82CbBA+RWoykec4clmC4wUi8FmPDGRVpBoY9icBANiDCL/wSZwwffDCwqZ/Pfvzhww8VdnIEtTBIoKgwIKQcbE0DMapGwSgYBaNgRAMAXCBFCJzprQ4AAAAASUVORK5CYII=","orcid":"","institution":"The First Affiliated Hospital of Jinan University","correspondingAuthor":true,"prefix":"","firstName":"Jiahui","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2026-03-14 01:08:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9118734/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9118734/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107706581,"identity":"2ecaea63-6799-46f1-9812-e1161cc78e1d","added_by":"auto","created_at":"2026-04-24 09:18:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":246287,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlowchart\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations: \u003c/strong\u003eICU, Intensive Care Unit; AMI, Acute Myocardial Infarction; AKI, Acute Kidney\u003c/p\u003e\n\u003cp\u003eInjury; ICD, International Classification of Diseases\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-9118734/v1/35aa6e261dcf4acd95ee20a3.png"},{"id":107658578,"identity":"819b0b39-9b42-430a-87e5-c8b3e0f53ffa","added_by":"auto","created_at":"2026-04-23 16:27:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":252883,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSimplified causal diagram of statin use and mortality\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e SBP, Systolic Blood Pressure; DBP, Diastolic Blood Pressure; MBP, Mean Blood Pressure; Spo2, Peripheral Capillary Oxygen Saturation; WBC, White Blood Cell; BUN, Blood Urea Nitrogen; RDW, Red Blood Cell Distribution Width; INR, International Normalized Ratio; APTT, Activated Partial Thromboplastin Time; CHF, Congestive Heart Failure; PVD, Peripheral Vascular Disease; CVD, Cerebrovascular Disease; CKD, Chronic Kidney Disease; SOFA score, Sequential Organ Failure Assessment score; OASIS score, Oxford Acute Severity of Illness Score; SAPS II score, Simplified Acute Physiology Score II; CCI, Charlson Comorbidity Index; CRRT, Continuous Renal Replacement Therapy; PCI, Percutaneous Coronary Intervention; CABG, Coronary Artery Bypass Grafting; ACEI, Angiotensin-Converting Enzyme Inhibitor; ARB, Angiotensin II Receptor Blocker.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-9118734/v1/0360980838ff9ef60affdd48.png"},{"id":107658579,"identity":"72dbccd0-962c-4941-9b3a-1ab4e924690a","added_by":"auto","created_at":"2026-04-23 16:27:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":529750,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAssociation between statin use and 28-day (A)、90-day (B)、in-hospital (C) and ICU mortality (D) in patients with AMI-AKI.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUnadjusted: without adjustment;\u003c/p\u003e\n\u003cp\u003eMultivariable adjusted: adjusted for demographic information (insurance type, race, sex, age, weight, smoking history, alcohol consumption history), vital signs (heart rate, respiratory rate, MAP, SBP, oxygen saturation, urine output), laboratory parameters (WBC, platelet count, hemoglobin, BUN, creatinine, RDW, anion gap, INR, APTT, potassium, sodium, calcium), comorbidities (hypertension, CHF, CVD, chronic pulmonary disease, CKD, malignancy, liver disease, diabetes, obesity, hyperlipidemia), disease severity scores (CCI, SOFA, OASIS, SAPS II), therapeutic interventions (mechanical ventilation, vasopressor use, CRRT), and medications (beta-blockers, antiplatelet agents, ACEI, ARB).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e HR, hazard ratio; OR,Odds Ratio; CI, confidence interval; PSM, propensity score matching; IPTW, Inverse Probability of Treatment Weighting.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-9118734/v1/9631938f7b92a437b9971fbf.png"},{"id":107706171,"identity":"2b65015a-f602-44d4-9c68-cce6c86e95ea","added_by":"auto","created_at":"2026-04-24 09:17:34","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":604145,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of survival curves of the non-statin and statin groups in the original cohort, after PSM, and after IPTW\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e28-day mortality in the original cohort (A); 90-day mortality in the original cohort(B); 28-day mortality after PSM (C); 90-day mortality after PSM (D); E: 28-day mortality after IPTW (E); \u0026nbsp;90-day mortality after IPTW (F).\u003c/p\u003e\n\u003cp\u003eAbbreviations: PSM, propensity score matching; IPTW, inverse probability of treatment weighting.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-9118734/v1/8250b649262bcaae5ac3cc88.png"},{"id":107658581,"identity":"63b80955-2684-4fc3-ad8d-81e739ebda3d","added_by":"auto","created_at":"2026-04-23 16:27:02","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":640407,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSubgroup analysis of the association between statin use and 28-day (A) and 90-day (B) mortality in patients with AMI-AKI\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003eAKI, Acute Kidney Injury; CHF, Congestive Heart Failure; CVD,Cerebrovascular Disease; CKD, Chronic Kidney Disease; CRRT,Continuous Renal Replacement Therapy; CABG, Coronary Artery Bypass Grafting; HR, hazard ratio.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-9118734/v1/cc46b33fe48b7d0b1bfde995.png"},{"id":107709072,"identity":"fe3e110d-15b4-4232-9644-51261bc865dd","added_by":"auto","created_at":"2026-04-24 09:34:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3318046,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9118734/v1/95fab310-f2d1-4a31-9170-4f674a6c8413.pdf"},{"id":107658577,"identity":"71a576d8-76e7-417d-b268-482dc2465198","added_by":"auto","created_at":"2026-04-23 16:27:02","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1420440,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-9118734/v1/627951ffd0034e879c608cf9.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prognostic Value of Statins in Critically Ill Patients with Acute Myocardial Infarction-Related Acute Kidney Injury: A Retrospective Cohort Study Based on the MIMIC-IV Database","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAcute myocardial infarction (AMI) is a critical condition resulting from thrombotic occlusion due to coronary plaque rupture or erosion, leading to myocardial ischemic hypoxia injury and necrosis. It can be classified into ST-segment elevation myocardial infarction (STEMI), caused by complete coronary artery occlusion, and non-ST-segment elevation myocardial infarction (NSTEMI), caused by partial or intermittent occlusion. Epidemiological data indicate that the prevalence of AMI is as high as 23.3%, with a mortality rate ranging from 7% to 10%, making it a significant cause of death among patients in intensive care unit (ICU)\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Acute kidney injury (AKI), a common complication in hospitalized patients with AMI, occurs in 12.1% to 55.6% of cases\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. Its pathogenesis involves multiple pathophysiological processes, including ischemia-reperfusion injury, oxidative stress, inflammation, and nephrotoxicity\u003csup\u003e[\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. AKI is an independent risk factor affecting both short-term and long-term prognosis in AMI patients, and mortality in patients with concomitant AKI is more than 10 times higher than in those without\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Therefore, strengthening clinical intervention for AKI following AMI is particularly urgent.\u003c/p\u003e\n\u003cp\u003eStatins, or 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors, are widely used for the primary and secondary prevention of cardiovascular events due to their established lipid-lowering efficacy\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. Their pleiotropic effects, including anti-inflammatory, immunomodulatory, and antioxidant activities, have expanded their potential applications in other diseases\u003csup\u003e[\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Studies have shown that statins significantly reduce cardiac and all-cause mortality in patients with AMI\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e, and multiple studies have also suggested their ability to lower the risk of developing AKI\u003csup\u003e[\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. Furthermore, a retrospective study by Tang et al. involving 5,376 patients with chronic kidney disease (CKD) reported that statin users had a 55% lower risk of in-hospital mortality compared with non-users\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. A retrospective study by Zheng et al. involving 2,034 patients with AKI also confirmed that statin use was significantly associated with reduced in-hospital mortality, although this association was only statistically significant in the atorvastatin subgroup\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. However, conflicting findings exist: a large cohort study of 43,438 patients reported that statin users had a 30% increased risk of developing AKI compared to non-users\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Similarly,a study by Wang et al. observed no significant improvement in prognosis with statin use in patients with severe AKI associated with sepsis\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. Currently, research on the impact of statins on short-term and long-term outcomes in AMI patients complicated by AKI remains limited.\u003c/p\u003e\n\u003cp\u003eGiven the contradictory nature of the existing evidence and the lack of specific clinical guidelines for statin therapy in this particular patient population, this study utilized real-world data to systematically evaluate the association between statin therapy and clinical outcomes in AMI patients with concomitant AKI, aiming to provide refined, evidence-based support for clinical pharmacotherapy in this group.\u003c/p\u003e\n"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1Data Source\u003c/h2\u003e \u003cp\u003e Data for this study were obtained from the publicly available Medical Information Mart for Intensive Care IV (MIMIC-Ⅳ-2.2) database, which contains clinical information on critically ill patients admitted to the Beth Israel Deaconess Medical Center between 2008 and 2019. All patient information in the database has been de-identified to protect privacy; therefore, this study was granted an exemption for ethical approval and the requirement for informed consent was waived. One of the authors (Jiahui Li) completed the Collaborative Institutional Training Initiative (CITI) program and passed the relevant examinations (Certification No.: 10125720) to obtain access to the database.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Inclusion and Exclusion Criteria\u003c/h2\u003e \u003cp\u003ePatients diagnosed with AMI were identified using the International Classification of Diseases (ICD) code 9/10 (see Supplementary Table\u0026nbsp;1). Among these patients, those who developed AKI during their ICU stay were included. AKI was defined according to the Kidney Disease Improving Global Outcomes (KDIGO) criteria\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e: an increase in serum creatinine (SCr) by \u0026ge;\u0026thinsp;0.3 mg/dL (26.5 \u0026micro;mol/L) within 48 hours, or an increase in SCr to \u0026ge;\u0026thinsp;1.5 times baseline within 7 days, or urine output\u0026thinsp;\u0026le;\u0026thinsp;0.5 mL/(kg\u0026middot;h) for 6 hours. Exclusion criteria were as follows: (1) patients with multiple ICU admissions, only the first ICU admission was included; (2) patients aged\u0026thinsp;\u0026lt;\u0026thinsp;18 years; and(3) ICU stay duration\u0026thinsp;\u0026lt;\u0026thinsp;24 h (discharged or death).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Data Extraction\u003c/h2\u003e \u003cp\u003eClinical data during hospitalization were extracted from the MIMIC-IV-2.2 database using the database management tool Navicat Premium (version 16.3.7) via Structured Query Language (SQL). The extracted variables included: (1) Demographic information: age, sex, race, weight, height, insurance type, smoking history, and alcohol consumption history; (2) Vital signs measured within the first 24 hours of ICU admission: heart rate, respiratory rate, systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), peripheral oxygen saturation (SpO₂), and urine output; (3) Laboratory parameters measured within the first 24 hours of ICU admission: white blood cell (WBC) count, platelet count, blood glucose, hemoglobin, blood urea nitrogen (BUN), creatinine, red cell distribution width (RDW), anion gap, lactate, international normalized ratio (INR), activated partial thromboplastin time (APTT), potassium, sodium, calcium, and troponin T (TNT); (4) Comorbidities: hypertension, congestive heart failure (CHF), peripheral vascular disease (PVD), cerebrovascular disease (CVD), chronic pulmonary disease, chronic kidney disease (CKD), malignancy, liver disease, diabetes, obesity, and hyperlipidemia; (5) Disease severity scores: Sequential Organ Failure Assessment (SOFA), Simplified Acute Physiology Score II (SAPS II), Oxford Acute Severity of Illness Score (OASIS), and Charlson Comorbidity Index (CCI); (6) Therapeutic interventions within 48 hours of ICU admission: mechanical ventilation, vasopressors, coronary artery bypass grafting (CABG), percutaneous coronary intervention (PCI), and continuous renal replacement therapy (CRRT); (7) Medications administered within 48 hours of ICU admission: beta-blockers, antiplatelet agents, angiotensin-converting enzyme inhibitors (ACEI), and angiotensin II receptor blockers (ARB); and(8) Outcome variables: 28-day mortality, 90-day mortality, in-hospital mortality, and ICU mortality.\u003c/p\u003e \u003cp\u003eFor missing data (covariate missingness is illustrated in Supplementary Fig.\u0026nbsp;1), variables with a missing rate exceeding 20% were excluded. Variables with a missing rate below 20% were imputed using Multiple Imputation by Chained Equations (MICE), generating five imputed datasets. After imputation, estimates from the five datasets were pooled according to Rubin's rules to account for the uncertainty associated with missing data. This process was performed using the \"mice\" package in R software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statin Use Patterns\u003c/h2\u003e \u003cp\u003ePatients were divided into a non-statin group and a statin group based on their receipt of statin therapy during the ICU stay. Furthermore, the association between different types of statins and mortality was evaluated by examining four commonly used statins: simvastatin, rosuvastatin, pravastatin, and atorvastatin. To further explore the impact of statin dosage on patient mortality, patients were categorized into a standard-dose group and a high-dose group according to the administered statin dose. High-dose statin therapy was defined as a daily dose exceeding the following thresholds: simvastatin 40 mg, rosuvastatin 20 mg, pravastatin 40 mg, and atorvastatin 80 mg\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e.Patients receiving multiple types of statins or varying doses were excluded to ensure consistency in exposure assessment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Clinical Outcomes\u003c/h2\u003e \u003cp\u003eThe primary outcome was 28-day mortality. Secondary outcomes included 90-day mortality, in-hospital mortality, and ICU mortality.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Statistical Analysis\u003c/h2\u003e \u003cp\u003eThe Shapiro-Wilk test was used to assess the normality of continuous variables. Normally distributed data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) and were compared using the independent samples t-test. Non-normally distributed data are expressed as median (interquartile range, IQR) and were analyzed with the Mann-Whitney U test. Categorical variables, presented as frequencies (percentages), were compared using the chi-square or Fisher's exact test, as appropriate.\u003c/p\u003e \u003cp\u003eBased on a directed acyclic graph (DAG), confounding variables requiring adjustment were identified. Only baseline variables influencing both exposure and outcome were included, while post-exposure variables or mediating variables were avoided.\u003c/p\u003e \u003cp\u003eTo mitigate imbalances in baseline characteristics between the two groups, propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) were employed. Specifically, propensity scores (PS) were calculated using a multivariate logistic regression model incorporating all baseline covariates. A 1:1 nearest neighbor matching algorithm with a caliper width of 0.05 and without replacement was applied to generate a matched cohort with comparable baseline characteristics. Simultaneously, stabilized inverse probability weights based on the PS were used to construct two pseudo-populations, with weights truncated at the 1st and 99th percentiles to control extreme values. The balance of covariates after PSM and IPTW was assessed using standardized mean differences (SMD), with |SMD| \u0026lt; 0.1 indicating adequate balance, and visualized using density plots.\u003c/p\u003e \u003cp\u003eCox proportional hazards regression and logistic regression models were constructed in the original, matched, and weighted cohorts to evaluate the association between statin use and patient mortality. The multivariate model incorporates confounding variables including: demographic information (insurance type, race, sex, age, weight, smoking history, alcohol consumption history), vital signs (heart rate, respiratory rate, MAP, SBP, blood oxygen saturation, urine output), laboratory parameters (WBC, platelet count, hemoglobin, BUN, creatinine, RDW, anion gap, INR, APTT, potassium, sodium, calcium), comorbidities (hypertension, CHF, CVD, chronic pulmonary disease, CKD, malignancy, liver disease, diabetes, obesity, hyperlipidemia),severity scores of the disease(CCI, SOFA, OASIS, SAPS II), therapeutic interventions (mechanical ventilation, vasopressor use, CRRT), and medications (beta-blockers, antiplatelet agents, ACEI, ARB). Multicollinearity among variables was assessed using the variance inflation factor (VIF), and variables with VIF\u0026thinsp;\u0026gt;\u0026thinsp;10 were excluded. All variables included in the multivariate Cox regression models had VIF\u0026thinsp;\u0026lt;\u0026thinsp;10 (see Supplementary Fig.\u0026nbsp;5).\u003c/p\u003e \u003cp\u003eKaplan-Meier survival curves were estimated for 28-day and 90-day survival in the non-statin and statin groups within the original, matched, and weighted cohorts, with differences between groups compared using the log-rank test.\u003c/p\u003e \u003cp\u003eIn the original cohort, multivariate Cox and logistic regression models were constructed to assess the association between statin type and dosage with mortality, adjusting for the same variables as described above. Finally, subgroup analyses were performed to evaluate the consistency of the association between statin use and 28-day and 90-day mortality across different patient populations. Stratification was based on age (\u0026gt;\u0026thinsp;65 years or \u0026le;\u0026thinsp;65 years), sex (male or female), weight (\u0026gt;\u0026thinsp;80 kg or \u0026le;\u0026thinsp;80 kg), AKI stage (1, 2, or 3), comorbidities (CVD, CKD, CHF, diabetes, hyperlipidemia), therapeutic interventions (mechanical ventilation, vasopressors, CRRT, CABG), and medications (beta-blockers and antiplatelet agents), with interaction terms introduced for testing.\u003c/p\u003e \u003cp\u003eAll statistical analyses were performed using R software (version 4.5.1). All tests were two-sided, and P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Baseline Characteristics\u003c/h2\u003e \u003cp\u003eThe patient selection process is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A total of 3,844 patients with AMI-AKI meeting the inclusion criteria were enrolled in this study. Among them, 2,792 patients (72.6%) received statin therapy after ICU admission, while 1,052 patients (27.4%) did not receive statins during this period. After PSM adjustment, 899 patients in the statin group and 899 patients in the non-statin group were included.\u003c/p\u003e \u003cp\u003eBaseline characteristics of the original cohort are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Significant differences in multiple baseline characteristics were observed between the two groups (SMD\u0026thinsp;\u0026gt;\u0026thinsp;0.1). Specifically, compared to the non-statin group, patients in the statin group had a higher proportion of males and greater body weight. Regarding vital signs, patients receiving statins exhibited relatively higher oxygen saturation and urine output, but lower heart rate and respiratory rate. Laboratory parameters showed that the statin group had relatively higher white blood cell count, hemoglobin, and calcium levels, but lower BUN, creatinine, anion gap and INR. Disease severity scores (including SOFA, OASIS, SAPS II, and CCI) were lower in the statin group compared to the non-statin group. Regarding comorbidities, the statin group had higher proportions of hypertension, chronic pulmonary disease, diabetes, obesity, and hyperlipidemia, but lower proportions of CHF, malignancy, and liver disease. In terms of therapeutic interventions, the number of patients receiving mechanical ventilation on the first day of ICU admission was higher in the statin group, while vasopressor use and CRRT were more common in the non-statin group. Patients in the statin group were more likely to undergo PCI and CABG. Furthermore, the proportion of patients receiving beta-blockers, antiplatelet agents, and ACEI was higher in the statin group.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of patients in the non-statin and statin groups in the original cohort\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-statin\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;1052)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStatin\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;2792)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSMD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDemographics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsurance, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedicare\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e622 (59.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1554 (55.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedicaid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e392 (37.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1142 (40.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e701 (66.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1812 (64.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e102 (9.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e200 (7.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther/Unknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e230 (21.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e728 (26.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.186\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e588 (55.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1813 (64.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e464 (44.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e979 (35.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAKI stage, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.199\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e207 (19.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e729 (26.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e487 (46.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1333 (47.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e358 (34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e730 (26.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74.9 (64.6, 83.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.6 (64.0, 80.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.1(66.6, 91.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82.5 (69.7, 97.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.166\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoke, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e296 (28.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e904 (32.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.092\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVital signs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart Rate(bpm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87 (74, 103)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84 (75, 96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory Rate (beats/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (16, 24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (15, 22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.207\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78 (67, 91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79 (69, 91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e118 (102, 136)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117 (104, 133)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.978\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65 (54, 78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66 (56, 78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpo2 (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97 (94, 100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98 (95, 100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.215\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrine output (ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1155 (675, 1905)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1455 (900, 2158)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLaboratory test\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC (K/uL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.3 (8.3, 15.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.3 (9, 16.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet (K/uL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e194 (137, 265)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e190 (141, 248)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlucose (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e140 (111, 188)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e136 (112, 184)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.2 (8.7, 11.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.5 (8.8, 12.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBUN (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (18, 49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (16, 37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.265\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.4 (0.9, 2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.1 (0.9, 1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.153\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRDW (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (13.8, 16.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.2 (13.3, 15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.399\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnion gap (mEq/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (13, 19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (12, 18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.255\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eINR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.3 (1.2, 1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3 (1.1, 1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAPTT (second)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.8 (28.2, 49.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.2 (28.8, 52.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotassium (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.3 (3.8, 4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.3 (3.9, 4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSodium (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e138 (135, 141)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e138 (136, 141)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.496\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCacium (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.3 (7.8, 8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.4 (7.9, 8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidities, n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e798 (75.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2246 (80.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.111\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e635 (60.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1578 (56.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePVD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e185 (17.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e479 (17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCVD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e177 (16.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e435 (15.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic pulmonary disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e314 (29.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e741 (26.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCKD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e382 (36.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e961 (34.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalignant Cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e123 (11.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e193 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.165\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e136 (12.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e194 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.201\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e435 (41.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1289 (46.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e119 (11.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e385 (13.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperlipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e506 (48.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1688 (60.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.250\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical scores\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOFA score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (3, 9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (3, 8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.178\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOASIS score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34 (28, 41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (28, 39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.115\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSAPS II score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (32, 52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (31, 48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.205\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (5, 9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (5, 8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.207\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTreatment, n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanical ventilation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e855(81.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2405 (86.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVasopressin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e127 (12.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e232 (8.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRRT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e172 (16.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e330 (11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.131\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43(4.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e240 (8.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.186\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCABG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13(1.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e499 (17.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.590\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedications, n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeta-blockers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e514 (48.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1799 (64.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.318\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntiplatelet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e421 (40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2244 (80.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.905\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACEI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117 (11.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e424 (15.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eAbbreviations\u003c/b\u003e: AKI, Acute Kidney Injury; SBP, Systolic Blood Pressure; DBP, Diastolic Blood Pressure; MBP, Mean Blood Pressure; Spo2, Peripheral Capillary Oxygen Saturation; WBC, White Blood Cell; BUN, Blood Urea Nitrogen; RDW, Red Blood Cell Distribution Width; INR,International Normalized Ratio; APTT, Activated Partial Thromboplastin Time; CHF, Congestive Heart Failure; PVD, Peripheral Vascular Disease; CVD, Cerebrovascular Disease; CKD, Chronic Kidney Disease; SOFA score, Sequential Organ Failure Assessment score; OASIS score, Oxford Acute Severity of Illness Score; SAPS II score, Simplified Acute Physiology Score II; CCI, Charlson Comorbidity Index; CRRT, Continuous Renal Replacement Therapy; PCI, Percutaneous Coronary Intervention; CABG, Coronary Artery Bypass Grafting; ACEI, Angiotensin-Converting Enzyme Inhibitor; ARB, Angiotensin II Receptor Blocker; HR, hazard ratio; OR, Odds Ratio; CI, confidence interval; SMD, Standardized Mean Difference.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAfter PSM and IPTW adjustments(baseline characteristics of the two groups are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e),in the matched cohort, baseline characteristics were well-balanced between the groups (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05 and SMD\u0026thinsp;\u0026lt;\u0026thinsp;0.1). In the weighted cohort, all baseline characteristics were balanced between the two groups (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05 and SMD\u0026thinsp;\u0026lt;\u0026thinsp;0.1), with the exception of CABG (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; SMD\u0026thinsp;=\u0026thinsp;0.340). Therefore, CABG was included as a confounding variable in the Cox and logistic regression models for the weighted cohort.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics and SMD of patients after PSM and IPTW\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003ePSM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eIPTW\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-statin (N\u0026thinsp;=\u0026thinsp;899)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStatin\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;899)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSMD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNon-statin (N\u0026thinsp;=\u0026thinsp;729.6)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eStatin\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;2499.6)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSMD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDemographics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsurance, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.868\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedicare\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e531 (59.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e520 (58.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e421 (57.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1419 (56.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedicaid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (3.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25 (3.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e84 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e328 (36.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e338 (38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e283 (38.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e997 (39.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.448\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e582 (65.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e580 (65.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e490 (67.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1642 (65.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e43 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88 (9.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81 (9.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e64 (8.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e192 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther/Unknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e203 (22.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e218 (24.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e165 (22.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e623 (24.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e515 (57.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e527 (59.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e435 (59.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1560 (62.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e374 (42.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e362 (40.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e295 (40.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e940 (37.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAKI stage, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e179 (20.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e199 (22.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e152 (20.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e614 (24.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e433 (48.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e401 (45.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e364 (49.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1168 (46.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e277 (31.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e289 (32.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e214 (29.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e717 (28.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75.1\u003c/p\u003e \u003cp\u003e(64.9, 83.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.1\u003c/p\u003e \u003cp\u003e(64.6, 82.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e75.1\u003c/p\u003e \u003cp\u003e(65.9, 83.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e72.8\u003c/p\u003e \u003cp\u003e(64.3, 81.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.6\u003c/p\u003e \u003cp\u003e(67.6, 92.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80.4\u003c/p\u003e \u003cp\u003e(68.0, 95.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e80.4\u003c/p\u003e \u003cp\u003e(68.9, 94.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e81.7\u003c/p\u003e \u003cp\u003e(68.5, 96.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoke, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e275 (30.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e253 (28.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e230 (31.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e783 (31.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.931\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (2.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e70 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVital signs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart Rate (bpm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87\u003c/p\u003e \u003cp\u003e(73, 102)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86\u003c/p\u003e \u003cp\u003e(75, 100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e86\u003c/p\u003e \u003cp\u003e(73, 100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e85\u003c/p\u003e \u003cp\u003e(75, 97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.676\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory Rate\u003c/p\u003e \u003cp\u003e(beats/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003cp\u003e(16, 23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003cp\u003e(15, 24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19\u003c/p\u003e \u003cp\u003e(15, 23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18\u003c/p\u003e \u003cp\u003e(15, 23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79\u003c/p\u003e \u003cp\u003e(67, 91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79\u003c/p\u003e \u003cp\u003e(69, 91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e79\u003c/p\u003e \u003cp\u003e(68, 92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e79\u003c/p\u003e \u003cp\u003e(69, 91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e119\u003c/p\u003e \u003cp\u003e(103, 136)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e118\u003c/p\u003e \u003cp\u003e(104, 135)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e119\u003c/p\u003e \u003cp\u003e(103, 136)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e117\u003c/p\u003e \u003cp\u003e(104, 134)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003cp\u003e(54, 78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66\u003c/p\u003e \u003cp\u003e(56, 78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e66\u003c/p\u003e \u003cp\u003e(55, 80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e66\u003c/p\u003e \u003cp\u003e(56, 78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpo2 (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98\u003c/p\u003e \u003cp\u003e(95, 100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98\u003c/p\u003e \u003cp\u003e(95, 100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e98\u003c/p\u003e \u003cp\u003e(95, 100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e98\u003c/p\u003e \u003cp\u003e(95, 100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrineoutput (ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1285\u003c/p\u003e \u003cp\u003e(740, 2045)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1315\u003c/p\u003e \u003cp\u003e(785, 2125)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1330\u003c/p\u003e \u003cp\u003e(780, 2075)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1400\u003c/p\u003e \u003cp\u003e(845, 2122)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLaboratory test\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC (K/uL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.3\u003c/p\u003e \u003cp\u003e(8.4, 15.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.2\u003c/p\u003e \u003cp\u003e(8.8, 16.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.3\u003c/p\u003e \u003cp\u003e(8.6,\u0026nbsp;15.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.2\u003c/p\u003e \u003cp\u003e(8.8,\u0026nbsp;16.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet (K/uL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e198\u003c/p\u003e \u003cp\u003e(142, 263)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e199\u003c/p\u003e \u003cp\u003e(144, 259)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.916\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e197\u003c/p\u003e \u003cp\u003e(144, 261)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e192\u003c/p\u003e \u003cp\u003e(142, 252)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlucose (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e140\u003c/p\u003e \u003cp\u003e(113, 190)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140\u003c/p\u003e \u003cp\u003e(112, 192)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e140\u003c/p\u003e \u003cp\u003e(114, 189)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e137\u003c/p\u003e \u003cp\u003e(111, 185)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.3\u003c/p\u003e \u003cp\u003e(8.7, 12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.3\u003c/p\u003e \u003cp\u003e(8.7, 12.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.5 (8.9,\u0026nbsp;12.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.5 (8.8,\u0026nbsp;12.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.767\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBUN (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003cp\u003e(18, 48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003cp\u003e(18, 43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25\u003c/p\u003e \u003cp\u003e(18,\u0026nbsp;44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24\u003c/p\u003e \u003cp\u003e(17,\u0026nbsp;40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003cp\u003e(0.9, 2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003cp\u003e(0.9, 2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.2 (0.9,\u0026nbsp;2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003cp\u003e(0.9,\u0026nbsp;1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.661\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRDW (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.8\u003c/p\u003e \u003cp\u003e(13.7, 16.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.6\u003c/p\u003e \u003cp\u003e(13.6, 16.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.6\u003c/p\u003e \u003cp\u003e(13.5, 16.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14.3\u003c/p\u003e \u003cp\u003e(13.4, 15.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnion gap (mEq/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003cp\u003e(13, 19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003cp\u003e(13, 19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003cp\u003e(13,\u0026nbsp;18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15\u003c/p\u003e \u003cp\u003e(12,\u0026nbsp;18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eINR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003cp\u003e(1.1, 1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003cp\u003e(1.1, 1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.3 (1.1,\u0026nbsp;1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003cp\u003e(1.1,\u0026nbsp;1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.545\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAPTT (second)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.9\u003c/p\u003e \u003cp\u003e(28, 51.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003cp\u003e(28.3, 52.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34.4\u003c/p\u003e \u003cp\u003e(28.2, 53.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e34\u003c/p\u003e \u003cp\u003e(28.6, 50.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.632\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotassium (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003cp\u003e(3.8, 4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003cp\u003e(3.8, 4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.3 (3.9,\u0026nbsp;4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003cp\u003e(3.9,\u0026nbsp;4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.576\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSodium (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e138\u003c/p\u003e \u003cp\u003e(135, 141)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e139\u003c/p\u003e \u003cp\u003e(136, 141)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e138\u003c/p\u003e \u003cp\u003e(135, 141)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e138\u003c/p\u003e \u003cp\u003e(136, 141)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.717\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalcium (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003cp\u003e(7.8, 8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003cp\u003e(7.8, 8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.959\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003cp\u003e(7.9, 8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003cp\u003e(7.9, 8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.687\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidities, n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e697 (78.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e680 (76.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e575 (78.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1988 (79.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.660\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e536 (60.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e531 (59.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.846\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e439 (60.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1443 (57.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePVD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e158 (17.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e162 (18.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e134 (18.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e430 (17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.448\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCVD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e158 (17.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e152 (17.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.755\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e128 (17.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e405 (16.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic Pulmonary Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e255 (28.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e249 (28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e211 (28.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e685 (27.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCKD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e332 (37.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e323 (36.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.694\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e256 (35.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e873 (34.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.941\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalignant Cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87 (9.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90 (10.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.874\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e64 (8.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e204 (8.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.549\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92 (10.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86 (9.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e65 (8.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e209 (8.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.638\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e377 (42.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e388 (43.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.632\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e320 (43.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1121 (44.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.658\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98 (11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e107 (12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e87 (11.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e324 (13.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.472\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperlipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e460 (51.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e466 (52.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e399 (54.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1437 (57.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical scores\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOFA score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (3, 8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (3, 8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (3, 8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (3, 8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOASIS score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34 (27, 40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (28, 40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34 (27, 40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e34 (28, 39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSAPS II score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (31, 51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (33, 51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40 (31, 50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40 (32, 49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.448\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (5, 9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (5, 9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.926\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7 (5, 9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7 (5, 9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTreatment, n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanical Ventilation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e729 (82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e733 (82.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.852\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e612 (83.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2121 (84.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVasopressin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88 (9.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84 (9.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e69 (9.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e229 (9.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.801\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRRT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e133 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e124 (13.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e94 (12.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e321 (12.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (4.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (4.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53 (7.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e184 (7.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCABG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e334 (13.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedications, n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeta-blockers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e472 (53.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e481 (54.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.704\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e414 (56.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1509 (60.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntiplatelet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e421 (47.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e425 (47.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e479 (65.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1741 (69.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACEI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e111 (12.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108 (12.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.885\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e108 (14.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e355 (14.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.734\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e72 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003cb\u003eAbbreviations\u003c/b\u003e: AKI, Acute Kidney Injury; SBP, Systolic Blood Pressure; DBP, Diastolic Blood Pressure; MBP, Mean Blood Pressure; Spo2, Peripheral Capillary Oxygen Saturation; WBC, White Blood Cell; BUN, Blood Urea Nitrogen; RDW, Red Blood Cell Distribution Width; INR,International Normalized Ratio; APTT, Activated Partial Thromboplastin Time; CHF, Congestive Heart Failure; PVD, Peripheral Vascular Disease; CVD, Cerebrovascular Disease; CKD, Chronic Kidney Disease; SOFA score, Sequential Organ Failure Assessment score; OASIS score, Oxford Acute Severity of Illness Score; SAPS II score, Simplified Acute Physiology Score II; CCI, Charlson Comorbidity Index; CRRT, Continuous Renal Replacement Therapy; PCI, Percutaneous Coronary Intervention; CABG, Coronary Artery Bypass Grafting; ACEI, Angiotensin-Converting Enzyme Inhibitor; ARB, Angiotensin II Receptor Blocker; HR, hazard ratio; OR, Odds Ratio; CI, confidence interval; SMD, Standardized Mean Difference.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Directed Acyclic Graph Analysis Results\u003c/h2\u003e \u003cp\u003eDAG was constructed to identify confounders and mediators in the association between statin use and mortality (see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Confounders identified included: age, alcohol consumption history, smoking history, comorbidities (hypertension, CHF, PVD, CVD, chronic pulmonary disease, CKD, malignancy, diabetes, liver disease, obesity, and hyperlipidemia), and disease severity scores (SOFA, SAPS II, OASIS, and CCI). Relevant variables included: vital signs (heart rate, respiratory rate, SBP, DBP, MAP, oxygen saturation, urine output), laboratory parameters (WBC, platelet count, blood glucose, hemoglobin, BUN, creatinine, RDW, anion gap, INR, APTT, potassium, sodium, calcium), therapeutic interventions (mechanical ventilation, vasopressors, CRRT, PCI, CABG), and medications (beta-blockers, antiplatelet agents, ACEI, ARB). No mediators were identified. Confounders were required to be included in the regression models. Furthermore, as relevant variables may also act as confounders, they were considered for inclusion in the models.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Association Between Statin Use and Patient Mortality\u003c/h2\u003e \u003cp\u003eIn unadjusted models, statin use was significantly associated with a reduced risk of 28-day mortality (HR\u0026thinsp;=\u0026thinsp;0.446, 95% CI : 0.387\u0026ndash;0.514, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), 90-day mortality (HR\u0026thinsp;=\u0026thinsp;0.491, 95% CI : 0.433\u0026ndash;0.556, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), in-hospital mortality (OR\u0026thinsp;=\u0026thinsp;0.407, 95% CI : 0.342\u0026ndash;0.484, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and ICU mortality (OR\u0026thinsp;=\u0026thinsp;0.388, 95% CI : 0.319\u0026ndash;0.471, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In multivariable-adjusted models, compared to the non-statin group, patients in the statin group exhibited a 37.9% reduction in 28-day mortality, a 29.0% reduction in 90-day mortality, a 38.8% reduction in in-hospital mortality, and a 46.5% reduction in ICU mortality. The significant protective effect of statins was consistently observed in both the matched and weighted cohorts (see Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Kaplan-Meier Survival Curves\u003c/h2\u003e \u003cp\u003eIn the original cohort, patients with AMI-AKI in the statin group demonstrated significantly higher 28-day and 90-day survival rates compared to those in the non-statin group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, B). The survival curves for the matched cohort (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC, D) and the weighted cohort (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE, F) were consistent with those of the original cohort (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Association of Statin Type and Dosage with Patient Mortality\u003c/h2\u003e \u003cp\u003eAfter applying the exclusion criteria, 2,593 patients were identified as having received a single type and dosage of statin therapy. The distribution of statin use was as follows: simvastatin (n\u0026thinsp;=\u0026thinsp;247), rosuvastatin (n\u0026thinsp;=\u0026thinsp;163), pravastatin (n\u0026thinsp;=\u0026thinsp;91), and atorvastatin (n\u0026thinsp;=\u0026thinsp;2,092). Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the association between different types of statins and mortality. Compared with the non-statin group, the use of simvastatin and atorvastatin was significantly associated with lower mortality among patients with AMI-AKI. Specifically, patients receiving simvastatin exhibited a 54.5% reduction in 28-day mortality (HR\u0026thinsp;=\u0026thinsp;0.455, 95% CI : 0.315\u0026ndash;0.658, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), a 42.7% reduction in 90-day mortality (HR\u0026thinsp;=\u0026thinsp;0.573, 95% CI : 0.425\u0026ndash;0.772, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), a 60.5% reduction in in-hospital mortality (OR\u0026thinsp;=\u0026thinsp;0.395, 95% CI : 0.242\u0026ndash;0.645, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and a 71.1% reduction in ICU mortality (OR\u0026thinsp;=\u0026thinsp;0.289, 95% CI : 0.157\u0026ndash;0.534, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Atorvastatin also demonstrated a significant protective effect, with reductions of 36.1%, 27.6%, 39.1%, and 35.4% in 28-day, 90-day, ICU, and in-hospital mortality, respectively. However, no significant association with reduced mortality was observed for rosuvastatin or pravastatin (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation of different statin types with patient mortality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e28-day\u003c/p\u003e \u003cp\u003emortality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e90-day\u003c/p\u003e \u003cp\u003emortality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eIn-Hospital\u003c/p\u003e \u003cp\u003emortality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eICU\u003c/p\u003e \u003cp\u003emortality\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003cp\u003e(95%Cl)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003cp\u003e(95%Cl)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e(95%Cl)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e(95%Cl)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e(95%Cl)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo statin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSimvastatin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003cp\u003e0.455\u003c/p\u003e \u003cp\u003e(0.315,\u003c/p\u003e \u003cp\u003e0.658)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003cp\u003e0.573\u003c/p\u003e \u003cp\u003e(0.425,\u003c/p\u003e \u003cp\u003e0.772)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e0.395\u003c/p\u003e \u003cp\u003e( 0.242,\u003c/p\u003e \u003cp\u003e0.645)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e0.289\u003c/p\u003e \u003cp\u003e(0.157,\u003c/p\u003e \u003cp\u003e0.534)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRosuvastatin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003cp\u003e0.734\u003c/p\u003e \u003cp\u003e(0.489,\u003c/p\u003e \u003cp\u003e1.102)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003cp\u003e0.803\u003c/p\u003e \u003cp\u003e(0.562,\u003c/p\u003e \u003cp\u003e1.146)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e0.701\u003c/p\u003e \u003cp\u003e(0.400,\u003c/p\u003e \u003cp\u003e1.226)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e0.397\u003c/p\u003e \u003cp\u003e(0.192,\u003c/p\u003e \u003cp\u003e0.817)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePravastatin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003cp\u003e0.864\u003c/p\u003e \u003cp\u003e(0.525,\u003c/p\u003e \u003cp\u003e1.422)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003cp\u003e0.975\u003c/p\u003e \u003cp\u003e(0.640,\u003c/p\u003e \u003cp\u003e1.486)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e0.941\u003c/p\u003e \u003cp\u003e(0.493,\u003c/p\u003e \u003cp\u003e1.795)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e0.540\u003c/p\u003e \u003cp\u003e(0.230,\u003c/p\u003e \u003cp\u003e1.265)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtorvastatin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003cp\u003e0.639\u003c/p\u003e \u003cp\u003e(0.538,\u003c/p\u003e \u003cp\u003e0.760)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003cp\u003e0.724\u003c/p\u003e \u003cp\u003e(0.623,\u003c/p\u003e \u003cp\u003e0.842)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e0.646\u003c/p\u003e \u003cp\u003e(0.507,\u003c/p\u003e \u003cp\u003e0.822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e0.609\u003c/p\u003e \u003cp\u003e(0.465,\u003c/p\u003e \u003cp\u003e0.800)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e\u003cb\u003eAbbreviations\u003c/b\u003e: HR, hazard ratio; OR,Odds Ratio; CI, confidence interval.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRegarding dosage stratification, 819 patients received standard-dose statin therapy, and 1,774 patients received high-dose statin therapy. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, compared to patients in the non-statin group, those receiving standard-dose statin therapy had significantly reduced 28-day (HR\u0026thinsp;=\u0026thinsp;0.497, 95% CI : 0.397\u0026ndash;0.622, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), 90-day (HR\u0026thinsp;=\u0026thinsp;0.612, 95% CI : 0.508\u0026ndash;0.736, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), in-hospital (OR\u0026thinsp;=\u0026thinsp;0.457, 95% CI : 0.338\u0026ndash;0.618, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and ICU mortality (OR\u0026thinsp;=\u0026thinsp;0.348, 95% CI : 0.241\u0026ndash;0.501, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similarly, patients receiving high-dose statin therapy also showed significantly reduced risks of 28-day (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), 90-day (P\u0026thinsp;=\u0026thinsp;0.004), in-hospital (P\u0026thinsp;=\u0026thinsp;0.025), and ICU mortality (P\u0026thinsp;=\u0026thinsp;0.011). Furthermore, patients with AMI-AKI treated with simvastatin and standard-dose statin therapy exhibited the greatest risk reduction in mortality.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation of different statin dosages with patient mortality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e28-day\u003c/p\u003e \u003cp\u003emortality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e90-day\u003c/p\u003e \u003cp\u003emortality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eIn-hospital mortality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eICU\u003c/p\u003e \u003cp\u003emortality\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003cp\u003e(95%Cl)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003cp\u003e(95%Cl)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e(95%Cl)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e(95%Cl)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo statin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStandard dose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003cp\u003e0.497\u003c/p\u003e \u003cp\u003e(0.397,\u003c/p\u003e \u003cp\u003e0.622)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003cp\u003e0.612\u003c/p\u003e \u003cp\u003e(0.508,\u003c/p\u003e \u003cp\u003e0.736)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e0.457\u003c/p\u003e \u003cp\u003e(0.338,\u003c/p\u003e \u003cp\u003e0.618)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e0.348\u003c/p\u003e \u003cp\u003e(0.241,\u003c/p\u003e \u003cp\u003e0.501)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh dose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003cp\u003e0.715\u003c/p\u003e \u003cp\u003e(0.597,\u003c/p\u003e \u003cp\u003e0.856)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003cp\u003e0.795\u003c/p\u003e \u003cp\u003e(0.679,\u003c/p\u003e \u003cp\u003e0.930)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e0.751\u003c/p\u003e \u003cp\u003e(0.584,\u003c/p\u003e \u003cp\u003e0.965)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e0.693\u003c/p\u003e \u003cp\u003e(0.523, 0.920)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003cb\u003eAbbreviations\u003c/b\u003e: HR, hazard ratio; OR,Odds Ratio; CI, confidence interval.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Subgroup Analysis Results\u003c/h2\u003e \u003cp\u003eIn the subgroup analysis, the protective effect of statins remained consistent across most subgroups. Additionally, we evaluated potential effect modification by stratified variables on the association between statin use and mortality. Significant interactions were observed between antiplatelet agents and statin use, as well as between CHF and statin use (P for interaction\u0026thinsp;\u0026lt;\u0026thinsp;0.05), suggesting that the use of antiplatelet agents attenuated the protective effect of statins, and that the protective effect of statins was more pronounced in patients without CHF. In the analysis of 28-day mortality, significant interactions were found between CABG and statin use, and between beta-blockers and statin use, indicating that patients undergoing CABG or receiving beta-blockers derived greater benefit from statin therapy. For 90-day mortality, a significant interaction was identified between age and statin use (P for interaction\u0026thinsp;\u0026lt;\u0026thinsp;0.05), suggesting a stronger protective effect of statins in AMI-AKI patients aged\u0026thinsp;\u0026le;\u0026thinsp;65 years. Furthermore, although no significant interaction was detected between AKI stage and statin use, a consistently observed pattern across mortality endpoints was that statins did not demonstrate significant benefit in AMI patients with AKI stages 1 or 2; however, the protective effect was more pronounced in patients with AKI stage 3(see Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn this large retrospective cohort study utilizing the MIMIC-IV database, we observed that patients with acute myocardial infarction complicated by acute kidney injury (AMI-AKI) who received statin therapy had a significantly reduced risk of mortality. This protective effect remained statistically significant after multivariable adjustment, propensity score matching (PSM), and inverse probability of treatment weighting (IPTW), and was further corroborated by Kaplan-Meier survival curves. Notably, this association was most pronounced in the simvastatin and atorvastatin subgroups, with the greatest reduction in mortality observed in the standard-dose treatment group. Subgroup analyses revealed that the protective effect of statins was more prominent in AMI patients with stage 3 AKI. Furthermore, patients aged\u0026thinsp;\u0026le;\u0026thinsp;65 years, those not receiving antiplatelet agents, those without concurrent chronic heart failure (CHF), those undergoing coronary artery bypass grafting (CABG), or those receiving beta-blocker therapy derived greater benefit from statin treatment.\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Potential Mechanisms Underlying the Reduction in Mortality Associated with Statin Use in AMI-AKI\u003c/h2\u003e \u003cp\u003ePrior to the present study, the association between statin use and prognosis in patients with AMI-AKI had not been investigated. Our study is the first to reveal that statin therapy is significantly associated with reduced mortality risk in this population. The potential protective mechanisms may involve: (1) activation of endothelial nitric oxide synthase (eNOS) in endothelial cells, increasing nitric oxide (NO) production, thereby ameliorating endothelial dysfunction, promoting vasodilation, and improving renal blood flow\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e; (2) inhibition of reactive oxygen species (ROS)-generating enzymes (e.g., NADPH oxidase) and upregulation of the expression and activity of ROS-scavenging enzymes (e.g., catalase and superoxide dismutase), consequently reducing ROS generation and mitigating oxidative stress-induced direct damage to renal vascular endothelial cells and tubular epithelial cells\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e; (3) synergistic inhibition of NF-κB activation and NLRP3 inflammasome assembly/activation, thereby reducing the production of key inflammatory cytokines such as interleukins (IL-6, IL-1β) and tumor necrosis factor-alpha (TNF-α), and attenuating renal tubular epithelial cell apoptosis, necrosis, and interstitial fibrosis\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e; and (4) upregulation of angiotensin-converting enzyme-2(ACE2) expression within the renin-angiotensin-aldosterone system (RAAS), leading to decreased angiotensin II (Ang II) levels and subsequent inhibition of cell proliferation and renal fibrosis\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Differential Efficacy of Statin Types and Dosages in Patients with AMI-AKI\u003c/h2\u003e \u003cp\u003eThis study revealed differential protective effects of various statins in patients with AMI-AKI: simvastatin and atorvastatin were associated with significantly reduced mortality, whereas no such benefit was observed for rosuvastatin or pravastatin. These findings are consistent with previous research:A meta-analysis encompassing 143,888 patients with chronic kidney disease (CKD) demonstrated that atorvastatin, simvastatin, and lovastatin reduced the risk of renal failure, while other statins did not exhibit this effect\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. A retrospective study by Li et al. involving 5,376 hospitalized patients with CKD also supported that atorvastatin was particularly effective in improving survival and reducing the risk of AKI\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. Furthermore, an animal study confirmed that simvastatin promoted renal functional recovery in mice with sepsis-associated AKI (SA-AKI) by regulating anti-apoptotic molecules\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. Conversely, rosuvastatin failed to prevent new-onset AKI or slow the progression of mild kidney injury in critically ill patients with acute respiratory distress syndrome (ARDS) and sepsis\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e.These discrepancies may be attributable to molecular structural differences: lipophilic statins (e.g., atorvastatin, simvastatin) more easily enter into the tissues by passive diffusion, exhibiting enhanc ed \"renophilic\" and demonstrating superiority over hydrophilic statins in ameliorating renal pathological damage and restoring renal function\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDosage stratification analysis indicated that the risk of mortality was significantly reduced in patients receiving either standard-dose or high-dose statin therapy; however, the magnitude of risk reduction was greatest in those receiving standard-dose statins. This finding suggests that, in the maintenance phase of treatment, standard-dose statins may provide adequate protection while being safer, whereas high-dose regimens, though similarly effective, could potentially increase the risk of dose-related adverse effects.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Subgroup Analysis\u003c/h2\u003e \u003cp\u003eSubgroup analysis revealed that the protective effect of statins was more pronounced in patients aged\u0026thinsp;\u0026le;\u0026thinsp;65 years, those without concurrent CHF, those not receiving antiplatelet agents, and those undergoing CABG or receiving beta-blocker therapy. Specifically, the age-stratified results are consistent with the research of Xiong et al.\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e, who found that the risk reduction for AKI associated with statin use was more prominent in obese patients with sepsis under 60 years of age, a finding potentially attributable to better baseline organ function and a lower burden of comorbidities in younger patients. Perioperative aspirin use has been shown to increase bleeding risk without reducing the risk of AKI in patients undergoing major non-cardiac surgery\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e, which may explain why the protective effect of statins in AMI-AKI patients could be attenuated by concomitant antiplatelet therapy. Statins may also trigger the systemic inflammatory response in patients with CHF\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e, so AMI-AKI patients without CHF may account for more pronounced benefit from statins.Conversely, the protective effect of statins was particularly prominent in patients undergoing CABG or receiving beta-blocker therapy. This finding may be related to the preoperative use of statins improving postoperative renal function following cardiac surgery\u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e and the potential synergistic effects of beta-blockers with statins in conferring renal protection in patients with AMI\u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Strengths and Limitations\u003c/h2\u003e \u003cp\u003eThis study was based on the publicly available and comprehensive MIMIC database, ensuring relatively high data reliability and integrity. As the first investigation to explore the association between statin therapy and prognosis in patients with AMI-AKI, we provide clear evidence that statin treatment is associated with a significantly reduced risk of mortality in this population, and further evaluate the impact of different statin types and dosages. These findings offer important insights for optimizing treatment strategies in critically ill patients with AMI-AKI and provide practical evidence for clinical decision-making in the ICU. However, this study has several limitations. First, the MIMIC-IV database predominantly comprises a White population; therefore, extrapolation of these findings to other racial or ethnic groups requires caution. Although the sample size was adequate and relatively representative, multicenter prospective studies are warranted to validate the generalizability of these results. Second, as a single-center retrospective study, despite the use of multivariable adjustment, PSM, and IPTW to control for confounding, potential biases cannot be entirely excluded. Prospective studies are needed to further validate the causal relationship and to comprehensively assess the benefits and risks associated with statin therapy in the future.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eStatin therapy was associated with a significantly reduced risk of mortality in patients with AMI-AKI, with more pronounced benefits observed for simvastatin and standard-dose strategies. This study supports the incorporation of statins into the comprehensive therapeutic management of critically ill patients with AMI-AKI to improve clinical outcomes.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAKI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAcute Kidney Injury\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAcute Myocardial Infarction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePSM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePropensity Score Matching\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIPTW\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInverse Probability of Treatment Weighting\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCABG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCoronary Artery Bypass Grafting\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCHF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCongestive Heart Failure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSTEMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eST-segment elevation myocardial infarction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNSTEMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enon-ST-segment elevation myocardial infarction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHMG-CoA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e3-hydroxy-3-methylglutaryl coenzyme A\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSBP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSystolic Blood Pressure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDBP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDiastolic Blood Pressure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMBP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMean Blood Pressure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSpO₂\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePeripheral Capillary Oxygen Saturation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWBC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWhite Blood Cell\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBUN\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBlood Urea Nitrogen\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRDW\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRed Blood Cell Distribution Width\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eINR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInternational Normalized Ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAPTT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eActivated Partial Thromboplastin Time\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTNT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTroponin T\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePVD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePeripheral Vascular Disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCVD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCardiovascular Disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCKD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChronic Kidney Disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSOFA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSequential Organ Failure Assessment\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSAPS II\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSimplified Acute Physiology Score II\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOASIS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOxford Acute Severity of Illness Score\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCharlson Comorbidity Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePercutaneous Coronary Intervention\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRRT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eContinuous Renal Replacement Therapy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eACEI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAngiotensin-Converting Enzyme Inhibitors\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eARB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAngiotensin II Receptor Blockers\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHazard Ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOdds Ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence Interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSMD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStandardized Mean Difference\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eML: Designed the study, and performed the statistical analysis. LL: Drafted the original manuscript. JL: Conducted data collection, and reviewed-edited the manuscript. All authors approved the final manuscript and are responsible for the content.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the National Natural Science Foundation of China (82003609), the Guangdong Basic and Applied Basic Research Foundation (2020A1515110453), Science and Technology Planning Project of Guangzhou (2024A04J4022 ).\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eD\u003c/strong\u003e\u003cstrong\u003eata a\u003c/strong\u003e\u003cstrong\u003evailability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets presented in the current study are available in the MIMIC-IV database (https://physionet.org/content/mimiciv/2.2/). All the data generated or analyzed during this study are available upon the corresponding author on reasonable request.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was conducted in compliance with the Helsinki Declaration\u0026rsquo;s guidelines. Approval for using the MIMIC-IV database was obtained from the IRBs of both MIT and BIDMC. The ethical approval previously granted for the MIMIC database covers the data used in this study, obviating the need for further ethical approval or informed consent.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAuthors information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLiying Luo and Mingliu Li contributed equally to this study and share first authorship.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eCorresponding author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to Jiahui Li\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eTsao CW, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, et al. 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KDIGO clinical practice guidelines for acute kidney injury [J]. Nephron Clin Pract. 2012;120(4):c179\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePandit AK, Kumar P, Kumar A, Chakravarty K, Misra S, Prasad K. High-dose statin therapy and risk of intracerebral hemorrhage: a meta-analysis [J]. Acta Neurol Scand. 2016;134(1):22\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen WH, Chen CH, Hsu MC, Chang RW, Wang CH, Lee TS. Advances in the molecular mechanisms of statins in regulating endothelial nitric oxide bioavailability: Interlocking biology between eNOS activity and L-arginine metabolism [J]. Biomed Pharmacother. 2024;171:116192.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiberale L, Carbone F, Montecucco F, Sahebkar A. Statins reduce vascular inflammation in atherogenesis: A review of underlying molecular mechanisms [J]. 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Protection of renal damage by HMG-CoA inhibitors: A comparative study between atorvastatin and rosuvastatin [J]. Iran J Basic Med Sci. 2020;23(2):206\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang J, Gu C, Gao M, Yu W, Yu Y. Preoperative Statin Therapy and Renal Outcomes After Cardiac Surgery: A Meta-analysis and Meta-regression of 59,771 Patients [J]. Can J Cardiol. 2015;31(8):1051\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarg AX, Kurz A, Sessler DI, Cuerden M, Robinson A, Mrkobrada M, et al. Perioperative aspirin and clonidine and risk of acute kidney injury: a randomized clinical trial [J]. JAMA. 2014;312(21):2254\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAhmad F, Karim A, Khan J, Qaisar R. Statin Therapy Induces Gut Leakage and Neuromuscular Disjunction in Patients With Chronic Heart Failure [J]. J Cardiovasc Pharmacol. 2023;82(3):189\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQueiroz RE, de Oliveira LS, de Albuquerque CA, Santana Cde A, Brasil PM, Carneiro LL, et al. Acute kidney injury risk in patients with ST-segment elevation myocardial infarction at presentation to the ED [J]. Am J Emerg Med. 2012;30(9):1921\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Acute myocardial infarction, Acute kidney injury, Statins, Propensity score matching, Inverse probability of treatment weighting","lastPublishedDoi":"10.21203/rs.3.rs-9118734/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9118734/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: Acute Kidney Injury (AKI) is a common complication in critically ill patients with Acute Myocardial Infarction (AMI) and is strongly associated with poor prognosis. Statins are widely used for cardiovascular protection, but their effect on AKI remains uncertain. This study aims to investigate the association between statin therapy and the prognosis of critically ill patients with myocardial infarction-related acute kidney injury (AMI-AKI), providing evidence-based support for clinical decision-making.\u003c/p\u003e\n\u003cp\u003eMethods: AMI-AKI patients were extracted from the MIMIC-IV database and divided into a statin group and a non-statin group based on statin use during their intensive care unit (ICU) stay. The primary outcome was 28-day mortality, and secondary outcomes included 90-day mortality, in-hospital mortality, and ICU mortality. Propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) were used to balance baseline differences between groups. Cox proportional hazards models and logistic regression models assessed the association of statin use, statin type, and statin dosage with clinical outcomes. Survival analysis was performed using Kaplan-Meier curves and Log-rank tests, and subgroup analyses were conducted to explore effect heterogeneity.\u003c/p\u003e\n\u003cp\u003eResults: A total of 3,844 AMI-AKI patients were included, of whom 72.6% received statin therapy during their ICU stay. Multivariable model results showed that statin use was significantly associated with reduced risks of 28-day mortality (HR = 0.621, 95% CI : 0.529-0.729), 90-day mortality (HR = 0.710, 95% CI : 0.617-0.816), in-hospital mortality (OR = 0.612, 95% CI : 0.489-0.767), and ICU mortality (OR = 0.535, 95% CI : 0.414-0.691). These associations remained significant after PSM and IPTW adjustments. Patients receiving simvastatin and standard-dose therapy showed the greatest reduction in mortality. Subgroup analysis revealed that the protective effect of statins was particularly pronounced in patients with AKI stage 3, age ≤65 years, those not using antiplatelet drugs, those without concomitant chronic heart failure (CHF), those undergoing coronary artery bypass grafting (CABG), or those receiving beta-blockers.\u003c/p\u003e\n\u003cp\u003eConclusion: Statin therapy is significantly associated with lower mortality risk in AMI-AKI patients, particularly with simvastatin and standard-dose strategies. This study supports integrating statins into the comprehensive treatment for critically ill AMI-AKI patients to improve clinical outcomes.\u003c/p\u003e","manuscriptTitle":"Prognostic Value of Statins in Critically Ill Patients with Acute Myocardial Infarction-Related Acute Kidney Injury: A Retrospective Cohort Study Based on the MIMIC-IV Database","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-23 16:26:57","doi":"10.21203/rs.3.rs-9118734/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"60783294309314156285330028745499836237","date":"2026-04-23T13:20:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-20T04:13:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"118485495046177873317695093642988187331","date":"2026-04-16T08:41:59+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-16T07:28:48+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-16T11:22:22+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-14T07:34:15+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-14T07:33:59+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cardiovascular Disorders","date":"2026-03-14T01:02:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8e00606b-36dc-45b2-86b7-97c10f63db9c","owner":[],"postedDate":"April 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-23T16:26:58+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-23 16:26:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9118734","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9118734","identity":"rs-9118734","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}