Association Between Lactate-to-Calcium Ratio and 28-Day Mortality in Patients With Sepsis-Induced Myocardial Injury: A Retrospective Cohort Study Based on the MIMIC-IV Database

Association Between Lactate-to-Calcium Ratio and 28-Day Mortality in Patients With Sepsis-Induced Myocardial 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 Association Between Lactate-to-Calcium Ratio and 28-Day Mortality in Patients With Sepsis-Induced Myocardial Injury: A Retrospective Cohort Study Based on the MIMIC-IV Database Li Dou, Sicheng Yuan, Xinru Hu, Yuwei Tan, Jing Wang, Jian Chen, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6788738/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Patients with sepsis-induced myocardial injury (SIMI) face a high risk of mortality. Although various biomarkers can be used to predict prognosis in SIMI patients, each has certain limitations. This study aimed to investigate the prognostic value of the lactate-to-calcium ratio (LCR) in patients with SIMI. Methods This retrospective cohort study was conducted using data from the MIMIC-IV database. Patients diagnosed with SIMI who were admitted to the ICU were included. The LCR was calculated based on the first arterial blood gas analysis performed within 24 hours of ICU admission. A restricted cubic spline (RCS) model was used to explore the nonlinear relationship between LCR and 28-day mortality. Patients were divided into high and low LCR groups based on the cutoff values, both overall and by sex. Kaplan–Meier survival curves were used to compare 28-day mortality between groups. Stratification analyses were conducted to assess the prognostic value of LCR across different age strata. Results A total of 1,631 patients were included. The RCS model revealed a positive association between higher LCR and increased 28-day mortality. The cut-off values for LCR were 2.96 for the overall population, 2.91 for females, and 2.16 for males. Cox regression analysis showed that high LCR was significantly associated with higher 28-day mortality (log-rank P < 0.001). Age-stratified analysis indicated that LCR had a higher predictive value in patients younger than 65 years. Among males, high LCR was associated with increased 28-day mortality only in those younger than 65. In females, the association was consistent regardless of age. Conclusion A higher LCR is associated with increased 28-day mortality in ICU patients with SIMI. The sex-specific cut-off values (2.91 for females and 2.16 for males) suggest that LCR may serve as a useful prognostic indicator for identifying high-risk patients with sepsis-induced myocardial injury. Sepsis-induced myocardial injury Lactate-to-ionized calcium ratio 28-day mortality Cut-off value Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Sepsis is a systemic inflammatory response triggered by infection, accompanied by immune dysregulation, microcirculatory dysfunction, and multiple organ failure. Despite significant advances in infection control, fluid resuscitation, and organ support in critical care medicine, the global mortality rate of sepsis remains as high as 20–30%[ 1 ]. Studies have shown that sepsis can lead to dysfunction in multiple organs, with the heart being one of the most vulnerable. The incidence of myocardial involvement ranges from 30–60%, making it one of the major contributors to sepsis-related mortality and prolonged treatment duration[ 2 ] Clinically, patients with sepsis and concurrent cardiac dysfunction are defined as having sepsis-induced myocardial injury (SIMI), which may be attributed to mechanisms such as systemic inflammation, oxidative stress, microcirculatory impairment, ischemia and hypoxia, as well as calcium homeostasis imbalance[ 3 ][ 4 ][ 5 ]. During sepsis, a large number of inflammatory mediators are released, which disrupt calcium homeostasis by impairing calcium absorption and increasing calcium excretion[ 6 ]. Calcium ions play a critical role in excitation-contraction coupling of cardiomyocytes. Hypocalcemia directly leads to insufficient cytoplasmic Ca²⁺ concentration in cardiac cells. Moreover, in sepsis, the function of calcium reuptake pumps (SERCA pumps)[ 7 ][ 8 ][ 9 ]and ryanodine receptors is impaired, further exacerbating calcium imbalance[ 10 ]. Such a hypocalcemic environment can directly reduce myocardial contractility, impair mitochondrial function by inhibiting ATP synthesis[ 11 ], or prolong cardiomyocyte action potential duration, which may trigger arrhythmias. These factors collectively contribute to the development of myocardial injury in patients with sepsis[ 12 ][ 13 ]. However, the pathophysiological mechanisms of sepsis are not limited to inflammatory responses[ 14 ]. Microcirculatory dysfunction, which leads to inadequate tissue perfusion and metabolic disturbances, also contributes significantly to cardiac dysfunction. Elevated lactate levels in patients are often indicative of poor tissue perfusion[ 15 ]. Accumulation of lactate can lower both intracellular and extracellular pH, thereby suppressing myocardial contractility. Lactate may also inhibit pyruvate dehydrogenase (PDH) activity[ 16 ][ 17 ], reduce the production of acetyl-CoA, and diminish ATP generation, further exacerbating myocardial energy deficiency. In a high-lactate environment, increased generation of reactive oxygen species (ROS) may occur, activating the NLRP3 inflammasome and amplifying myocardial inflammation[ 18 ]. Several studies have demonstrated a synergistic effect between Ca²⁺ deficiency and lactic acidosis. For instance, protons (H⁺) may compete with Ca²⁺ for binding to troponin C, further impairing contractility. Additionally, lactate may enter cardiomyocytes via monocarboxylate transporters (MCTs) and directly inhibit L-type calcium channel (LTCC) activity[ 19 ][ 20 ], thereby reducing Ca²⁺ influx. In the prognostic evaluation of sepsis-induced myocardial injury (SIMI), relying solely on either blood calcium or lactate levels has inherent limitations. Lactate levels can be influenced by early resuscitation and liver function, while serum calcium levels are affected by parathyroid function and acid–base balance. By combining these two indicators into the lactate-to-ionized calcium ratio (LCR), it is possible to integrate information on both calcium homeostasis imbalance and metabolic dysfunction, offering a more comprehensive and dynamic assessment of SIMI pathophysiology and prognosis. Therefore, in this study, we utilized the Medical Information Mart for Intensive Care IV (MIMIC-IV) database to construct a nonlinear regression model, determine optimal LCR cut-off values, and investigate the association between LCR and adverse outcomes in patients with SIMI. Methods and Materials Data Source The data used in this study were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database, a large, publicly available critical care database developed and maintained by the Laboratory for Computational Physiology at the Massachusetts Institute of Technology (MIT). The database contains de-identified health-related data of patients admitted to the intensive care units (ICUs) of Beth Israel Deaconess Medical Center between 2008 and 2019. The first author of this study completed the required training and obtained access to the database (Certification Number: 67880992). The use of the MIMIC-IV database for research has been approved by the Institutional Review Boards of MIT and Beth Israel Deaconess Medical Center, with a waiver of informed consent. Study Population and Definitions Data were extracted from the MIMIC-IV database for patients who were admitted to the ICU for the first time and met the diagnostic criteria for sepsis-induced myocardial injury (SIMI). The inclusion criteria for patient selection were as follows:(1) Meeting the Sepsis-3 diagnostic criteria;(2) Meeting the diagnostic definition of SIMI;(3) Age ≥ 18 years. Based on the diagnostic criteria and limitations of the database, SIMI was defined as a cardiac troponin T (cTnT) level greater than 0.01 ng/mL measured within the first 24 hours of ICU admission. Exclusion criteria were established to eliminate cases in which elevated cTnT levels might be attributed to other causes, including acute coronary syndrome, myocarditis, pericarditis, valvular heart disease, congestive heart failure, or cardiac arrest. All diagnoses were based on ICD-9/10 codes. Data Extraction The extracted variables included demographic information, vital signs, comorbidities, basic laboratory parameters, and pre-treatment severity scores:(1) Demographics: sex and age;(2) Vital signs: heart rate, respiratory rate, peripheral oxygen saturation (SpO₂), systolic blood pressure (SBP), diastolic blood pressure (DBP), and body temperature;(3) Comorbidities: chronic pulmonary disease, diabetes, renal insufficiency, severe liver disease, cerebrovascular disease, and malignant cancer;(4) Laboratory tests: the first laboratory values obtained within 24 hours of ICU admission, including white blood cell (WBC) count, hemoglobin, platelet count, blood urea nitrogen (BUN), creatinine, glucose, creatine kinase-MB (CK-MB), aspartate aminotransferase (AST), alanine aminotransferase (ALT), total bilirubin, cardiac troponin T (cTnT), lactate, and ionized calcium;(5) Additional clinical information during ICU stay: the first Sequential Organ Failure Assessment (SOFA) score, Acute Physiology Score III (APS III), Simplified Acute Physiology Score II (SAPS II), Logistic Organ Dysfunction Score (LODS), Oxford Acute Severity of Illness Score (OASIS), Glasgow Coma Scale (GCS), and Charlson Comorbidity Index. Exposure All laboratory parameters obtained from the MIMIC-IV (v3.0) database were assessed at the time of the first measurement after ICU admission. The LCR was calculated as the ratio of lactate to ionized calcium, with a low LCR defined as low exposure and a high LCR defined as high exposure based on the cut-off point. Outcomes Survival status at 28 days (death or survival) was measured starting from the day of ICU admission. The event of interest is defined as the time of death on day 28. Covariates The baseline characteristics of patients including time of ICU admission, demographic characteristics (gender and age), medical history (cerebrovascular disease, chronic pulmonary disease, diabetes, renal disease, malignant cancer and severe liver disease ), laboratory tests ( troponin T, hemoglobin, platelet, WBC, BUM, creatinine, glucose, CK-MB, ALT, AST, bilirubin total and the current health status (the score of SIRS, SOFA, SAPS II, GCS, LODS,APS III, and OASIS, and heart rate, SBP, DBP, temperature, resp rate and SpO2). Statistical Analysis Variables with more than 20% missing data were excluded. Missing values for remaining variables were imputed using multiple imputation, and the imputed dataset was analyzed for three distinct populations: the overall population, and separate male and female populations. A restricted cubic spline (RCS) plot was created to explore the non-linear relationship between LCR and 28-day mortality. The optimal cut-off value for LCR was determined using the surv_cutpoint function from the survminer R package, categorizing the population into low and high LCR groups, both for the entire cohort and stratified by sex. Continuous variables were described as means with standard deviations (SD) or medians with interquartile ranges (IQR), based on their distribution. The normality of the data was assessed using the Shapiro-Wilk test, and t-tests or Wilcoxon rank-sum tests were applied accordingly. Categorical variables were presented as frequencies and percentages, with differences between groups evaluated using the Chi-square test or Fisher's exact test when appropriate. Kaplan-Meier survival curves were constructed to compare 28-day mortality between LCR groups, with statistical significance tested by the Log-rank test. Cox proportional hazards models were used to estimate the association between the LCR and 28-day mortality, with the hazard ratio (HR) representing the strength of the association. Model 1 included only the LCR without any additional adjustments. Model 2 adjusted for confounders, including the SOFA score, APACHE II score, and age. Model 3 incorporated further adjustments for laboratory tests and comorbidities that significantly differed between groups. To examine potential age-related differences in the effect of LCR on 28-day mortality, stratified Cox regression analyses were performed by age, with a cut-off at 65 years, and adjustments were made for the same confounders as in Model 3. All statistical analyses were conducted using R (version 4.3.0). R packages tidyverse, mice, glm, autoReg, survival, survminer, splines, forestplot and ggplot2 were used for data management, statistical analysis and drawing statistical plots. Two-sided hypothesis test was used, and the significance level α = 0.05 was set. Results Baseline Figure 1 illustrates the flowchart of the participant screening process. According to the inclusion criteria, a total of 1,631 patients were enrolled in this study from the MIMIC-IV database based on the inclusion and exclusion criteria, consisting of 671 females(41.14%,64.89 ± 15.73 years) and 960 males(58.86%,62.73 ± 16.97years). More details in Table S1 . Detection of nonlinear relationship The restricted cubic spline regression model was applied, revealing that as LCR increases, the hazard ratio (HR) for 28-day mortality also increases(Fig. 2 ), indicating a positive association between higher LCR and an elevated risk of mortality. Cutoff values for different groups Based on the LCR distribution and maximally selected rank statistics graphs, the LCR values differentiate the two groups, with the high group showing a stronger association between the variable and the outcome. The cut-off values were 2.96 for all, 2.91 for females, and 2.16 for males(Fig. 3 A- 3 C). Each picture consists of two parts, the upper and the lower. The upper graph is the LCR (Log-Cumulative Rank) Distribution Graph, showing the density distribution and cumulative distribution function (CDF) of LCR values for different groups. The lower graph is the Maximally Selected Rank Statistics Graph, illustrating the relationship between standardized log-rank statistics and LCR values, highlighting statistical differences between the groups across different LCR ranges. Comparison of patients’ baseline information In Table 1 , a comparison between the high and low groups revealed that patients in the high group were more likely to experience a death outcome within 28 days. These patients tended to be younger, with a lower prevalence of cerebrovascular disease and chronic pulmonary disease, but a higher prevalence of renal disease, severe liver disease, and elevated heart rate and respiratory rate. Moreover, patients in the high group demonstrated significantly higher levels of SIRS, SOFA,SAPSII, GCS, APS III, LODS, OASIS, Troponin T, hemoglobin, WBC, creatinine, glucose, CK-MB, ALT, AST, and bilirubin. Similarly, among both females and males, the high group was more likely to experience a death outcome within 28 days, with a younger age and higher SOFA and APS III scores compared to the low group. Detailed baseline characteristics are presented in Table 1 A- 1 C. Table 1 A Differential analysis between high and low LCR groups in the overall patients. Variables group Statistics P low ( n = 1130) high ( n = 501) Characteristic Sex, n (%) χ 2 = 1.217 1 0.270 Female 475 (42.04) 196 (39.12) Male 655 (57.96) 305 (60.88) Age, y,Mean ± SD 64.73 ± 16.02 61.10 ± 17.30 t = 3.998 2 < 0.001 Vital signs, Mean ± SD Heart rate, beats/min 92.00 ± 21.30 100.76 ± 22.42 t =-7.537 4 < 0.001 Systolic blood pressure, mmHg 123.18 ± 26.86 116.30 ± 27.49 t = 4.737 4 < 0.001 Diastolic blood pressure, mmHg 68.71 ± 19.42 67.32 ± 19.90 t = 1.325 4 0.185 Temperature,℃ 36.76 ± 1.03 36.28 ± 1.49 t = 6.496 2 < 0.001 Resp rate, beats/min 20.88 ± 6.13 22.44 ± 6.93 t =-4.322 2 < 0.001 SpO2,% 96.64 ± 4.34 96.48 ± 5.81 t = 0.577 2 0.564 Scores SIRS, Mean ± SD 2.99 ± 0.87 3.31 ± 0.72 t =-7.169 4 < 0.001 SOFA, M (Q 1 , Q 3 ) 7.00 (4.00, 10.00) 9.00 (7.00, 12.00) Z =-11.920 3 < 0.001 SAPSII, Mean ± SD 44.98 ± 14.20 53.19 ± 16.13 t =-9.821 2 < 0.001 GCS, Mean ± SD 14.85 ± 0.78 14.92 ± 0.53 t =-2.136 2 0.033 APSIII, M (Q 1 , Q 3 ) 57.00 (43.00, 74.00) 72.00 (55.00, 93.00) Z =-10.968 3 < 0.001 LODS, M (Q 1 , Q 3 ) 7.00 (5.00, 9.00) 8.00 (6.00, 11.00) Z =-9.670 3 < 0.001 OASIS, Mean ± SD 37.50 ± 8.11 40.88 ± 8.71 t =-7.379 2 < 0.001 Charlson comorbidity index, M (Q 1 , Q 3 ) 5.00 (3.00, 7.00) 4.00 (2.00, 6.00) Z = 3.721 3 < 0.001 Laboratory values on admission Troponin T,ng/mL, M (Q 1 , Q 3 ) 0.06 (0.03, 0.15) 0.08 (0.04, 0.25) Z =-4.505 3 < 0.001 Hemoglobin, g/dL,Mean ± SD 10.72 ± 2.41 11.02 ± 2.71 t =-2.132 2 0.033 Platelet,×10 9 ,M (Q 1 , Q 3 ) 192.00 (128.00, 263.75) 166.00 (100.00, 243.00) Z = 4.746 3 < 0.001 WBC,×10 9 , M (Q 1 , Q 3 ) 12.50 (8.50, 17.60) 14.70 (8.80, 21.10) Z =-3.666 3 < 0.001 BUN,mg/dL, M (Q 1 , Q 3 ) 26.00 (16.00, 45.00) 25.00 (16.00, 44.00) Z = 0.352 3 0.725 Creatinine, mg/dL,M (Q 1 , Q 3 ) 1.20 (0.80, 2.30) 1.60 (1.10, 2.50) Z =-5.044 3 < 0.001 Glucose,mg/dL, M (Q 1 , Q 3 ) 136.00 (109.25, 174.00) 168.00 (124.00, 246.00) Z =-8.324 3 < 0.001 CK-MB,IU/L, M (Q 1 , Q 3 ) 6.00 (3.00, 11.75) 10.00 (4.00, 24.00) Z =-7.293 3 < 0.001 ALT,U/L, M (Q 1 , Q 3 ) 31.00 (18.00, 68.75) 70.00 (28.00, 245.00) Z =-10.940 3 < 0.001 AST,U/L, M (Q 1 , Q 3 ) 48.00 (28.00, 114.00) 133.00 (48.00, 492.00) Z =-12.398 3 < 0.001 Bilirubin total, mg/dL,M (Q 1 , Q 3 ) 0.60 (0.40, 1.30) 0.90 (0.50, 2.20) Z =-5.701 3 < 0.001 Comorbidites, n (%) Cerebrovascula χ 2 = 28.851 1 < 0.001 No 856 (75.75) 438 (87.43) Yes 274 (24.25) 63 (12.57) Chronic pulmonary disease χ 2 = 6.415 1 0.011 No 866 (76.64) 412 (82.24) Yes 264 (23.36) 89 (17.76) Diabetes χ 2 = 0.697 1 0.404 No 805 (71.24) 367 (73.25) Yes 325 (28.76) 134 (26.75) Renal disease χ 2 = 23.959 1 < 0.001 No 853 (75.49) 432 (86.23) Yes 277 (24.51) 69 (13.77) Malignant cancer χ 2 = 0.124 1 0.725 No 975 (86.28) 429 (85.63) Yes 155 (13.72) 72 (14.37) Severe liver disease χ 2 = 11.985 1 0.001 No 1010 (89.38) 417 (83.23) Yes 120 (10.62) 84 (16.77) Outcomes 28-day mortality, n (%) χ 2 = 53.571 1 < 0.001 Alive 770 (68.14) 246 (49.10) Dead 360 (31.86) 255 (50.90) Survival,day, M (Q 1 , Q 3 ) 19.13 (6.82, 28.00) 6.27 (1.86, 23.01) Z = 9.205 3 < 0.001 1.Pearson χ² test 2.Variance-corrected independent samples t-test 3.Mann-Whitney U test 4.Independent samples t-test SIRS:Systemic Inflanmmatory Response Syndrome, SOFA: Sepsis-Organ Failure Assessment Score, SAPSII: Simplified Acute Physiology Score II, GCS: Glasgow Coma Scale, APSIII: Acute Physiology Score III, LODS: Logistic Organ Dysfunction Score, OASIS: Oxford Acute Severity of Illness,WBC: white blood cells, BUN: blood urea nitrogen, ALT: alanine aminotransferase, AST: aspartate aminotransferase, CK-MB:Creatine Kinase,MB Form Table 1 B Differential analysis between high and low LCR groups in the female patients. Variables group Statistic P low ( n = 472) high ( n = 199) Age,y, Mean ± SD 65.48 ± 15.25 63.47 ± 16.78 t = 1.510 1 0.131 Vital signs,Mean ± SD Heart rate, beats/min, Mean ± SD 93.32 ± 20.98 98.40 ± 23.58 t =-2.627 4 0.009 Systolic blood pressure, mmHg, Mean ± SD 121.83 ± 27.06 117.23 ± 28.39 t = 1.982 1 0.048 Diastolic blood pressure, mmHg, Mean ± SD 66.99 ± 19.82 67.59 ± 20.32 t =-0.351 1 0.726 Temperature,℃, Mean ± SD 36.73 ± 1.09 36.11 ± 1.45 t = 5.493 4 < 0.001 Resp rate, beats/min, M (Q 1 , Q 3 ) 20.00 (17.00, 24.00) 21.00 (17.00, 28.00) Z =-2.249 2 0.025 SpO2,%, Mean ± SD 96.67 ± 4.13 96.61 ± 5.55 t = 0.136 4 0.892 Scores SIRS, Mean ± SD 3.05 ± 0.88 3.29 ± 0.74 t =-3.365 1 0.001 SOFA, M (Q 1 , Q 3 ) 6.50 (4.00, 9.00) 9.00 (6.00, 12.00) Z =-7.292 2 < 0.001 SAPSII, Mean ± SD 45.11 ± 14.35 53.21 ± 15.52 t =-6.516 1 < 0.001 GCS, Mean ± SD 14.86 ± 0.67 14.88 ± 0.74 t =-0.256 1 0.798 APSIII, M (Q 1 , Q 3 ) 57.50 (42.75, 75.00) 72.00 (53.00, 89.00) Z =-6.469 2 < 0.001 LODS, M (Q 1 , Q 3 ) 6.00 (5.00, 9.00) 8.00 (6.00, 11.00) Z =-5.800 2 < 0.001 OASIS, Mean ± SD 37.76 ± 7.95 40.83 ± 8.41 t =-4.496 1 < 0.001 Charlson comorbidity index, M (Q 1 , Q 3 ) 5.00 (3.00, 7.00) 4.00 (2.00, 6.00) Z = 1.485 2 0.138 Laboratory values on admission Troponin T,ng/mL, M (Q 1 , Q 3 ) 0.06 (0.03, 0.15) 0.09 (0.04, 0.32) Z =-3.157 2 0.002 Hemoglobin, g/dL,Mean ± SD 10.41 ± 2.19 10.44 ± 2.29 t =-0.118 1 0.906 Platelet,×10 9 ,M (Q 1 , Q 3 ) 201.00 (131.75, 277.50) 164.00 (102.50, 250.50) Z = 3.377 2 0.001 WBC,×10 9 , M (Q 1 , Q 3 ) 13.20 (9.20, 18.02) 15.10 (8.90, 21.40) Z =-1.947 2 0.052 BUN,mg/dL, M (Q 1 , Q 3 ) 24.00 (14.00, 42.25) 23.00 (14.00, 40.00) Z = 0.393 2 0.695 Creatinine, mg/dL,M (Q 1 , Q 3 ) 1.10 (0.70, 2.10) 1.20 (0.90, 2.10) Z =-2.032 2 0.042 Glucose,mg/dL, M (Q 1 , Q 3 ) 141.00 (116.00, 181.25) 162.00 (128.50, 239.50) Z =-4.330 2 < 0.001 CK-MB,IU/L, M (Q 1 , Q 3 ) 6.00 (3.00, 11.00) 10.00 (4.00, 24.50) Z =-5.367 2 < 0.001 ALT,U/L, M (Q 1 , Q 3 ) 31.00 (17.00, 67.25) 65.00 (25.00, 283.50) Z =-6.385 2 < 0.001 AST,U/L, M (Q 1 , Q 3 ) 47.00 (28.00, 115.75) 124.00 (42.00, 660.00) Z =-8.005 2 < 0.001 Bilirubin total, mg/dL,M (Q 1 , Q 3 ) 0.60 (0.30, 1.20) 0.90 (0.50, 2.25) Z =-4.341 2 < 0.001 Comorbidites, n (%) Cerebrovascular, n (%) χ 2 = 6.974 3 0.008 No 352 (74.58) 167 (83.92) Yes 120 (25.42) 32 (16.08) Chronic pulmonary disease, n (%) χ 2 = 0.127 3 0.722 No 352 (74.58) 151 (75.88) Yes 120 (25.42) 48 (24.12) Diabetes, n (%) χ 2 = 2.065 3 0.151 No 340 (72.03) 154 (77.39) Yes 132 (27.97) 45 (22.61) Renal disease, n (%) χ 2 = 12.903 3 < 0.001 No 357 (75.64) 175 (87.94) Yes 115 (24.36) 24 (12.06) Malignant cancer, n (%) χ 2 = 1.733 3 0.188 No 414 (87.71) 167 (83.92) Yes 58 (12.29) 32 (16.08) Severe liver disease, n (%) χ 2 = 0.704 3 0.401 No 421 (89.19) 173 (86.93) Yes 51 (10.81) 26 (13.07) Outcomes survival, day, M (Q 1 , Q 3 ) 17.77 (6.63, 28.00) 6.35 (1.84, 21.33) Z = 5.770 2 < 0.001 28-day mortality, n (%) χ 2 = 31.853 3 < 0.001 Alive 323 (68.43) 90 (45.23) Dead 149 (31.57) 109 (54.77) 1.Pearson χ² test Independent samples t-test 2.Mann-Whitney U test 3. Pearson χ² test 4.Variance-corrected independent samples t-test SIRS:Systemic Inflanmmatory Response Syndrome, SOFA: Sepsis-Organ Failure Assessment Score, SAPSII: Simplified Acute Physiology Score II, GCS: Glasgow Coma Scale, APSIII: Acute Physiology Score III, LODS: Logistic Organ Dysfunction Score, OASIS: Oxford Acute Severity of Illness,WBC: white blood cells, BUN: blood urea nitrogen, ALT: alanine aminotransferase, AST: aspartate aminotransferase, CK-MB:Creatine Kinase,MB Form Table 1 C Differential analysis between high and low LCR groups in the male patients. Variables group Statistic P low ( n = 534) high ( n = 426) Age,y, Mean ± SD 64.37 ± 16.21 60.68 ± 17.69 t = 3.335 1 0.001 Vital signs,Mean ± SD Heart rate, beats/min, Mean ± SD 90.04 ± 21.42 100.31 ± 21.66 t =-7.342 4 < 0.001 Systolic blood pressure, mmHg, Mean ± SD 125.22 ± 26.58 116.81 ± 26.91 t = 4.843 4 < 0.001 Diastolic blood pressure, mmHg, Mean ± SD 70.27 ± 18.61 67.56 ± 19.99 t = 2.169 4 0.030 Temperature,℃, Mean ± SD 36.79 ± 0.98 36.48 ± 1.40 t = 3.978 1 < 0.001 Resp rate, beats/min, M (Q 1 , Q 3 ) 20.70 ± 6.20 22.19 ± 6.70 t =-3.571 4 < 0.001 SpO2,%, Mean ± SD 96.61 ± 4.63 96.48 ± 5.45 t = 0.410 4 0.682 Scores SIRS, Mean ± SD 2.92 ± 0.87 3.24 ± 0.74 t =-6.176 4 < 0.001 SOFA, M (Q 1 , Q 3 ) 7.00 (4.00, 10.00) 9.00 (7.00, 12.00) Z =-8.911 2 < 0.001 SAPSII, Mean ± SD 44.41 ± 14.06 51.36 ± 16.12 t =-7.025 1 < 0.001 GCS, Mean ± SD 14.85 ± 0.84 14.92 ± 0.57 t =-1.430 1 0.153 APSIII, M (Q 1 , Q 3 ) 56.00 (42.25, 70.75) 69.00 (54.00, 92.00) Z =-9.067 2 < 0.001 LODS, M (Q 1 , Q 3 ) 7.00 (5.00, 9.00) 8.00 (6.00, 10.00) Z =-7.407 2 < 0.001 OASIS, Mean ± SD 37.25 ± 8.17 39.95 ± 8.91 t =-4.855 1 < 0.001 Charlson comorbidity index, M (Q 1 , Q 3 ) 5.00 (3.00, 7.00) 4.00 (2.00, 6.00) Z = 2.802 2 0.005 Laboratory values on admission Troponin T,ng/mL, M (Q 1 , Q 3 ) 0.06 (0.03, 0.15) 0.08 (0.04, 0.19) Z =-2.720 2 0.007 Hemoglobin, g/dL,Mean ± SD 10.93 ± 2.43 11.28 ± 2.90 t =-2.046 1 0.041 Platelet,×10 9 ,M (Q 1 , Q 3 ) 187.50 (129.25, 253.75) 170.50 (101.00, 242.00) Z = 3.439 2 0.001 WBC,×10 9 , M (Q 1 , Q 3 ) 11.80 (7.80, 16.80) 13.85 (9.00, 20.28) Z =-4.086 2 < 0.001 BUN,mg/dL, M (Q 1 , Q 3 ) 26.00 (18.00, 47.00) 27.00 (17.00, 46.75) Z =-0.062 2 0.950 Creatinine, mg/dL,M (Q 1 , Q 3 ) 1.25 (0.90, 2.38) 1.60 (1.10, 2.60) Z =-4.315 2 < 0.001 Glucose,mg/dL, M (Q 1 , Q 3 ) 130.00 (107.00, 164.00) 160.00 (115.00, 235.00) Z =-6.190 2 < 0.001 CK-MB,IU/L, M (Q 1 , Q 3 ) 6.00 (3.00, 12.75) 8.00 (4.00, 19.75) Z =-3.827 2 < 0.001 ALT,U/L, M (Q 1 , Q 3 ) 31.00 (18.00, 69.75) 55.50 (26.00, 195.00) Z =-7.271 2 < 0.001 AST,U/L, M (Q 1 , Q 3 ) 46.00 (27.00, 111.00) 96.00 (46.00, 324.75) Z =-8.643 2 < 0.001 Bilirubin total, mg/dL,M (Q 1 , Q 3 ) 0.60 (0.40, 1.20) 0.90 (0.50, 2.27) Z =-5.664 2 < 0.001 Comorbidites, n (%) Cerebrovascular, n (%) χ 2 = 27.940 3 < 0.001 No 399 (74.72) 376 (88.26) Yes 135 (25.28) 50 (11.74) Chronic pulmonary disease, n (%) χ 2 = 9.889 3 0.002 No 412 (77.15) 363 (85.21) Yes 122 (22.85) 63 (14.79) Diabetes, n (%) χ 2 = 0.000 3 0.984 No 377 (70.60) 301 (70.66) Yes 157 (29.40) 125 (29.34) Renal disease, n (%) χ 2 = 9.838 3 0.002 No 399 (74.72) 354 (83.10) Yes 135 (25.28) 72 (16.90) Malignant cancer, n (%) χ 2 = 0.001 3 0.969 No 458 (85.77) 365 (85.68) Yes 76 (14.23) 61 (14.32) Severe liver disease, n (%) χ 2 = 30.163 3 < 0.001 No 492 (92.13) 341 (80.05) Yes 42 (7.87) 85 (19.95) Outcomes survival, day, M (Q 1 , Q 3 ) 24.86 (8.08, 28.00) 6.90 (2.08, 25.70) Z = 7.717 2 < 0.001 28-day mortality, n (%) χ 2 = 35.907 3 < 0.001 Alive 380 (71.16) 223 (52.35) Dead 154 (28.84) 203 (47.65) 1. Variance-corrected independent samples t-test 2.Mann-Whitney U test 3. Pearson χ² test 4.Independent samples t-test SIRS:Systemic Inflanmmatory Response Syndrome, SOFA: Sepsis-Organ Failure Assessment Score, SAPSII: Simplified Acute Physiology Score II, GCS: Glasgow Coma Scale, APSIII: Acute Physiology Score III, LODS: Logistic Organ Dysfunction Score, OASIS: Oxford Acute Severity of Illness,WBC: white blood cells, BUN: blood urea nitrogen, ALT: alanine aminotransferase, AST: aspartate aminotransferase, CK-MB:Creatine Kinase,MB Form Survival analysis We conducted a Kaplan-Meier survival analysis to compare the incidence of 28-day mortality and survival time between the groups. The 28-day mortality rate was significantly higher in the high group compared to the low group (log-rank P < 0.001)(Fig. 4 A). Similarly, within both the female and male subgroups, the high group demonstrated a significantly higher mortality rate than the low group (log-rank P < 0.001)(Fig. 4 B- 4 C). Relationship between different levels of LCR and clinical outcome indicators We used Cox proportional hazards models to examine the association between LCR and 28-day mortality across different subgroups. In Model 1 (unadjusted), patients in the high LCR group had a significantly higher risk of 28-day mortality compared to the low LCR group, with a 102% increase in the overall population [HR (95% CI): 2.02 (1.72–2.37), P < 0.001], a 100% increase among females [HR (95% CI): 2.00 (1.56–2.56), P < 0.001], and a 113% increase among males [HR (95% CI): 2.13 (1.73–2.63), P < 0.001]. In Model 2, after adjusting for SOFA score, APS III score, and age, the high LCR group remained significantly associated with increased 28-day mortality in the overall cohort [HR (95% CI): 1.77 (1.49–2.09), P < 0.001], females [HR (95% CI): 1.82 (1.49–2.36), P < 0.001], and males [HR (95% CI): 1.83 (1.47–2.28), P < 0.001]. In Model 3, after further adjustment for additional confounders including clinical scores, laboratory markers, vital signs, and comorbidities, high LCR remained independently associated with increased 28-day mortality in the overall population [HR (95% CI): 1.67 (1.38–2.02), P < 0.001], females [HR (95% CI): 1.82 (1.49–2.36), P < 0.001], and males [HR (95% CI): 1.83 (1.44–2.33), P < 0.001] (Table 2 ). Table 2 Cox regression of LCR and 28-day mortality Population Categories Model 1 Model 2 Model 3 HR(95%CI) P-value HR(95%CI) P-value HR(95%CI) P-value All LCR low Ref Ref Ref high 2.02 (1.72, 2.37) < 0.001 1.77 (1.49, 2.09) < 0.001 1.67 (1.38–2.02) < 0.001 Female LCR low Ref Ref Ref high 2.00 (1.56, 2.56) < 0.001 1.82 (1.40, 2.36) < 0.001 1.73 (1.29–2.32) < 0.001 Male LCR low Ref Ref Ref high 2.13 (1.73, 2.63) < 0.001 1.83 (1.47, 2.28) < 0.001 1.83 (1.44–2.33) < 0.001 Model 1: unadjusted model. Mode 2: adjusted for sofa, apsiii, age. Mode 3: adjusted for sofa, apsiii, age, sirs, sapsii, gcs, lods, oasis, troponin t, hemoglobin, wbc, creatinine, glucose, ck-mb, al, ast, bilirubin total, cerebrovascular, chronic pulmonary disease, renal disease, heart rate, resp rate, platelet, severe liver disease, charlson comorbidity, sbp, temperature in the overall population; adjusted for sofa, apsiii, age, sirs, sapsii, lods, oasis, troponin t, creatinine, glucos, ck-mb, alt, as, bilirubin total, cerebrovascular disease, renal disease, heart rate, resp rate, platele, sbp, temperature in the female; adjusted for sofa, apsiii, age, sirs, sapsii, lods, oasis, troponin t, hemoglobin, wbc, creatinine, glucose, ck-mb, alt, ast, bilirubin total, cerebrovascular disease, chronic pulmonary disease, renal disease, heart rate, resp rate, platelet, severe liver disease, charlson comorbidit, sbp, dbp, temperatur in the male. Stratification analysis The age-stratified Cox regression analysis showed that in the overall population, patients with high LCR aged < 65 years had a significantly higher 28-day mortality risk [HR (95% CI): 1.99 (1.47–2.69)] than thoese aged ≥ 65 years[HR (95% CI): 1.35 (1.05–1.74)], and the multiplicative interaction between age group and LCR was statistically significant (P for interaction < 0.05). In females, the 28-day mortality risk in the high LCR group was similar between those aged 0.05). However, among male patients, those aged < 65 years with high LCR had a notably higher 28-day mortality risk [HR (95% CI): 2.76 (1.86–4.10)]. In contrast, high LCR was not significantly associated with 28-day mortality risk in males aged ≥ 65 years [HR (95% CI): 1.34 (0.97–1.85), P > 0.05] (Fig. 5 ). Discussion Currently, studies focusing on prognostic predictors for patients with SIMI are relatively limited. Most existing literature investigates single biomarkers; however, due to the complex pathological features of SIMI, relying on a single indicator has obvious limitations. In this retrospective study based on the MIMIC-IV database, we found that an increased LCR was significantly positively associated with 28-day all-cause mortality during ICU stay in patients with SIMI [ 21 ][ 22 ]. This index reflects the pathological changes of septic myocardial injury from multiple perspectives. We identified the optimal cutoff value of LCR as 2.96. Considering gender differences, we performed subgroup analyses and found that the optimal cutoff values were 2.91 and 2.18 for female and male patients, respectively. The underlying reasons for these gender differences remain unclear but may be related to higher muscle mass in males, which accelerates anaerobic metabolism and lactate production during tissue hypoxia. Meanwhile, the increased calcium demand in males may make them more susceptible to mild hypocalcemia, leading to muscle weakness and diaphragmatic dysfunction. Furthermore, survival advantage in females may shift the cutoff values upward. Previous studies have shown that female septic patients tend to have higher survival rates than males [ 23 ][ 24 ]. Therefore, at equivalent lactate and ionized calcium levels, females appear to have a lower risk of mortality, requiring higher lactate or lower calcium levels to reach statistical significance. We stratified patients into high and low LCR groups based on the cutoff values, and the results demonstrated a significantly increased 28-day mortality rate in the high LCR group. To further validate the stability of these findings, we constructed Cox proportional hazards models to explore the relationship between LCR and 28-day mortality across different subpopulations. Based on previous studies, we included covariates most likely associated with mortality in sepsis-associated myocardial injury[ 25 ][ 26 ][ 27 ]—SOFA score, APSIII score, and age—in the analysis to construct Model 2. Model 3 incorporated all variables involved in this study. All three models yielded consistent positive results. These findings suggest that stratifying patients by gender and using gender-specific LCR cutoff values allows for a more precise assessment of disease severity and prognosis in sepsis-associated myocardial injury patients. Obviously, stratifying patients solely by gender has limitations, we further conducted subgroup analyses stratified by age. The statistical results revealed an interesting trend: in the overall population and in male patients, those aged < 65 years in the high LCR group had a higher 28-day mortality risk compared to patients aged ≥ 65 years. This finding is contrary to conventional expectations. However, younger patients generally produce more lactate in response to inflammatory stimuli. At the same time, the impact of comorbidities should be considered. Older patients often have more underlying diseases, which may mask the predictive ability of LCR for mortality risk. In contrast, among female patients, no significant differences in risk were observed between different age groups, and the interaction was not statistically significant. This may be related to the protective effects of female hormones [ 28 ][ 29 ], especially estrogen levels in premenopausal women, which might attenuate inflammatory responses or improve microcirculation, thereby equalizing the impact of high LCR across age groups. Prior to our study, the relationship between LCR and mortality risk in patients with SIMI had not been investigated. Our findings provide the first evidence supporting the prognostic value of LCR in SIMI patients. However, the exact pathophysiological mechanisms underlying this association remain unclear.Previous studies have indicated that the pathogenesis of SIMI involves complex and multifactorial processes, including uncontrolled systemic inflammatory responses, oxidative stress, microcirculatory dysfunction, ischemia and hypoxia, mitochondrial dysfunction, excessive nitric oxide production, sympathetic overactivation, direct effects of myocardial depressant factors, and calcium homeostasis imbalance [ 18 ][ 30 ][ 31 ]. Due to the complexity, as well as the asynchronous and heterogeneous nature of these pathological factors during the disease course, no single biomarker can fully reflect the severity of SIMI. LCR, as an integrated parameter that is readily available in the ICU, reflects both tissue perfusion and myocardial contractility. It offers a simple, rapid, and accurate means to predict 28-day outcomes in patients with sepsis-associated myocardial injury. Moreover, the optimal LCR cutoff value determined in this study may serve as an independent and important risk stratification tool for critically ill patients. This study has several limitations. First, the data were derived from the MIMIC database, which is a single-center dataset with a relatively homogeneous population, potentially limiting the generalizability of our findings. Second, LCR was not dynamically monitored. Third, several confounding factors—such as the use of continuous renal replacement therapy (CRRT), administration of positive inotropic agents, nutritional status, and hormone levels—were not adequately accounted for, all of which could potentially affect the results. Fourth, certain malignancies, such as multiple myeloma or bone metastases, as well as the patient's acid-base balance, may influence serum ionized calcium levels, potentially leading to decreased LCR values. However, given our relatively large sample size, the impact of these factors on the overall results is likely mitigated. Further research is warranted to elucidate the key mechanisms underlying sepsis-associated myocardial injury. Conclusion Elevated LCR is closely associated with increased 28-day mortality in patients with SIMI. Statistically, the optimal cutoff values for LCR were 2.91 for females and 2.16 for males. These findings suggest that LCR may help identify SIMI patients at high risk of mortality. Abbreviations MIMIC Medical Information Mart in Intensive Care SIMI Sepsis-induced Myocardial Injury LCR Lactate-to-Calcium Ratio ICU Intensive care unit RCS Restricted cubic spline PDH Pyruvate dehydrogenase SpO₂ Peripheral oxygen saturation SBP Systolic blood pressure MAP Mean arterial pressure WBC White blood cell BUN Blood urea nitrogen CK-MB Creatine kinase-MB AST Aspartate aminotransferase ALT Alanine aminotransferase cTnT Cardiac troponin T SOFA Sequential organ failure assessment SAPS II Simplified acute physiology score II APS III Acute Physiology Score III LODS Logistic Organ Dysfunction Score OASIS Oxford Acute Severity of Illness Score GCS Glasgow Coma Scale HR hazard ratio SMD Standardized mean difference IQR Interquartile range CI Confidence interval Declarations Acknowledgements We are appreciative of the MIMIC-IV (v 3.0) participants and staff. We thank all reviewers who participated in the review. Author Contributions ： Dou Li contributed to study design, data curation, and manuscript writing. Yuan Sicheng contributed to data analysis, grammar check. Hu Xinru contributed to data analysis and revise the manuscript. All authors approved the final manuscript and are responsible for the content. Funding: This work was supported by “Jiuangsu Provincial Program for the Development of Traditional Chinese Medicine Science and Technology”and “Research Project of Jiangsu Provincial Center for Traditional Chinese Medicine in Epidemic Disease in 2024” (MS2022018),and (JSBY2024KF7, JSBY2024KF9). Data Availability The datasets analyzed in the current study are available in the MIMIC-IV database. (https://physionet.org/content/mimiciv/3.1/) Ethics approval and consent to participate The MIMIC protocol was approved by the review boards of the Massachusetts Institute of Technology and Beth Israel Deaconess Medical Center. 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Sun Z, Qu J, Xia X, Pan Y, Liu X, Liang H, Dou H, Hou Y. 17β-Estradiol promotes LC3B-associated phagocytosis in trained immunity of female mice against sepsis. Int J Biol Sci. 2021;17:460–74. Shields CA, Wang X, Cornelius DC. Sex differences in cardiovascular response to sepsis. Am J Physiol Cell Physiol. 2023;324(2):C458–66. Kuroshima T, Kawaguchi S, Okada M. Current Perspectives of Mitochondria in Sepsis-Induced Cardiomyopathy. Int J Mol Sci. 2024;25(9):4710. Fang X, Ardehali H, Min J, Wang F. The molecular and metabolic landscape of iron and ferroptosis in cardiovascular disease. Nat Rev Cardiol. 2023;20(1):7–23. Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterials.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6788738","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":469803943,"identity":"6020b0f0-a188-49ab-9def-1cd0644043ca","order_by":0,"name":"Li Dou","email":"","orcid":"","institution":"Affiliated Hospital of Nanjing University of Traditional Chinese Medicine (Jiangsu Hospital of Traditional Chinese Medicine)","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Dou","suffix":""},{"id":469803944,"identity":"31acaf72-94a0-40a3-b6e4-ffefc327da5d","order_by":1,"name":"Sicheng Yuan","email":"","orcid":"","institution":"Affiliated Hospital of Nanjing University of Traditional Chinese Medicine (Jiangsu Hospital of Traditional Chinese Medicine)","correspondingAuthor":false,"prefix":"","firstName":"Sicheng","middleName":"","lastName":"Yuan","suffix":""},{"id":469803945,"identity":"9a425b1a-bb5a-4523-a29d-f92111d28359","order_by":2,"name":"Xinru Hu","email":"","orcid":"","institution":"Nanjing University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Xinru","middleName":"","lastName":"Hu","suffix":""},{"id":469803946,"identity":"e4fd6410-0cc4-4617-91b8-50d54ee8dae7","order_by":3,"name":"Yuwei Tan","email":"","orcid":"","institution":"Affiliated Hospital of Nanjing University of Traditional Chinese Medicine (Jiangsu Hospital of Traditional Chinese Medicine)","correspondingAuthor":false,"prefix":"","firstName":"Yuwei","middleName":"","lastName":"Tan","suffix":""},{"id":469803947,"identity":"109e7f20-c2c1-43cb-8029-b8d93b6361ae","order_by":4,"name":"Jing Wang","email":"","orcid":"","institution":"Affiliated Hospital of Nanjing University of Traditional Chinese Medicine (Jiangsu Hospital of Traditional Chinese Medicine)","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Wang","suffix":""},{"id":469803948,"identity":"659a7f31-bb7e-4ae9-ae87-4def90483f63","order_by":5,"name":"Jian Chen","email":"","orcid":"","institution":"Affiliated Hospital of Nanjing University of Traditional Chinese Medicine (Jiangsu Hospital of Traditional Chinese Medicine)","correspondingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Chen","suffix":""},{"id":469803949,"identity":"b6d4fd7c-dff2-4d3e-9784-cc85803ed786","order_by":6,"name":"Shunjuan Xu","email":"","orcid":"","institution":"Nanjing University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Shunjuan","middleName":"","lastName":"Xu","suffix":""},{"id":469803950,"identity":"dffb58fb-5ad3-428b-ab17-6959ad910828","order_by":7,"name":"Tao Guo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxklEQVRIiWNgGAWjYFACHhAhwcDA3tj44ANpWngONxvOIEELSFd6mzQHMRrk288e/FxRYyFvcPNhgzQDg52cbgMBLQZn8pIlzxyTMNxwO7HBuIAh2djsACEtDDkGkg1sEgkGQC3JMxgOJG4jpEW+/43xz4Z/QC03DzYc5iFGC8ONHDPJxjaglhuMjc1EaTG48cbMsrFPwnDmmcRmxhkGRPhFvj/H+GbDtzp5vuPHn//4UGEnR1ALuqWkKR8Fo2AUjIJRgAMAAN/AQ1PheLYmAAAAAElFTkSuQmCC","orcid":"","institution":"Nanjing University of Chinese Medicine","correspondingAuthor":true,"prefix":"","firstName":"Tao","middleName":"","lastName":"Guo","suffix":""}],"badges":[],"createdAt":"2025-05-31 05:08:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6788738/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6788738/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84690890,"identity":"fabc55fa-0275-4ad9-ac90-9ebafa239497","added_by":"auto","created_at":"2025-06-16 09:40:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":82886,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart for study participants enrolling.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6788738/v1/4993e7e67d77bc4fa5047ea8.png"},{"id":84689832,"identity":"6dced6d9-5d3e-4eff-b768-3ccc4ecec543","added_by":"auto","created_at":"2025-06-16 09:32:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":24493,"visible":true,"origin":"","legend":"\u003cp\u003eRestricted cubic spline regression analysis of LCR with 28-day all-cause mortality\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6788738/v1/ec41d5f682eb848c9cdb1aaf.png"},{"id":84689823,"identity":"2d85a9a4-6af0-489b-9361-97d765f810ea","added_by":"auto","created_at":"2025-06-16 09:32:23","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":49105,"visible":true,"origin":"","legend":"\u003cp\u003eA.Cutoff of all group; B.Cutoff of female group; C.Cutoff of male group;\u003c/p\u003e\n\u003cp\u003eEach picture consists of two parts, the upper and the lower. The upper graph is the LCR (Log-Cumulative Rank) Distribution Graph, showing the density distribution and cumulative distribution function (CDF) of LCR values for different groups. The lower graph is the Maximally Selected Rank Statistics Graph, illustrating the relationship between standardized log-rank statistics and LCR values, highlighting statistical differences between the groups across different LCR ranges.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6788738/v1/d8dafea16cc1e49c321f03b1.png"},{"id":84690896,"identity":"99fcd248-b8a7-4a56-8f47-323000a2dc54","added_by":"auto","created_at":"2025-06-16 09:40:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":71309,"visible":true,"origin":"","legend":"\u003cp\u003eA.K-M curves of all people in the high and low LCR; B.K-M curves of female in the high and low LCR; C.K-M curves of male in the high and low LCR;\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6788738/v1/a6876e6496830a3e80d0bffd.png"},{"id":84690889,"identity":"c7df231a-bbc3-41e4-a5db-987fa9bb9f5b","added_by":"auto","created_at":"2025-06-16 09:40:23","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":46947,"visible":true,"origin":"","legend":"\u003cp\u003eStratified analysis of LCR and 28-day mortality\u003c/p\u003e\n\u003cp\u003eHR hazard ratio: adjusted for sofa, apsiii, sirs, sapsii, gcs, lods, oasis, troponin_t_idx1, hemoglobin, wbc_idx1, creatinine_idx1, glucose_idx1, ck_mb_idx1, alt_idx1, ast_idx1, bilirubin_total_idx1, cerebrovascular_disease, chronic_pulmonary_disease, renal_disease, heart_rate_idx1, resp_rate_idx1, platelet_idx1, severe_liver_disease, charlson_comorbidity_index, sbp_idx1 , temperature_idx1 in the overall population; adjusted for sofa, apsiii, sirs, sapsii, lods, oasis, troponin_t_idx1, creatinine_idx1, glucose_idx1, ck_mb_idx1, alt_idx1, ast_idx1, bilirubin_total_idx1, cerebrovascular_disease, renal_disease, heart_rate_idx1, resp_rate_idx1, platelet_idx1, sbp_idx1 , temperature_idx1 in the female; adjusted for sofa, apsiii, sirs, sapsii, lods, oasis, troponin_t_idx1, hemoglobin, wbc_idx1, creatinine_idx1, glucose_idx1, ck_mb_idx1, alt_idx1, ast_idx1, bilirubin_total_idx1, cerebrovascular_disease, chronic_pulmonary_disease, renal_disease, heart_rate_idx1, resp_rate_idx1, platelet_idx1, severe_liver_disease, charlson_comorbidity_index, sbp_idx1 , dbp_idx1, temperature_idx1 in the male.\u003c/p\u003e\n\u003cp\u003eP for INTM: multiplicative interaction.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6788738/v1/b86a35e9c632c34b7f13e263.png"},{"id":87815527,"identity":"636c79c6-6492-43e7-9ac5-c54a99084ae8","added_by":"auto","created_at":"2025-07-29 10:02:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1943153,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6788738/v1/03feaf5f-365a-43f3-84ab-119c9da17a6c.pdf"},{"id":84690888,"identity":"cb1b8ebb-e55f-4aab-ab10-535c03033fb9","added_by":"auto","created_at":"2025-06-16 09:40:23","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":19999,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-6788738/v1/666c9ff21232abb0780cfa05.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association Between Lactate-to-Calcium Ratio and 28-Day Mortality in Patients With Sepsis-Induced Myocardial Injury: A Retrospective Cohort Study Based on the MIMIC-IV Database","fulltext":[{"header":"Background","content":"\u003cp\u003eSepsis is a systemic inflammatory response triggered by infection, accompanied by immune dysregulation, microcirculatory dysfunction, and multiple organ failure. Despite significant advances in infection control, fluid resuscitation, and organ support in critical care medicine, the global mortality rate of sepsis remains as high as 20\u0026ndash;30%[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Studies have shown that sepsis can lead to dysfunction in multiple organs, with the heart being one of the most vulnerable. The incidence of myocardial involvement ranges from 30\u0026ndash;60%, making it one of the major contributors to sepsis-related mortality and prolonged treatment duration[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] Clinically, patients with sepsis and concurrent cardiac dysfunction are defined as having sepsis-induced myocardial injury (SIMI), which may be attributed to mechanisms such as systemic inflammation, oxidative stress, microcirculatory impairment, ischemia and hypoxia, as well as calcium homeostasis imbalance[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e][\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e][\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDuring sepsis, a large number of inflammatory mediators are released, which disrupt calcium homeostasis by impairing calcium absorption and increasing calcium excretion[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Calcium ions play a critical role in excitation-contraction coupling of cardiomyocytes. Hypocalcemia directly leads to insufficient cytoplasmic Ca\u0026sup2;⁺ concentration in cardiac cells. Moreover, in sepsis, the function of calcium reuptake pumps (SERCA pumps)[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e][\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e][\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]and ryanodine receptors is impaired, further exacerbating calcium imbalance[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Such a hypocalcemic environment can directly reduce myocardial contractility, impair mitochondrial function by inhibiting ATP synthesis[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], or prolong cardiomyocyte action potential duration, which may trigger arrhythmias. These factors collectively contribute to the development of myocardial injury in patients with sepsis[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e][\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, the pathophysiological mechanisms of sepsis are not limited to inflammatory responses[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Microcirculatory dysfunction, which leads to inadequate tissue perfusion and metabolic disturbances, also contributes significantly to cardiac dysfunction. Elevated lactate levels in patients are often indicative of poor tissue perfusion[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Accumulation of lactate can lower both intracellular and extracellular pH, thereby suppressing myocardial contractility. Lactate may also inhibit pyruvate dehydrogenase (PDH) activity[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e][\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], reduce the production of acetyl-CoA, and diminish ATP generation, further exacerbating myocardial energy deficiency. In a high-lactate environment, increased generation of reactive oxygen species (ROS) may occur, activating the NLRP3 inflammasome and amplifying myocardial inflammation[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Several studies have demonstrated a synergistic effect between Ca\u0026sup2;⁺ deficiency and lactic acidosis. For instance, protons (H⁺) may compete with Ca\u0026sup2;⁺ for binding to troponin C, further impairing contractility. Additionally, lactate may enter cardiomyocytes via monocarboxylate transporters (MCTs) and directly inhibit L-type calcium channel (LTCC) activity[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e][\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], thereby reducing Ca\u0026sup2;⁺ influx.\u003c/p\u003e \u003cp\u003eIn the prognostic evaluation of sepsis-induced myocardial injury (SIMI), relying solely on either blood calcium or lactate levels has inherent limitations. Lactate levels can be influenced by early resuscitation and liver function, while serum calcium levels are affected by parathyroid function and acid\u0026ndash;base balance. By combining these two indicators into the lactate-to-ionized calcium ratio (LCR), it is possible to integrate information on both calcium homeostasis imbalance and metabolic dysfunction, offering a more comprehensive and dynamic assessment of SIMI pathophysiology and prognosis. Therefore, in this study, we utilized the Medical Information Mart for Intensive Care IV (MIMIC-IV) database to construct a nonlinear regression model, determine optimal LCR cut-off values, and investigate the association between LCR and adverse outcomes in patients with SIMI.\u003c/p\u003e"},{"header":"Methods and Materials","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Source\u003c/h2\u003e \u003cp\u003eThe data used in this study were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database, a large, publicly available critical care database developed and maintained by the Laboratory for Computational Physiology at the Massachusetts Institute of Technology (MIT). The database contains de-identified health-related data of patients admitted to the intensive care units (ICUs) of Beth Israel Deaconess Medical Center between 2008 and 2019. The first author of this study completed the required training and obtained access to the database (Certification Number: 67880992). The use of the MIMIC-IV database for research has been approved by the Institutional Review Boards of MIT and Beth Israel Deaconess Medical Center, with a waiver of informed consent.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Population and Definitions\u003c/h3\u003e\n\u003cp\u003eData were extracted from the MIMIC-IV database for patients who were admitted to the ICU for the first time and met the diagnostic criteria for sepsis-induced myocardial injury (SIMI). The inclusion criteria for patient selection were as follows:(1) Meeting the Sepsis-3 diagnostic criteria;(2) Meeting the diagnostic definition of SIMI;(3) Age\u0026thinsp;\u0026ge;\u0026thinsp;18 years. Based on the diagnostic criteria and limitations of the database, SIMI was defined as a cardiac troponin T (cTnT) level greater than 0.01 ng/mL measured within the first 24 hours of ICU admission. Exclusion criteria were established to eliminate cases in which elevated cTnT levels might be attributed to other causes, including acute coronary syndrome, myocarditis, pericarditis, valvular heart disease, congestive heart failure, or cardiac arrest. All diagnoses were based on ICD-9/10 codes.\u003c/p\u003e\n\u003ch3\u003eData Extraction\u003c/h3\u003e\n\u003cp\u003eThe extracted variables included demographic information, vital signs, comorbidities, basic laboratory parameters, and pre-treatment severity scores:(1) Demographics: sex and age;(2) Vital signs: heart rate, respiratory rate, peripheral oxygen saturation (SpO₂), systolic blood pressure (SBP), diastolic blood pressure (DBP), and body temperature;(3) Comorbidities: chronic pulmonary disease, diabetes, renal insufficiency, severe liver disease, cerebrovascular disease, and malignant cancer;(4) Laboratory tests: the first laboratory values obtained within 24 hours of ICU admission, including white blood cell (WBC) count, hemoglobin, platelet count, blood urea nitrogen (BUN), creatinine, glucose, creatine kinase-MB (CK-MB), aspartate aminotransferase (AST), alanine aminotransferase (ALT), total bilirubin, cardiac troponin T (cTnT), lactate, and ionized calcium;(5) Additional clinical information during ICU stay: the first Sequential Organ Failure Assessment (SOFA) score, Acute Physiology Score III (APS III), Simplified Acute Physiology Score II (SAPS II), Logistic Organ Dysfunction Score (LODS), Oxford Acute Severity of Illness Score (OASIS), Glasgow Coma Scale (GCS), and Charlson Comorbidity Index.\u003c/p\u003e\n\u003ch3\u003eExposure\u003c/h3\u003e\n\u003cp\u003eAll laboratory parameters obtained from the MIMIC-IV (v3.0) database were assessed at the time of the first measurement after ICU admission. The LCR was calculated as the ratio of lactate to ionized calcium, with a low LCR defined as low exposure and a high LCR defined as high exposure based on the cut-off point.\u003c/p\u003e\n\u003ch3\u003eOutcomes\u003c/h3\u003e\n\u003cp\u003eSurvival status at 28 days (death or survival) was measured starting from the day of ICU admission. The event of interest is defined as the time of death on day 28.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCovariates\u003c/h2\u003e \u003cp\u003eThe baseline characteristics of patients including time of ICU admission, demographic characteristics (gender and age), medical history (cerebrovascular disease, chronic pulmonary disease, diabetes, renal disease, malignant cancer and severe liver disease ), laboratory tests ( troponin T, hemoglobin, platelet, WBC, BUM, creatinine, glucose, CK-MB, ALT, AST, bilirubin total and the current health status (the score of SIRS, SOFA, SAPS II, GCS, LODS,APS III, and OASIS, and heart rate, SBP, DBP, temperature, resp rate and SpO2).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eVariables with more than 20% missing data were excluded. Missing values for remaining variables were imputed using multiple imputation, and the imputed dataset was analyzed for three distinct populations: the overall population, and separate male and female populations. A restricted cubic spline (RCS) plot was created to explore the non-linear relationship between LCR and 28-day mortality. The optimal cut-off value for LCR was determined using the surv_cutpoint function from the survminer R package, categorizing the population into low and high LCR groups, both for the entire cohort and stratified by sex. Continuous variables were described as means with standard deviations (SD) or medians with interquartile ranges (IQR), based on their distribution. The normality of the data was assessed using the Shapiro-Wilk test, and t-tests or Wilcoxon rank-sum tests were applied accordingly. Categorical variables were presented as frequencies and percentages, with differences between groups evaluated using the Chi-square test or Fisher's exact test when appropriate. Kaplan-Meier survival curves were constructed to compare 28-day mortality between LCR groups, with statistical significance tested by the Log-rank test. Cox proportional hazards models were used to estimate the association between the LCR and 28-day mortality, with the hazard ratio (HR) representing the strength of the association. Model 1 included only the LCR without any additional adjustments. Model 2 adjusted for confounders, including the SOFA score, APACHE II score, and age. Model 3 incorporated further adjustments for laboratory tests and comorbidities that significantly differed between groups. To examine potential age-related differences in the effect of LCR on 28-day mortality, stratified Cox regression analyses were performed by age, with a cut-off at 65 years, and adjustments were made for the same confounders as in Model 3.\u003c/p\u003e \u003cp\u003eAll statistical analyses were conducted using R (version 4.3.0). R packages tidyverse, mice, glm, autoReg, survival, survminer, splines, forestplot and ggplot2 were used for data management, statistical analysis and drawing statistical plots. Two-sided hypothesis test was used, and the significance level α\u0026thinsp;=\u0026thinsp;0.05 was set.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eBaseline\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the flowchart of the participant screening process. According to the inclusion criteria, a total of 1,631 patients were enrolled in this study from the MIMIC-IV database based on the inclusion and exclusion criteria, consisting of 671 females(41.14%,64.89\u0026thinsp;\u0026plusmn;\u0026thinsp;15.73 years) and 960 males(58.86%,62.73\u0026thinsp;\u0026plusmn;\u0026thinsp;16.97years). More details in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDetection of nonlinear relationship\u003c/h2\u003e \u003cp\u003eThe restricted cubic spline regression model was applied, revealing that as LCR increases, the hazard ratio (HR) for 28-day mortality also increases(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), indicating a positive association between higher LCR and an elevated risk of mortality.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCutoff values for different groups\u003c/h2\u003e \u003cp\u003eBased on the LCR distribution and maximally selected rank statistics graphs, the LCR values differentiate the two groups, with the high group showing a stronger association between the variable and the outcome. The cut-off values were 2.96 for all, 2.91 for females, and 2.16 for males(Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eEach picture consists of two parts, the upper and the lower. The upper graph is the LCR (Log-Cumulative Rank) Distribution Graph, showing the density distribution and cumulative distribution function (CDF) of LCR values for different groups. The lower graph is the Maximally Selected Rank Statistics Graph, illustrating the relationship between standardized log-rank statistics and LCR values, highlighting statistical differences between the groups across different LCR ranges.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eComparison of patients\u0026rsquo; baseline information\u003c/h2\u003e \u003cp\u003eIn Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e1\u003c/span\u003e, a comparison between the high and low groups revealed that patients in the high group were more likely to experience a death outcome within 28 days. These patients tended to be younger, with a lower prevalence of cerebrovascular disease and chronic pulmonary disease, but a higher prevalence of renal disease, severe liver disease, and elevated heart rate and respiratory rate. Moreover, patients in the high group demonstrated significantly higher levels of SIRS, SOFA,SAPSII, GCS, APS III, LODS, OASIS, Troponin T, hemoglobin, WBC, creatinine, glucose, CK-MB, ALT, AST, and bilirubin. Similarly, among both females and males, the high group was more likely to experience a death outcome within 28 days, with a younger age and higher SOFA and APS III scores compared to the low group. Detailed baseline characteristics are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e1\u003c/span\u003eA-\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e1\u003c/span\u003eC.\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\u003e\u003cb\u003eA\u003c/b\u003e Differential analysis between high and low LCR groups in the overall patients.\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003egroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003elow (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1130)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ehigh (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;501)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\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\u003eSex, \u003cem\u003en\u003c/em\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 \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;1.217\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.270\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e475 (42.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e196 (39.12)\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\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e655 (57.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e305 (60.88)\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, y,Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64.73\u0026thinsp;\u0026plusmn;\u0026thinsp;16.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61.10\u0026thinsp;\u0026plusmn;\u0026thinsp;17.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.998\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eVital signs,\u003c/p\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\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, beats/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e92.00\u0026thinsp;\u0026plusmn;\u0026thinsp;21.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100.76\u0026thinsp;\u0026plusmn;\u0026thinsp;22.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-7.537\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eSystolic blood pressure, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e123.18\u0026thinsp;\u0026plusmn;\u0026thinsp;26.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e116.30\u0026thinsp;\u0026plusmn;\u0026thinsp;27.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.737\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eDiastolic blood pressure, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68.71\u0026thinsp;\u0026plusmn;\u0026thinsp;19.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67.32\u0026thinsp;\u0026plusmn;\u0026thinsp;19.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.325\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.185\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemperature,℃\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.28\u0026thinsp;\u0026plusmn;\u0026thinsp;1.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6.496\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eResp rate, beats/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20.88\u0026thinsp;\u0026plusmn;\u0026thinsp;6.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.44\u0026thinsp;\u0026plusmn;\u0026thinsp;6.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-4.322\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eSpO2,%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e96.64\u0026thinsp;\u0026plusmn;\u0026thinsp;4.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e96.48\u0026thinsp;\u0026plusmn;\u0026thinsp;5.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.577\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.564\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScores\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\u003eSIRS, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-7.169\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eSOFA, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.00 (4.00, 10.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.00 (7.00, 12.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-11.920\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eSAPSII, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44.98\u0026thinsp;\u0026plusmn;\u0026thinsp;14.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53.19\u0026thinsp;\u0026plusmn;\u0026thinsp;16.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-9.821\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eGCS, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-2.136\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAPSIII, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57.00 (43.00, 74.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72.00 (55.00, 93.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-10.968\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eLODS, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.00 (5.00, 9.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.00 (6.00, 11.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-9.670\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eOASIS, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37.50\u0026thinsp;\u0026plusmn;\u0026thinsp;8.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.88\u0026thinsp;\u0026plusmn;\u0026thinsp;8.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-7.379\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharlson comorbidity index, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.00 (3.00, 7.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.00 (2.00, 6.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.721\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eLaboratory values on admission\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\u003eTroponin T,ng/mL, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.06 (0.03, 0.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.08 (0.04, 0.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-4.505\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eHemoglobin, g/dL,Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.72\u0026thinsp;\u0026plusmn;\u0026thinsp;2.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.02\u0026thinsp;\u0026plusmn;\u0026thinsp;2.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-2.132\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet,\u0026times;10\u003csup\u003e9\u003c/sup\u003e,M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e192.00 (128.00, 263.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e166.00 (100.00, 243.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.746\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eWBC,\u0026times;10\u003csup\u003e9\u003c/sup\u003e, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.50 (8.50, 17.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.70 (8.80, 21.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-3.666\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eBUN,mg/dL, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26.00 (16.00, 45.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.00 (16.00, 44.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.352\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.725\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine, mg/dL,M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.20 (0.80, 2.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.60 (1.10, 2.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-5.044\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eGlucose,mg/dL, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e136.00 (109.25, 174.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e168.00 (124.00, 246.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-8.324\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eCK-MB,IU/L, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.00 (3.00, 11.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.00 (4.00, 24.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-7.293\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eALT,U/L, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31.00 (18.00, 68.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70.00 (28.00, 245.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-10.940\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eAST,U/L, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48.00 (28.00, 114.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e133.00 (48.00, 492.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-12.398\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eBilirubin total, mg/dL,M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.60 (0.40, 1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.90 (0.50, 2.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-5.701\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eComorbidites, \u003cem\u003en\u003c/em\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\u003eCerebrovascula\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 \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;28.851\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e856 (75.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e438 (87.43)\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e274 (24.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63 (12.57)\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\u003eChronic pulmonary disease\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 \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;6.415\u003csup\u003e1\u003c/sup\u003e\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e866 (76.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e412 (82.24)\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e264 (23.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e89 (17.76)\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\u003eDiabetes\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 \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.697\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.404\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e805 (71.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e367 (73.25)\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e325 (28.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e134 (26.75)\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\u003eRenal disease\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 \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;23.959\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e853 (75.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e432 (86.23)\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e277 (24.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69 (13.77)\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\u003eMalignant cancer\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 \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.124\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.725\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e975 (86.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e429 (85.63)\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e155 (13.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72 (14.37)\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\u003eSevere liver disease\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 \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;11.985\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1010 (89.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e417 (83.23)\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e120 (10.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84 (16.77)\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\u003eOutcomes\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\u003e28-day mortality, \u003cem\u003en\u003c/em\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 \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;53.571\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eAlive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e770 (68.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e246 (49.10)\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\u003eDead\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e360 (31.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e255 (50.90)\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\u003eSurvival,day, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19.13 (6.82, 28.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.27 (1.86, 23.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;9.205\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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=\"5\"\u003e1.Pearson χ\u0026sup2; test\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e2.Variance-corrected independent samples t-test\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e3.Mann-Whitney U test\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e4.Independent samples t-test\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eSIRS:Systemic Inflanmmatory Response Syndrome, SOFA: Sepsis-Organ Failure Assessment Score, SAPSII: Simplified Acute Physiology Score II, GCS: Glasgow Coma Scale, APSIII: Acute Physiology Score III, LODS: Logistic Organ Dysfunction Score, OASIS: Oxford Acute Severity of Illness,WBC: white blood cells, BUN: blood urea nitrogen, ALT: alanine aminotransferase, AST: aspartate aminotransferase, CK-MB:Creatine Kinase,MB Form\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eB\u003c/b\u003e Differential analysis between high and low LCR groups in the female patients.\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=\"left\" 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\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003egroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStatistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003elow (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;472)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ehigh (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;199)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge,y, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65.48\u0026thinsp;\u0026plusmn;\u0026thinsp;15.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.47\u0026thinsp;\u0026plusmn;\u0026thinsp;16.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.510\u003csup\u003e1\u003c/sup\u003e\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\u003eVital signs,Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\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, beats/min, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93.32\u0026thinsp;\u0026plusmn;\u0026thinsp;20.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98.40\u0026thinsp;\u0026plusmn;\u0026thinsp;23.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-2.627\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystolic blood pressure, mmHg, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e121.83\u0026thinsp;\u0026plusmn;\u0026thinsp;27.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117.23\u0026thinsp;\u0026plusmn;\u0026thinsp;28.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.982\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiastolic blood pressure, mmHg, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66.99\u0026thinsp;\u0026plusmn;\u0026thinsp;19.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.59\u0026thinsp;\u0026plusmn;\u0026thinsp;20.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-0.351\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.726\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemperature,℃, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.73\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.11\u0026thinsp;\u0026plusmn;\u0026thinsp;1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.493\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eResp rate, beats/min, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.00 (17.00, 24.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.00 (17.00, 28.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-2.249\u003csup\u003e2\u003c/sup\u003e\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\u003eSpO2,%, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96.67\u0026thinsp;\u0026plusmn;\u0026thinsp;4.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96.61\u0026thinsp;\u0026plusmn;\u0026thinsp;5.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.136\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.892\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScores\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\u003eSIRS, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-3.365\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOFA, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.50 (4.00, 9.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.00 (6.00, 12.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-7.292\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eSAPSII, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.11\u0026thinsp;\u0026plusmn;\u0026thinsp;14.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.21\u0026thinsp;\u0026plusmn;\u0026thinsp;15.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-6.516\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eGCS, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-0.256\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.798\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAPSIII, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57.50 (42.75, 75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.00 (53.00, 89.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-6.469\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eLODS, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.00 (5.00, 9.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.00 (6.00, 11.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-5.800\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eOASIS, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.76\u0026thinsp;\u0026plusmn;\u0026thinsp;7.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.83\u0026thinsp;\u0026plusmn;\u0026thinsp;8.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-4.496\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharlson comorbidity index, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.00 (3.00, 7.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.00 (2.00, 6.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.485\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaboratory values on admission\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\u003eTroponin T,ng/mL, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.06 (0.03, 0.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.09 (0.04, 0.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-3.157\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin, g/dL,Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.41\u0026thinsp;\u0026plusmn;\u0026thinsp;2.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.44\u0026thinsp;\u0026plusmn;\u0026thinsp;2.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-0.118\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.906\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet,\u0026times;10\u003csup\u003e9\u003c/sup\u003e,M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e201.00 (131.75, 277.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e164.00 (102.50, 250.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.377\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC,\u0026times;10\u003csup\u003e9\u003c/sup\u003e, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.20 (9.20, 18.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.10 (8.90, 21.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-1.947\u003csup\u003e2\u003c/sup\u003e\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\u003eBUN,mg/dL, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.00 (14.00, 42.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.00 (14.00, 40.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.393\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.695\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine, mg/dL,M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.10 (0.70, 2.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.20 (0.90, 2.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-2.032\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlucose,mg/dL, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e141.00 (116.00, 181.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e162.00 (128.50, 239.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-4.330\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eCK-MB,IU/L, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.00 (3.00, 11.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.00 (4.00, 24.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-5.367\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eALT,U/L, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.00 (17.00, 67.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65.00 (25.00, 283.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-6.385\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eAST,U/L, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47.00 (28.00, 115.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e124.00 (42.00, 660.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-8.005\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eBilirubin total, mg/dL,M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.60 (0.30, 1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.90 (0.50, 2.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-4.341\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eComorbidites, \u003cem\u003en\u003c/em\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\u003eCerebrovascular, \u003cem\u003en\u003c/em\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 \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;6.974\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e352 (74.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e167 (83.92)\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e120 (25.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (16.08)\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\u003eChronic pulmonary disease, \u003cem\u003en\u003c/em\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 \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.127\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.722\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e352 (74.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e151 (75.88)\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e120 (25.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 (24.12)\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\u003eDiabetes, \u003cem\u003en\u003c/em\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 \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;2.065\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e340 (72.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e154 (77.39)\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e132 (27.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (22.61)\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\u003eRenal disease, \u003cem\u003en\u003c/em\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 \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;12.903\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e357 (75.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e175 (87.94)\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e115 (24.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (12.06)\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\u003eMalignant cancer, \u003cem\u003en\u003c/em\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 \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;1.733\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.188\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e414 (87.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e167 (83.92)\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58 (12.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (16.08)\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\u003eSevere liver disease, \u003cem\u003en\u003c/em\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 \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.704\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.401\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e421 (89.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e173 (86.93)\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51 (10.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (13.07)\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\u003eOutcomes\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\u003esurvival, day, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.77 (6.63, 28.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.35 (1.84, 21.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.770\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003e28-day mortality, \u003cem\u003en\u003c/em\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 \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;31.853\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eAlive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e323 (68.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90 (45.23)\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\u003eDead\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e149 (31.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e109 (54.77)\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 \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e1.Pearson χ\u0026sup2; test Independent samples t-test\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e2.Mann-Whitney U test\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e3. Pearson χ\u0026sup2; test\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e4.Variance-corrected independent samples t-test\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eSIRS:Systemic Inflanmmatory Response Syndrome, SOFA: Sepsis-Organ Failure Assessment Score, SAPSII: Simplified Acute Physiology Score II, GCS: Glasgow Coma Scale, APSIII: Acute Physiology Score III, LODS: Logistic Organ Dysfunction Score, OASIS: Oxford Acute Severity of Illness,WBC: white blood cells, BUN: blood urea nitrogen, ALT: alanine aminotransferase, AST: aspartate aminotransferase, CK-MB:Creatine Kinase,MB Form\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eC\u003c/b\u003e Differential analysis between high and low LCR groups in the male patients.\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=\"left\" 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\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003egroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStatistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003elow (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;534)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ehigh (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;426)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge,y, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64.37\u0026thinsp;\u0026plusmn;\u0026thinsp;16.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60.68\u0026thinsp;\u0026plusmn;\u0026thinsp;17.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.335\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVital signs,Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\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, beats/min, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90.04\u0026thinsp;\u0026plusmn;\u0026thinsp;21.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100.31\u0026thinsp;\u0026plusmn;\u0026thinsp;21.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-7.342\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eSystolic blood pressure, mmHg, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e125.22\u0026thinsp;\u0026plusmn;\u0026thinsp;26.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e116.81\u0026thinsp;\u0026plusmn;\u0026thinsp;26.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.843\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eDiastolic blood pressure, mmHg, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70.27\u0026thinsp;\u0026plusmn;\u0026thinsp;18.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.56\u0026thinsp;\u0026plusmn;\u0026thinsp;19.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.169\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemperature,℃, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.978\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eResp rate, beats/min, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.70\u0026thinsp;\u0026plusmn;\u0026thinsp;6.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.19\u0026thinsp;\u0026plusmn;\u0026thinsp;6.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-3.571\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eSpO2,%, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96.61\u0026thinsp;\u0026plusmn;\u0026thinsp;4.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96.48\u0026thinsp;\u0026plusmn;\u0026thinsp;5.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.410\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.682\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScores\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\u003eSIRS, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-6.176\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eSOFA, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.00 (4.00, 10.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.00 (7.00, 12.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-8.911\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eSAPSII, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.41\u0026thinsp;\u0026plusmn;\u0026thinsp;14.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.36\u0026thinsp;\u0026plusmn;\u0026thinsp;16.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-7.025\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eGCS, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-1.430\u003csup\u003e1\u003c/sup\u003e\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\u003eAPSIII, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.00 (42.25, 70.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.00 (54.00, 92.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-9.067\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eLODS, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.00 (5.00, 9.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.00 (6.00, 10.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-7.407\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eOASIS, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.25\u0026thinsp;\u0026plusmn;\u0026thinsp;8.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.95\u0026thinsp;\u0026plusmn;\u0026thinsp;8.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-4.855\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharlson comorbidity index, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.00 (3.00, 7.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.00 (2.00, 6.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.802\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaboratory values on admission\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\u003eTroponin T,ng/mL, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.06 (0.03, 0.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.08 (0.04, 0.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-2.720\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin, g/dL,Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.93\u0026thinsp;\u0026plusmn;\u0026thinsp;2.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.28\u0026thinsp;\u0026plusmn;\u0026thinsp;2.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-2.046\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet,\u0026times;10\u003csup\u003e9\u003c/sup\u003e,M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e187.50 (129.25, 253.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e170.50 (101.00, 242.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.439\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC,\u0026times;10\u003csup\u003e9\u003c/sup\u003e, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.80 (7.80, 16.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.85 (9.00, 20.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-4.086\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eBUN,mg/dL, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.00 (18.00, 47.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.00 (17.00, 46.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-0.062\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.950\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine, mg/dL,M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.25 (0.90, 2.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.60 (1.10, 2.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-4.315\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eGlucose,mg/dL, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130.00 (107.00, 164.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e160.00 (115.00, 235.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-6.190\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eCK-MB,IU/L, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.00 (3.00, 12.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.00 (4.00, 19.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-3.827\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eALT,U/L, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.00 (18.00, 69.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.50 (26.00, 195.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-7.271\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eAST,U/L, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46.00 (27.00, 111.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96.00 (46.00, 324.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-8.643\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eBilirubin total, mg/dL,M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.60 (0.40, 1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.90 (0.50, 2.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e=-5.664\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eComorbidites, \u003cem\u003en\u003c/em\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\u003eCerebrovascular, \u003cem\u003en\u003c/em\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 \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;27.940\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e399 (74.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e376 (88.26)\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e135 (25.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (11.74)\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\u003eChronic pulmonary disease, \u003cem\u003en\u003c/em\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 \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;9.889\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e412 (77.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e363 (85.21)\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e122 (22.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63 (14.79)\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\u003eDiabetes, \u003cem\u003en\u003c/em\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 \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.000\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.984\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e377 (70.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e301 (70.66)\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e157 (29.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e125 (29.34)\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\u003eRenal disease, \u003cem\u003en\u003c/em\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 \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;9.838\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e399 (74.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e354 (83.10)\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e135 (25.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72 (16.90)\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\u003eMalignant cancer, \u003cem\u003en\u003c/em\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 \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.001\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.969\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e458 (85.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e365 (85.68)\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76 (14.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (14.32)\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\u003eSevere liver disease, \u003cem\u003en\u003c/em\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 \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;30.163\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e492 (92.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e341 (80.05)\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (7.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85 (19.95)\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\u003eOutcomes\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\u003esurvival, day, M (Q\u003csub\u003e1\u003c/sub\u003e, Q\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.86 (8.08, 28.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.90 (2.08, 25.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;7.717\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003e28-day mortality, \u003cem\u003en\u003c/em\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 \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;35.907\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\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\u003eAlive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e380 (71.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e223 (52.35)\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\u003eDead\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e154 (28.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e203 (47.65)\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 \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e1. Variance-corrected independent samples t-test\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e2.Mann-Whitney U test\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e3. Pearson χ\u0026sup2; test\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e4.Independent samples t-test\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eSIRS:Systemic Inflanmmatory Response Syndrome, SOFA: Sepsis-Organ Failure Assessment Score, SAPSII: Simplified Acute Physiology Score II, GCS: Glasgow Coma Scale, APSIII: Acute Physiology Score III, LODS: Logistic Organ Dysfunction Score, OASIS: Oxford Acute Severity of Illness,WBC: white blood cells, BUN: blood urea nitrogen, ALT: alanine aminotransferase, AST: aspartate aminotransferase, CK-MB:Creatine Kinase,MB Form\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\u003eSurvival analysis\u003c/h2\u003e \u003cp\u003eWe conducted a Kaplan-Meier survival analysis to compare the incidence of 28-day mortality and survival time between the groups. The 28-day mortality rate was significantly higher in the high group compared to the low group (log-rank P\u0026thinsp;\u0026lt;\u0026thinsp;0.001)(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Similarly, within both the female and male subgroups, the high group demonstrated a significantly higher mortality rate than the low group (log-rank P\u0026thinsp;\u0026lt;\u0026thinsp;0.001)(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB-\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eRelationship between different levels of LCR and clinical outcome indicators\u003c/h2\u003e \u003cp\u003eWe used Cox proportional hazards models to examine the association between LCR and 28-day mortality across different subgroups. In Model 1 (unadjusted), patients in the high LCR group had a significantly higher risk of 28-day mortality compared to the low LCR group, with a 102% increase in the overall population [HR (95% CI): 2.02 (1.72\u0026ndash;2.37), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001], a 100% increase among females [HR (95% CI): 2.00 (1.56\u0026ndash;2.56), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001], and a 113% increase among males [HR (95% CI): 2.13 (1.73\u0026ndash;2.63), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001]. In Model 2, after adjusting for SOFA score, APS III score, and age, the high LCR group remained significantly associated with increased 28-day mortality in the overall cohort [HR (95% CI): 1.77 (1.49\u0026ndash;2.09), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001], females [HR (95% CI): 1.82 (1.49\u0026ndash;2.36), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001], and males [HR (95% CI): 1.83 (1.47\u0026ndash;2.28), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001]. In Model 3, after further adjustment for additional confounders including clinical scores, laboratory markers, vital signs, and comorbidities, high LCR remained independently associated with increased 28-day mortality in the overall population [HR (95% CI): 1.67 (1.38\u0026ndash;2.02), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001], females [HR (95% CI): 1.82 (1.49\u0026ndash;2.36), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001], and males [HR (95% CI): 1.83 (1.44\u0026ndash;2.33), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001] (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\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 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCox regression of LCR and 28-day mortality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePopulation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHR(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHR(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLCR\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.02\u003c/p\u003e \u003cp\u003e(1.72, 2.37)\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=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.77\u003c/p\u003e \u003cp\u003e(1.49, 2.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.67 (1.38\u0026ndash;2.02)\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 \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\u003eLCR\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003cp\u003e(1.56, 2.56)\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=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.82\u003c/p\u003e \u003cp\u003e(1.40, 2.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.73 (1.29\u0026ndash;2.32)\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 \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\u003eLCR\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.13\u003c/p\u003e \u003cp\u003e(1.73, 2.63)\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=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003cp\u003e(1.47, 2.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.83 (1.44\u0026ndash;2.33)\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 \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eModel 1: unadjusted model.\u003c/p\u003e \u003cp\u003eMode 2: adjusted for sofa, apsiii, age.\u003c/p\u003e \u003cp\u003eMode 3: adjusted for sofa, apsiii, age, sirs, sapsii, gcs, lods, oasis, troponin t, hemoglobin, wbc, creatinine, glucose, ck-mb, al, ast, bilirubin total, cerebrovascular, chronic pulmonary disease, renal disease, heart rate, resp rate, platelet, severe liver disease, charlson comorbidity, sbp, temperature in the overall population; adjusted for sofa, apsiii, age, sirs, sapsii, lods, oasis, troponin t, creatinine, glucos, ck-mb, alt, as, bilirubin total, cerebrovascular disease, renal disease, heart rate, resp rate, platele, sbp, temperature in the female; adjusted for sofa, apsiii, age, sirs, sapsii, lods, oasis, troponin t, hemoglobin, wbc, creatinine, glucose, ck-mb, alt, ast, bilirubin total, cerebrovascular disease, chronic pulmonary disease, renal disease, heart rate, resp rate, platelet, severe liver disease, charlson comorbidit, sbp, dbp, temperatur in the male.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eStratification analysis\u003c/h2\u003e \u003cp\u003eThe age-stratified Cox regression analysis showed that in the overall population, patients with high LCR aged\u0026thinsp;\u0026lt;\u0026thinsp;65 years had a significantly higher 28-day mortality risk [HR (95% CI): 1.99 (1.47\u0026ndash;2.69)] than thoese aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years[HR (95% CI): 1.35 (1.05\u0026ndash;1.74)], and the multiplicative interaction between age group and LCR was statistically significant (P for interaction\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In females, the 28-day mortality risk in the high LCR group was similar between those aged\u0026thinsp;\u0026lt;\u0026thinsp;65 and \u0026ge;\u0026thinsp;65 years (P for interaction\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, among male patients, those aged\u0026thinsp;\u0026lt;\u0026thinsp;65 years with high LCR had a notably higher 28-day mortality risk [HR (95% CI): 2.76 (1.86\u0026ndash;4.10)]. In contrast, high LCR was not significantly associated with 28-day mortality risk in males aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years [HR (95% CI): 1.34 (0.97\u0026ndash;1.85), P\u0026thinsp;\u0026gt;\u0026thinsp;0.05] (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e "},{"header":"Discussion","content":"\u003cp\u003eCurrently, studies focusing on prognostic predictors for patients with SIMI are relatively limited. Most existing literature investigates single biomarkers; however, due to the complex pathological features of SIMI, relying on a single indicator has obvious limitations. In this retrospective study based on the MIMIC-IV database, we found that an increased LCR was significantly positively associated with 28-day all-cause mortality during ICU stay in patients with SIMI [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e][\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This index reflects the pathological changes of septic myocardial injury from multiple perspectives. We identified the optimal cutoff value of LCR as 2.96. Considering gender differences, we performed subgroup analyses and found that the optimal cutoff values were 2.91 and 2.18 for female and male patients, respectively. The underlying reasons for these gender differences remain unclear but may be related to higher muscle mass in males, which accelerates anaerobic metabolism and lactate production during tissue hypoxia. Meanwhile, the increased calcium demand in males may make them more susceptible to mild hypocalcemia, leading to muscle weakness and diaphragmatic dysfunction. Furthermore, survival advantage in females may shift the cutoff values upward. Previous studies have shown that female septic patients tend to have higher survival rates than males [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e][\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Therefore, at equivalent lactate and ionized calcium levels, females appear to have a lower risk of mortality, requiring higher lactate or lower calcium levels to reach statistical significance.\u003c/p\u003e \u003cp\u003eWe stratified patients into high and low LCR groups based on the cutoff values, and the results demonstrated a significantly increased 28-day mortality rate in the high LCR group. To further validate the stability of these findings, we constructed Cox proportional hazards models to explore the relationship between LCR and 28-day mortality across different subpopulations. Based on previous studies, we included covariates most likely associated with mortality in sepsis-associated myocardial injury[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e][\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e][\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u0026mdash;SOFA score, APSIII score, and age\u0026mdash;in the analysis to construct Model 2. Model 3 incorporated all variables involved in this study. All three models yielded consistent positive results. These findings suggest that stratifying patients by gender and using gender-specific LCR cutoff values allows for a more precise assessment of disease severity and prognosis in sepsis-associated myocardial injury patients.\u003c/p\u003e \u003cp\u003eObviously, stratifying patients solely by gender has limitations, we further conducted subgroup analyses stratified by age. The statistical results revealed an interesting trend: in the overall population and in male patients, those aged\u0026thinsp;\u0026lt;\u0026thinsp;65 years in the high LCR group had a higher 28-day mortality risk compared to patients aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years. This finding is contrary to conventional expectations. However, younger patients generally produce more lactate in response to inflammatory stimuli. At the same time, the impact of comorbidities should be considered. Older patients often have more underlying diseases, which may mask the predictive ability of LCR for mortality risk. In contrast, among female patients, no significant differences in risk were observed between different age groups, and the interaction was not statistically significant. This may be related to the protective effects of female hormones [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e][\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], especially estrogen levels in premenopausal women, which might attenuate inflammatory responses or improve microcirculation, thereby equalizing the impact of high LCR across age groups.\u003c/p\u003e \u003cp\u003ePrior to our study, the relationship between LCR and mortality risk in patients with SIMI had not been investigated. Our findings provide the first evidence supporting the prognostic value of LCR in SIMI patients. However, the exact pathophysiological mechanisms underlying this association remain unclear.Previous studies have indicated that the pathogenesis of SIMI involves complex and multifactorial processes, including uncontrolled systemic inflammatory responses, oxidative stress, microcirculatory dysfunction, ischemia and hypoxia, mitochondrial dysfunction, excessive nitric oxide production, sympathetic overactivation, direct effects of myocardial depressant factors, and calcium homeostasis imbalance [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e][\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e][\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Due to the complexity, as well as the asynchronous and heterogeneous nature of these pathological factors during the disease course, no single biomarker can fully reflect the severity of SIMI. LCR, as an integrated parameter that is readily available in the ICU, reflects both tissue perfusion and myocardial contractility. It offers a simple, rapid, and accurate means to predict 28-day outcomes in patients with sepsis-associated myocardial injury. Moreover, the optimal LCR cutoff value determined in this study may serve as an independent and important risk stratification tool for critically ill patients.\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, the data were derived from the MIMIC database, which is a single-center dataset with a relatively homogeneous population, potentially limiting the generalizability of our findings. Second, LCR was not dynamically monitored. Third, several confounding factors\u0026mdash;such as the use of continuous renal replacement therapy (CRRT), administration of positive inotropic agents, nutritional status, and hormone levels\u0026mdash;were not adequately accounted for, all of which could potentially affect the results. Fourth, certain malignancies, such as multiple myeloma or bone metastases, as well as the patient's acid-base balance, may influence serum ionized calcium levels, potentially leading to decreased LCR values. However, given our relatively large sample size, the impact of these factors on the overall results is likely mitigated. Further research is warranted to elucidate the key mechanisms underlying sepsis-associated myocardial injury.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eElevated LCR is closely associated with increased 28-day mortality in patients with SIMI. Statistically, the optimal cutoff values for LCR were 2.91 for females and 2.16 for males. These findings suggest that LCR may help identify SIMI patients at high risk of mortality.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cb\u003eMIMIC\u003c/b\u003e Medical Information Mart in Intensive Care\u003c/p\u003e\u003cp\u003e\u003cb\u003eSIMI\u003c/b\u003e Sepsis-induced Myocardial Injury\u003c/p\u003e\u003cp\u003e\u003cb\u003eLCR\u003c/b\u003e Lactate-to-Calcium Ratio\u003c/p\u003e\u003cp\u003e\u003cb\u003eICU\u003c/b\u003e Intensive care unit\u003c/p\u003e\u003cp\u003e\u003cb\u003eRCS\u003c/b\u003e Restricted cubic spline\u003c/p\u003e\u003cp\u003e\u003cb\u003ePDH\u003c/b\u003e Pyruvate dehydrogenase\u003c/p\u003e\u003cp\u003e\u003cb\u003eSpO₂\u003c/b\u003e Peripheral oxygen saturation\u003c/p\u003e\u003cp\u003e\u003cb\u003eSBP\u003c/b\u003e Systolic blood pressure\u003c/p\u003e\u003cp\u003e\u003cb\u003eMAP\u003c/b\u003e Mean arterial pressure\u003c/p\u003e\u003cp\u003e\u003cb\u003eWBC\u003c/b\u003e White blood cell\u003c/p\u003e\u003cp\u003e\u003cb\u003eBUN\u003c/b\u003e Blood urea nitrogen\u003c/p\u003e\u003cp\u003e\u003cb\u003eCK-MB\u003c/b\u003e Creatine kinase-MB\u003c/p\u003e\u003cp\u003e\u003cb\u003eAST\u003c/b\u003e Aspartate aminotransferase\u003c/p\u003e\u003cp\u003e\u003cb\u003eALT\u003c/b\u003e Alanine aminotransferase\u003c/p\u003e\u003cp\u003e\u003cb\u003ecTnT\u003c/b\u003e Cardiac troponin T\u003c/p\u003e\u003cp\u003e\u003cb\u003eSOFA\u003c/b\u003e Sequential organ failure assessment\u003c/p\u003e\u003cp\u003e\u003cb\u003eSAPS II\u003c/b\u003e Simplified acute physiology score II\u003c/p\u003e\u003cp\u003e\u003cb\u003eAPS III\u003c/b\u003e Acute Physiology Score III\u003c/p\u003e\u003cp\u003e\u003cb\u003eLODS\u003c/b\u003e Logistic Organ Dysfunction Score\u003c/p\u003e\u003cp\u003e\u003cb\u003eOASIS\u003c/b\u003e Oxford Acute Severity of Illness Score\u003c/p\u003e\u003cp\u003e\u003cb\u003eGCS\u003c/b\u003e Glasgow Coma Scale\u003c/p\u003e\u003cp\u003e\u003cb\u003eHR\u003c/b\u003e hazard ratio\u003c/p\u003e\u003cp\u003e\u003cb\u003eSMD\u003c/b\u003e Standardized mean difference\u003c/p\u003e\u003cp\u003e\u003cb\u003eIQR\u003c/b\u003e Interquartile range\u003c/p\u003e\u003cp\u003e\u003cb\u003eCI\u003c/b\u003e Confidence interval\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are appreciative of the MIMIC-IV (v 3.0) participants and staff. We thank all reviewers who participated in the review.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDou Li contributed to study design, data curation, and manuscript writing. Yuan Sicheng contributed to data analysis, grammar check. Hu Xinru contributed to data analysis and revise the manuscript. All authors approved the final manuscript and are responsible for the content.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by \u0026ldquo;Jiuangsu Provincial Program for the Development of Traditional Chinese Medicine Science and Technology\u0026rdquo;and \u0026ldquo;Research Project of Jiangsu Provincial Center for Traditional Chinese Medicine in Epidemic Disease in 2024\u0026rdquo; (MS2022018),and \u0026nbsp;(JSBY2024KF7, JSBY2024KF9).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets analyzed in the current study are available in the MIMIC-IV database. (https://physionet.org/content/mimiciv/3.1/)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe MIMIC protocol was approved by the review boards of the Massachusetts Institute of Technology and Beth Israel Deaconess Medical Center. As the data were publicly available, the study was exempt from the requirements of an ethics approval statement and informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDesposito L, Bascara C. Review: sepsis guidelines and core measure bundles. 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Med (Baltim). 2022;101(48):e31895.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun Z, Qu J, Xia X, Pan Y, Liu X, Liang H, Dou H, Hou Y. 17β-Estradiol promotes LC3B-associated phagocytosis in trained immunity of female mice against sepsis. Int J Biol Sci. 2021;17:460\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShields CA, Wang X, Cornelius DC. Sex differences in cardiovascular response to sepsis. Am J Physiol Cell Physiol. 2023;324(2):C458\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKuroshima T, Kawaguchi S, Okada M. Current Perspectives of Mitochondria in Sepsis-Induced Cardiomyopathy. Int J Mol Sci. 2024;25(9):4710.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFang X, Ardehali H, Min J, Wang F. The molecular and metabolic landscape of iron and ferroptosis in cardiovascular disease. Nat Rev Cardiol. 2023;20(1):7\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Sepsis-induced myocardial injury, Lactate-to-ionized calcium ratio, 28-day mortality, Cut-off value","lastPublishedDoi":"10.21203/rs.3.rs-6788738/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6788738/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePatients with sepsis-induced myocardial injury (SIMI) face a high risk of mortality. Although various biomarkers can be used to predict prognosis in SIMI patients, each has certain limitations. This study aimed to investigate the prognostic value of the lactate-to-calcium ratio (LCR) in patients with SIMI.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis retrospective cohort study was conducted using data from the MIMIC-IV database. Patients diagnosed with SIMI who were admitted to the ICU were included. The LCR was calculated based on the first arterial blood gas analysis performed within 24 hours of ICU admission. A restricted cubic spline (RCS) model was used to explore the nonlinear relationship between LCR and 28-day mortality. Patients were divided into high and low LCR groups based on the cutoff values, both overall and by sex. Kaplan\u0026ndash;Meier survival curves were used to compare 28-day mortality between groups. Stratification analyses were conducted to assess the prognostic value of LCR across different age strata.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 1,631 patients were included. The RCS model revealed a positive association between higher LCR and increased 28-day mortality. The cut-off values for LCR were 2.96 for the overall population, 2.91 for females, and 2.16 for males. Cox regression analysis showed that high LCR was significantly associated with higher 28-day mortality (log-rank P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Age-stratified analysis indicated that LCR had a higher predictive value in patients younger than 65 years. Among males, high LCR was associated with increased 28-day mortality only in those younger than 65. In females, the association was consistent regardless of age.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eA higher LCR is associated with increased 28-day mortality in ICU patients with SIMI. The sex-specific cut-off values (2.91 for females and 2.16 for males) suggest that LCR may serve as a useful prognostic indicator for identifying high-risk patients with sepsis-induced myocardial injury.\u003c/p\u003e","manuscriptTitle":"Association Between Lactate-to-Calcium Ratio and 28-Day Mortality in Patients With Sepsis-Induced Myocardial Injury: A Retrospective Cohort Study Based on the MIMIC-IV Database","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-16 09:32:18","doi":"10.21203/rs.3.rs-6788738/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9b3d3c53-b5b9-4f07-9659-06eae4b7217f","owner":[],"postedDate":"June 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-27T11:56:02+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-16 09:32:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6788738","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6788738","identity":"rs-6788738","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}