Correlation between lactate dehydrogenase to albumin ratio and prognosis of patients with acute pancreatitis

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Methods: We retrospectively analyzed the clinical data of 82 patients with acute pancreatitis admitted to the Intensive Care Unit of Shanghai East Hospital from 2019 to 2024. Based on their 28-day survival outcomes, the patients were categorized into a death group(n=10) and a survival group(n=72). Various clinical indicators, including age, gender, hemoglobin (Hb), total bilirubin (TB), and creatinine (Cr), were evaluated to further identify independent prognostic factors. The predictive power of LAR values was evaluated through Cox multivariate regression analysis and ROC curve, while Kaplan Meier survival analysis was used to analyze the survival differences among patients with different LAR levels. To verify the robustness of the results, we further independently validated the predictive ability of LAR using the eICU database. Results: Compared with the survival group, the LAR of patients in the death group was significantly increased (p<0.01), and the ICU hospitalization time and total hospitalization time were significantly prolonged. Cox regression analysis showed that LAR was an independent predictor of 28-day mortality in AP patients (HR 1.03; 95% CI: 1.01-1.06). ROC analysis shows that the AUC of LAR is 0.943 and the cutoff value is 29.050. The 28-day mortality rate of patients in the high LAR group was significantly higher than that in the low LAR group (p<0.01). In the validation of eICU database, LAR also showed high prognostic predictive performance (AUC=0.898), indicating that this indicator has strong stability and universality. Concliusions: LAR is an independent risk factor for 28-day mortality in AP patients and can effectively identify high-risk patients. acute pancreatitis lactate dehydrogenase albumin prognosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction AP is a common digestive system disease in clinical practice, caused by various factors such as biliary tract disease, alcohol, surgery, trauma, etc., which can lead to multiple organ failure in severe cases [ 1 ] . AP generally occurs in middle-aged and elderly people, with a global incidence rate of 34 per 100000 people [ 2 , 3 ] ,and poses a significant challenge in clinical practice,despite a declining mortality rate over the years [ 4 ] . The high mortality associated with severe acute pancreatitis underscores the importance of early monitoring of biomarkers that can predict prognosis and facilitate timely clinical intervention. Lactate dehydrogenase (LDH), an oxidoreductase isoenzyme catalyzing reversible reactions between pyruvate and lactate, primarily exists in the cytoplasm and plays a crucial role in glycolysis [ 5 ] .Elevated LDH levels have been confirmed to have diagnostic value for severe acute pancreatitis and are a sensitive predictor of AP complicated by multiple organ failure. [ 6 – 8 ] . However, LDH's non-specificity and widespread distribution in multiple tissues and organs limit its standalone clinical value in predicting AP prognosis. Serum albumin, on the other hand, has been independently associated with persistent organ failure caused by AP and exhibits certain predictive value for AP prognosis [ 9 ] . LAR is a novel inflammatory biomarker with certain predictive value for colorectal cancer [ 10 ] .Studies indicate that an elevated LAR upon admission is a risk factor for the prognosis of critically ill patients with acute kidney injury(AKI). [ 11 ] . Although research on LAR in other diseases is gradually increasing, there is currently a lack of relevant studies on the prognostic evaluation value of LAR in patients with acute pancreatitis. Considering the important roles of LDH and albumin in acute pancreatitis, LAR may amplify their effects and reflect systemic inflammatory response and metabolic disorders to a greater extent. This study aimed to assess the predictive ability of LAR for 28-day mortality in AP patients and validate its clinical utility in risk stratification.Initially, a prognostic analysis of LAR was conducted on single-center AP patients, followed by external validation using data from the eICU database. Our research will provide a new possibility for early risk assessment of AP patients and provide theoretical basis for optimizing clinical intervention strategies. This study has been approved by (2024YS-200) Materials and methods Research Design and Data Sources This study is a single center retrospective cohort study, with data sourced from AP patients admitted to the Intensive Care Unit of Shanghai East Hospital from 2019 to 2024. To further validate the effectiveness of LAR in predicting the prognosis of AP, we conducted external validation using eICU database data. Study population Inclusion criteria for the study population included patients aged 18 to 85 years, meeting the diagnostic criteria for AP [ 12 ] ,while exclusion criteria encompassed ICU stays of less than 24 hours, history of malignant tumors or chronic kidney disease, severe infection prior to admission, and missing key data. Data extraction Collect demographic data (gender, age, medical history), laboratory indicators (LDH, albumin [ALB], Cr, CysC, Hb, TB, white blood cell count [WBC], alanine aminotransferase [ALT], aspartate aminotransferase [AST], platelet count [PLT], triglycerides(Tg), and cholesterol, and calculate LAR, ICU length of stay, total length of stay, and 28-day prognosis. Statistical methods Univariate analysis Continuous variables with normal distribution are represented by mean ± standard deviation (X ± SD). Independent sample t-test was used for comparison between the two groups; Non normally distributed continuous variables are represented by median and quartile range(M [Q₁, Q₃]), and rank sum test is used; The categorical variables are represented by frequency (n [%]), and the comparison of differences between two groups is performed using chi square test or Fisher's exact probability method. The significance standard for differences is set at p < 0.05. Multivariate Cox regression analysis Include variables significantly correlated with 28-day mortality rate in univariate analysis (p < 0.05) into the Cox multivariate regression model. Regression analysis calculates the hazard ratio (HR) and its 95% confidence interval (CI), where each unit increase in LAR represents a change in the hazard ratio. ROC Curve Analysis of Subjects Using ROC curve analysis to assess the predictive efficacy of LAR for 28-day mortality in AP patients, calculating the area under the curve (AUC) and determining the optimal cutoff value to evaluate the predictive accuracy of LAR in the study population. Kaplan Meier survival analysis Use Kaplan Meier survival analysis to evaluate the survival differences between high LAR group and low LAR group patients. The comparison between groups was conducted using the Log rank test, and the results were presented in the form of Kaplan Meier survival curves. Validation analysis We used independent AP patients data from the eICU database for external validation, calculated the AUC of LAR in the eICU validation set, and compared it with the main study data to evaluate the predictive performance of LAR in different populations. Results Baseline characteristics This study included a total of 82 AP patients, and detailed baseline characteristics are shown in Table 1 . All patients were divided into a death group (n = 10) and a survival group (n = 72) based on a 28-day prognosis. Baseline characteristics revealed no significant differences between the death and survival groups in terms of age, gender, Hb, cholesterol, triglyceride levels, diabetes incidence(p > 0.05). Compared with the survival group, the LAR, ICU length of stay, total length of stay, Cr, TB, CysC, and proportion of hypertension were significantly increased in the death group, while PLT was significantly reduced (p < 0.01) Table 1 Baseline characteristics of the study population variables Total (n = 82) Survival group (n = 72) Death group (n = 10) t/Z/X 2 P Hb, X ± SD 133.23 ± 28.64 135.01 ± 26.92 120.40 ± 38.13 t = 1.52 0.131 LAR, M (Q₁, Q₃) 10.64 (6.90, 24.09) 9.41 (6.31, 17.30) 56.80 (38.68, 65.06) Z=-4.51 < .001 ICU length of stay, M (Q₁, Q₃) 6.00 (5.00, 13.75) 6.00 (5.00, 9.50) 26.00 (23.25, 42.75) Z=-4.18 < .001 Total length of stay, M (Q₁, Q₃) 17.50 (12.25, 28.25) 16.00 (12.00, 25.00) 29.50 (25.25, 47.75) Z=-2.65 0.008 Age, M (Q₁, Q₃) 60.00 (42.00, 73.75) 58.00 (41.50, 73.50) 67.50 (60.00, 73.25) Z=-0.79 0.427 Cr, M (Q₁, Q₃) 74.45 (56.25, 112.25) 70.00 (55.50, 96.70) 371.95 (159.93, 656.75) Z=-3.78 < .001 TB, M (Q₁, Q₃) 19.85 (11.12, 36.72) 17.95 (10.35, 30.57) 58.05 (19.25, 98.05) Z=-2.39 0.017 ALT, M (Q₁, Q₃) 30.50 (19.00, 85.50) 29.70 (18.00, 68.18) 59.00 (33.00, 399.25) Z=-1.80 0.072 AST, M (Q₁, Q₃) 32.40 (20.00, 103.10) 30.00 (19.50, 88.03) 74.70 (30.68, 693.60) Z=-1.78 0.075 PLT, M (Q₁, Q₃) 195.50 (152.50, 247.00) 202.50 (158.00, 252.50) 134.50 (118.25, 198.75) Z=-2.15 0.032 WBC, M (Q₁, Q₃) 13.50 (11.60, 17.64) 13.61 (11.65, 17.99) 12.52 (10.60, 14.51) Z=-0.57 0.566 Tg, M (Q₁, Q₃) 4.71 (1.10, 8.84) 4.35 (1.03, 8.84) 6.45 (2.00, 8.84) Z=-0.23 0.820 cholesterol, M (Q₁, Q₃) 5.54 (3.19, 7.10) 5.82 (3.25, 7.29) 3.86 (2.90, 6.13) Z=-0.98 0.327 CysC, M (Q₁, Q₃) 1.23 (0.78, 1.26) 1.06 (0.78, 1.26) 1.87 (1.26, 3.52) Z=-3.36 < .001 gender, n(%) χ²=0.27 0.600 Femal 35 (42.68) 32 (44.44) 3 (30.00) Male 47 (57.32) 40 (55.56) 7 (70.00) Hypertension, n(%) χ²=4.50 0.034 No 38 (46.34) 37 (51.39) 1 (10.00) Yes 44 (53.66) 35 (48.61) 9 (90.00) Diabetes, n(%) χ²=0.25 0.617 No 51 (62.20) 46 (63.89) 5 (50.00) Yes 31 (37.80) 26 (36.11) 5 (50.00) The relationship between LAR and 28 day mortality rate Cox multivariate regression analysis Univariate analysis showed that variables significantly associated with 28-day mortality included LAR, ICU length of stay, total length of stay, Cr, TB, CysC, and PLT. Cox multivariate regression analysis further validated LAR as an independent predictor of 28-day mortality in AP patients. The results showed that for every unit increase in LAR, the 28 day mortality risk increased by 3% (HR = 1.03, 95% CI: 1.01–1.06, p < 0.01), as shown in Table 2 . Table 2 Univariate analysis and Cox multivariate regression analysis variables Univariate analysis Cox multivariate regression analysis β S.E Z P HR (95%CI) β S.E Z P HR (95%CI) Gender Femal 1.00 (Reference) Male 0.77 0.70 1.10 0.27 2.15 (0.55 ~ 8.40) Hypertension No 1.00 (Reference) Yes 1.74 1.06 1.64 0.10 5.69 (0.71 ~ 45.52) Diabetes No 1.00 (Reference) Yes 1.01 0.66 1.53 0.13 2.75 (0.75 ~ 10.11) LAR 0.03 0.01 2.94 < .01 1.03 (1.01 ~ 1.05) 0.03 0.01 2.73 < .01 1.03 (1.01 ~ 1.06) Age 0.02 0.02 0.84 0.40 1.02 (0.97 ~ 1.07) Cr 0.01 0.00 2.51 0.01 1.01 (1.01 ~ 1.01) -0.01 0.01 -1.00 0.32 0.99 (0.99 ~ 1.00) TB 0.01 0.00 1.72 0.09 1.01 (1.00 ~ 1.01) ALT 0.00 0.00 0.79 0.43 1.00 (1.00 ~ 1.00) AST 0.00 0.00 0.90 0.37 1.00 (1.00 ~ 1.00) PLT -0.01 0.00 -1.26 0.21 0.99 (0.99 ~ 1.00) WBC 0.02 0.05 0.48 0.63 1.02 (0.93 ~ 1.12) Tg 0.01 0.03 0.19 0.85 1.01 (0.95 ~ 1.07) Cholesterol 0.02 0.09 0.17 0.87 1.02 (0.85 ~ 1.22) CysC 0.60 0.23 2.61 < .01 1.83 (1.16 ~ 2.88) 1.43 0.89 1.60 0.11 4.17 (0.73 ~ 23.91) Hb -0.01 0.01 -1.24 0.21 0.99 (0.97 ~ 1.01) ROC curve analysis ROC curve analysis demonstrated that LAR had a high prediction accuracy for 28-day mortality, with an AUC of 0.943. The optimal cutoff value, determined based on the maximum Youden index, was 29.050, corresponding to a sensitivity of 90.0% and a specificity of 88.9%, as shown in Fig. 1 . Clinical differences between high LAR and low LAR groups According to the cutoff value of LAR (29.050), patients were divided into high LAR group (≥ 29.050) and low LAR group (< 29.050). Kaplan Meier survival analysis showed that the 28-day survival rate of patients in the high LAR group was significantly lower than that in the low LAR group (p < 0.01). At 28 days, the cumulative mortality rate of patients in the high LAR group was significantly higher than that in the low LAR group, indicating the potential role of LAR in patient risk stratification, as shown in Fig. 2 . Moreover, both ICU length of day and total length of day were significantly prolonged (p < 0.01), as shown in Fig. 3 . In addition, the Cr, TB, ALT, and AST levels in the high LAR group were significantly increased, while PLT was significantly decreased (p < 0.01), as shown in Table 3 and Fig. 4 . Table 3 Clinical data and laboratory indicators of high LAR and low LAR patients Variables Total (n = 82) Low LAR(n = 69) high LAR (n = 13) t/Z/X 2 P Hb, X ± SD 133.23 ± 28.64 135.75 ± 27.22 119.85 ± 33.27 t = 1.87 0.066 LAR, M (Q₁, Q₃) 10.64 (6.90, 24.09) 9.23 (6.27, 15.33) 50.23 (38.37, 58.97) Z=-5.69 < .001 ICU length of stay, M (Q₁, Q₃) 6.00 (5.00, 13.75) 6.00 (5.00, 11.00) 24.00 (8.00, 38.00) Z=-3.88 < .001 Total length of day, M (Q₁, Q₃) 17.50 (12.25, 28.25) 16.00 (12.00, 25.00) 29.00 (19.00, 49.00) Z=-2.69 0.007 Age, M (Q₁, Q₃) 60.00 (42.00, 73.75) 58.00 (40.00, 71.00) 66.00 (60.00, 82.00) Z=-1.51 0.131 Cr, M (Q₁, Q₃) 74.45 (56.25, 112.25) 69.00 (54.00, 94.00) 204.70 (95.00, 384.90) Z=-3.80 < .001 TB, M (Q₁, Q₃) 19.85 (11.12, 36.72) 17.20 (10.20, 29.90) 60.10 (24.20, 94.40) Z=-3.47 < .001 ALT, M (Q₁, Q₃) 30.50 (19.00, 85.50) 29.00 (18.00, 60.00) 88.00 (42.00, 276.90) Z=-2.79 0.005 AST, M (Q₁, Q₃) 32.40 (20.00, 103.10) 28.00 (18.00, 77.00) 112.00 (44.70, 595.00) Z=-3.19 0.001 PLT, M (Q₁, Q₃) 195.50 (152.50, 247.00) 206.00 (158.00, 257.00) 139.00 (116.00, 202.00) Z=-2.49 0.013 WBC, M (Q₁, Q₃) 13.50 (11.60, 17.64) 13.59 (11.67, 17.79) 12.76 (10.11, 17.05) Z=-0.44 0.657 Tg, M (Q₁, Q₃) 4.71 (1.10, 8.84) 4.41 (1.09, 8.84) 6.05 (1.67, 8.84) Z=-0.27 0.784 Cholesterol, M (Q₁, Q₃) 5.54 (3.19, 7.10) 5.88 (3.25, 7.51) 3.45 (2.97, 6.13) Z=-1.02 0.306 CysC, M (Q₁, Q₃) 1.23 (0.78, 1.26) 1.04 (0.77, 1.26) 1.30 (1.26, 2.12) Z=-3.46 < .001 Gender, n(%) χ²=0.79 0.375 Femal 35 (42.68) 28 (40.58) 7 (53.85) Male 47 (57.32) 41 (59.42) 6 (46.15) Death, n(%) χ²=40.82 < .001 No 72 (87.80) 68 (98.55) 4 (30.77) Yes 10 (12.20) 1 (1.45) 9 (69.23) Hypertension, n(%) χ²=3.36 0.067 No 38 (46.34) 35 (50.72) 3 (23.08) Yes 44 (53.66) 34 (49.28) 10 (76.92) Dm, n(%) χ²=0.00 1.000 No 51 (62.20) 43 (62.32) 8 (61.54) Yes 31 (37.80) 26 (37.68) 5 (38.46) Linear relationship between LAR and ICU length of stay As the linear regression analysis yields the equation: y = 0.5715*x + 2.103 (where y represents ICU length of stay and x represents LAR),a moderate positive correlation was observed between LAR and ICU length of stay(Pearson correlation coefficient rho = 0.544, p < 0.01), with the average ICU length of stay increasing by approximately 0.57 days for each unit increase in LAR (R²=0.3254).The Pearson correlation coefficient (rho) is 0.544, indicating a moderate positive correlation between LAR and ICU length of stay. The p-value is 1.276e-07, indicating a highly significant correlation, suggesting that the relationship between LAR and ICU length of stay is likely not caused by randomness. The coefficient of determination (R ²) is 0.3254, indicating that LAR can explain approximately 32.54% of the variation in ICU stay days. This indicates that LAR to some extent affects the length of ICU stay, as shown in Fig. 5 . Validation analysis In the independent validation set of the eICU database, LAR's predictive effect on 28-day mortality rate of AP patients was consistent with the main dataset, with an AUC of 0.898, as shown in Fig. 6 . Patients in the high LAR group had a significantly prolonged ICU length of stay and increased 28-day mortality (p < 0.01), as shown in Fig. 7 . Discussion This study evaluated the prognostic value of LAR in AP patients through retrospective analysis. The results showed that LAR was an independent predictor of 28-day mortality in AP patients, and high LAR patients had a significantly increased risk of 28-day mortality. This discovery supports the potential of LAR as an effective biomarker in early risk stratification of AP, and also provides new ideas for the management of severe acute pancreatitis. The pathogenesis of AP is due to impaired calcium signal transduction, mitochondrial dysfunction, premature activation of trypsinogen in acinar cells and macrophages, leading to pancreatic self digestion and causing a series of pathophysiological reactions such as pancreatic tissue necrosis [ 13 , 14 ] . Currently, there is no effective treatment for AP in clinical practice. Therefore, early prediction of AP prognosis and timely strengthening of clinical management are of great significance for patients. LDH is an important glycolytic enzyme in cells, commonly used for tumor recognition and treatment. It has carcinogenic and immunosuppressive effects, is a marker of decreased anti-tumor immune function, and is also a potential therapeutic target for cancer [ 15 – 17 ] . When tissue undergoes inflammation, hypoxia, or injury, its release significantly increases, which is particularly evident in the pathological process of acute pancreatitis. LDH is also one of the indicators of Ranson score, which is of great significance for evaluating the severity of AP [ 18 ] . Previous studies have shown that LDH levels are high in patients with severe infections and multiple organ dysfunction, and are associated with an increased risk of AKI and other serious complications [ 19 – 21 ] . At the same time, low albumin levels often indicate disease progression and poor nutritional status of the body, which is a common feature in wasting diseases such as AP. The role of albumin combined with other indicators in AP has been widely used, which can help clinicians to preliminarily stratify AP patients to a certain extent [ 22 , 23 ] . LAR, as the ratio of LDH to ALB, has been applied to assess the severity and prognosis of various metabolic disorders such as infections and AKI in the body [ 24 , 25 ] . It can more sensitively reflect the stress response and nutritional status of the body, thus having the advantage of prognosis prediction. It's easy acquisition and low cost of LAR which makes it suitable for promotion and application in ICU and primary healthcare institutions. This feature is particularly suitable for medical environments with limited resources. It can help identify high-risk patients early and facilitate early intervention measures to reduce mortality with LAR. In addition, LAR is significantly positively correlated with ICU length of stay, indicating that LAR can not only serve as a predictive indicator of mortality risk, but also predict disease complexity and resource requirements, providing decision support for clinical doctors to optimize treatment and resource allocation. This study further expands the application scenarios of LAR in acute intensive care patients. Previous literature has explored the prognostic value of LAR in patients with tumors, infections, and acute kidney injury [ 26 , 27 ] , but its application in patients with AP has not been widely studied. The findings of this study further validate the significance of LAR as an inflammatory response indicator. However, there are differences in LAR expression between this study and cancer patients. The prognosis of AP patients with high LAR seems to be closely related to the occurrence of multiple organ dysfunction syndrome, which may be related to the pathophysiological characteristics of AP. The high mortality prediction accuracy of LAR in this study (AUC = 0.943) aligns with research findings in patients with acute kidney injury, further validating the prognostic value of LAR in acute inflammatory diseases. However, it should be noted that LAR is influenced by factors such as renal and liver function in AP patients. Therefore, LAR can serve as a preliminary screening tool, combined with other clinical and laboratory parameters, to form a multidimensional evaluation system. Despite its promising results, this study has certain limitations. Firstly,as a retrospective, single-center study, it requires further validation through multicenter and large sample studies. Although preliminary validation was conducted using the eICU database, variations in diagnosis, treatment processes, demographic characteristics, and patient clarification may impact the generalizability of the findings. Secondly, further longitudinal studies should to be explored whether the dynamic changes of LAR are synchronized with the progression of AP. The LAR values in this study were measured at the time of admission to the ICU, and it need further clarification of the relationship between their changing trends and prognosis. In addition, future research could be considerd combining LAR with other biomarkers to improve the accuracy of AP prognosis assessment. According to the results of this study, the evaluation of LAR on the prognosis of AP patients can be clarified. Due to its simple and fast detection characteristics, when patients are admitted to the ICU, it can help clinical doctors make preliminary judgments on AP patients, and then timely clinical intervention can be carried out to minimize the probability of severe transformation of AP patients and improve patient prognosis. Conclusion In conclusion, this study establishes that the lactate dehydrogenase to albumin ratio (LAR) is a robust independent predictor of 28-day mortality in patients with acute pancreatitis. Its strong association with key clinical outcomes highlights its potential as a valuable biomarker for early risk stratification and prognosis in AP. By integrating LAR into routine clinical practice, clinicians can gain a more comprehensive understanding of patient prognosis and tailor treatment strategies accordingly. Declarations Ethics declarations: This study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. The study protocol was reviewed and approved by the Ethics Committee of Shanghai East Hospital, Tongji University School of Medicine (Approval No. 2024YS-200). Given the retrospective nature of the study and the use of anonymized patient data, the requirement for informed consent was waived by the Ethics Committee. The study also utilized data from the eICU Collaborative Research Database, a publicly available database managed by the Massachusetts Institute of Technology (MIT). Access to the database was granted after completing the required training and obtaining certification in the use of human research data (Certification No.53376570). All data were de-identified, and the database complies with the Health Insurance Portability and Accountability Act (HIPAA) to ensure patient privacy. All methods were performed in compliance with relevant guidelines and regulations. Consent for publication All participating authors agree to publication of the article Availability of data and materials The datasets generated and analyzed during the current study are available upon reasonable request from the corresponding author. The study also utilized publicly available data from the eICU Collaborative Research Database, which can be accessed at https://eicu-crd.mit.edu/ following the completion of the required data use agreement and certification process. Competing interests The authors declare that they have no competing interests Clinical Trial Number:not applicable Funding: The peak supporting clinical discipline of Shanghai health bureau (2023ZDFC0104 to L.T) Author information Authors and Affiliations Department of Critical Care Medicine, Shanghai East Hospital, School of Medicine, Tongji University , Shanghai, 200120, China. Chun Wang, Xingping Lv,Xiaobin Liu, Wei Zhou, Tuo Shen, Qimin Ma, Shuyue Sheng, Yezhou Shen, Mei Yang, Shaolin Ma, Feng Zhu Contributions Chun Wang designed the study and wrote the paper.Xingping Lv analyzed the data. Prof. Shaolin Ma and Feng Zhu polished the manuscript and gave valuable suggestions for revision of the manuscript. All other authors interpreted data and provided critical revision of the manuscript. The final version to be submitted was approved by all the authors. References Habtezion A, Gukovskaya AS, Pandol SJ. Acute Pancreatitis: A Multifaceted Set of Organelle and Cellular Interactions. Gastroenterology. 2019;156(7):1941–50. Boxhoorn L, et al. Acute pancreatitis. Lancet. 2020;396(10252):726–34. Petrov MS, Yadav D. Global epidemiology and holistic prevention of pancreatitis. Nat Rev Gastroenterol Hepatol. 2019;16(3):175–84. Krishna SG, et al. The Changing Epidemiology of Acute Pancreatitis Hospitalizations: A Decade of Trends and the Impact of Chronic Pancreatitis. 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The association between lactate dehydrogenase to serum albumin ratio and the 28-day mortality in patients with sepsis-associated acute kidney injury in intensive care: a retrospective cohort study. Ren Fail. 2023;45(1):2212080. Shokr H et al. Lactate Dehydrogenase/Albumin To-Urea Ratio: A Novel Prognostic Maker for Fatal Clinical Complications in Patients with COVID-19 Infection. J Clin Med, 2022. 12(1). Jeon SY, et al. Lactate dehydrogenase to albumin ratio as a prognostic factor for patients with severe infection requiring intensive care. Med (Baltim). 2021;100(41):e27538. Fang Y, Zhang Y, Zhang X. The elevated lactate dehydrogenase to albumin ratio is a risk factor for developing sepsis-associated acute kidney injury: a single-center retrospective study. BMC Nephrol. 2024;25(1):201. Additional Declarations No competing interests reported. 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Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xingping","middleName":"","lastName":"Lv","suffix":""},{"id":462847148,"identity":"068e2b54-af1a-42f2-af44-b532ed2d3f2f","order_by":2,"name":"Xiaobin Liu","email":"","orcid":"","institution":"Shanghai East Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiaobin","middleName":"","lastName":"Liu","suffix":""},{"id":462847149,"identity":"1a3b52d1-ad3e-4f58-ac78-cab5ea220d73","order_by":3,"name":"Wei Zhou","email":"","orcid":"","institution":"Shanghai East Hospital","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Zhou","suffix":""},{"id":462847150,"identity":"a8b78b0d-905a-4fa1-9c63-abf4d43dc368","order_by":4,"name":"Tuo Shen","email":"","orcid":"","institution":"Shanghai East Hospital","correspondingAuthor":false,"prefix":"","firstName":"Tuo","middleName":"","lastName":"Shen","suffix":""},{"id":462847151,"identity":"8927381f-5afb-4b9a-a145-696027816a55","order_by":5,"name":"Qimin Ma","email":"","orcid":"","institution":"Shanghai East Hospital","correspondingAuthor":false,"prefix":"","firstName":"Qimin","middleName":"","lastName":"Ma","suffix":""},{"id":462847152,"identity":"2f2456c6-6320-44e3-b084-9e59fc9bdb66","order_by":6,"name":"Shuyue Sheng","email":"","orcid":"","institution":"Shanghai East Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shuyue","middleName":"","lastName":"Sheng","suffix":""},{"id":462847153,"identity":"70ad324e-7fbf-441b-9142-7f429df24902","order_by":7,"name":"Yezhou Shen","email":"","orcid":"","institution":"Shanghai East Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yezhou","middleName":"","lastName":"Shen","suffix":""},{"id":462847154,"identity":"731a5421-8b06-4608-95cb-31ea9eeb0937","order_by":8,"name":"Mei Yang","email":"","orcid":"","institution":"Shanghai East Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mei","middleName":"","lastName":"Yang","suffix":""},{"id":462847155,"identity":"c66d3c44-4d1c-4b99-ad82-8255f7bf9803","order_by":9,"name":"Shaolin Ma","email":"","orcid":"","institution":"Shanghai East Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shaolin","middleName":"","lastName":"Ma","suffix":""},{"id":462847156,"identity":"6a859023-f6f9-4f70-8f84-3af5df13b4f8","order_by":10,"name":"Feng Zhu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABA0lEQVRIiWNgGAWjYDACdiBmbGBgBlJsDAkVB8CCBx7g08KMouXMAQYekJYEIrQwgLUwtkG0MODTwt/MfEzy547D7Aa3m589eDjvjpy92OGHQFvs5HQbsGuROMyWbCB55jCzwZ1j5gaJ254Z80inGQC1JBubHcBhzWEewweGbUAtN3LYJBK3HU7skU4AaTmQuA2HFvnD/B8OJMK1zAFpSf+AV4vBYR7GBwfhWhpAWnLw22J4mM3YsLEtnVnyRpqZRMKxw8Y8t3MKDiQY4PaL3PHmZ5I/26yT+W4kP5P8UXNYjn12+uYPHyrs5HB6HwqS0R2MXzkI2BFWMgpGwSgYBSMWAAC4U2NOkFJm/QAAAABJRU5ErkJggg==","orcid":"","institution":"Shanghai East Hospital","correspondingAuthor":true,"prefix":"","firstName":"Feng","middleName":"","lastName":"Zhu","suffix":""}],"badges":[],"createdAt":"2025-04-19 10:23:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6484105/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6484105/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83676578,"identity":"59d1f5b0-8276-435e-ba07-9ed8ac48f0ad","added_by":"auto","created_at":"2025-05-30 14:59:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":23847,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve of 28-day mortality risk analysis between LAR and AP patients: The AUC of LAR in predicting 28-day mortality is 0.943, the optimal cutoff value is 29.050, the sensitivity is 90.0%, and the specificity is 88.9%.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-6484105/v1/b5af978829c0ee4c85ed554c.png"},{"id":83675824,"identity":"5c04b724-5568-43f0-9fca-722642d569a9","added_by":"auto","created_at":"2025-05-30 14:51:58","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":26766,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan Meier survival curves for high LAR and low LAR: High represents the high LAR group, Low represents the low LAR group\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-6484105/v1/49af062e870ae67c886aab00.png"},{"id":83675823,"identity":"493d9dfd-085e-45ac-9ebd-11d18e5daa0b","added_by":"auto","created_at":"2025-05-30 14:51:58","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":46901,"visible":true,"origin":"","legend":"\u003cp\u003eICU length of stay and total length of stay in high LAR and low LAR and: 1 represents the low LAR group, 2 represents the high LAR group\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-6484105/v1/6dde8b2db44954fa0292ec04.png"},{"id":83676579,"identity":"29315524-b233-4949-b3b0-fa9fdced910c","added_by":"auto","created_at":"2025-05-30 14:59:58","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":32696,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of laboratory indicators between high LAR and low LAR: 1 represents the low LAR group, 2 represents the high LAR group\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-6484105/v1/f4324e72a843e85c05f65588.png"},{"id":83675826,"identity":"e54f9398-4cb0-4e92-954c-f6a4d6231d77","added_by":"auto","created_at":"2025-05-30 14:51:58","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":54995,"visible":true,"origin":"","legend":"\u003cp\u003eThe relationship between LAR and ICU length of stay: LAR is linearly related to ICU stay, and there is a positive correlation between LAR and ICU length of stay, indicating that as LAR values increase, ICU length of stay also shows an increasing trend. Linear regression equation: y=0.5715 ⋅ x+2.103, where y represents ICU days and x represents LAR. Rho: Pearson correlation coefficient; R ^ 2: coefficient of determination.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-6484105/v1/7714bc7848d7c59a6a043a47.png"},{"id":83676584,"identity":"018978b3-ccd9-457b-84af-79f04e7662ea","added_by":"auto","created_at":"2025-05-30 14:59:58","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1223186,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve of validation set LAR and 28 day mortality risk analysis for AP patients: AUC 0.898\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-6484105/v1/1ab51d0b07039fc9fa67a127.png"},{"id":83676583,"identity":"e41ccf0e-26fe-4afd-9c5e-6f9894aa309c","added_by":"auto","created_at":"2025-05-30 14:59:58","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1899911,"visible":true,"origin":"","legend":"\u003cp\u003eThe relationship between high LAR and low LAR in the validation set and ICU length of stay and 28-day mortality rate in AP patients: The ICU length of stay and 28-day mortality rate of patients in the high LAR group were significantly prolonged, and the 28-day mortality rate was significantly increased (p\u0026lt;0.01)\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-6484105/v1/8883b5dd29ef1bda3ad32bf1.png"},{"id":101744541,"identity":"4eb574d0-f4ab-4c4f-b10f-95c0d1fe7f66","added_by":"auto","created_at":"2026-02-03 08:57:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1399215,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6484105/v1/179e2c1d-629b-45f3-a96d-6fa2a91a5239.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Correlation between lactate dehydrogenase to albumin ratio and prognosis of patients with acute pancreatitis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAP is a common digestive system disease in clinical practice, caused by various factors such as biliary tract disease, alcohol, surgery, trauma, etc., which can lead to multiple organ failure in severe cases\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. AP generally occurs in middle-aged and elderly people, with a global incidence rate of 34 per 100000 people\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e,and poses a significant challenge in clinical practice,despite a declining mortality rate over the years\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. The high mortality associated with severe acute pancreatitis underscores the importance of early monitoring of biomarkers that can predict prognosis and facilitate timely clinical intervention.\u003c/p\u003e \u003cp\u003eLactate dehydrogenase (LDH), an oxidoreductase isoenzyme catalyzing reversible reactions between pyruvate and lactate, primarily exists in the cytoplasm and plays a crucial role in glycolysis \u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e.Elevated LDH levels have been confirmed to have diagnostic value for severe acute pancreatitis and are a sensitive predictor of AP complicated by multiple organ failure.\u003csup\u003e[\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. However, LDH's non-specificity and widespread distribution in multiple tissues and organs limit its standalone clinical value in predicting AP prognosis. Serum albumin, on the other hand, has been independently associated with persistent organ failure caused by AP and exhibits certain predictive value for AP prognosis \u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. LAR is a novel inflammatory biomarker with certain predictive value for colorectal cancer\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e.Studies indicate that an elevated LAR upon admission is a risk factor for the prognosis of critically ill patients with acute kidney injury(AKI).\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAlthough research on LAR in other diseases is gradually increasing, there is currently a lack of relevant studies on the prognostic evaluation value of LAR in patients with acute pancreatitis. Considering the important roles of LDH and albumin in acute pancreatitis, LAR may amplify their effects and reflect systemic inflammatory response and metabolic disorders to a greater extent. This study aimed to assess the predictive ability of LAR for 28-day mortality in AP patients and validate its clinical utility in risk stratification.Initially, a prognostic analysis of LAR was conducted on single-center AP patients, followed by external validation using data from the eICU database. Our research will provide a new possibility for early risk assessment of AP patients and provide theoretical basis for optimizing clinical intervention strategies. This study has been approved by (2024YS-200)\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eResearch Design and Data Sources\u003c/h2\u003e \u003cp\u003eThis study is a single center retrospective cohort study, with data sourced from AP patients admitted to the Intensive Care Unit of Shanghai East Hospital from 2019 to 2024. To further validate the effectiveness of LAR in predicting the prognosis of AP, we conducted external validation using eICU database data.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy population\u003c/h3\u003e\n\u003cp\u003eInclusion criteria for the study population included patients aged 18 to 85 years, meeting the diagnostic criteria for AP\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e,while exclusion criteria encompassed ICU stays of less than 24 hours, history of malignant tumors or chronic kidney disease, severe infection prior to admission, and missing key data.\u003c/p\u003e\n\u003ch3\u003eData extraction\u003c/h3\u003e\n\u003cp\u003eCollect demographic data (gender, age, medical history), laboratory indicators (LDH, albumin [ALB], Cr, CysC, Hb, TB, white blood cell count [WBC], alanine aminotransferase [ALT], aspartate aminotransferase [AST], platelet count [PLT], triglycerides(Tg), and cholesterol, and calculate LAR, ICU length of stay, total length of stay, and 28-day prognosis.\u003c/p\u003e\n\u003ch3\u003eStatistical methods\u003c/h3\u003e\n\u003cp\u003e \u003cb\u003eUnivariate analysis\u003c/b\u003e Continuous variables with normal distribution are represented by mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (X\u0026thinsp;\u0026plusmn;\u0026thinsp;SD). Independent sample t-test was used for comparison between the two groups; Non normally distributed continuous variables are represented by median and quartile range(M [Q₁, Q₃]), and rank sum test is used; The categorical variables are represented by frequency (n [%]), and the comparison of differences between two groups is performed using chi square test or Fisher's exact probability method. The significance standard for differences is set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMultivariate Cox regression analysis\u003c/b\u003e Include variables significantly correlated with 28-day mortality rate in univariate analysis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) into the Cox multivariate regression model. Regression analysis calculates the hazard ratio (HR) and its 95% confidence interval (CI), where each unit increase in LAR represents a change in the hazard ratio.\u003c/p\u003e \u003cp\u003e \u003cb\u003eROC Curve Analysis of Subjects\u003c/b\u003e Using ROC curve analysis to assess the predictive efficacy of LAR for 28-day mortality in AP patients, calculating the area under the curve (AUC) and determining the optimal cutoff value to evaluate the predictive accuracy of LAR in the study population.\u003c/p\u003e \u003cp\u003e \u003cb\u003eKaplan Meier survival analysis\u003c/b\u003e Use Kaplan Meier survival analysis to evaluate the survival differences between high LAR group and low LAR group patients. The comparison between groups was conducted using the Log rank test, and the results were presented in the form of Kaplan Meier survival curves.\u003c/p\u003e \u003cp\u003e \u003cb\u003eValidation analysis\u003c/b\u003e We used independent AP patients data from the eICU database for external validation, calculated the AUC of LAR in the eICU validation set, and compared it with the main study data to evaluate the predictive performance of LAR in different populations.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics\u003c/h2\u003e \u003cp\u003eThis study included a total of 82 AP patients, and detailed baseline characteristics are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. All patients were divided into a death group (n\u0026thinsp;=\u0026thinsp;10) and a survival group (n\u0026thinsp;=\u0026thinsp;72) based on a 28-day prognosis. Baseline characteristics revealed no significant differences between the death and survival groups in terms of age, gender, Hb, cholesterol, triglyceride levels, diabetes incidence(p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Compared with the survival group, the LAR, ICU length of stay, total length of stay, Cr, TB, CysC, and proportion of hypertension were significantly increased in the death group, while PLT was significantly reduced (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of the study population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003evariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;82)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSurvival group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;72)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDeath group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003et/Z/X\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHb, X\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e133.23\u0026thinsp;\u0026plusmn;\u0026thinsp;28.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135.01\u0026thinsp;\u0026plusmn;\u0026thinsp;26.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120.40\u0026thinsp;\u0026plusmn;\u0026thinsp;38.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.131\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAR, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.64 (6.90, 24.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.41 (6.31, 17.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56.80 (38.68, 65.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-4.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICU length of stay, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.00 (5.00, 13.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.00 (5.00, 9.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.00 (23.25, 42.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-4.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal length of stay, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.50 (12.25, 28.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.00 (12.00, 25.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.50 (25.25, 47.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-2.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60.00 (42.00, 73.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.00 (41.50, 73.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67.50 (60.00, 73.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.427\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCr, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74.45 (56.25, 112.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.00 (55.50, 96.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e371.95 (159.93, 656.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-3.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTB, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.85 (11.12, 36.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.95 (10.35, 30.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58.05 (19.25, 98.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.50 (19.00, 85.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.70 (18.00, 68.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.00 (33.00, 399.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-1.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.40 (20.00, 103.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.00 (19.50, 88.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74.70 (30.68, 693.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLT, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e195.50 (152.50, 247.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e202.50 (158.00, 252.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e134.50 (118.25, 198.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-2.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.50 (11.60, 17.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.61 (11.65, 17.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.52 (10.60, 14.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.566\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTg, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.71 (1.10, 8.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.35 (1.03, 8.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.45 (2.00, 8.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.820\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003echolesterol,\u003c/p\u003e \u003cp\u003eM (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.54 (3.19, 7.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.82 (3.25, 7.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.86 (2.90, 6.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.327\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCysC, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.23 (0.78, 1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.06 (0.78, 1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.87 (1.26, 3.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-3.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egender, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u0026sup2;=0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.600\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (42.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (44.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (30.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e47 (57.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40 (55.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (70.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u0026sup2;=4.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.034\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\u003e38 (46.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (51.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (10.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\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\u003e44 (53.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (48.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (90.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u0026sup2;=0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.617\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\u003e51 (62.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46 (63.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (50.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\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\u003e31 (37.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (36.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (50.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eThe relationship between LAR and 28 day mortality rate\u003c/h3\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eCox multivariate regression analysis\u003c/h2\u003e \u003cp\u003eUnivariate analysis showed that variables significantly associated with 28-day mortality included LAR, ICU length of stay, total length of stay, Cr, TB, CysC, and PLT. Cox multivariate regression analysis further validated LAR as an independent predictor of 28-day mortality in AP patients. The results showed that for every unit increase in LAR, the 28 day mortality risk increased by 3% (HR\u0026thinsp;=\u0026thinsp;1.03, 95% CI: 1.01\u0026ndash;1.06, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate analysis and Cox multivariate regression analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\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=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c12\" namest=\"c8\"\u003e \u003cp\u003eCox multivariate regression analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eS.E\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eZ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eS.E\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eZ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\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\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.15 (0.55\u0026thinsp;~\u0026thinsp;8.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\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\u003e1.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.69 (0.71\u0026thinsp;~\u0026thinsp;45.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\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\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.75 (0.75\u0026thinsp;~\u0026thinsp;10.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.03 (1.01\u0026thinsp;~\u0026thinsp;1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1.03 (1.01\u0026thinsp;~\u0026thinsp;1.06)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.02 (0.97\u0026thinsp;~\u0026thinsp;1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.01 (1.01\u0026thinsp;~\u0026thinsp;1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.99 (0.99\u0026thinsp;~\u0026thinsp;1.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.01 (1.00\u0026thinsp;~\u0026thinsp;1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00 (1.00\u0026thinsp;~\u0026thinsp;1.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00 (1.00\u0026thinsp;~\u0026thinsp;1.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.99 (0.99\u0026thinsp;~\u0026thinsp;1.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.02 (0.93\u0026thinsp;~\u0026thinsp;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.01 (0.95\u0026thinsp;~\u0026thinsp;1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCholesterol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.02 (0.85\u0026thinsp;~\u0026thinsp;1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCysC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.83 (1.16\u0026thinsp;~\u0026thinsp;2.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e4.17 (0.73\u0026thinsp;~\u0026thinsp;23.91)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.99 (0.97\u0026thinsp;~\u0026thinsp;1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eROC curve analysis\u003c/h2\u003e \u003cp\u003eROC curve analysis demonstrated that LAR had a high prediction accuracy for 28-day mortality, with an AUC of 0.943. The optimal cutoff value, determined based on the maximum Youden index, was 29.050, corresponding to a sensitivity of 90.0% and a specificity of 88.9%, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eClinical differences between high LAR and low LAR groups\u003c/h2\u003e \u003cp\u003eAccording to the cutoff value of LAR (29.050), patients were divided into high LAR group (\u0026ge;\u0026thinsp;29.050) and low LAR group (\u0026lt;\u0026thinsp;29.050). Kaplan Meier survival analysis showed that the 28-day survival rate of patients in the high LAR group was significantly lower than that in the low LAR group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). At 28 days, the cumulative mortality rate of patients in the high LAR group was significantly higher than that in the low LAR group, indicating the potential role of LAR in patient risk stratification, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Moreover, both ICU length of day and total length of day were significantly prolonged (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. In addition, the Cr, TB, ALT, and AST levels in the high LAR group were significantly increased, while PLT was significantly decreased (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\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 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinical data and laboratory indicators of high LAR and low LAR patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;82)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow LAR(n\u0026thinsp;=\u0026thinsp;69)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ehigh LAR (n\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003et/Z/X\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHb, X\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e133.23\u0026thinsp;\u0026plusmn;\u0026thinsp;28.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135.75\u0026thinsp;\u0026plusmn;\u0026thinsp;27.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e119.85\u0026thinsp;\u0026plusmn;\u0026thinsp;33.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;1.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAR, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.64 (6.90, 24.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.23 (6.27, 15.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.23 (38.37, 58.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-5.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICU length of stay,\u003c/p\u003e \u003cp\u003eM (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.00 (5.00, 13.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.00 (5.00, 11.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.00 (8.00, 38.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-3.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal length of day,\u003c/p\u003e \u003cp\u003eM (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.50 (12.25, 28.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.00 (12.00, 25.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.00 (19.00, 49.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-2.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60.00 (42.00, 73.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.00 (40.00, 71.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66.00 (60.00, 82.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.131\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCr, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74.45 (56.25, 112.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.00 (54.00, 94.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e204.70 (95.00, 384.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-3.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTB, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.85 (11.12, 36.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.20 (10.20, 29.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.10 (24.20, 94.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-3.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.50 (19.00, 85.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.00 (18.00, 60.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88.00 (42.00, 276.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-2.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.40 (20.00, 103.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.00 (18.00, 77.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e112.00 (44.70, 595.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-3.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLT, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e195.50 (152.50, 247.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e206.00 (158.00, 257.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e139.00 (116.00, 202.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-2.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.50 (11.60, 17.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.59 (11.67, 17.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.76 (10.11, 17.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.657\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTg, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.71 (1.10, 8.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.41 (1.09, 8.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.05 (1.67, 8.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.784\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCholesterol, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.54 (3.19, 7.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.88 (3.25, 7.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.45 (2.97, 6.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.306\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCysC, M (Q₁, Q₃)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.23 (0.78, 1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.04 (0.77, 1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.30 (1.26, 2.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZ=-3.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u0026sup2;=0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.375\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (42.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (40.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (53.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e47 (57.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (59.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (46.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeath, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u0026sup2;=40.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.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\u003e72 (87.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68 (98.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (30.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\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\u003e10 (12.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (69.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u0026sup2;=3.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.067\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\u003e38 (46.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (50.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (23.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\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\u003e44 (53.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (49.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (76.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDm, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u0026sup2;=0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.000\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\u003e51 (62.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43 (62.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (61.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\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\u003e31 (37.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (37.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (38.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eLinear relationship between LAR and ICU length of stay\u003c/h2\u003e \u003cp\u003eAs the linear regression analysis yields the equation: y\u0026thinsp;=\u0026thinsp;0.5715*x\u0026thinsp;+\u0026thinsp;2.103 (where y represents ICU length of stay and x represents LAR),a moderate positive correlation was observed between LAR and ICU length of stay(Pearson correlation coefficient rho\u0026thinsp;=\u0026thinsp;0.544, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), with the average ICU length of stay increasing by approximately 0.57 days for each unit increase in LAR (R\u0026sup2;=0.3254).The Pearson correlation coefficient (rho) is 0.544, indicating a moderate positive correlation between LAR and ICU length of stay. The p-value is 1.276e-07, indicating a highly significant correlation, suggesting that the relationship between LAR and ICU length of stay is likely not caused by randomness. The coefficient of determination (R \u0026sup2;) is 0.3254, indicating that LAR can explain approximately 32.54% of the variation in ICU stay days. This indicates that LAR to some extent affects the length of ICU stay, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eValidation analysis\u003c/h2\u003e \u003cp\u003eIn the independent validation set of the eICU database, LAR's predictive effect on 28-day mortality rate of AP patients was consistent with the main dataset, with an AUC of 0.898, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. Patients in the high LAR group had a significantly prolonged ICU length of stay and increased 28-day mortality (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study evaluated the prognostic value of LAR in AP patients through retrospective analysis. The results showed that LAR was an independent predictor of 28-day mortality in AP patients, and high LAR patients had a significantly increased risk of 28-day mortality. This discovery supports the potential of LAR as an effective biomarker in early risk stratification of AP, and also provides new ideas for the management of severe acute pancreatitis.\u003c/p\u003e \u003cp\u003eThe pathogenesis of AP is due to impaired calcium signal transduction, mitochondrial dysfunction, premature activation of trypsinogen in acinar cells and macrophages, leading to pancreatic self digestion and causing a series of pathophysiological reactions such as pancreatic tissue necrosis\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. Currently, there is no effective treatment for AP in clinical practice. Therefore, early prediction of AP prognosis and timely strengthening of clinical management are of great significance for patients.\u003c/p\u003e \u003cp\u003eLDH is an important glycolytic enzyme in cells, commonly used for tumor recognition and treatment. It has carcinogenic and immunosuppressive effects, is a marker of decreased anti-tumor immune function, and is also a potential therapeutic target for cancer\u003csup\u003e[\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. When tissue undergoes inflammation, hypoxia, or injury, its release significantly increases, which is particularly evident in the pathological process of acute pancreatitis. LDH is also one of the indicators of Ranson score, which is of great significance for evaluating the severity of AP\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Previous studies have shown that LDH levels are high in patients with severe infections and multiple organ dysfunction, and are associated with an increased risk of AKI and other serious complications\u003csup\u003e[\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. At the same time, low albumin levels often indicate disease progression and poor nutritional status of the body, which is a common feature in wasting diseases such as AP. The role of albumin combined with other indicators in AP has been widely used, which can help clinicians to preliminarily stratify AP patients to a certain extent\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. LAR, as the ratio of LDH to ALB, has been applied to assess the severity and prognosis of various metabolic disorders such as infections and AKI in the body\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. It can more sensitively reflect the stress response and nutritional status of the body, thus having the advantage of prognosis prediction.\u003c/p\u003e \u003cp\u003eIt's easy acquisition and low cost of LAR which makes it suitable for promotion and application in ICU and primary healthcare institutions. This feature is particularly suitable for medical environments with limited resources. It can help identify high-risk patients early and facilitate early intervention measures to reduce mortality with LAR. In addition, LAR is significantly positively correlated with ICU length of stay, indicating that LAR can not only serve as a predictive indicator of mortality risk, but also predict disease complexity and resource requirements, providing decision support for clinical doctors to optimize treatment and resource allocation.\u003c/p\u003e \u003cp\u003eThis study further expands the application scenarios of LAR in acute intensive care patients. Previous literature has explored the prognostic value of LAR in patients with tumors, infections, and acute kidney injury\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e, but its application in patients with AP has not been widely studied. The findings of this study further validate the significance of LAR as an inflammatory response indicator. However, there are differences in LAR expression between this study and cancer patients. The prognosis of AP patients with high LAR seems to be closely related to the occurrence of multiple organ dysfunction syndrome, which may be related to the pathophysiological characteristics of AP.\u003c/p\u003e \u003cp\u003eThe high mortality prediction accuracy of LAR in this study (AUC\u0026thinsp;=\u0026thinsp;0.943) aligns with research findings in patients with acute kidney injury, further validating the prognostic value of LAR in acute inflammatory diseases. However, it should be noted that LAR is influenced by factors such as renal and liver function in AP patients. Therefore, LAR can serve as a preliminary screening tool, combined with other clinical and laboratory parameters, to form a multidimensional evaluation system.\u003c/p\u003e \u003cp\u003eDespite its promising results, this study has certain limitations. Firstly,as a retrospective, single-center study, it requires further validation through multicenter and large sample studies. Although preliminary validation was conducted using the eICU database, variations in diagnosis, treatment processes, demographic characteristics, and patient clarification may impact the generalizability of the findings. Secondly, further longitudinal studies should to be explored whether the dynamic changes of LAR are synchronized with the progression of AP. The LAR values in this study were measured at the time of admission to the ICU, and it need further clarification of the relationship between their changing trends and prognosis. In addition, future research could be considerd combining LAR with other biomarkers to improve the accuracy of AP prognosis assessment.\u003c/p\u003e \u003cp\u003eAccording to the results of this study, the evaluation of LAR on the prognosis of AP patients can be clarified. Due to its simple and fast detection characteristics, when patients are admitted to the ICU, it can help clinical doctors make preliminary judgments on AP patients, and then timely clinical intervention can be carried out to minimize the probability of severe transformation of AP patients and improve patient prognosis.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this study establishes that the lactate dehydrogenase to albumin ratio (LAR) is a robust independent predictor of 28-day mortality in patients with acute pancreatitis. Its strong association with key clinical outcomes highlights its potential as a valuable biomarker for early risk stratification and prognosis in AP. By integrating LAR into routine clinical practice, clinicians can gain a more comprehensive understanding of patient prognosis and tailor treatment strategies accordingly.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics declarations:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. The study protocol was reviewed and approved by the Ethics Committee of Shanghai East Hospital, Tongji University School of Medicine (Approval No. 2024YS-200). Given the retrospective nature of the study and the use of anonymized patient data, the requirement for informed consent was waived by the Ethics Committee.\u003c/p\u003e\n\u003cp\u003eThe study also utilized data from the eICU Collaborative Research Database, a publicly available database managed by the Massachusetts Institute of Technology (MIT). Access to the database was granted after completing the required training and obtaining certification in the use of human research data (Certification No.53376570). All data were de-identified, and the database complies with the Health Insurance Portability and Accountability Act (HIPAA) to ensure patient privacy.\u003c/p\u003e\n\u003cp\u003eAll methods were performed in compliance with relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participating authors agree to publication of the article\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are available upon reasonable request from the corresponding author.\u003c/p\u003e\n\u003cp\u003eThe study also utilized publicly available data from the eICU Collaborative Research Database, which can be accessed at https://eicu-crd.mit.edu/ following the completion of the required data use agreement and certification process.\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\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number:not applicable\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u0026nbsp; The peak supporting clinical discipline of Shanghai health bureau (2023ZDFC0104 to L.T)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and Affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDepartment of Critical Care Medicine, Shanghai East Hospital, School of Medicine, Tongji University , Shanghai, 200120, China.\u003c/p\u003e\n\u003cp\u003eChun Wang, Xingping Lv,Xiaobin Liu, Wei Zhou, Tuo Shen, Qimin Ma, Shuyue Sheng, Yezhou Shen, Mei Yang, Shaolin Ma, Feng Zhu \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChun Wang designed the study and wrote the paper.Xingping Lv analyzed the data. Prof. Shaolin Ma and Feng Zhu polished the manuscript and gave valuable suggestions for revision of the manuscript. All other authors interpreted data and provided critical revision of the manuscript. The final version to be submitted was approved by all the authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHabtezion A, Gukovskaya AS, Pandol SJ. Acute Pancreatitis: A Multifaceted Set of Organelle and Cellular Interactions. Gastroenterology. 2019;156(7):1941\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoxhoorn L, et al. Acute pancreatitis. Lancet. 2020;396(10252):726\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePetrov MS, Yadav D. Global epidemiology and holistic prevention of pancreatitis. Nat Rev Gastroenterol Hepatol. 2019;16(3):175\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKrishna SG, et al. 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Serum lactate dehydrogenase is predictive of persistent organ failure in acute pancreatitis. J Crit Care. 2017;41:161\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHong W et al. Serum Albumin Is Independently Associated with Persistent Organ Failure in Acute Pancreatitis. Can J Gastroenterol Hepatol, 2017. 2017: p. 5297143.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu J, et al. The value of lactate dehydrogenase to albumin ratio and immune inflammation biomarkers in colorectal cancer. Front Surg. 2023;10:1118403.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDeng Y, et al. Prognostic implication of lactic dehydrogenase-to-albumin ratio in critically ill patients with acute kidney injury. Clin Exp Nephrol. 2023;27(4):349\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLankisch PG, Apte M, Banks PA. Acute pancreatitis. 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Use of the C-Reactive Protein (CRP)/Albumin Ratio as a Severity Tool in Acute Pancreatitis. Syst Rev Cureus. 2022;14(9):e29243.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaad H, THOROUGH STUDY AND META-ANALYSIS OF THE PROGNOSTIC A, RELEVANCE OF THE C-REACTIVE-ALBUMIN RATIO IN ACUTE PANCREATITIS. Georgian Med News, 2023(343): pp. 111\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiang M, et al. The association between lactate dehydrogenase to serum albumin ratio and the 28-day mortality in patients with sepsis-associated acute kidney injury in intensive care: a retrospective cohort study. Ren Fail. 2023;45(1):2212080.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShokr H et al. Lactate Dehydrogenase/Albumin To-Urea Ratio: A Novel Prognostic Maker for Fatal Clinical Complications in Patients with COVID-19 Infection. J Clin Med, 2022. 12(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJeon SY, et al. Lactate dehydrogenase to albumin ratio as a prognostic factor for patients with severe infection requiring intensive care. Med (Baltim). 2021;100(41):e27538.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFang Y, Zhang Y, Zhang X. The elevated lactate dehydrogenase to albumin ratio is a risk factor for developing sepsis-associated acute kidney injury: a single-center retrospective study. BMC Nephrol. 2024;25(1):201.\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":"acute pancreatitis, lactate dehydrogenase, albumin, prognosis","lastPublishedDoi":"10.21203/rs.3.rs-6484105/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6484105/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003eThe aim of this study is to evaluate the relationship between lactate dehydrogenase to albumin ratio (LAR) and the prognosis of patients with acute pancreatitis (AP), and further validate its clinical utility as a biomarker.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eWe retrospectively analyzed the clinical data of 82 patients with acute pancreatitis admitted to the Intensive Care Unit of Shanghai East Hospital from 2019 to 2024. Based on their 28-day survival outcomes, the patients were categorized into a death group(n=10) and a survival group(n=72). Various clinical indicators, including age, gender, hemoglobin (Hb), total bilirubin (TB), and creatinine (Cr), were evaluated to further identify independent prognostic factors. The predictive power of LAR values was evaluated through Cox multivariate regression analysis and ROC curve, while Kaplan Meier survival analysis was used to analyze the survival differences among patients with different LAR levels. To verify the robustness of the results, we further independently validated the predictive ability of LAR using the eICU database.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eCompared with the survival group, the LAR of patients in the death group was significantly increased (p\u0026lt;0.01), and the ICU hospitalization time and total hospitalization time were significantly prolonged. Cox regression analysis showed that LAR was an independent predictor of 28-day mortality in AP patients (HR 1.03; 95% CI: 1.01-1.06). ROC analysis shows that the AUC of LAR is 0.943 and the cutoff value is 29.050. The 28-day mortality rate of patients in the high LAR group was significantly higher than that in the low LAR group (p\u0026lt;0.01). In the validation of eICU database, LAR also showed high prognostic predictive performance (AUC=0.898), indicating that this indicator has strong stability and universality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConcliusions: \u003c/strong\u003eLAR is an independent risk factor for 28-day mortality in AP patients and can effectively identify high-risk patients.\u003c/p\u003e","manuscriptTitle":"Correlation between lactate dehydrogenase to albumin ratio and prognosis of patients with acute pancreatitis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-30 14:51:53","doi":"10.21203/rs.3.rs-6484105/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":"4d3f9ccd-61f9-4064-b82e-31387c2dd0ad","owner":[],"postedDate":"May 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-03T08:57:12+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-30 14:51:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6484105","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6484105","identity":"rs-6484105","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}