Predictive Value of The Lactate-to-Albumin Ratio for 28-Day and 90-Day Mortality in Patients with Sepsis-Induced Coagulopathy
DOI:
https://doi.org/10.54097/vnn0pk11Keywords:
Sepsis-induced Coagulopathy, Lactate-to-albumin Ratio, Mortality, Prognosis, Retrospective StudyAbstract
Background/Objectives: To investigate the utility of the lactate-to-albumin ratio (LAR) as a novel clinical risk stratification tool for predicting 28-day and 90-day mortality in patients with sepsis-induced coagulopathy (SIC). Methods: We identified patients meeting Sepsis-3 and International Society on Thrombosis and Haemostasis (ISTH) SIC criteria from the MIMIC-IV database. The cohort was stratified into high-LAR (n=1,343) and low-LAR (n=1,344) groups based on the median value (M=0.805). Baseline characteristics were analyzed, and survival patterns were assessed using Kaplan–Meier analysis and multivariable Cox regression. Restricted cubic splines (RCS) were employed to detect nonlinear relationships, while threshold effect analysis identified specific inflection points. Predictive performance was quantified using the area under the receiver operating characteristic curve (AUC). Results: Baseline and Kaplan–Meier analyses revealed significantly elevated mortality risks in the high-LAR group compared to the low-LAR group (28-day: 50.89% vs 32.39%, P < 0.001; 90-day: 64.14% vs 46.91%, P < 0.001; log-rank P < 0.0001). Multivariable Cox regression confirmed LAR as an independent risk factor for SIC outcomes (28-day: HR=1.11, 95% CI: 1.06–1.16, P < 0.001; 90-day: HR=1.12, 95% CI: 1.08–1.17, P < 0.001). The AUCs for 28-day and 90-day mortality were 0.64 (95% CI: 0.62–0.66) and 0.63 (95% CI: 0.61–0.65), respectively. RCS and threshold analyses indicated a nonlinear association; below an inflection point of approximately 1.5, mortality risk increased progressively with rising LAR (28-day: LAR < 1.56, HR=1.42, P=0.002; 90-day: LAR < 1.50, HR=1.42, P < 0.001). Conclusions: LAR is an independent risk factor for both 28-day and 90-day mortality in patients with SIC and serves as a practical tool for early clinical risk stratification.
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