Lactate-albumin ratio predicts in-hospital mortality in critically Ill patients with congestive heart failure and diabetes
Year: 2026
Type: article
Study design: Observational Study
Abstract: OBJECTIVE: To evaluate the predictive utility of the initial lactate-to-albumin ratio (LAR) measured within 24 h of admission for in-hospital all-cause mortality in critically ill patients with congestive heart failure (CHF) and diabetes mellitus (DM). METHODS: A retrospective cohort study was performed using the Medical Information Mart for Intensive Care IV (MIMIC-IV; n = 960) and the eICU Collaborative Research Database (eICU-CRD; n = 1,850). Kaplan-Meier curves, Cox regression, restricted cubic splines (RCS), subgroup analyses, and five machine learning models were applied, with predictive performance assessed via receiver operating characteristic (ROC), calibration curves, and decision curve analysis (DCA). RESULTS: The highest LAR quartile (Q4) was associated with higher in-hospital mortality (MIMIC-IV: 50.83%; eICU-CRD: 29.71%) than lower quartiles (all P < 0.001). LAR was identified as an independent predictor of in-hospital mortality (MIMIC-IV: HR = 1.878, P = 0.009; eICU-CRD: HR = 3.141, P < 0.001). RCS analysis revealed a positive association between LAR and in-hospital mortality. The most rapid slope change occurred at LAR = 2.73 in the MIMIC-IV cohort (nonlinear P = 0.072) and at LAR = 2.50 in the eICU-CRD cohort (nonlinear P < 0.001). For both outcomes, higher discriminative performance was observed for LAR than for lactate alone in both cohorts. Model performance was further improved when incorporating into machine learning models. CONCLUSION: Initial LAR is a reliable predictor of in-hospital mortality in critically ill CHF-DM patients.
Authors: Xiang Huang, Liang Zhao, Zhenxin Feng, Weihua Cai
Institution: Southern Medical University
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,990
OpenAlex ID: W7155638103
