Association of lactate-to-albumin ratio with 28-day mortality in elderly sepsis patients: a retrospective MIMIC-IV

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Updated: Feb 6, 2026

The ITS2 Database
16:17

The ITS2 Database

Published on: March 12, 2012

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Minhui Dai1,2,3,4,5,6, Bowen Yuan7, Yun Tan8

  • 1Department of Respiratory Medicine, Branch of National Clinical Research Center for Respiratory Disease, Xiangya Hospital, National Key Clinical Specialty, Central South University, Changsha, China.

BMC Infectious Diseases
|February 4, 2026
PubMed
Abstract

Insights

The lactate-to-albumin ratio (LAR) predicts 28-day mortality in elderly sepsis patients. An integrated machine learning model incorporating LAR shows robust prognostic performance for clinical decision-making.

Area of Science:

  • Critical Care Medicine
  • Geriatric Medicine
  • Biomarker Research

Background:

  • The lactate-to-albumin ratio (LAR) is linked to mortality in critically ill individuals.
  • Its predictive utility for sepsis outcomes in the elderly population requires further investigation.

Purpose of the Study:

  • To evaluate the lactate-to-albumin ratio (LAR) as a predictor of 28-day mortality in elderly patients diagnosed with sepsis.
  • To assess the performance of machine learning models incorporating LAR for predicting sepsis mortality in this demographic.

Main Methods:

  • Retrospective cohort study utilizing the MIMIC-IV database.
  • Analysis included multivariate logistic regression, restricted cubic splines, subgroup analyses, and machine learning algorithms (LightGBM, XGBoost, SVM).
  • Primary endpoint was 28-day intensive care unit (ICU) mortality.

Main Results:

  • Elevated log (LAR) was an independent predictor of 28-day mortality in elderly sepsis patients (adjusted OR = 3.29).
  • A linear association was observed between LAR and mortality.
  • The LightGBM model demonstrated strong discriminative ability (AUC = 0.788), with log (LAR) being a key feature.

Conclusions:

  • The lactate-to-albumin ratio (LAR) is a significant independent predictor of 28-day mortality in elderly sepsis patients.
  • An integrated machine learning model incorporating LAR offers robust prognostic performance.
  • This model may assist in clinical decision-making for elderly sepsis patients, pending external validation.
Keywords:
Elderly patientsLactate-to-albumin ratioMachine learning modelsMortalitySepsis

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