Association of platelet-to-lymphocyte ratio with 1-year all-cause mortality in ICU patients with heart failure

Sci Rep. 2024 Dec 30;14(1):32016. doi: 10.1038/s41598-024-83583-1.

Abstract

The Platelet-to-Lymphocyte Ratio (PLR) has emerged as a cost-effective biomarker for systemic inflammation and adverse cardiovascular outcomes, yet its prognostic value in critically ill patients with heart failure (HF) remains unclear. Leveraging the MIMIC-IV database, this study investigates the association between PLR and 1-year all-cause mortality in 7,217 ICU patients with HF. Patients were stratified into tertiles (0-126.45, 126.45-252.40, and 252.40-1000), and mortality risk was analyzed using Kaplan-Meier survival curves and Cox proportional hazards models. Elevated PLR was independently associated with higher mortality, with the highest tertile showing a 36% increased risk compared to the lowest (HR 1.36, 95% CI: 1.23-1.50, P < 0.001). Each tertile increment corresponded to a 17% rise in risk. Subgroup analyses revealed stronger associations in hypertensive patients and identified renal dysfunction and red cell distribution width as key modifiers. Integrating PLR with SOFA and APS III scores significantly enhanced predictive accuracy. By reflecting systemic inflammation and immune dysregulation, PLR offers a robust tool for long-term risk stratification and personalized management of ICU patients with HF. These findings highlight the potential of PLR to refine prognostic models, guide clinical decision-making, and improve critical care outcomes.

Keywords: All-cause mortality; Heart failure; Inflammation; MIMIC-IV; PLR.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Biomarkers / blood
  • Blood Platelets* / pathology
  • Critical Illness / mortality
  • Female
  • Heart Failure* / blood
  • Heart Failure* / mortality
  • Humans
  • Intensive Care Units*
  • Kaplan-Meier Estimate
  • Lymphocyte Count
  • Lymphocytes*
  • Male
  • Middle Aged
  • Platelet Count
  • Prognosis
  • Proportional Hazards Models

Substances

  • Biomarkers