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Updated: Apr 30, 2026
Microfluidics in Assessing Platelet Function
Published on: November 8, 2024
Platelet-To-Lymphocyte Ratio and 28-Day Survival in Critically Ill Patients With Pulmonary Hypertension: Insights
1Department of Cardiology, Affiliated Hospital of Yangzhou University, Yangzhou University, 225001 Yangzhou, Jiangsu, China.
Aims/Background:
Existing pulmonary arterial hypertension (PAH) risk stratification, based on hemodynamics and functional parameters, is often inadequate in critical illness. The platelet-to-lymphocyte ratio (PLR), reflecting inflammatory and thrombotic pathways, may enhance outcome prediction. This study aimed to determine the prognostic value of PLR for 28-day mortality in critically ill PAH patients, evaluate nonlinear thresholds, and validate predictive performance using machine learning.
Methods:
A retrospective cohort of 1512 PAH patients was extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) v3.0 database (2008-2022). PLR was derived from admission hematologic parameters. Multivariable Cox regression, restricted cubic spline (RCS) models, and machine learning algorithms were employed to assess associations between PLR and mortality.
Results:
RCS analysis revealed a U-shaped relationship with mortality, identifying critical thresholds: PLR <67.32 was associated with reduced risk, while PLR >75.92 indicated an abrupt risk escalation (adjusted hazard ratio (HR) = 2.261, 95% confidence interval (CI): 1.053-4.854, p = 0.014). Machine learning models incorporating PLR achieved moderate discrimination (concordance index [C-index] = 0.700). Subgroup analyses confirmed consistent prognostic value across age, sex, chronic kidney disease (CKD), and chronic obstructive pulmonary disease (COPD) subgroups (all p-interaction > 0.05).
Conclusion:
PLR represents an independent predictor of short-term mortality in critically ill PAH patients, with nonlinear thresholds offering actionable risk stratification. Integration of PLR into prognostic models may strengthen early risk assessment and guide timely interventions in critical care settings.
