ArticlePeerJ2026
Platelet-lymphocyte ratio and its dynamic changes predict mortality in septic acute kidney injury patients: a retrospective multi-center study using U.S. database and Chinese hospital data.
Article in PeerJ, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: The platelet-to-lymphocyte ratio (PLR), a readily available marker that integrates systemic inflammatory burden and immune competence, has emerged as a cost-effective prognostic biomarker in critical care medicine. Elevated PLR has been linked to adverse outcomes across a spectrum of critical illnesses, yet its utility in predicting prognosis among patients with septic acute kidney injury (AKI) remains undefined. Moreover, little is known about how in-hospital trajectories of PLR influence survival outcomes. Method: This retrospective study employed data from the Medical Information Mart for Intensive Care IV and West China Hospital of Sichuan University. The primary endpoints were 28-day and 90-day all-cause mortality. The association between baseline PLR/changes in PLR (ΔPLR) and 28-day and 90-day mortality was investigated by survival analysis and Cox proportional hazards models. ΔPLR was calculated as PLR at discharge minus PLR at admission. Patients were stratified based on optimal PLR cut-off values determined from the training cohort, and results were validated internally and externally. Predefined subgroup analyses probed for effect modification across key clinical populations, and mediation analysis was conducted to quantify intermediate variables linking PLR/ΔPLR dynamics to patient outcomes. Result: A total of 1,478 patients were included in the baseline-PLR cohort and 982 in the ΔPLR cohort. In the training set, an elevated baseline PLR (≥335.44) was associated with significantly higher 28-day mortality (26.56% Conclusion: Both baseline PLR and its dynamic change during hospitalization may serve as significant predictors of mortality in septic AKI. PLR-based indices could aid in risk stratification and early identification of high-risk patients.
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