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Retrospective cohort study reveals elevated glucose-to-lymphocyte ratio predicts increased 30-day and 360-day mortality in ICU pneumonia patients, highlighting its value for risk stratification.
This study aims to evaluate the correlation between the glucose-to-lymphocyte ratio (GLR) and prognosis in patients with pneumonia admitted to the intensive care unit (ICU). This retrospective cohort study analyzed data from the MIMIC-IV database. A total of 4,049 ICU patients with pneumonia were included. GLR was calculated as log₂{[glucose (mg/dL) ÷ 18] ÷ [lymphocyte (×10⁹/L)]}. The optimal cut-off value (3.152) was determined using the Youden index. Cox proportional hazards regression, Kaplan-Meier survival curves, and restricted cubic splines were used to assess the association between GLR and mortality. The incremental predictive value of GLR was evaluated by receiver operating characteristic (ROC) curve analysis. Patients were stratified into low GLR (< 3.152, n = 2,091) and high GLR (≥ 3.152, n = 1,958) groups. High GLR was associated with significantly worse clinical outcomes. In the fully adjusted model, each one-unit increase in GLR was associated with a 5% increase in 30-day mortality risk (HR = 1.05, 95% CI: 1.01–1.10) and a 6% increase in 360-day mortality risk (HR = 1.06, 95% CI: 1.02–1.09). Using the binary classification, high GLR was associated with a 20% increase in 30-day mortality (HR = 1.20, 95% CI: 1.06–1.36) and a 21% increase in 360-day mortality (HR = 1.21, 95% CI: 1.10–1.33). RCS analysis revealed linear relationships for both endpoints (p for nonlinear > 0.05). Subgroup analyses revealed no statistically significant interaction across the prespecified subgroups (all p-values for interaction > 0.05). ROC analysis showed that adding GLR to SOFA improved the AUC from 0.625 to 0.719 for 30-day mortality and from 0.616 to 0.718 for 360-day mortality. GLR is associated with 30-day and 360-day mortality in ICU patients with pneumonia. As a low-cost, readily available biomarker, GLR may aid in early risk stratification and clinical decision-making.
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Wang et al. (2026) studied this question.
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