ArticleFrontiers in neurology2025
Predicting long-term mortality in spontaneous intracerebral hemorrhage patients using the advanced lung cancer inflammation index.
Article in Frontiers in neurology, 2025. 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 Advanced Lung Cancer Inflammation Index (ALI), a composite measure of inflammatory and nutritional status, has demonstrated prognostic value across various diseases. Given the involvement of systemic inflammation and malnutrition in post-stroke pathophysiology, ALI may serve as a physiologically relevant indicator for predicting long-term outcomes in patients with spontaneous intracerebral hemorrhage (ICH). This study aimed to assess the predictive accuracy of ALI for long-term mortality in ICH patients. Methods: This retrospective cohort study, conducted at West China Hospital, Sichuan University, included 2,541 patients with spontaneous ICH. Neutrophil count, lymphocyte count, serum albumin, and BMI were recorded within 24 h of admission to calculate ALI patients were into quartiles based on ALI values. Cox proportional hazards regression and restricted cubic spline analyses were used to evaluate the association between ALI and long-term mortality. Results: RCS analyses demonstrated a linear association between higher ALI values and a lower risk of all-cause mortality. This inverse relationship remained consistent after excluding in-hospital deaths, underscoring the robustness of the findings. Patients with higher ALI values, indicating better inflammatory and nutritional status, exhibited improved long-term survival. Furthermore, ROC analysis showed that ALI had modestly better predictive performance compared to other biomarkers (AUC = 0.67), highlighting its potential clinical utility in outcome prediction and management. Conclusion: In patients with spontaneous ICH, ALI is a practical and independent prognostic indicator of long-term mortality. By integration inflammatory and nutritional factors, ALI enhances risk stratification and may support individualized clinical decision-making.
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