Abstract
Background
The albumin-bilirubin (ALBI) score, an objective liver function and prognostic indicator, has shown predictive value in various diseases, but its long-term prognostic significance in stroke survivors remains unclear.Objective
To evaluate the ALBI score's predictive value for all-cause mortality (ACM) in individuals with stroke.Methods
Data from the National Health and Nutrition Examination Survey (1999-2018) were analyzed. The Boruta algorithm selected key variables associated with ACM. Kaplan-Meier curves, Cox regression, and restricted cubic splines examined associations and nonlinearity between ALBI and ACM risk. Five machine learning (ML) models were built with 10-fold cross-validation; performance was assessed via C-index, integrated Brier score, time-dependent AUC, and calibration curves. SHapley Additive exPlanations (SHAP) interpreted the best model.Results
Among 1838 stroke survivors (median follow-up: 78 months), Boruta-selected variables included age, sex, race, marital status, body mass index, cardiovascular disease, lymphocyte count, aspartate/alanine aminotransferase, uric acid (UA), polyunsaturated fatty acids, basophil percentage, and creatinine. Kaplan-Meier curves showed significant survival differences across ALBI quartiles (log-rank P Conclusion
In stroke survivors, the ALBI score independently predicts ACM and may aid risk stratification and individualized management.