Head-to-head comparison of glucose-to-albumin ratio against five albumin-derived indices for predicting 28-day ICU mortality in critically ill patients with spontaneous intracerebral hemorrhage: a multicenter retrospective study

Background Spontaneous intracerebral hemorrhage (ICH) carries a 30-day mortality exceeding 40%. The glucose-to-albumin ratio (GAR) reflects metabolic stress and nutritional status. Although previous studies have demonstrated its prognostic value in ICH, its utility specifically in ICU-admitted patients and its comparative performance against other albumin-derived indices remain incompletely characterized. Methods We included 1,625 ICU ICH patients from MIMIC-IV (derivation) and 861 from two Chinese centers (external validation). Log-transformed GAR (LogGAR) was the exposure; 28-day ICU mortality was the primary outcome. Cox regression, restricted cubic splines, Kaplan–Meier, and Fine–Gray competing-risk models assessed LogGAR’s independent prognostic value, compared head-to-head with five albumin-derived indices. Lasso-selected features informed a multilayer perceptron (MLP), benchmarked against severity scores and a penalized logistic regression on identical features. Results LogGAR was independently associated with 28-day ICU mortality (derivation: HR = 1.81, 95% CI 1.33–2.47, p < 0.001; external: HR = 3.48, 95% CI 2.54–4.78, p < 0.001), with linear dose–response (RCS P-nonlinear = 0.315). Fine–Gray competing-risk analysis confirmed robustness (subdistribution HR = 2.01, 95% CI 1.58–2.57, p < 0.001). Adding LogGAR to six severity scores improved discrimination (external ΔAUC = 0.085–0.107, all p < 0.001). Among six indices, LogGAR was comparable to logLDAR in the derivation cohort (0.679 vs. 0.681, p = 0.78) and highest in the external cohort (0.691). Subgroup analyses identified significant effect modification only for AKI (FDR = 0.029). The Lasso-MLP (8 features) and penalized logistic regression achieved comparable performance (validation AUC 0.718 for both; external AUC 0.759 vs. 0.783), indicating no added value from nonlinearity. Calibration slopes were 0.66 (validation) and 0.91 (external). SHAP identified LogGAR as the top predictor. Conclusion LogGAR is independently associated with 28-day ICU mortality in critically ill patients with ICH and shows discriminative performance comparable to logLDAR and superior to the remaining four indices. A penalized logistic regression on Lasso-selected features matched the MLP, suggesting the predictive signal lies in features rather than model complexity—a pragmatic consideration for clinical implementation. As a readily available biomarker, LogGAR may support early ICU risk stratification.