Joint effect of triglyceride-glucose index and low-density lipoprotein cholesterol on mortality and days alive out of hospital in acute stroke: a multi-center machine learning-based cohort study.

Published in Diabetes research and clinical practice. Abstract: The lipid paradox suggests low LDL-C is paradoxically associated with poor outcomes, yet its joint effect with insulin resistance in acute stroke remains unclear. This study aimed to evaluate the combined association of triglyceride-glucose (TyG) index and LDL-C with mortality and days alive out of hospital (DAOH) METHODS: This multi-center cohort study used MIMIC as the derivation cohort and eICU-CRD as external validation. Multivariable regression, survival analysis, and RCS were used to assess the associations of TyG and LDL-C with mortality and DAOH90. Mediation analysis explored potential mechanisms. Boruta and LASSO selected features for ten machine learning models, with SHAP for interpretation. Among 3,028 MIMIC and 2,385 eICU patients, TyG showed a positive linear association with mortality, while LDL-C exhibited an L-shaped association. The low LDL-C + high TyG group had the highest in-hospital mortality (OR = 3.36, 95%CI: 2.37-4.76) and shortest DAOH90. Inpatient statin use was associated with lower mortality. WBC statistically accounted for 15.46% of the observed association between TyG and in-hospital mortality. Among multivariable machine-learning models incorporating nine selected predictors, GBM achieved the best performance (AUC = 0.802). High TyG combined with low LDL-C identifies a high-risk phenotype in acute stroke, significantly associated with adverse outcomes. TyG and LDL-C may serve as accessible biomarkers for risk stratification in acute stroke.