Triglyceride-glucose index combined with estimated pulse wave velocity improves stroke risk stratification in the CHARLS cohort.

Stroke remains a leading cause of morbidity and mortality globally, necessitating effective and accurate prediction strategies. Cardiovascular risk factors such as the triglyceride-glucose (TyG) index and estimated pulse wave velocity (ePWV) have been implicated in stroke risk, yet their combined impact on stroke prediction remains unclear. This study explores the association between the TyG index, ePWV, and their combined index (TyG-ePWV) in predicting stroke risk using data from the China Health and Retirement Longitudinal Study (CHARLS). Data from 8,444 participants aged 45 and older, collected over five waves from 2011 to 2020, were analyzed. Multivariable Cox proportional hazards models and Kaplan-Meier survival curves were used to assess the relationships between TyG, ePWV, and stroke risk. The combined TyG-ePWV index was examined for its predictive accuracy in stroke risk stratification. Both baseline TyG and ePWV were independently associated with an increased risk of stroke, with the combined TyG-ePWV index demonstrating the highest predictive power (HR = 1.99, 95% CI: 1.55-2.56, p < 0.001). A bidirectional interaction between TyG and ePWV was observed, indicating that each factor influences the other over time. ROC curve analysis showed that TyG-ePWV had superior stroke prediction accuracy (AUC = 0.754) compared to TyG and ePWV alone. Subgroup analyses revealed a stronger association between TyG-ePWV and stroke risk in older individuals. Sensitivity analyses confirmed the robustness of these findings across various datasets and subgroup conditions. Our study highlights the independent and synergistic role of TyG and ePWV in stroke risk prediction. The combined TyG-ePWV index proves to be a valuable tool for stroke risk stratification, offering enhanced predictive ability compared to traditional risk factors.