Relationship between nine triglyceride-glucose-related indices and cardiometabolic multimorbidity incidence in patients with cardiovascular-kidney-metabolic syndrome stage 0–3: a nationwide prospective cohort study

BACKGROUND: Cardiovascular-kidney-metabolic (CKM) syndrome integrates metabolic, renal, and cardiovascular disease risk. While increasing evidence suggests that triglyceride-glucose (TyG)-related indices are associated with the future risk of cardiometabolic multimorbidity (CMM), their link to CMM in CKM syndrome has not been established. METHODS: This study analyzed participants with CKM syndrome stage 0-3 from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2020. We used Cox regression analysis, restricted cubic spline (RCS) curves, and Kaplan-Meier (K-M) survival curves to evaluate the relationship between TyG-related indices and CMM risk in patients with CKM stage 0-3 syndrome. Receiver operating characteristic (ROC) curves, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) analyses were used to assess the predictive performance of the TyG-related indices for CMM. RESULTS: During a median follow-up of 9 years, 652 participants (9.5%) developed CMM. The fully adjusted model revealed an elevated CMM risk across the highest quartiles of all indices, with hazard increases ranging from 72 to over 200%. A linear dose-response relationship was observed for most indices, except for triglyceride glucose-a body shape index (TyG-ABSI) and C-reactive protein-triglyceride-glucose index (CTI). The triglyceride glucose-Chinese visceral adiposity index (TyG-CVAI) achieved the highest area under the curve (AUC) for CMM prediction (0.679), and compared with the fully adjusted model (Model 4), all indices provided significant incremental predictive values. CONCLUSION: Nine TyG-related indices, particularly TyG-CVAI, are strong independent predictors of future CMM in patients with CKM syndrome stage 0-3. These findings underscore the utility of TyG-related indices, particularly TyG-CVAI, in identifying high-risk individuals, thereby informing strategies for the early detection and prevention of CKM syndrome.