Abstract
BACKGROUND: Previous studies have demonstrated that the triglyceride-glucose (TyG) index in combination with the estimated glucose disposal rate (eGDR) could predict mortality risks in the normal population. Our studies have focused on their additive effects on patients with cardiovascular-kidney metabolic syndrome (CKM) syndrome stages 0-3. METHODS: Participants were sourced from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018. The restricted cubic spline (RCS) curves modeled the associations between the TyG index, eGDR, and mortality. Cox proportional regression models, Kaplan-Meier (KM) curve and subgroup analysis were performed to investigate the combined association. Machine learning was used in the development of predictive models. RESULTS: A total of 11,206 participants with CKM syndrome stages 0-3 were involved. The median follow-up time was 104 days, in which 1,079 cases of all-cause death and 299 cases of cardiovascular death were recorded. The RCS curve proved that the associations of the TyG index and eGDR with mortality followed a J-shape and an L-shape, respectively. Compared with the low TyG/high eGDR group, the all-cause mortality rate in TyG ≥ 8.72 and eGDR < 10.8 group was 14.9%, with a hazard ratio (HR) of 3.338 (95% confidence interval [CI]: 1.448-7.696), while the cardiovascular mortality rate was 4.8%, with an HR of 1.786 (95% CI: 1.023-3.119). CONCLUSIONS: In individuals with CKM syndrome stages 0-3, it is more advisable to integrate the TyG index and eGDR when assessing insulin resistance and predicting the risks of long-term mortality.