Association between C-reactive protein-triglyceride glucose index (CTI) and cardiovascular and all-cause mortality risk among the elderly population: insights from three datasets

BACKGROUND: Cardiovascular disease (CVD) is a leading cause of death globally, especially in the aging population. As a novel biomarker integrating inflammation and metabolic dysregulation, the C-reactive protein-triglyceride glucose index (CTI) may offer superior risk stratification, but its prognostic value for mortality in the elderly remains unclear. METHODS: This multi-cohort retrospective study analyzed data from the NHANES (1999-2010), the CHARLS, and the regional Gaoyou datasets, focusing on participants aged ≥ 60 years. Associations between CTI quartiles and all-cause/cardiovascular mortality were assessed using Cox proportional hazards models, Kaplan-Meier curves, and restricted cubic splines. The predictive performance of CTI was compared with other metabolic indices (TyG, TyG-WC, etc.) using time-dependent ROC curves and net reclassification improvement (NRI). RESULTS: Among 11,619 elderly participants, higher CTI levels were significantly associated with increased risks of all-cause and cardiovascular mortality across all three cohorts after full adjustment. A J-shaped nonlinear relationship was identified with an inflection point at CTI = 8.31, and subgroup analyses confirmed consistency across most strata. CTI demonstrated superior predictive performance for mortality (AUCs: 0.8445 for all-cause mortality and 0.8208 for cardiovascular mortality) and significantly improved risk reclassification (NRI > 0, p < 0.05) compared with other indices. The effectiveness of the prediction models was respectively verified in different Chinese databases. Sensitivity analyses on dynamic changes indicated that elevated trajectory of CTI represented higher mortality. CONCLUSION: Elevated CTI is a robust and independent predictor of all-cause and cardiovascular mortality in the elderly populations of both the USA and China. Its integration into clinical practice could enhance early risk stratification and guide targeted interventions to mitigate mortality risk in aging adults.