Volume 11,Issue 1
Predictive Value of the C-Reactive Protein–Triglyceride–Glucose Composite Index for All-Cause Mortality in General Population: A Dual-Cohort Study Based on NHANES and CHARLS
Background: Metabolic dysregulation and chronic inflammation coexist commonly, synergistically increasing cardiovascular and all-cause mortality. Single biomarkers fail to comprehensively assess metabolism-inflammation imbalance. This study first validates the dose-response relationship between CTI (a novel dual-pathway composite biomarker) and all-cause mortality across two cross-continental cohorts. Methods: Data from NHANES (n = 7, 752) and CHARLS (n = 9, 352) were integrated. CTI was calculated for all participants. Statistical methods including multivariable Cox model, propensity score overlap weighting, RCS regression, and competing risk model analyzed CTI-mortality correlation. Sensitivity analysis and external validation ensured result robustness. Results: Median follow-ups: 11.3 years (NHANES, 1, 260 deaths) and 9 years (CHARLS, 236 deaths). Fully adjusted Model 3: Each 1-unit CTI increase linked to 21% (NHANES: HR = 1.21, 95% CI: 1.12–1.31) and 56% (CHARLS: HR = 1.56, 95% CI: 1.34–1.82) higher all-cause mortality. All-cause mortality surged when CTI > 9.77 (NHANES) or > 7.54 (CHARLS) (P < 0.001). Highest CTI quartile had 37% (NHANES) and 221% (CHARLS) higher mortality vs. lowest; effect pronounced in middle-aged and elderly (CHARLS, median age 58). CTI (AUC = 0.61) outperformed TyG or CRP alone. Conclusions: CTI, integrating inflammatory and metabolic indicators, effectively identifies high-risk individuals across populations. With population-specific thresholds, it is promising for routine health screening risk stratification, guiding early intervention.
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