Association between C-reactive protein-triglyceride glucose index (CTI) and cardiovascular and all-cause mortality
Gehui Ni1, Ziqi Chen1, Aijing Zhu2
1State Key Laboratory for Innovation and Transformation of Luobing Theory, Department of Cardiology, The First Affiliated Hospital With Nanjing Medical University, Jiangsu Province Hospital, Nanjing, 210029, China.
Insights
The C-reactive protein-triglyceride glucose index (CTI) is a strong predictor of mortality in older adults. Higher CTI levels indicate increased risk for all-cause and cardiovascular death, aiding in early risk stratification.
Area of Science:
- Gerontology and Geriatric Medicine
- Cardiovascular Disease Epidemiology
- Biomarker Discovery and Validation
Background:
- Cardiovascular disease (CVD) is a primary cause of mortality in aging populations worldwide.
- Existing biomarkers may not fully capture the combined risks of inflammation and metabolic dysfunction.
- The prognostic value of the C-reactive protein-triglyceride glucose index (CTI) in elderly individuals requires further investigation.
Purpose of the Study:
- To evaluate the association between the C-reactive protein-triglyceride glucose index (CTI) and all-cause and cardiovascular mortality in elderly populations.
- To compare the predictive performance of CTI against other established metabolic indices for mortality risk stratification.
- To assess the potential of CTI for enhancing early risk identification and guiding interventions in older adults.
Main Methods:
- A multi-cohort retrospective analysis involving NHANES, CHARLS, and Gaoyou datasets (n=11,619) of participants aged ≥60 years.
- Cox proportional hazards models, Kaplan-Meier curves, and restricted cubic splines were used to assess CTI and mortality associations.
- Time-dependent ROC curves and net reclassification improvement (NRI) were employed to compare CTI's predictive accuracy with other indices.
Main Results:
- Elevated CTI levels were significantly associated with increased risks of all-cause and cardiovascular mortality in fully adjusted models across all cohorts.
- A J-shaped nonlinear relationship between CTI and mortality was observed, with superior predictive performance (AUCs > 0.82) and improved risk reclassification compared to other indices.
- Sensitivity analyses confirmed the robustness of CTI's predictive power, with dynamic changes in CTI trajectory correlating with higher mortality.
Conclusions:
- The C-reactive protein-triglyceride glucose index (CTI) is a reliable and independent predictor of mortality in elderly populations in both the USA and China.
- CTI demonstrates superior predictive capability for mortality compared to other metabolic indices.
- Integrating CTI into clinical practice can improve early risk stratification and inform targeted interventions for aging adults at risk of CVD.
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.
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