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Relationship between C-reactive protein triglyceride glucose index and cardiovascular disease risk: a cross-sectional
Ruwen Zheng1, Tianyi Wang1, Min Liu2
1Heilongjiang University of Chinese Medicine, Harbin, 150040, China.
Insights
The C-reactive protein-triglyceride-glucose (CTI) index is linked to increased odds of cardiovascular disease (CVD). Higher CTI levels may help identify existing CVD cases, particularly in younger individuals.
Area of Science:
- Biomarkers and Diagnostics
- Cardiovascular Health
- Public Health Research
Background:
- Cardiovascular disease (CVD) remains a leading global health concern, necessitating effective risk assessment tools.
- Identifying novel biomarkers is crucial for early detection and management of CVD.
- This study focuses on the C-reactive protein-triglyceride-glucose (CTI) index as a potential CVD biomarker.
Purpose of the Study:
- To investigate the association between the CTI index and prevalent cardiovascular disease (CVD).
- To evaluate the CTI index's utility in classifying CVD status.
- To assess the performance of machine learning models in CVD risk stratification using the CTI index.
Main Methods:
- Analysis of 14,899 participants from the National Health and Nutrition Examination Survey (1999-2020).
- Utilized regression analysis, restricted cubic splines, and interaction tests to examine CTI-CVD relationships.
- Employed receiver operating characteristic (ROC) curves, decision curve analysis, SHAP analysis, and various machine learning models for risk assessment.
Main Results:
- A 1-unit increase in CTI was associated with an 18% higher odds of CVD (OR=1.18).
- Significant associations were found with specific CVD outcomes including congestive heart failure, heart attack, coronary heart disease, angina, and stroke.
- The CTI index demonstrated greater contribution to CVD classification than CRP or TyG in machine learning models, with AUCs >0.70.
Conclusions:
- Elevated CTI levels correlate with increased odds of prevalent CVD.
- The CTI index shows potential as a marker for identifying existing CVD.
- Further longitudinal studies are recommended to confirm predictive value in risk assessment.
Background:
Cardiovascular disease (CVD) continues to be a leading cause of disease burden and mortality worldwide. Identifying reliable biomarkers for CVD risk assessment is essential. This study investigates the association between the C-reactive protein-triglyceride-glucose (CTI) index and CVD, evaluating its potential value in CVD classification.
Methods:
This study included 14,899 participants aged 20 years and older from the 1999-2020 National Health and Nutrition Examination Survey. Regression analysis and restricted cubic splines (RCS) were used to examine the relationship between the CTI and CVD, along with its five specific outcomes. An interaction test assessed the impact of different subgroups on the association between CTI and CVD. Furthermore, the potential of CTI to assess CVD risk was evaluated through receiver operating characteristic (ROC) curves, decision curve analysis, and SHAP analysis, with machine learning models, including XGBoost, LASSO, random forest, support vector machine, and Naive Bayes, used for evaluation.
Results:
For each 1-unit higher CTI, the odds of having CVD were 18% higher (OR = 1.18, 95% CI: 1.10-1.28, P < 0.01). Specific associations include congestive heart failure (29%) (OR = 1.29, 95% CI: 1.14-1.47, P < 0.001), heart attack (29%) (OR = 1.29, 95% CI: 1.15-1.44, P < 0.001), coronary heart disease (20%) (OR = 1.20, 95% CI: 1.07-1.35, P < 0.01), angina (21%) (OR = 1.21, 95% CI: 1.06-1.36, P < 0.01), and stroke (13%) (OR = 1.13, 95% CI: 1.01-1.27, P < 0.05). Age influences the association between CTI and CVD, with individuals under 60 years being more affected. Machine-learning models achieved AUC > 0.70, indicating moderate discriminatory ability; these findings suggest promising potential for risk stratification. SHAP analysis indicated that CTI showed larger SHAP contributions to CVD classification than CRP and TyG within our models.
Conclusion:
Higher CTI levels were associated with higher odds of prevalent CVD, indicating that CTI may serve as a marker of CVD status and aid cross-sectional discrimination of prevalent CVD. Prospective longitudinal studies are needed to establish temporality and to evaluate whether CTI adds predictive value in longitudinal risk assessment.
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