Comprehensive Analysis of the Relationship Between Cardiometabolic Index and Coronary Heart Disease

Ruoling Guo,1,* Mingliang Sun,1,* Wenxin Lin,1 Huihui Yang,1 Jie Dou,1 Jie Gao,2 Ji Wang,3 Lina Liu,3 Tiejun Wei,3 Tong Liu,4 Xiaoyun Yang,3 Donglei Luo3,5 1Graduate School, Chengde Medical University, Chengde, 067000, People’s Republic of China; 2Department of Emergency Medicine, Handan First Hospital, Handan, 056000, People’s Republic of China; 3Department of Cardiology, Chengde Central Hospital/Second Clinical College of Chengde Medical University, Chengde, 067000, People’s Republic of China; 4Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, second Hospital of Tianjin Medical University, Tianjin, 300000, People’s Republic of China; 5Information Centre, Chengde Central Hospital/Second Clinical College of Chengde Medical University, Chengde, 067000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Donglei Luo, Department of Cardiology, Information Centre, Chengde Central Hospital/Second Clinical College of Chengde Medical University, Chengde, 067000, People’s Republic of China, Email dongleiluocn@aliyun.com Xiaoyun Yang, Department of Cardiology, Chengde Central Hospital/Second Clinical College of Chengde Medical University, Chengde, 067000, People’s Republic of China, Email 1831484837@qq.comObjective: Emerging evidence substantiates the cardiometabolic index (CMI) as a pivotal indicator demonstrating robust associations with an array of cardiovascular pathologies. However, its specific link to coronary heart disease (CHD) remains insufficiently explored. This study aimed to investigate both the association and the predictive value of CMI for CHD in a clinical cohort.Methods: This retrospective study included patients with suspected CHD who underwent coronary angiography at the Cardiology Department of Chengde Central Hospital between October 2023 and December 2024. Participants were stratified into CHD and non-CHD groups based on angiographic results. A LASSO regression and a logistic regression framework was implemented to examine the influence of age, sex, hypertension, diabetes, smoking, WBC, CK, CMI, and LDL-C on CHD. The association between CMI and CHD was explored using restricted cubic spline (RCS) methodology. The diagnostic efficacy of the model was scrutinized through the utilization of the area under the curve (AUC).Results: CMI exhibits an independent predictor for CHD, particularly in individuals with high CMI values (Q4 group), where the risk of CHD is markedly elevated. Furthermore, a linear relationship exists between CMI and CHD. Calibration curves demonstrate a strong alignment correlation linking predicted to observed probabilities. Decision curve analysis (DCA) reveals that the model provides substantial clinical benefit within a threshold probability range of 0.13 to 0.72. Receiver operating characteristic (ROC) curve analysis indicates that CMI possesses certain predictive merit for the occurrence of CHD.Conclusion: A positive association exists between CMI and incidence of CHD. Additionally, CMI serves as an independent risk factor, demonstrating certain predictive power in clinical settings, thereby effectively forecasting the risk of CHD occurrence.Keywords: coronary heart disease, cardiometabolic index, restricted cubic spline