The development of a coronary heart disease risk prediction model based on non-invasive myocardial work parameters and lipid metabolism indicators

Objective： The aim is to develop a new risk prediction model for coronary heart disease (CHD) by utilizing Non-invasive Myocardial Work（MW）parameters and lipid metabolism indicators, so as to identify and manage populations at high risk of CHD at an early stage. Methods： Patients with suspected CHD who were admitted to the Affiliated Hospital of Youjiang Medical University for Nationalities from October 2024 to June 2025 and scheduled to undergo Coronary Angiography (CAG) were prospectively collected. They were divided into the CHD group and the non-CHD group according to the CAG results. Logistic regression was used to identify factors related to CHD, and R-Studio was employed to construct a nomogram model for predicting CHD based on independent predictors. Results ：Pearson correlation analysis and multivariate logistic regression analysis showed that the Atherogenic Index of Plasma (AIP), Global Work Index (GWI), Global Wasted Work (GWW), and Left Ventricular Posterior Wall （LVPW）at End - Diastole were independent risk factors associated with CHD.Based on the results of multivariate logistic regression, the CHD risk prediction model constructed using R-Studio showed an average AUC of 0.836 and a C-index of 0.847 in the validation set, indicating that the model can well distinguish between high-risk and low-risk populations for CHD. After calibration, the Mean Absolute Error (MAE) of the calibration curve was 0.017, which further verified the robustness and reliability of its discriminative efficacy. Decision curve analysis showed that when the threshold probability was in the range of 10%-95%, the model had a relatively high clinical net benefit value. Conclusion： This study established a CHD risk prediction model based on non-invasive myocardial work parameters and lipid metabolism indicators, which can effectively identify high-risk populations of CHD. It provides a non-invasive, portable and accurate CHD risk assessment tool for most medical institutions in China, assists clinicians in making correct clinical decisions, and thus improves the prognostic effect.