Abstract
OBJECTIVE: To evaluate the predictive value of lipid levels for coronary heart disease (CHD) risk in elderly hypertensive patients and to establish a prediction model. METHODS: Data from 428 elderly hypertensive patients attending the First Affiliated Hospital of Anhui Medical University between January 2021 and December 2023 were retrospectively collected. Patients were categorized into CHD and non-CHD groups based on the presence of comorbid CHD. Risk factors were identified using logistic regression, and a clinical prediction model was constructed. Model discrimination and calibration were assessed using receiver operating characteristic (ROC) curves and the Hosmer-Lemeshow test. Decision curve analysis (DCA) was used to assess the clinical application value of the model. RESULTS: Advanced age, smoking, hypertension duration >10 years, and abnormal total cholesterol (TC) were independently associated with an increased risk of CHD in elderly hypertensive patients. In addition, there was a trend linking abnormalities in low-density lipoprotein cholesterol (LDL-C) and lipoprotein(a) [Lp(a)] with higher CHD risk in this population. The developed clinical prediction model showed good discrimination (AUC=0.71) and calibration (P=0.907). The model's accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 0.69, 0.72, 0.60, 0.82, and 0.46, respectively. CONCLUSION: Abnormal lipid levels are independent predictors of increased CHD risk in elderly hypertensive patients. The prediction model developed in this study holds clinical value in assessing CHD risk, enabling early identification of high-risk patients and the development of individualized preventive strategies.