Development and Validation of a Novel Model for Predicting Coronary Heart Disease in Snoring Hypertensive Patients with Hyperhomocysteinemia

Hypertensive patients with snoring and elevated plasma homocysteine levels are common. When these factors are combined, the risk of coronary heart disease (CHD) is high. Herein, we developed and validated an easy-to-use nomogram to predict high-risk CHD in snoring hypertensive patients with elevated plasma homocysteine. Snoring patients (n = 1,962) with hyperhomocysteinemia and hypertension were divided into training (n = 1,373, 70%) and validation (n = 589, 30%) sets. We extracted CHD predictors using multivariate Cox regression analysis, then constructed a nomogram model. Internal validation using 1,000 bootstrap resampling was performed to assess the consistency and discrimination of the predictive model using the area under the receiver operating characteristic curve (AUC) and calibration plots. We constructed a nomogram model with the extracted predictors, including age, waist-height ratio, smoking, and low-density lipoprotein cholesterol levels. The AUCs of the training and validation cohorts at 80 months were 0.735 (95% CI: 0.678-0.792) and 0.646 (95% CI: 0.547-0.746), respectively. The consistency between the observed CHD survival and the probability of CHD survival in the training and validation sets was acceptable based on the calibration plots. A total of more than 151 points in the nomogram can be used in the identification of high-risk patients for CHD among snoring hypertensive patients with elevated plasma homocysteine. We developed a CHD risk prediction model for snoring hypertension patients with hyperhomocysteinemia. Our findings provide a useful clinical tool for the rapid identification of high-risk CHD at an early stage.