Related Experiment Video
Updated: Sep 24, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Development and Validation of a Prognostic Model to Predict High-Risk Patients for Coronary Heart Disease in Snorers
Meng-Hui Wang1,2,3, Mulalibieke Heizhati1,2,3, Nan-Fang Li1,2,3
1Hypertension Center of People's Hospital of Xinjiang Uygur Autonomous Region, Ürümqi, China.
Insights
This study developed a new risk model for coronary heart disease (CHD) in patients who snore and have uncontrolled hypertension. The model uses age, waist circumference, and cholesterol levels to identify high-risk individuals for early intervention.
Area of Science:
- Cardiology
- Sleep Medicine
- Preventive Medicine
Background:
- Snoring and obstructive sleep apnea (OSA) are prevalent conditions.
- Uncontrolled hypertension is a significant risk factor for cardiovascular disease.
- Combined, OSA and uncontrolled hypertension substantially elevate the risk of coronary heart disease (CHD).
Purpose of the Study:
- To develop and validate a predictive model for CHD risk.
- To identify patients with snoring and uncontrolled hypertension who are at high risk for CHD.
- To aid clinicians in early risk stratification and intervention.
Main Methods:
- A cohort of 1,822 snorers with uncontrolled hypertension was analyzed.
- Data were randomly split into training (70%) and validation (30%) sets.
- A nomogram model was constructed using multivariate Cox regression, incorporating predictors like age, waist circumference, HDL-C, and LDL-C. Internal validation was performed using bootstrapping and C-index analysis.
Main Results:
- The final model included age, waist circumference (WC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C).
- The model demonstrated good discrimination, with C-indices of 0.720 in the derivation cohort and 0.703 in the validation cohort.
- Calibration plots confirmed acceptable consistency between predicted and observed CHD-free survival rates.
Conclusions:
- A validated CHD risk prediction model was successfully developed for snorers with uncontrolled hypertension.
- The model, utilizing age, WC, HDL-C, and LDL-C, facilitates early identification of high-risk individuals.
- This tool can assist clinicians in proactive patient management to mitigate CHD risk.
Purpose:
Snoring or obstructive sleep apnea, with or without uncontrolled hypertension, is common and significantly increases the risk of coronary heart disease (CHD). The aim of this study was to develop and validate a prognostic model to predict and identify high-risk patients for CHD among snorers with uncontrolled hypertension.
Methods:
Records from 1,822 snorers with uncontrolled hypertension were randomly divided into a training set (n = 1,275, 70%) and validation set (n = 547, 30%). Predictors for CHD were extracted to construct a nomogram model based on multivariate Cox regression analysis. We performed a single-split verification and 1,000 bootstraps resampling internal validation to assess the discrimination and consistency of the prediction model using area under the receiver operating characteristic curve (AUC) and calibration plots. Based on the linear predictors, a risk classifier for CHD could be set.
Results:
Age, waist circumference (WC), and high- and low-density lipoprotein cholesterol (HDL-C and LDL-C) were extracted as the predictors to generate this nomogram model. The C-index was 0.720 (95% confidence interval 0.663-0.777) in the derivation cohort and 0.703 (0.630-0.776) in the validation cohort. The AUC was 0.757 (0.626-0.887), 0.739 (0.647-0.831), and 0.732 (0.665-0.799) in the training set and 0.689 (0.542-0.837), 0.701 (0.606-0.796), and 0.712 (0.615-0.808) in the validation set at 3, 5, and 8 years, respectively. The calibration plots showed acceptable consistency between the probability of CHD-free survival and the observed CHD-free survival in the training and validation sets. A total of more than 134 points in the nomogram can be used in the identification of high-risk patients for CHD among snorers with uncontrolled hypertension.
Conclusion:
We developed a CHD risk prediction model in snorers with uncontrolled hypertension, which includes age, WC, HDL-C, and LDL-C, and can help clinicians with early and quick identification of patients with a high risk for CHD.
Related Concept Videos
Hypertension III: Clinical Manifestations and Diagnostic Studies
Sleep Apnea
The condition is more prevalent among...
Hypertension II: Pathophysiology
Coronary Artery Disease I: Introduction
Pulmonary Hypertension: Classification and Pathogenesis
There are various classifications for PH, each relating to different underlying causes and also...
Hypertension V: Nursing Management

