Development and Validation of a Coronary Heart Disease Risk Prediction Model in Snorers with Hypertension: A Retrospective Observed Study - Wang M; Wang M; Zhu Q; Yao X; Heizhati M; Cai X; Ma Y; Wang R; Hong J; Yao L; Sun L; Yue N; et al. (Dove Medical Press, 2022)
Mengru Wang,1,* Menghui Wang,1,* Qing Zhu,1,2 Xiaoguang Yao,1 Mulalibieke Heizhati,1 Xintian Cai,1,2 Yue Ma,1 Run Wang,1 Jing Hong,1 Ling Yao,1 Le Sun,1 Na Yue,1 Yingli Ren,1 Nanfang Li1 1Hypertension Center, Xinjiang Hypertension Institute, National Health Committee Key Laboratory of Hypertension Clinical Research, Key Laboratory of Xinjiang Uygur Autonomous Region, Xinjiang Clinical Medical Research Center for Hypertension Diseases, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, Xinjiang, People's Republic of China; 2Graduate School, Xinjiang Medical University, Urumqi, Xinjiang, People's Republic of China*These authors contributed equally to this workCorrespondence: Nanfang Li, Hypertension Center, Xinjiang Hypertension Institute, National Health Committee Key Laboratory of Hypertension Clinical Research, Key Laboratory of Xinjiang Uygur Autonomous Region, Xinjiang Clinical Medical Research Center for Hypertension Diseases, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, Xinjiang, People's Republic of China, Email lnanfang2016@sina.comPurpose: To develop and validate a risk prediction model for coronary heart disease (CHD) in snorers with hypertension, including traditional and new risk factors.Patients and Methods: Twenty factors were evaluated in the records of 2810 snorers with hypertension. Training (70%) and validation (30%) sets were created by random allocation of data, and a new nomogram model was developed. The model's discrimination and calibration were measured by calculating the area under the receiver operating curve (AUC) and creating calibration charts. The performance of the nomogram model was compared with that of the Prediction for ASCVD Risk in China (China-PAR) and Framingham models by decision curve analysis. An optimal cutoff point for the risk score in the training set was computed to stratify patients.Results: In the nomogram model, the AUCs for predicting CHD at 5, 7 and 9 years in the training set were 0.706 (95% confidence interval [CI] 0.649- 0.763), 0.703 (95% CI 0.655- 0.751) and 0.669 (95% CI 0.593- 0.744), respectively. The respective AUCs were 0.682 (95% CI 0.607- 0.758), 0.689 (95% CI 0.618- 0.760) and 0.664 (95% CI 0.539- 0.789) in the validation set. The calibration chart showed that the predicted events from the nomogram score were close to the observed events. Decision curve analysis indicated that the nomogram score was slightly better than the Prediction for ASCVD Risk in China (China-PAR) and Framingham models for predicting the risk of CHD in snorers with hypertension. A cutoff point was identified for being CHD-free (a nomogram score of ≤ 121), which could be helpful for the early identification of individuals at high-risk of CHD.Conclusion: The nomogram score predicts the risk probability of CHD in snorers with hypertension at 5, 7 and 9 years, and shows good capability in terms of discrimination and calibration. It may be a useful tool for identifying individuals at high risk of CHD.Keywords: snorer, hypertension, coronary heart disease, prediction model