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.
Abstract

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