Abstract
OBJECTIVE: To construct a novel model or a scoring system to predict hypertension comorbidity in older patients with obstructive sleep apnea syndrome (OSAS). METHODS: A total of 1290 older patients with OSAS from six tertiary hospitals in China were enrolled. The sample was randomly divided into a modeling set (80%) and validation set (20%) using a bootstrap method. Binary logistic regression analysis was used to identify influencing factors. According to the regression coefficients, a vivid nomogram was drawn, and an intuitive score was determined. The model and score were evaluated for discrimination and calibration. The Z-test was utilized to compare the predictive ability between the model and scoring system. RESULTS: In the multivariate analysis, age, body mass index (BMI), apnea-hypopnea index (AHI), total bilirubin (TB), high-density lipoprotein cholesterol (HDL-C), and fasting blood glucose (FBG) were significant predictors of hypertension. The area under the receiver operating characteristic curve of the model in the modeling and validation sets was 0.714 and 0.662, respectively. The scoring system had predictive ability equivalent to that of the model. Moreover, the calibration curve showed that the risk predicted by the model and the score was in good agreement with the actual hypertension risk. CONCLUSIONS: This accessible and practical correlation model and diagram can reliably identify older patients with OSAS at high risk of developing hypertension and facilitate solutions on modifying this risk most effectively.