Key result
Novel clinical score predicts hypertension risk in older OSAS patients with ~0.71 AUC.
Why the study?
To construct a novel model or scoring system to predict hypertension comorbidity in older patients with obstructive sleep apnea syndrome.
Does a clinical scoring model based on age, BMI, AHI, TB, HDL-C, and FBG accurately predict hypertension comorbidity in older patients with obstructive sleep apnea syndrome?
Cross-Sectional (n=1,290)
Yes
Does a clinical scoring model based on age, BMI, AHI, TB, HDL-C, and FBG accurately predict hypertension comorbidity in older patients with obstructive sleep apnea syndrome?
A novel, accessible scoring system incorporating six clinical and laboratory variables can reliably identify older patients with OSAS who are at high risk of comorbid hypertension.
May aid risk stratification in older OSAS; leaves open prospective validation before clinical adoption.
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.
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Zhao et al. (2025) conducted a cross-sectional in Obstructive sleep apnea syndrome (OSAS) (n=1,290). Predictive nomogram and scoring system was evaluated on Area under the ROC curve (AUC) for the prediction model in the modeling set (95% CI 0.6700-0.7588). A novel predictive model and scoring system incorporating age, BMI, AHI, fasting blood glucose, total bilirubin, and HDL-C reliably identified older OSAS patients at high risk of hypertension.
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