Abstract
Obstructive sleep apnea (OSA) is a well-known risk factor for hypertension. Moderate-to-severe OSA is more likely to lead to resistant hypertension (RH) compared to the absence of moderate-to-severe OSA. Early identification of patients with OSA among those with RH is crucial for prioritizing diagnosis and reducing the burden. However, currently, there is a lack of specific tools for assessing the risk of moderate-to-severe OSA in patients with RH. In this retrospective cohort study conducted from October 2023 to August 2024, 659 patients with RH from the health examination center of a tertiary hospital in Northeast China completed polysomnography. Based on the polysomnography results, the participants were divided into a group without moderate-to-severe OSA (control group) and a moderate-to-severe OSA group. The sample was randomly divided into a development cohort (461 patients) and a validation cohort (198 patients), and the incidence of OSA in the two groups was comparable (P > 0.05). Relevant clinical data of patients with RH were collected. The Least Absolute Shrinkage and Selection Operator method was used to identify independent risk factors. Subsequently, three predictive models were developed based on ten variables, including waist circumference, waist-to-hip ratio, low-density lipoprotein, morning dry mouth, serum creatinine, homocysteine, drinking, cholesterol, triglycerides and smoking. Among these models, the random forest model showed excellent discrimination and calibration in development and validation cohorts. Additionally, decision curve analysis was performed on the random forest model, as well as the STOP-Bang questionnaire and the Berlin questionnaire, to evaluate their clinical benefits. Finally, Shapley Additive Explanations analysis clearly indicated that waist circumference was the most important factor in predicting comorbid moderate-to-severe OSA in RH patients.