The Exploration of the Relationship Between Hypertension and Sleep Apnea Through Heart Rate Variability and the Investigation of Treatments

What this Trial Is About

This research aims to explore how hypertension and obstructive sleep apnea (OSA) are related by using heart rate variability (HRV) as a non-invasive marker of the autonomic nervous system. The study will focus on adults aged 18 to 65 years with diagnosed hypertension or resistant hypertension who are at high risk for OSA, indicated by a STOP-Bang score of 3 or higher. Researchers will analyze the connection between HRV measures and OSA severity to improve early detection and management of OSA in these patients. Participants will undergo 24-hour Holter electrocardiogram monitoring to capture HRV data, including time-domain and frequency-domain indices. Alongside this, overnight polysomnography (PSG) will be used to assess sleep parameters and determine the severity of OSA through the apnea-hypopnea index (AHI). Clinical information such as blood pressure and laboratory results will also be collected. Machine learning models will be developed and tested to predict OSA severity based on HRV features. Those diagnosed with OSA will be followed over time after receiving standard treatments like continuous positive airway pressure (CPAP) to evaluate changes in HRV and blood pressure. During the study, participants will provide informed consent and attend monitoring visits for HRV and sleep studies. Researchers will collect demographic and clinical data, perform statistical and machine learning analyses, and observe treatment effects on autonomic function and blood pressure up to 12 months. The main outcome is to predict OSA severity using HRV data, with secondary outcomes focusing on changes in HRV after treatment. This observational study offers a potential cost-effective method for OSA risk assessment in hypertensive patients.

Assessment of Heart Rate Variability for Predicting Obstructive Sleep Apnea in Patients With Hypertension