![]() ![]() In recent years, studies have attempted using ECG-derived respiratory waveforms and heart rate variability (HRV) to diagnose OSA ( 7, 8). Its technology is mature and has been widely promoted and applied in various clinic and hospital settings. ![]() Patients usually visit a cardiologist, ignoring the symptoms of OSA, which can lead to a missed diagnosis or misdiagnosis.Ī Holter monitor is a wearable electrocardiogram (ECG) that is commonly used to assess patients with suspected cardiovascular diseases. In addition to snoring, suffocating at night, abrupt awakening, and daytime sleepiness, OSA also often manifests as cardiovascular symptoms ( 6) such as chest tightness, nocturnal arrhythmia, nocturnal angina pectoris, and refractory hypertension. The prevalence of OSA is higher in patients with cardiovascular diseases such as hypertension, coronary heart disease, and arrhythmia, and can affect the occurrence and development of cardiovascular diseases ( 3- 5). Obstructive sleep apnea (OSA) is a common disease with high morbidity ( 1) though frequently underdiagnosed ( 2). Keywords: Holter respiratory waveform heart rate variability (HRV) obstructive sleep apnea (OSA) Therefore, the risk of OSA may be assessed using the Holter examination to improve the diagnosis and treatment rate of OSA. Males with standard deviation of all NN intervals during 24 hours ≤177 ms or females with standard deviation of all NN intervals during 24 hours ≤80.9 ms were considered to be at high risk for OSA.Ĭonclusions: Commercial and common parameters from Holter monitoring could predict the risk of OSA with high sensitivity. Logistic regression showed that standard deviation of all NN intervals during 24 hours and gender could predict the risk of OSA (P<0.001), with a sensitivity for diagnosing moderate to severe OSA of 87.5% and could accurately distinguish the risk of OSA in 77.8% of patients. The time domain indices including standard deviation of all NN intervals during 24 hours, mean of standard deviation of the averages of NN intervals in all 5-minute segments, square root of the mean squared differences of successive NN intervals, percentage of beat-to-beat NN interval differences that were more than 50 milliseconds, and the frequency domain index of high frequency decreased in participants with OSA and correlated with the PSG derived indices including apnea-hypopnea index (AHI), oxygen reduction index (ODI) and nadir SaO 2. ![]() Results: The sensitivity of the Holter-derived respiratory waveform for OSA was 90.0%, and the specificity was 82.6%. Respiration and heart rate variability (HRV) indices were calculated from the Holter and compared with PSG indices. Methods: Patients (n=63) suspected of OSA underwent Holter monitoring with concurrent PSG at a sleep center. In this study, by comparing Holter monitoring to polysomnography (PSG), we try to find out an operable way for clinicians to use Holter to predict OSA risk. Holter monitors were reported to predict sleep apnea, though were rarely used in everyday clinical practice. Miaochan Lao 1, Qiong Ou 1, Cui’e Li 2, Qian Wang 1, Ping Yuan 3, Yilu Cheng 4ġDepartment of Sleep Center, Department of Pulmonary and Critical Care Medicine, Guangdong Provincial People’s Hospital/Guangdong Academy of Medical Sciences/Guangdong Provincial Geriatrics Institute, Guangzhou, China 2Electrocardiographic Room, Guangdong Provincial People’s Hospital/Guangdong Academy of Medical Sciences/Guangdong Cardiovascular Institute, Guangzhou, China 3Department of Sleep Center, Department of Pulmonary and Critical Care Medicine, Guangdong Provincial People’s Hospital/Guangdong Academy of Medical Sciences/Guangdong Provincial Geriatrics Institute/The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China 4Department of Sleep Center, Department of Pulmonary and Critical Care Medicine, Guangdong Provincial People’s Hospital/Guangdong Academy of Medical Sciences/Guangdong Provincial Geriatrics Institute/Medical College, South China University of Technology, Guangzhou, ChinaĬontributions: (I) Conception and design: Q Ou (II) Administrative support: Q Ou (III) Provision of study materials or patients: All authors (IV) Collection and assembly of data: M Lao, C Li, Q Wang, P Yuan (V) Data analysis and interpretation: M Lao, Q Ou (VI) Manuscript writing: All authors (VII) Final approval of manuscript: All authors.īackground: Patients with obstructive sleep apnea (OSA) often present with cardiovascular symptoms.
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