Abstract
Background: Obstructive sleep apnea (OSA), a highly prevalent sleep disorder, is closely related to cardiovascular disease (CVD). Our previous work demonstrated that Shannon entropy of the degree distribution (EDD), obtained from the network domain of heart rate variability (HRV), might be a potential indicator for CVD. Method: To investigate the potential association between OSA and EDD, OSA patients and healthy controls (HCs) were identified from a sleep study database. Then EDD was calculated from electrocardiogram (ECG) signals during sleep, followed by cross-sectional comparisons between OSA patients and HCs, and longitudinal comparisons from baseline to follow-up visits. Furthermore, for OSA patients, the association between EDD and OSA severity, measured by apnea-hypopnea index (AHI), was also analyzed. Results: Compared with HCs, OSA patients had significantly increased EDD during sleep. A positive correlation between EDD and the severity of OSA was also observed. Although the value of EDD became larger with aging, it was not OSA-specified. Conclusion: Increased EDD derived from ECG signals during sleep might be a potential dynamic biomarker to identify OSA patients from HCs, which may be used in screening OSA with high risk before polysomnography is considered.
Highlights
Obstructive sleep apnea (OSA), characterized by cyclic collapse of the upper airway and partial or complete cessation of airflow during sleep, is highly prevalent with prevalence of 34% in men and 17% in women in the general population [1]
Increased entropy of the degree distribution (EDD) derived from ECG signals during sleep might be a potential dynamic biomarker to identify OSA patients from healthy controls (HCs), which may be used in screening OSA with high risk before polysomnography is considered
There is no significant alteration in apnea-hypopnea index (AHI) for OSA patients, a significant increase of AHI was observed in HCs
Summary
Obstructive sleep apnea (OSA), characterized by cyclic collapse of the upper airway and partial or complete cessation of airflow during sleep, is highly prevalent with prevalence of 34% in men and 17% in women in the general population [1]. The gold standard for OSA diagnosis is polysomnography (PSG), which is usually conducted in fully equipped and controlled sleep laboratories. In such PSG-based studies, multiple sensors are placed to record simultaneously nasal airflow, respiratory movement, oxygen saturation (SpO2), electroencephalogram (EEG), electro-oculogram (EOG), electromyogram (EMG), electrocardiogram (ECG) and body position [3]. Obstructive sleep apnea (OSA), a highly prevalent sleep disorder, is closely related to cardiovascular disease (CVD). Method: To investigate the potential association between OSA and EDD , OSA patients and healthy controls (HCs) were identified from a sleep study database. For OSA patients, the association between EDD and OSA severity, measured by apnea-hypopnea index (AHI), was analyzed. The value of EDD became larger with aging, it was not OSA-specified
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