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.
Interaction between sleep EEG and ECG signals during and after obstructive sleep apnea events with or without arousals
