| Summary: | 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 (E<sub>DD</sub>), 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 E<sub>DD</sub>, OSA patients and healthy controls (HCs) were identified from a sleep study database. Then E<sub>DD</sub> 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 E<sub>DD</sub> and OSA severity, measured by apnea-hypopnea index (AHI), was also analyzed. Results: Compared with HCs, OSA patients had significantly increased E<sub>DD</sub> during sleep. A positive correlation between E<sub>DD</sub> and the severity of OSA was also observed. Although the value of E<sub>DD</sub> became larger with aging, it was not OSA-specified. Conclusion: Increased E<sub>DD</sub> 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.
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