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01-03-2020 | Sleep Apnea | Sleep Breathing Physiology and Disorders • Original Article

Electrocardiogram-based sleep analysis for sleep apnea screening and diagnosis

Authors: Yan Ma, Shuchen Sun, Ming Zhang, Dan Guo, Arron Runzhou Liu, Yulin Wei, Chung-Kang Peng

Published in: Sleep and Breathing | Issue 1/2020

Abstract

Purpose

Despite the increasing number of research studies of cardiopulmonary coupling (CPC) analysis, an electrocardiogram-based technique, the use of CPC in underserved population remains underexplored. This study aimed to first evaluate the reliability of CPC analysis for the detection of obstructive sleep apnea (OSA) by comparing with polysomnography (PSG)-derived sleep outcomes.

Methods

Two hundred five PSG data (149 males, age 46.8 ± 12.8 years) were used for the evaluation of CPC regarding the detection of OSA. Automated CPC analyses were based on ECG signals only. Respiratory event index (REI) derived from CPC and apnea–hypopnea index (AHI) derived from PSG were compared for agreement tests.

Results

CPC-REI positively correlated with PSG-AHI (r = 0.851, p < 0.001). After adjusting for age and gender, CPC-REI and PSG-AHI were still significantly correlated (r = 0.840, p < 0.001). The overall results of sensitivity and specificity of CPC-REI were good.

Conclusion

Compared with the gold standard PSG, CPC approach yielded acceptable results among OSA patients. ECG recording can be used for the screening or diagnosis of OSA in the general population.

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Title: Electrocardiogram-based sleep analysis for sleep apnea screening and diagnosis
Authors: Yan Ma
Shuchen Sun
Ming Zhang
Dan Guo
Arron Runzhou Liu
Yulin Wei
Chung-Kang Peng
Publication date: 01-03-2020
Publisher: Springer International Publishing
Keywords: Sleep Apnea
Polysomnography
Published in: Sleep and Breathing / Issue 1/2020
Print ISSN: 1520-9512
Electronic ISSN: 1522-1709
DOI: https://doi.org/10.1007/s11325-019-01874-8

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