Validation of a portable monitoring device for the diagnosis of obstructive sleep apnea: electrocardiogram-based cardiopulmonary coupling
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We aimed to evaluate the validity of the cardiopulmonary coupling (CPC) device, a limited-channel portable monitoring device for obstructive sleep apnea (OSA) screening in one single-center cohort, in particular in those with some cardiovascular diseases since the cardiopulmonary coupling might be different from those without.
Consecutive patients referred to the sleep medical center for assessment of possible OSA were enrolled in this study. Patients were examined with standard polysomnography (PSG) and CPC evaluation simultaneously. The results of the two examinations were compared in all subjects and in those with or without cardiovascular abnormalities.
A total of 179 subjects suspected with OSA were finally analyzed. According to OSA severity degree based on AHI, the area under ROC curve for the CPC device in the whole cohort patients was 0.79 (mild), 0.79 (moderate), and 0.86 (severe OSA), respectively (all p < 0.001). For patients with cardiovascular disease with different OSA severity, the area under the ROC curve was 0.86 (mild), 0.73 (moderate), and 0.83 (severe OSA), respectively (all p < 0.0001), and 0.74 (mild), 0.85 (moderate), and 0.91 (severe OSA), respectively in patients without cardiovascular disease (all p < 0.0001).
The overall performance of CPC technique was acceptable to assess OSA in subjects with clinical suspicion of OSA, and thus it might act as a fast tool to screen OSA patients. However, the sensitivity of CPC technology for patients with cardiovascular disease was relatively insufficient. Therefore, CPC technology should be carefully interpreted in OSA screening in those with cardiovascular disease.
KeywordsCardiopulmonary coupling analysis Validation Obstructive sleep apnea Cardiovascular disease
American Academy of Sleep Medicine
area under the ROC curve
body mass index
continuous positive airway pressure
elevated low-frequency coupling
Epworth Sleepiness Scale
positive likelihood ratio
negative likelihood ratio
negative predictive value
obstructive sleep apnea
positive predictive value
receiver operating characteristics
total sleep time
The authors gratefully acknowledge the patients who have participated in this study and thank the staff at the sleep medical center, Beijing Anzhen Hospital, China, for scoring the PSG studies according to the updated AASM scoring guidelines. In addition, we also thank Nanjing Fengsheng Yongkang Software Technology Co., Ltd. for providing the CPC devices.
Conception and design: Mi Lu, Fang Fang, and Yongxiang Wei. Collection and assembly of data: Mi Lu, Qianqian Wang, and Chenyao Ma. Data analysis and interpretation: Mi Lu and Fang Fang. PSG data scoring: Fei Xie, Lei Xiao, Hu Liu, Xiaojun Zhan, and Hongyan Liu. Manuscript writing: Mi Lu, Fang Fang, and John E. Sanderson. Revised the language/article: Mi Lu, Fang Fang, John E. Sanderson, and Xiaojun Zhan. Final approval of manuscript: all authors.
This study was supported by NSFC (Project 81870335), Beijing Medical Project 2016-4, the Beijing Key Laboratory of Upper Airway Dysfunction and Related Cardiovascular Diseases (BZ0377), Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support (ZYLX201605), Beijing Municipal Science and Technology Commission (Z141100006014057), and the project of Beijing Institute of Heart Lung and Blood Vessel Diseases (2018S14).
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflicts of interest.
This study was approved by the local institutional review board of Beijing Anzhen Hospital (Capital Medical University, Beijing, China). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent was obtained from all individual participants included in the study.
- 6.Tregear S, Reston J, Schoelles K, Phillips B (2009) Obstructive sleep apnea and risk of motor vehicle crash: systematic review and meta-analysis. J Clin Sleep Med 5(6):573–581Google Scholar
- 16.Huikuri HV, Stein PK. Heart rate variability in risk stratification of cardiac patients (2013) Prog Cardiovasc Dis 56(2): 153–159Google Scholar
- 18.Berry RB, Budhiraja R, Gottlieb DJ, Gozal D, Iber C, Kapur VK, Marcus CL, Mehra R (2012) Rules for scoring respiratory events in sleep: update of the 2007 AASM Manual for the Scoring of Sleep and Associated Events. Deliberations of the Sleep Apnea Definitions Task Force of the American Academy of Sleep Medicine. J Clin Sleep Med 8(5):597–619Google Scholar
- 20.Thomas RJ (2016) Cardiopulmonary coupling sleep spectrograms. In: Kryger MH, Roth T, Dement WC (eds) Principles and practice of sleep medicine, 6rd edn. Elsevier, Inc., Philadelphia, pp 1615–1623Google Scholar