Serrano Alarcón Ángel, Martínez Madrid Natividad, Seepold Ralf
School of Informatics, Reutlingen University, Alteburgstr. 150, 72762 Reutlingen, Germany.
Institute of Digital Medicine, I.M. Sechenov First Moscow State Medical University, 2-4 Bolshaya Pirogovskaya st., 119435 Moscow, Russian Federation.
Life (Basel). 2021 Nov 17;11(11):1249. doi: 10.3390/life11111249.
Despite its high accuracy, polysomnography (PSG) has several drawbacks for diagnosing obstructive sleep apnea (OSA). Consequently, multiple portable monitors (PMs) have been proposed. This systematic review aims to investigate the current literature to analyze the sets of physiological parameters captured by a PM to select the minimum number of such physiological signals while maintaining accurate results in OSA detection. Inclusion and exclusion criteria for the selection of publications were established prior to the search. The evaluation of the publications was made based on one central question and several specific questions. The abilities to detect hypopneas, sleep time, or awakenings were some of the features studied to investigate the full functionality of the PMs to select the most relevant set of physiological signals. Based on the physiological parameters collected (one to six), the PMs were classified into sets according to the level of evidence. The advantages and the disadvantages of each possible set of signals were explained by answering the research questions proposed in the methods. The minimum number of physiological signals detected by PMs for the detection of OSA depends mainly on the purpose and context of the sleep study. The set of three physiological signals showed the best results in the detection of OSA.
尽管多导睡眠图(PSG)具有很高的准确性,但在诊断阻塞性睡眠呼吸暂停(OSA)方面仍存在一些缺点。因此,人们提出了多种便携式监测仪(PM)。本系统评价旨在研究现有文献,分析PM采集的生理参数集,以选择最少数量的此类生理信号,同时在OSA检测中保持准确的结果。在检索之前确定了选择出版物的纳入和排除标准。基于一个核心问题和几个具体问题对出版物进行评估。检测呼吸暂停低通气、睡眠时间或觉醒的能力是研究的一些特征,以调查PM的全部功能,从而选择最相关的生理信号集。根据收集到的生理参数(一到六个),将PM根据证据水平分为几组。通过回答方法中提出的研究问题,解释了每组可能信号的优缺点。PM检测OSA所需的最少生理信号数量主要取决于睡眠研究的目的和背景。由三个生理信号组成的信号集在OSA检测中显示出最佳结果。