Morristown Memorial Hospital, NJ, USA.
J Sleep Res. 2012 Feb;21(1):94-100. doi: 10.1111/j.1365-2869.2011.00927.x. Epub 2011 Jun 14.
Sleep-disordered breathing and Cheyne-Stokes breathing are often not diagnosed, especially in cardiovascular patients. An automated system based on photoplethysmographic signals might provide a convenient screening and diagnostic solution for patient evaluation at home or in an ambulatory setting. We compared event detection and classification obtained by full polysomnography (the 'gold standard') and by an automated new algorithm system in 74 subjects. Each subject underwent overnight polysomnography, 60 in a hospital cardiology department and 14 while being tested for suspected sleep-disordered breathing in a sleep laboratory. The sleep-disordered breathing and Cheyne-Stokes breathing parameters measured by a new automated algorithm system correlated very well with the corresponding results obtained by full polysomnography. The sensitivity of the Cheyne-Stokes breathing detected from the system compared to full polysomnography was 92% [95% confidence interval (CI): 78.6-98.3%] and specificity 94% (95% CI: 81.3-99.3%). Comparison of the Apnea Hyponea Index with a cutoff level of 15 shows a sensitivity of 98% (95% CI: 87.1-99.6%) and specificity of 96% (95% CI: 79.8-99.3%). The detection of respiratory events showed agreement of approximately 80%. Regression and Bland-Altman plots revealed good agreement between the two methods. Relative to gold-standard polysomnography, the simply used automated system in this study yielded an acceptable analysis of sleep- and/or cardiac-related breathing disorders. Accordingly, and given the convenience and simplicity of its application, this system can be considered as a suitable platform for home and ambulatory screening and diagnosis of sleep-disordered breathing in patients with cardiovascular disease.
睡眠呼吸障碍和 Cheyne-Stokes 呼吸通常未被诊断出来,尤其是在心血管病患者中。基于光电容积脉搏波信号的自动化系统可能为患者在家或在门诊环境中的评估提供一种便捷的筛查和诊断解决方案。我们比较了 74 名受试者的全睡眠多导图(“金标准”)和自动新算法系统的事件检测和分类结果。每个受试者都接受了一整夜的睡眠多导图检查,其中 60 名在医院心内科进行,14 名在睡眠实验室中接受疑似睡眠呼吸障碍的测试。新自动化算法系统测量的睡眠呼吸障碍和 Cheyne-Stokes 呼吸参数与全睡眠多导图的相应结果非常相关。系统检测到的 Cheyne-Stokes 呼吸的灵敏度与全睡眠多导图相比为 92%(95%置信区间:78.6-98.3%),特异性为 94%(95%置信区间:81.3-99.3%)。将呼吸暂停低通气指数与 15 的截止值进行比较,灵敏度为 98%(95%置信区间:87.1-99.6%),特异性为 96%(95%置信区间:79.8-99.3%)。呼吸事件的检测结果显示出约 80%的一致性。回归和 Bland-Altman 图显示两种方法之间具有良好的一致性。与金标准睡眠多导图相比,本研究中简单使用的自动化系统对睡眠和/或心脏相关呼吸障碍的分析具有可接受的效果。因此,鉴于其应用的便利性和简单性,该系统可以被视为心血管疾病患者在家和门诊进行睡眠呼吸障碍筛查和诊断的合适平台。