Le Grande Michael R, Jackson Alun C, Beauchamp Alison, Kerr Debra, Driscoll Andrea
Australian Centre for Heart Health, 75 Chetwynd Street, North Melbourne, VIC, 3051, Australia; Faculty of Health, Deakin University, Burwood, VIC, 3216, Australia; Melbourne Centre for Behaviour Change, School of Psychological Sciences, The University of Melbourne, Parkville, VIC, 3052, Australia.
Australian Centre for Heart Health, 75 Chetwynd Street, North Melbourne, VIC, 3051, Australia; Faculty of Health, Deakin University, Burwood, VIC, 3216, Australia; Centre on Behavioural Health, Hong Kong University, Pakfulam, Hong Kong.
Sleep Med. 2021 Oct;86:135-160. doi: 10.1016/j.sleep.2021.02.021. Epub 2021 Feb 18.
A number of clinical guidelines recommend that all cardiac rehabilitation patients should be screened for potential sleep disorders with a validated screening instrument. There is currently no consensus on what specific tools should be used.
To identify tools that are practical to use in the clinical environment and have high diagnostic accuracy.
We systematically searched online databases to identify patient reported outcome instruments that have been used in published research studies to assess the likelihood of obstructive sleep apnoea (OSA) in cardiac patients. In studies that provided diagnostic data, these data were extracted and verified via an evidence-based diagnostic calculator. Where sufficient numbers of studies were available, a meta-analysis was conducted to determine pooled estimates of specificity, sensitivity and diagnostic odds ratios. Selected papers were qualitatively assessed using the Standards for Reporting Diagnostic accuracy studies (STARD).
Of the 21 instruments identified, six detected likelihood of OSA, two assessed daytime sleepiness, five assessed insomnia and eight examined sleep quality. A meta-analysis of 14 studies that assessed diagnostic accuracy of moderate OSA, revealed moderate sensitivity for the Berlin Questionnaire, Sens = 0.49 (95% CI 0.45-0.52) and good sensitivity for the Stop-BANG, Sens = 0.93 (95% CI 0.87-0.96) but poor specificity at standard cut-off criteria.
There are promising practical tools available to screen patients with OSA and other sleep disorders in cardiac rehabilitation settings, but specificity could be improved. Additional assessment of sleep quality may enhance prognostic ability with both OSA and insomnia screening.
多项临床指南建议,所有心脏康复患者都应使用经过验证的筛查工具对潜在睡眠障碍进行筛查。目前对于应使用何种具体工具尚无共识。
确定在临床环境中实用且具有高诊断准确性的工具。
我们系统地检索了在线数据库,以确定在已发表的研究中用于评估心脏病患者阻塞性睡眠呼吸暂停(OSA)可能性的患者报告结局工具。在提供诊断数据的研究中,这些数据通过基于证据的诊断计算器进行提取和验证。在有足够数量研究的情况下,进行荟萃分析以确定特异性、敏感性和诊断比值比的合并估计值。使用诊断准确性研究报告标准(STARD)对选定的论文进行定性评估。
在确定的21种工具中,6种检测OSA的可能性,2种评估日间嗜睡,5种评估失眠,8种检查睡眠质量。对14项评估中度OSA诊断准确性的研究进行的荟萃分析显示,柏林问卷的敏感性中等,敏感性 = 0.49(95%CI 0.45 - 0.52),而Stop - BANG的敏感性良好,敏感性 = 0.93(95%CI 0.87 - 0.96),但在标准截断标准下特异性较差。
在心脏康复环境中,有一些有前景的实用工具可用于筛查OSA和其他睡眠障碍患者,但特异性有待提高。对睡眠质量的额外评估可能会提高OSA和失眠筛查的预后能力。