Department of Neurology, Medical University of Vienna, Vienna, Austria.
J Clin Sleep Med. 2021 May 1;17(5):917-924. doi: 10.5664/jcsm.9086.
Self-reported perception of sleep often differs from objective sleep study measures, but factors predicting the discrepancy between self-reported and objective sleep parameters are controversial, and a comparison of laboratory vs ambulatory polysomnography (PSG) is lacking.
We retrospectively analyzed PSGs conducted between 2012 and 2016. Linear regression was applied to predict the discrepancy between self-reported and objective sleep parameters (total sleep time, sleep efficiency, sleep latency, using age, sex, arousal index, type of sleep disorder, and PSG type [laboratory vs ambulatory] as regressors).
A total of 303 PSGs were analyzed (49% women, median age 48 years), comprising patients with insomnia (32%), sleep-related breathing disorders (27%), sleep-related movement disorders (15%), hypersomnia/narcolepsy (14%), and parasomnias (12%). Sleep disorder was the best predictor of discrepancy between self-reported and objective total sleep time, and patients with insomnia showed higher discrepancy values compared to all other patient groups (P < .001), independent of age and PSG type (P > .05). Contributory effects for higher discrepancy values were found for lower arousal index. Patients with insomnia underestimated both total sleep time (median discrepancy: 46 minutes, P < .001) and sleep efficiency (median discrepancy: 11%, P < .001). No significant predictor for discrepancy of sleep latency was found.
Misperception of sleep duration and efficiency is common in sleep lab patients, but most prominent in insomnia, independent of age, sex, or laboratory vs ambulatory recording setting. This underlines the role of PSG in patients with a clinical diagnosis of insomnia and its use in cognitive behavioral therapy.
自我报告的睡眠感知通常与客观睡眠研究测量结果不同,但预测自我报告和客观睡眠参数之间差异的因素存在争议,且实验室与动态多导睡眠图(PSG)之间的比较尚缺乏。
我们回顾性分析了 2012 年至 2016 年进行的 PSG。线性回归用于预测自我报告和客观睡眠参数之间的差异(总睡眠时间、睡眠效率、睡眠潜伏期,使用年龄、性别、觉醒指数、睡眠障碍类型和 PSG 类型(实验室与动态)作为回归量)。
共分析了 303 例 PSG(女性占 49%,中位年龄 48 岁),包括失眠症(32%)、睡眠相关呼吸障碍(27%)、睡眠相关运动障碍(15%)、发作性睡病/嗜睡症(14%)和睡眠-觉醒障碍(12%)。睡眠障碍是自我报告和客观总睡眠时间差异的最佳预测因素,与所有其他患者群体相比,失眠症患者的差异值更高(P<.001),且独立于年龄和 PSG 类型(P>.05)。较低的觉醒指数发现与更高的差异值有关。失眠症患者均低估了总睡眠时间(中位数差异:46 分钟,P<.001)和睡眠效率(中位数差异:11%,P<.001)。未发现睡眠潜伏期差异的显著预测因素。
睡眠实验室患者对睡眠持续时间和效率的感知存在偏差,但在失眠症中最为明显,与年龄、性别或实验室与动态记录设置无关。这强调了 PSG 在临床诊断为失眠症患者中的作用及其在认知行为疗法中的应用。