Kuhn Jasmin, Schiphorst Laura R B, Wulterkens Bernice M, Asin Jerryll, Duis Nanny, Overeem Sebastiaan, van Gilst Merel M, Fonseca Pedro
Department of Electrical Engineering, Eindhoven University of Technology, 5612AP Eindhoven, The Netherlands.
Philips Sleep and Respiratory Care, 5656AE Eindhoven, The Netherlands.
Clocks Sleep. 2024 Dec 5;6(4):777-788. doi: 10.3390/clockssleep6040050.
Total sleep time (TST) misperception has been reported in obstructive sleep apnea (OSA). However, previous findings on predictors were inconsistent and predominantly relied on single-night polysomnography, which may alter patients' sleep perception. We leveraged advances in wearable sleep staging to investigate predictors of TST misperception in OSA over multiple nights in the home environment. The study included 141 patients with OSA, 75 without insomnia symptoms (OSA group), and 66 with insomnia symptoms (OSA-I group). Objective TST was measured using a previously validated wrist-worn photoplethysmography and accelerometry device. Self-reported TST was assessed using a digital sleep diary. TST misperception was quantified with the misperception index (MI), calculated as (objective - self-reported TST)/objective TST. MI values differed significantly between the OSA (median = -0.02, IQR = [-0.06, 0.02]) and the OSA-I group (0.05, [-0.02, 0.13], < 0.001). Multilevel modeling revealed that the presence of insomnia symptoms (β = 0.070, < 0.001) and lower daily reported sleep quality (β = -0.229, < 0.001) were predictive of higher MI (TST underestimation), while a higher apnea-hypopnea index (AHI) was predictive of lower MI (TST overestimation; β = -0.001, = 0.006). Thus, insomnia symptoms and AHI are associated with TST misperception in OSA patients, but in opposite directions. This association extends over multiple nights in the home environment.
阻塞性睡眠呼吸暂停（OSA）患者中存在总睡眠时间（TST）感知错误的情况。然而，之前关于预测因素的研究结果并不一致，且主要依赖单夜多导睡眠监测，这可能会改变患者的睡眠感知。我们利用可穿戴睡眠分期技术的进展，在家中环境下对多个夜晚的OSA患者TST感知错误的预测因素进行研究。该研究纳入了141例OSA患者，其中75例无失眠症状（OSA组），66例有失眠症状（OSA-I组）。使用先前验证过的腕部光电容积脉搏波描记术和加速度计设备测量客观TST。通过数字睡眠日记评估自我报告的TST。TST感知错误用感知错误指数（MI）进行量化，计算方法为（客观TST - 自我报告的TST）/客观TST。OSA组（中位数 = -0.02，四分位数间距 = [-0.06, 0.02]）和OSA-I组（0.05，[-0.02, 0.13]，P < 0.001）的MI值有显著差异。多水平模型显示，存在失眠症状（β = 0.070，P < 0.001）和每日报告的睡眠质量较低（β = -0.229，P < 0.001）可预测较高的MI（TST低估），而较高的呼吸暂停低通气指数（AHI）可预测较低的MI（TST高估；β = -0.001，P = 0.006）。因此，失眠症状和AHI与OSA患者的TST感知错误有关，但方向相反。这种关联在家庭环境中的多个夜晚都存在。
