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Total durations of respiratory events are modulated within REM and NREM sleep by sleeping position and obesity in OSA patients

非快速眼动睡眠 医学 呼吸暂停 艾普沃思嗜睡量表 多导睡眠图 仰卧位 呼吸不足 阻塞性睡眠呼吸暂停 麻醉 睡眠呼吸暂停 睡眠(系统调用) 肥胖 睡眠阶段 内科学 眼球运动 眼科 操作系统 计算机科学
作者
Marika Rissanen,Arie Oksenberg,Juha Töyräs,Sami Myllymaa,Timo Leppänen
出处
期刊:Sleep Medicine [Elsevier]
卷期号:81: 394-400 被引量:5
标识
DOI:10.1016/j.sleep.2021.02.020
摘要

Supine sleeping position and obesity are well-known risk factors for obstructive sleep apnea (OSA) and modulate the risk for OSA-related daytime symptoms. Although respiratory event durations are associated with OSA-related severe health consequences, it is unclear how sleeping position, obesity, and daytime sleepiness are associated with respiratory event durations during REM and NREM sleep. We hypothesize that irrespective of the apnea-hypopnea index (AHI), respiratory event durations differ significantly between various OSA subgroups during REM and NREM sleep. One night in-lab polysomnographic recordings were retrospectively analyzed from 1910 untreated suspected OSA patients. 599 patients (AHI ≥ 5) were included in study and divided into subgroups based on positional dependency, BMI, and daytime sleepiness (Epworth Sleepiness Scale and Multiple Sleep Latency Test). Differences in total hypopnea time (THT), total apnea time (TAT), and total apnea-hypopnea time (TAHT) within REM and NREM sleep between the subgroups were evaluated. During REM sleep, positional OSA patients had lower THT (OR = 0.952, p < 0.001) and TAHT (OR = 0.943, p < 0.001) than their non-positional counterparts. Compared to normal-weight patients (BMI < 25 kg/m2), obese patients (BMI ≥ 30 kg/m2) had lower THT, TAT, and TAHT (ORs = 0.942–0.971, p ≤ 0.009) during NREM sleep but higher THT (OR = 1.057, p = 0.001) and TAHT (OR = 1.052, p = 0.001) during REM sleep. No significant differences were observed in THT, TAT, and TAHT between patients with and without daytime sleepiness. Regardless of the AHI, respiratory event durations vary significantly between OSA sub-groups during REM and NREM sleep. Therefore, to personalize OSA severity estimation the diagnosis should be tailored based on patient's demographics, clinical phenotype, and PSG characteristics.

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