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  • Title: Analysing the impact of body position shift on sleep architecture and stage transition: A comprehensive multidimensional study using event-synchronised polysomnography data.
    Author: Ahn HK, Kang YJ, Yoon W, Shin HW.
    Journal: J Sleep Res; 2024 Aug; 33(4):e14115. PubMed ID: 38083980.
    Abstract:
    Although understanding the physiological mechanisms of obstructive sleep apnea (OSA) is important for treating OSA, limited studies have examined OSA patients' sleep architecture at the epoch-by-epoch level and analysed the impact of sleep position and stage on OSA pathogenesis. The epoch-labelled polysomnogram was analysed multidimensionally to investigate the effect of sleep position on the sleep architecture and risk factors of apnea in patients with OSA. This retrospective multicentric case-control study reviewed full-night diagnostic polysomnography of 6983 participants. The difference in the proportion of time spent supine during non-rapid eye movement (NREM) and REM stages, and the mean duration of respiratory events per body position were evaluated. The frequency of sleep stage transition per body position shift type was computed. Further subgroup analysis was performed based on OSA severity and positional dependency. Supine time in patients with OSA varied across sleep stages, with lower proportions in N3 and REM, and shorter durations with severity. Patients with OSA spent less time in supine positions during N3 and REM, and experienced longer apnea events in both positions compared to the control group. The frequency of all sleep stage transitions increased with OSA severity and was higher among non-positional OSA than positional OSA and the control group, regardless of body position shift type. The sleep stage transition from N3 and REM to wakefulness was notably heightened during position shift. Understanding the sleep architecture of patients with OSA requires analysing various sleep characteristics including sleep position simultaneously, with future studies focusing on position detection to predict sleep stages and respiratory events.
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