Department of Clinical Neurophysiology, HUS Medical Imaging Center, Helsinki University Central Hospital and University of Helsinki, Helsinki, FIN-00029, Finland.
Clin Neurophysiol. 2013 Sep;124(9):1807-14. doi: 10.1016/j.clinph.2013.03.010. Epub 2013 Apr 30.
To document the occurrence of genuine sleep stages in the early preterm babies, and to develop an EEG-based index for following sleep wake cyclicity.
Twelve preterm babies were recruited from a study that assessed ventilator strategies. We used altogether 18 polysomnography recordings that were collected at mean conceptional age of 29.3 (25.9-32.7) weeks. Spontaneous activity transients (SAT) were detected automatically and their cumulative coverage in each 20s interval was computed from the EEG derivations C3-A2 and O2-A1. Mean SAT% values between sleep stages were compared.
All babies exhibited all sleep stages, however the sleep was remarkably fragmentary in infants due to their respiratory issues. The EEG index, SAT% showed temporal behavior that strikingly well compared with the sleep stage fluctuations in the hypnogram. In the statistical analysis we found significant differences in all recordings between the deep (quiet) sleep and the REM sleep.
Genuine sleep states exist in the early preterm babies, and changes in sleep stages are reflected in the EEG activity in a way that can be readily measured by assessing fluctuation of the automatically detected, EEG based index, the SAT%.
The findings open a possibility to construct automated analysis or monitoring of sleep wake cyclicity into brain monitors in neonatal intensive care unit.
记录早期早产儿中真正的睡眠阶段,并开发一种基于脑电图的指数来跟踪睡眠-觉醒循环。
从一项评估呼吸机策略的研究中招募了 12 名早产儿。我们总共使用了 18 个多导睡眠描记术记录,这些记录是在平均妊娠年龄为 29.3(25.9-32.7)周时收集的。自动检测自发活动瞬变(SAT),并从 EEG 推导 C3-A2 和 O2-A1 中计算每个 20s 间隔的累积覆盖率。比较睡眠阶段之间的平均 SAT% 值。
所有婴儿都表现出所有的睡眠阶段,但由于呼吸问题,婴儿的睡眠非常零碎。脑电图指数 SAT% 的时间行为与睡眠图中睡眠阶段的波动非常吻合。在统计分析中,我们在所有记录中都发现深度(安静)睡眠和 REM 睡眠之间存在显著差异。
真正的睡眠状态存在于早期早产儿中,睡眠阶段的变化以一种可以通过评估自动检测的 EEG 活动波动来测量的方式反映在 EEG 活动中,这种波动可以通过评估自动检测的、基于 EEG 的指数 SAT% 来测量。
这些发现为在新生儿重症监护病房中构建自动化分析或监测睡眠-觉醒循环提供了可能性。