Dereymaeker Anneleen, Pillay Kirubin, Vervisch Jan, De Vos Maarten, Van Huffel Sabine, Jansen Katrien, Naulaers Gunnar
Department of Development and Regeneration, University Hospitals Leuven, Neonatal Intensive Care Unit, KU Leuven (University of Leuven), Leuven, Belgium.
Institute of Biomedical Engineering (IBME), Department of Engineering Science, University of Oxford, Oxford, United Kingdom..
Early Hum Dev. 2017 Oct;113:87-103. doi: 10.1016/j.earlhumdev.2017.07.003. Epub 2017 Jul 12.
Neonatal sleep is a crucial state that involves endogenous driven brain activity, important for neuronal survival and guidance of brain networks. Sequential EEG-sleep analysis in preterm infants provides insights into functional brain integrity and can document deviations of the biologically pre-programmed process of sleep ontogenesis during the neonatal period. Visual assessment of neonatal sleep-EEG, with integration of both cerebral and non-cerebral measures to better define neonatal state, is still considered the gold standard. Electrographic patterns evolve over time and are gradually time locked with behavioural characteristics which allow classification of quiet sleep and active sleep periods during the last 10weeks of gestation. Near term age, the neonate expresses a short ultradian sleep cycle, with two distinct active and quiet sleep, as well as brief periods of transitional or indeterminate sleep. Qualitative assessment of neonatal sleep is however challenged by biological and environmental variables that influence the expression of EEG-sleep patterns and sleep organization. Developing normative EEG-sleep data with the aid of automated analytic methods, can further improve our understanding of extra-uterine brain development and state organization under stressful or pathological conditions. Based on those developmental biomarkers of normal and abnormal brain function, research can be conducted to support and optimise sleep in the NICU, with the ultimate goal to improve therapeutic interventions and neurodevelopmental outcome.
新生儿睡眠是一种关键状态,涉及内源性驱动的大脑活动,这对神经元存活和脑网络的引导很重要。对早产儿进行连续脑电图睡眠分析有助于了解大脑功能完整性,并能记录新生儿期睡眠个体发生这一生物预编程过程的偏差。将大脑和非大脑测量方法相结合以更好地定义新生儿状态,对新生儿睡眠脑电图进行视觉评估仍被视为金标准。脑电图模式会随时间演变,并逐渐与行为特征同步,这使得在妊娠最后10周期间能够对安静睡眠期和活跃睡眠期进行分类。接近足月时,新生儿表现出短暂的超日睡眠周期,包括两个不同的活跃睡眠期和安静睡眠期,以及短暂的过渡性或不确定睡眠期。然而,新生儿睡眠的定性评估受到影响脑电图睡眠模式表达和睡眠组织的生物和环境变量的挑战。借助自动分析方法建立标准化脑电图睡眠数据,可进一步增进我们对宫外大脑发育以及压力或病理条件下状态组织的理解。基于这些正常和异常脑功能的发育生物标志物,可以开展研究以支持和优化新生儿重症监护病房(NICU)中的睡眠,最终目标是改善治疗干预措施和神经发育结局。