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脑电图频谱分析能否区分发作性睡病儿童与特发性嗜睡症儿童及主观嗜睡者?

Can EEG spectral analysis distinguish children with narcolepsy from those with idiopathic hypersomnia and subjective sleepiness?

作者信息

Plunkett Georgina, Shetty Marisha, Davey Margot J, Nixon Gillian M, Walter Lisa M, Horne Rosemary S C

机构信息

Department of Paediatrics, Monash University, Melbourne, Victoria, Australia.

Melbourne Children's Sleep Centre, Monash Children's Hospital, Melbourne, Victoria, Australia.

出版信息

J Sleep Res. 2025 Aug;34(4):e14428. doi: 10.1111/jsr.14428. Epub 2024 Nov 28.

DOI:10.1111/jsr.14428
PMID:39609258
Abstract

EEG spectral analysis provides a more sensitive measure of sleep disruption than conventional sleep macro-architecture. We aimed to examine the use of this technique applied to overnight polysomnography in distinguishing children with narcolepsy and idiopathic hypersomnia (IH) from subjectively sleepy children with a non-diagnostic multiple sleep latency test. The relative power was calculated for delta (0.5-3.9 Hz), theta (4-7.9 Hz), alpha (8-11.9 Hz), sigma (12-13.9 Hz), and beta power (14-30 Hz). A mean value for each frequency was calculated for each 30 s epoch then averaged for each sleep stage within each child. Data are presented as median and interquartile range. Twenty-eight children with narcolepsy, 11 with IH, and 26 with subjective sleepiness were included and individually matched for age and sex with a control child. In N2, the F4 beta power was lower in the narcolepsy compared with the IH group (p < 0.05). The F4 theta power was higher in the narcolepsy compared with the subjectively sleepy group during wake (p < 0.001), N2 (p < 0.01), N3 (p < 0.05), and total sleep (p < 0.01). During total sleep the F4 delta power was lower in both the narcolepsy and IH groups compared with the subjectively sleepy group (p < 0.05 for both). Our study identified specific EEG frequencies which differed between groups of children referred for assessment of EDS. In particular, differences in theta and delta power in children with narcolepsy and IH compared with others with subjective sleepiness may provide insights into the pathophysiology associated these conditions.

摘要

脑电图频谱分析比传统的睡眠宏观结构测量更能敏感地检测睡眠中断情况。我们旨在研究将该技术应用于夜间多导睡眠图,以区分发作性睡病和特发性嗜睡症(IH)患儿与多次睡眠潜伏期测试结果无诊断意义但主观困倦的患儿。计算了δ波(0.5 - 3.9赫兹)、θ波(4 - 7.9赫兹)、α波(8 - 11.9赫兹)、σ波(12 - 13.9赫兹)和β波功率(14 - 30赫兹)的相对功率。对每个30秒时段的每个频率计算平均值,然后对每个儿童的每个睡眠阶段进行平均。数据以中位数和四分位间距表示。纳入了28例发作性睡病患儿、11例IH患儿和26例主观困倦患儿,并按年龄和性别与对照儿童进行个体匹配。在N2期,发作性睡病组的F4β波功率低于IH组(p < 0.05)。在清醒期(p < 0.001)、N2期(p < 0.01)、N3期(p < 0.05)和总睡眠期(p < 0.01),发作性睡病组的F4θ波功率高于主观困倦组。在总睡眠期,发作性睡病病和IH组的F4δ波功率均低于主观困倦组(两者p均 < 0.05)。我们的研究确定了在因评估日间过度嗜睡而转诊的儿童组之间存在差异的特定脑电图频率。特别是,发作性睡病和IH患儿与其他主观困倦患儿相比,θ波和δ波功率的差异可能有助于深入了解与这些病症相关的病理生理学。

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