Zhu Binbin, Zou Kun, He Jianhua, Huang Xueqin, Zhu Weichao, Ahmad Harb Ahmad Khaled, Wang Jianhua, Luo Aiping
Department of Anesthesia, The Affiliated Hospital of Medical School of Ningbo University, Ningbo, China.
Department of Electrophysiology, The Affiliated Hospital of Medical School of Ningbo University, Ningbo, China.
Front Pediatr. 2021 Sep 30;9:701251. doi: 10.3389/fped.2021.701251. eCollection 2021.
The purpose of this article is to provide a succinct summary of the sleep monitoring efforts that have been used in nocturnal enuresis (NE) and an overview of the knowledge that has accrued. This is not intended to be a comprehensive review, but rather is intended to highlight how polysomnography (PSG), a common sleep detection tool, has contributed to our understanding of NE, as arousal disorder is considered to be one of the important mechanisms. The authors have organized this report by analysis and display of different ingredients of PSG, starting with comparing the electroencephalogram (EEG) of controls and the enuretic children and then moving to evaluation of respiratory patterns of NE and comorbid disease obstructive sleep apnea (OSA). In addition, the authors' goal is to better understand the mechanism of NE by integrating various levels of sleep monitoring; those sleep-related clinical scale scores for NE are presented to date. Finally, we propose further research of NE to explore the microstructure alterations PSG combined with EEG-fMRI or to use novel technology like portable device internet and deep learning strategy.
本文旨在简要总结用于夜间遗尿症（NE）的睡眠监测研究，并概述已积累的相关知识。本文并非全面综述，而是旨在突出多导睡眠图（PSG）这一常见睡眠检测工具如何增进了我们对NE的理解，因为觉醒障碍被认为是重要机制之一。作者通过分析和展示PSG的不同组成部分来组织本报告，首先比较对照组和遗尿儿童的脑电图（EEG），然后评估NE的呼吸模式和合并症阻塞性睡眠呼吸暂停（OSA）。此外，作者的目标是通过整合不同层面的睡眠监测来更好地理解NE的机制；文中呈现了迄今为止NE的那些与睡眠相关的临床量表评分。最后，我们提议对NE开展进一步研究，以探索PSG结合脑电图功能磁共振成像（EEG-fMRI）的微观结构改变，或使用便携式设备互联网和深度学习策略等新技术。
