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用于帕金森病及相关α-突触核蛋白病家庭筛查的快速眼动睡眠行为障碍检测新技术。

Novel technologies for REM sleep behavior disorder detection for home screening in Parkinson's disease and related alpha-synucleinopathies.

作者信息

Colman Kaat, Schyvens An-Marie, De Volder Ilse, Verbraecken Johan, Pijpers Angelique, Viaene Mineke, Oertel Wolfgang, Dijkstra Femke, Crosiers David

机构信息

Department of Neurology, Antwerp University Hospital, Antwerp, Belgium.

Translational Neurosciences, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium.

出版信息

NPJ Parkinsons Dis. 2025 Jul 3;11(1):196. doi: 10.1038/s41531-025-01032-w.

Abstract

Isolated REM sleep behavior disorder (iRBD) is a prodromal marker of Parkinson's disease (PD) and related alpha-synucleinopathies. Identification of RBD is crucial for timely intervention and disease-modifying treatments. While video-polysomnography (vPSG) remains the diagnostic gold standard, its costly and resource-intensive nature limits its utility. This systematic review evaluates emerging non-PSG tools and modalities for home-based RBD detection. A systematic search of PubMed, Web of Science, and Cochrane Library identified 17 studies, categorized into actigraphy devices (n = 9), novel tools (n = 5), and emerging modalities (n = 3). Advances in actigraphy, through machine learning integration, have significantly improved RBD detection. Novel tools, including portable biopotential systems and temporary tattoo electrodes, show promise for home-based REM sleep without atonia monitoring, while contactless cameras demonstrate high sensitivity for dream-enacting behavior detection. Future studies for validation are needed, ensuring reliability and clinical applicability for large-scale screening efforts aimed at identifying individuals at risk for PD and related alpha-synucleinopathies.

摘要

孤立性快速眼动睡眠行为障碍(iRBD)是帕金森病(PD)及相关α-突触核蛋白病的前驱标志物。识别RBD对于及时干预和疾病修饰治疗至关重要。虽然视频多导睡眠图(vPSG)仍然是诊断金标准,但其成本高且资源密集的性质限制了其应用。本系统评价评估了用于家庭RBD检测的新兴非PSG工具和方法。对PubMed、科学网和考克兰图书馆进行系统检索,确定了17项研究,分为活动记录仪设备(n = 9)、新型工具(n = 5)和新兴方法(n = 3)。通过机器学习整合,活动记录仪的进展显著改善了RBD检测。新型工具,包括便携式生物电位系统和临时纹身电极,显示出在家中监测快速眼动睡眠时无张力的前景,而无接触摄像头对梦呓行为检测具有高敏感性。需要进一步的验证研究,以确保其可靠性和临床适用性,用于大规模筛查,以识别有患PD及相关α-突触核蛋白病风险的个体。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c06/12229318/b10a7ae52f23/41531_2025_1032_Fig1_HTML.jpg

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