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Lookup NU author(s): Dr Zhe Kang Law, Carein Todd, Ramtin Mehraram, Julia SchumacherORCiD, Professor Mark BakerORCiD, Dr Fiona LeBeau, Professor Alison Yarnall, Professor Alan ThomasORCiD, Professor John-Paul TaylorORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2020 by the authors.Despite improvements in diagnostic criteria for dementia with Lewy bodies (DLB), the ability to discriminate DLB from Alzheimer’s disease (AD) and other dementias remains suboptimal. Electroencephalography (EEG) is currently a supportive biomarker in the diagnosis of DLB. We performed a systematic review to better clarify the diagnostic and prognostic role of EEG in DLB and define the clinical correlates of various EEG features described in DLB. MEDLINE, EMBASE, and PsycINFO were searched using search strategies for relevant articles up to 6 August 2020. We included 43 studies comparing EEG in DLB with other diagnoses, 42 of them included a comparison of DLB with AD, 10 studies compared DLB with Parkinson’s disease dementia, and 6 studies compared DLB with other dementias. The studies were visual EEG assessment (6), quantitative EEG (35) and event-related potential studies (2). The most consistent observation was the slowing of the dominant EEG rhythm (<8 Hz) assessed visually or through quantitative EEG, which was observed in ~90% of patients with DLB and only ~10% of patients with AD. Other findings based on qualitative rating, spectral power analyses, connectivity, microstate and machine learning algorithms were largely heterogenous due to differences in study design, EEG acquisition, preprocessing and analysis. EEG protocols should be standardized to allow replication and validation of promising EEG features as potential biomarkers in DLB.
Author(s): Law ZK, Todd C, Mehraram R, Schumacher J, Baker MR, LeBeau FEN, Yarnall A, Onofrj M, Bonanni L, Thomas A, Taylor J-P
Publication type: Review
Publication status: Published
Journal: Diagnostics
Year: 2020
Volume: 10
Issue: 9
Print publication date: 01/09/2020
Online publication date: 20/08/2020
Acceptance date: 18/08/2020
ISSN (electronic): 2075-4418
Publisher: MDPI AG
URL: https://doi.org/10.3390/diagnostics10090616
DOI: 10.3390/diagnostics10090616
