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Quantitative measures of the resting EEG in stroke: a systematic review on clinical correlation and prognostic value

Object Quantitative electroencephalography (qEEG) has shown promising results as a predictor of clinical impairment in stroke. We systematically reviewed published papers that focus on qEEG metrics in the resting EEG of patients with mono-hemispheric stroke, to summarize current knowledge and pave t...

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Bibliographic Details
Published in:Neurological sciences 2023-12, Vol.44 (12), p.4247-4261
Main Authors: Lanzone, J., Motolese, F., Ricci, L., Tecchio, F., Tombini, M., Zappasodi, F., Cruciani, A., Capone, F., Di Lazzaro, V., Assenza, G.
Format: Article
Language:English
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Summary:Object Quantitative electroencephalography (qEEG) has shown promising results as a predictor of clinical impairment in stroke. We systematically reviewed published papers that focus on qEEG metrics in the resting EEG of patients with mono-hemispheric stroke, to summarize current knowledge and pave the way for future research. Methods Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we systematically searched the literature for papers that fitted our inclusion criteria. Rayyan QCRR was used to allow deduplication and collaborative blinded paper review. Due to multiple outcomes and non-homogeneous literature, a scoping review approach was used to address the topic. Results Or initial search (PubMed, Embase, Google scholar) yielded 3200 papers. After proper screening, we selected 71 papers that fitted our inclusion criteria and we developed a scoping review thar describes the current state of the art of qEEG in stroke. Notably, among selected papers 53 (74.3%) focused on spectral power; 11 (15.7%) focused on symmetry indexes, 17 (24.3%) on connectivity metrics, while 5 (7.1%) were about other metrics (e.g. detrended fluctuation analysis). Moreover, 42 (58.6%) studies were performed with standard 19 electrodes EEG caps and only a minority used high-definition EEG. Conclusions We systematically assessed major findings on qEEG and stroke, evidencing strengths and potential pitfalls of this promising branch of research.
ISSN:1590-1874
1590-3478
DOI:10.1007/s10072-023-06981-9