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Bedside EEG predicts longitudinal behavioural changes in disorders of consciousness

Providing an accurate prognosis for prolonged disorder of consciousness (pDOC) patients remains a clinical challenge. Large cross-sectional studies have demonstrated the diagnostic and prognostic value of functional brain networks measured using high-density electroencephalography (hdEEG). Nonethele...

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Autores principales: Bareham, Corinne A., Roberts, Neil, Allanson, Judith, Hutchinson, Peter J.A., Pickard, John D., Menon, David K., Chennu, Srivas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7426558/
https://www.ncbi.nlm.nih.gov/pubmed/32795964
http://dx.doi.org/10.1016/j.nicl.2020.102372
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author Bareham, Corinne A.
Roberts, Neil
Allanson, Judith
Hutchinson, Peter J.A.
Pickard, John D.
Menon, David K.
Chennu, Srivas
author_facet Bareham, Corinne A.
Roberts, Neil
Allanson, Judith
Hutchinson, Peter J.A.
Pickard, John D.
Menon, David K.
Chennu, Srivas
author_sort Bareham, Corinne A.
collection PubMed
description Providing an accurate prognosis for prolonged disorder of consciousness (pDOC) patients remains a clinical challenge. Large cross-sectional studies have demonstrated the diagnostic and prognostic value of functional brain networks measured using high-density electroencephalography (hdEEG). Nonetheless, the prognostic value of these neural measures has yet to be assessed by longitudinal follow-up. We address this gap by assessing the utility of hdEEG to prognosticate long-term behavioural outcome, employing longitudinal data collected from a cohort of patients assessed systematically with resting hdEEG and the Coma Recovery Scale-Revised (CRS-R) at the bedside over a period of two years. We used canonical correlation analysis to relate clinical (including CRS-R scores combined with demographic variables) and hdEEG variables to each other. This analysis revealed that the patient’s age, and the hdEEG theta band power and alpha band connectivity, contributed most significantly to the relationship between hdEEG and clinical variables. Further, we found that hdEEG measures recorded at the time of assessment augmented clinical measures in predicting CRS-R scores at the next assessment. Moreover, the rate of hdEEG change not only predicted later changes in CRS-R scores, but also outperformed clinical measures in terms of prognostic power. Together, these findings suggest that improvements in functional brain networks precede changes in behavioural awareness in pDOC. We demonstrate here that bedside hdEEG assessments conducted at specialist nursing homes are feasible, have clinical utility, and can complement clinical knowledge and systematic behavioural assessments to inform prognosis and care.
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spelling pubmed-74265582020-08-16 Bedside EEG predicts longitudinal behavioural changes in disorders of consciousness Bareham, Corinne A. Roberts, Neil Allanson, Judith Hutchinson, Peter J.A. Pickard, John D. Menon, David K. Chennu, Srivas Neuroimage Clin Regular Article Providing an accurate prognosis for prolonged disorder of consciousness (pDOC) patients remains a clinical challenge. Large cross-sectional studies have demonstrated the diagnostic and prognostic value of functional brain networks measured using high-density electroencephalography (hdEEG). Nonetheless, the prognostic value of these neural measures has yet to be assessed by longitudinal follow-up. We address this gap by assessing the utility of hdEEG to prognosticate long-term behavioural outcome, employing longitudinal data collected from a cohort of patients assessed systematically with resting hdEEG and the Coma Recovery Scale-Revised (CRS-R) at the bedside over a period of two years. We used canonical correlation analysis to relate clinical (including CRS-R scores combined with demographic variables) and hdEEG variables to each other. This analysis revealed that the patient’s age, and the hdEEG theta band power and alpha band connectivity, contributed most significantly to the relationship between hdEEG and clinical variables. Further, we found that hdEEG measures recorded at the time of assessment augmented clinical measures in predicting CRS-R scores at the next assessment. Moreover, the rate of hdEEG change not only predicted later changes in CRS-R scores, but also outperformed clinical measures in terms of prognostic power. Together, these findings suggest that improvements in functional brain networks precede changes in behavioural awareness in pDOC. We demonstrate here that bedside hdEEG assessments conducted at specialist nursing homes are feasible, have clinical utility, and can complement clinical knowledge and systematic behavioural assessments to inform prognosis and care. Elsevier 2020-08-05 /pmc/articles/PMC7426558/ /pubmed/32795964 http://dx.doi.org/10.1016/j.nicl.2020.102372 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Regular Article
Bareham, Corinne A.
Roberts, Neil
Allanson, Judith
Hutchinson, Peter J.A.
Pickard, John D.
Menon, David K.
Chennu, Srivas
Bedside EEG predicts longitudinal behavioural changes in disorders of consciousness
title Bedside EEG predicts longitudinal behavioural changes in disorders of consciousness
title_full Bedside EEG predicts longitudinal behavioural changes in disorders of consciousness
title_fullStr Bedside EEG predicts longitudinal behavioural changes in disorders of consciousness
title_full_unstemmed Bedside EEG predicts longitudinal behavioural changes in disorders of consciousness
title_short Bedside EEG predicts longitudinal behavioural changes in disorders of consciousness
title_sort bedside eeg predicts longitudinal behavioural changes in disorders of consciousness
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7426558/
https://www.ncbi.nlm.nih.gov/pubmed/32795964
http://dx.doi.org/10.1016/j.nicl.2020.102372
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