Bedside EEG predicts longitudinal behavioural changes in disorders of consciousness

•pDOC patients are assessed for 2-years longitudinally with both the CRS-R and EEG.•Theta power and alpha clustering correlated strongest with changes in CRS-R scores.•EEG combined with CRS-R improved predictive power of future CRS-R scores.•Early changes in EEG outperformed early changes in CRS-R i...

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Veröffentlicht in:NeuroImage clinical 2020-01, Vol.28, p.102372-102372, Article 102372
Hauptverfasser: Bareham, Corinne A., Roberts, Neil, Allanson, Judith, Hutchinson, Peter J.A., Pickard, John D., Menon, David K., Chennu, Srivas
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Sprache:eng
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Zusammenfassung:•pDOC patients are assessed for 2-years longitudinally with both the CRS-R and EEG.•Theta power and alpha clustering correlated strongest with changes in CRS-R scores.•EEG combined with CRS-R improved predictive power of future CRS-R scores.•Early changes in EEG outperformed early changes in CRS-R in terms of prognostic power.•Regular and repeated bedside EEG is feasible and has clinical utility for pDOC. 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.
ISSN:2213-1582
2213-1582
DOI:10.1016/j.nicl.2020.102372