Abstract

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.

Highlights

  • IntroductionClinicians face a difficult challenge at predicting the longer-term outcome of prolonged disorder of consciousness (pDOC) patients following brain injury

  • Our analysis has indicated that the high-density electroencephalography (hdEEG) measures of theta power and the connectivity measures of clustering and median debiased weighted phase lag index (dwPLI) in the alpha band are the strongest contributors to the canonical scores of clinical-behavioural trajectories

  • These findings indicate that resting state hdEEG measures have significant prognostic value for predicting long-term behavioural outcomes in prolonged disorder of consciousness (pDOC)

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Summary

Introduction

Clinicians face a difficult challenge at predicting the longer-term outcome of pDOC patients following brain injury. This is in part due to a lack of studies that have tracked patients systematically to characterise the history of recovery. Longitudinal studies that undertake systematic follow-up of such patients are challenging as, after acute care, many patients are transferred to specialist neurological centres, nursing homes or repatriated to the family home, with incomplete records of the clinical course and outcomes. Clinical practice guidelines highlight the need for more longitudinal studies to assist with understanding long-term recovery following severe brain injury (Physicians RCo, 2020; Giacino et al, 2018; Royal College of Physicians, 2020)

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