The role of etiology in the identification of clinical markers of consciousness: comparing EEG alpha power, complexity, and spectral exponent

Accurate assessment of level of consciousness and potential to recover in severe brain injury patients underpins crucial decisions in the intensive care unit but remains a major challenge for the clinical team. The neurological wake-up test (NWT) is a widely used assessment tool, but many patients' behavioral response during a short interruption of sedation is ambiguous or absent, with little prognostic value. This study assesses the brain's electroencephalogram response during an interruption of propofol sedation to complement behavioral assessment during the NWT to predict survival, recovery of consciousness, and long-term functional outcome in acute severe brain injury patients. We recorded 128-channel EEG of 41 severely brain-injured patients during a clinically indicated NWT. The Glasgow Coma Scale (GCS) was used to assess behavioral responsiveness before and after interruption of sedation (GCS_observed). During the NWT, nine patients regained responsiveness, 13 patients showed ambiguous responsiveness and 19 patients were not responsive. Brain response to sedation interruption was quantified using EEG power, spatial ratios and the spectral exponent. We trained a linear regression model to identify brain patterns related to regaining behavioral responsiveness. We then applied this model to patients whose behavioral responses were ambiguous or absent, using their NWT brain responses to predict a change in behavioral response (Delta_GCS_predicted). Prognostic value of the Delta_GCS_predicted was assessed using the Mann-Whitney-U test and group-separability. The patients' survival, recovery of responsiveness, and functional outcomes were assessed up to 12 months post-recording. EEG patterns during interruption of sedation reliably predicted the GCS_observed in patients who regained responsiveness during the NWT. Electrophysiological patterns of waking-up were observed in some patients whose behavioral response was ambiguous or absent. Compared to the GCS_observed, the Delta_GCS_predicted improved separability of prognostic groups and significantly distinguished patients according to survival (U = 87, p<0.05). The EEG-trained model outperformed outcome predictions of the patients' attending physician and predictions based on the patients' APACHE score. EEG can complement behavioral assessment during the NWT to improve prognostication, inform clinicians, family members and caregivers, and to set realistic goals for treatment and therapy.

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A systematic review of aperiodic neural activity in clinical investigations

Donoghue

2024

Preprint

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In the study of neuro-electrophysiological recordings, aperiodic neural activity - activity with no characteristic frequency - has increasingly become a common feature of study. This interest has rapidly extended to clinical work, with many reports investigating aperiodic activity from patients from a broad range of clinical disorders. This work typically seeks to evaluate aperiodic activity as a putative biomarker relating to diagnosis or treatment response, and/or as a potential marker of underlying physiological activity. There is thus far no clear consensus on if and how aperiodic neural activity relates to clinical disorders, nor on the best practices for how to study it in clinical research. To address this, this systematic literature review, following PRISMA guidelines, examines reports of aperiodic activity in electrophysiological recordings with human patients with psychiatric and/or neurological disorders, finding 143 reports across 35 distinct disorders. Reports within and across disorders are summarized to evaluate current findings and examine what can be learned as pertains to the analysis, interpretations, and overall utility of aperiodic neural activity in clinical investigations. Aperiodic activity is commonly reported to relate to clinical diagnoses, with 31 of 35 disorders reporting a significant effect in diagnostic and/or treatment related studies. However, there is variation in the consistency of results across disorders, with the heterogeneity of patient groups, disease etiologies, and treatment status arising as common themes across different disorders. Overall, the current variability of results, potentially confounding covariates, and limitations in current understanding of aperiodic activity suggests further work is needed before aperiodic activity can be established as a potential biomarker and/or marker of underlying pathological physiology. Finally, a series of recommendations are proposed, based on the findings, limitations, and key discussion topics of the current literature to assist with guiding productive future work on the clinical utility of studying aperiodic neural activity.

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The role of etiology in the identification of clinical markers of consciousness: comparing EEG alpha power, complexity, and spectral exponent

Cited by 4 publications

References 53 publications

Spectral peak analysis and intrinsic neural timescales as markers for the state of consciousness

Spectral peak analysis and intrinsic neural timescales as markers for the state of consciousness

EEG response during sedation interruption complements behavioral assessment following severe brain injury

A systematic review of aperiodic neural activity in clinical investigations

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