EEG to detect early recovery of consciousness in amantadine-treated acute brain injury patients
Bibliographic record
Abstract
Disorder of consciousness (DOC) is common in patients with acute brain injury (ABI) and it weighs heavily in goals of care discussion.1 Dopaminergic agents to support recovery have shown encouraging results in chronic DOC following traumatic brain injury (TBI) and are currently the most promising candidates to also support recovery during the acute post injury phase.2 Amantadine is a neurohormonal modulator that increases the concentration of dopamine at the synaptic cleft. Behavioural assessments of consciousness alone are often operator dependent, time consuming to obtain and may miss patients with covert consciousness.3 Our hypothesis is that resting Electroencephalogram (EEG) features follow a predictable course preceding behavioural recovery in patients with acute non-hypoxic-ischaemic brain injury receiving amantadine and may serve as biomarkers for recovery of consciousness. We studied 44 patients with ABI that were not following commands and were on EEG monitoring before and after the start of amantadine. A full description of the methods is available in the online supplementary file. ### Supplementary data [jnnp-2019-322645supp001.pdf] ### Study cohort From a cohort of 44 patients, 30 (68%) recovered consciousness prior to hospital discharge (online supplementary tables S1, S2). ### Baseline predictors of recovery Age, focal versus diffuse brain injury and admission Glasgow Coma Score were not associated with recovery of command following. Presence of sleep structures in the EEG (spindles and K-complexes) prior to starting amantadine was independently associated with recovery of command following (online supplementary table S3). Average spectrogram plots for each EEG recording classified according to the ‘ABCD’ model representing thalamocortical integrity were generated (figure 1A, online supplementary figure).4 The percent of patients that recovered command following did not increase hierarchically with higher ‘ABCD’ levels (figure 1B). Power spectral density analysis …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".