Abstract WMP46: Quantitative Electroencephalogram To Assess Neurovascular Coupling Post Endovascular Thrombectomy
Bibliographic record
Abstract
Introduction: Persistent neurovascular uncoupling may be associated with poor outcome in patients with ischemic stroke after successful recanalization. Quantitative electroencephalography (EEG) can be used to assess neuronal function. We assessed relation between degree of recanalization post-endovascular thrombectomy (EVT), quantitative EEG based parameters and severity of neurological deficits. Methods: Patients with acute ischemic stroke with large vessel occlusion in anterior circulation were enrolled. EEG was recorded using a modified Muse headband (InteraXon) before, immediately after and at 24 hours post-EVT. Pairwise-derived brain symmetry index (pdBSI) and delta-to-alpha ratio (DAR) were computed using Fitting Oscillation & one-over F (FOOOF) MATLAB wrapper. Results: A total of six patients with mean age 73.6±11.6 years and baseline median (IQR) NIHSS of 13.5 (11-15) were included. Expanded thrombolysis in cerebral infarction (eTICI) scores were 2b67 in one, 2c in two and 3 in three cases. Baseline EEG was recorded at 75 minutes (60-100) from arrival, second at 255 minutes (90-420) after recanalization and third at 28.5 hours (27-31) after recanalization. Four patients with improvement in NIHSS of >10 had 46.6±31.7% change in pdBSI at 24 h. One patient with NIHSS <10 improvement had -25.3% change in pdBSI. One patient with low baseline NIHSS (9) had 90.9% change in pdBSI. There was linear correlation between baseline infarct volume on perfusion studies and change in pdBSI at 24 h (r=0.86, p<0.0001, Figure 1). There was no difference in the DAR in the ipsilateral hemisphere pre-EVT, immediately post-EVT (p=0.6) and 24 h post-EVT (p=0.8). Conclusion: Preliminary data suggest return of neuronal function and clinical recovery may lag after successful recanalization, due to persistent neurovascular uncoupling. Higher baseline infarct volume may predict lower pdBSI change. Portable EEG may help characterise this novel treatment target.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".