Predicting Outcome in Acute Stroke: A Comparison between QEEG and the Canadian Neurological Scale
Bibliographic record
Abstract
OBJECTIVE: To determine and compare the predictive value of quantitative EEG (QEEG) and the Canadian Neurological Scale (CaNS), in patients with an acute cerebral stroke. METHODOLOGY: Twenty-eight patients were studied with the diagnosis of acute ischemic middle cerebral artery stroke, within the first 72 hours of clinical evolution. Thirty-seven EEGs and clinical evaluations were collected: 13 during the first 24 hours after stroke onset, 9 between 24-48 hours and 15 between 48-72 hours. The QEEG studied variables were: the Z values (maximum, minimum and the Z medians from the 5 nearest points to each one) of absolute energies (AE) from the 4 classic frequencies bands. The clinical scale showed a smaller percent of correct prognosis than QEEG variables. CONCLUSIONS: QEEG was demonstrated to be a powerful tool to predict the degree of residual functional disabilities after an acute ischemic stroke and showed a higher prognostic value than CaNS when they are performed within the first 72 hours of brain infarct.
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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 | 0.001 | 0.009 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".