Assess the Correlation Between Electroencephalogram, National Institutes of Health Stroke Scale and Montreal Cognitive Assessment in Patients with Acute Ischemic Stroke
Bibliographic record
Abstract
is more suggested for cognitive disorders post stroke because the examination is more sensitive to diagnose mild impairment compared with the MMSE examination [5].The test administration of MoCA was applicable in patients with mild-to-moderate stroke, either acute ischemic or hemorrhagic strokes and TIA [6,7].Recently, aphasia and hemiplegia can preclude the use of the MoCA to assess global cognitive impairment, in addition to hearing loss and visual impairment [8].qEEG can detect changes in CBF and brain metabolism in 28 to 104 seconds [9].When normal CBF declines to 25 -35 ml/100 g/ min, the EEG loses its faster frequencies, then as the CBF decreases to 17 -18 ml/100 g/min, the slower frequencies gradually rise.This represents a crucial ischemic threshold at which neurons start to lose their transmembrane gradients, leading to cell infarction [10].qEEG is a powerful tool for predicting the degree of functional disability and cognitive impairment post-acute ischemic stroke events [11,12].
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".