Combining Computed Tomography Perfusion and Baseline National Institutes of Health Stroke Scale to Assess the Clinical Penumbra in Ischemic Stroke
Bibliographic record
Abstract
In acute ischemic stroke, some neurological deficits may be reversible (corresponding topographically to the ischemic penumbra), while others are not (ischemic core).Computed tomography perfusion (CTP) can quantify the ischemic penumbra volume. 1 However, the clinical eloquence of different brain regions varies considerably, often resulting in a clinical-radiological mismatch: small ischemic areas might cause substantial deficits, whereas large volumes may produce minimal symptoms.2 Therefore, clinical and radiological information should be viewed as complementary, and combining their insights might provide a more accurate assessment of the clinical penumbra, namely, the potentially reversible clinical deficits of stroke patients caused by the ischemic penumbra.We aim to evaluate how CTP-derived measures, weighted by baseline National Institutes of Health Stroke Scale (NIHSS) scores, correlate with NIHSS improvement after complete reperfusion-the clinical penumbra.We included patients from the randomized ESCAPE-NA1 (Efficacy and Safety of Nerinetide for the Treatment of Acute Ischaemic Stroke) trial 3 (1) with available baseline CTP, (2) who achieved near-complete reperfusion, and (3) without parenchy-
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".