Which Acute Ischemic Stroke Patients Are Fast Progressors?
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Fast infarct progression in acute ischemic stroke has a severe impact on patient prognosis and benefit of endovascular thrombectomy. In this post hoc analysis of the ESCAPE trial (Endovascular Treatment for Small Core and Proximal Occlusion Ischemic Stroke), we identified acute ischemic stroke patients with rapid infarct growth and investigated their baseline clinical and imaging characteristics. METHODS: Control arm patients were included if they had follow-up imaging at 2-8 hours without substantial recanalization, and if their baseline Alberta Stroke Program Early CT Score was ≥9. Fast infarct progression was defined as Alberta Stroke Program Early CT Score decay ≥3 points from baseline to 2- to 8-hour follow-up imaging. Clinical and imaging baseline characteristics were compared between fast progressors and other patients, and occlusion site and collateral flow patterns were assessed in detail. RESULTS: =0.021). In 8 out of 15 (53.3%), occlusion site and circle of Willis configuration prevented collateral flow via the anterior or posterior cerebral artery. CONCLUSIONS: Most patients with fast infarct progression had terminal carotid occlusions and impaired collateral flow via the anterior or posterior cerebral artery, indicating that occlusion location and intracranial vascular anatomy are relevant for infarct progression.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".