Impact of Endovascular Therapy in Patients With Large Ischemic Core
Bibliographic record
Abstract
Background and Purpose: Endovascular therapy (EVT) is strongly recommended for acute cerebral large vessel occlusion with the Alberta Stroke Program Early CT Score (ASPECTS) ≥6 due to occlusion of the internal carotid artery or M1 segment of the middle cerebral artery. However, the effect of EVT for patients who have ischemic core with ASPECTS ≤5 (0–5) was not established. The purpose of this study was to elucidate the outcomes of EVT for patients with large ischemic core. Methods: Based on the data of The Recovery by Endovascular Salvage for Cerebral Ultra-Acute Embolism Japan Registry 2, patients with internal carotid artery or M1 segment of the middle cerebral artery occlusion and pretreatment ASPECTS 0 to 5 on noncontrast CT or diffusion-weighted image were extracted, and the outcomes by EVT were analyzed. Primary end point was defined as a good functional outcome (modified Rankin Scale score of ≤2) after 90 days. Result: Among 2420 registered patients, 504 patients were with internal carotid artery or M1 segment of the middle cerebral artery occlusion and ASPECTS 0 to 5. Among these 504 patients, 172 (34.1 %) were treated with EVT (EVT group) and 332 (65.9 %) without (no-EVT group). In the no-EVT group, elderly patients, females, poor prestroke modified Rankin Scale, high National Institutes of Health Stroke Scale, low ASPECTS, and late admission were significantly more observed. Good functional outcomes were significantly more observed in the EVT group than in the no-EVT group (19.8 % versus 4.2 %; P<0.0001; adjusted odds ratio, 2.33; 95% CI, 1.10–4.94). The incidences of symptomatic intracranial hemorrhage within 72 hours did not significantly different between the EVT group and the no-EVT group (3.7 % versus 4.9%; P=0.55; adjusted odds ratio, 0.50; 95% CI, 0.14–1.73). Conclusions: Although outcomes in this group of patients were usually poor, the data suggested EVT may increase the likelihood of a good functional outcome.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".