Endovascular Thrombectomy for Extracranial Internal Carotid Artery Occlusions With Large Ischemic Strokes
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Although previous trials have established the efficacy and safety of endovascular thrombectomy (EVT) in large ischemic core strokes, most of them excluded patients with extracranial internal carotid artery (e-ICA) occlusion. We aimed to compare outcomes in patients with e-ICA occlusion and large ischemic core infarcts treated with EVT vs medical management (MM). METHODS: This was a secondary analysis of the SELECT2 trial, a randomized controlled trial conducted at 31 international sites. Adult patients with proximal intracranial anterior circulation large ischemic strokes, defined as Alberta Stroke Program Early CT Score (ASPECTS) 3-5 on noncontrast CT or ischemic core ≥50 mL on CT-perfusion/magnetic resonance-diffusion imaging, and concomitant e-ICA occlusion were selected. The primary outcomes were the distribution of modified Rankin Scale (mRS) score at 90-day follow-up and symptomatic intracranial hemorrhage (sICH). RESULTS: = 0.388). DISCUSSION: Among patients with e-ICA occlusions and large ischemic core stroke, EVT was associated with better functional outcomes without significant safety concerns when compared with MM. Our findings suggest that EVT in these patients is beneficial, while the optimal treatment of the extracranial carotid occlusion remains unclear. TRIAL REGISTRATION INFORMATION: Name of the trial: SELECT2 trial. Registration number: ClinicalTrials.gov Identifier: NCT03876457. Date of registration submission: August 3, 2019. Date of first patient enrollment: November 10, 2019. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that for patients with large core acute ischemic stroke and concomitant e-ICA occlusion, EVT is associated with better functional outcome at 90 days compared with MM alone.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".