Indications for Mechanical Thrombectomy for Acute Ischemic Stroke: Current Guidelines and Beyond.
Bibliographic record
Abstract
PURPOSE OF THE REVIEW: This article reviews recent breakthroughs in the treatment of acute ischemic stroke, mainly focusing on the evolution of endovascular thrombectomy, its impact on guidelines, and the need for and implications of next-generation randomized controlled trials. RECENT FINDINGS: Endovascular thrombectomy is a powerful tool to treat large vessel occlusion strokes and multiple trials over the past 5 years have established its safety and efficacy in the treatment of anterior circulation large vessel occlusion strokes up to 24 hours from stroke onset. SUMMARY: In 2015, multiple landmark trials (MR CLEAN, ESCAPE, SWIFT PRIME, REVASCAT, and EXTEND IA) established the superiority of endovascular thrombectomy over medical management for the treatment of anterior circulation large vessel occlusion strokes. Endovascular thrombectomy has a strong treatment effect with a number needed to treat ranging from 3 to 10. These trials selected patients based on occlusion location (proximal anterior occlusion: internal carotid or middle cerebral artery), time from stroke onset (early window: up to 6-12 hours), and acceptable infarct burden (Alberta Stroke Program Early CT Score [ASPECTS] ≥6 or infarct volume <50 mL). In 2017, the DAWN and DEFUSE-3 trials successfully extended the time window up to 24 hours in appropriately selected patients. Societal and national thrombectomy guidelines have incorporated these findings and offer Class 1A recommendation to a subset of well-selected patients. Thrombectomy ineligible stroke subpopulations are being studied in ongoing randomized controlled trials. These trials, built on encouraging data from pooled analysis of early trials (HERMES collaboration) and emerging retrospective data, are studying large vessel occlusion strokes with mild deficits (National Institutes of Health Stroke Scale <6) and large infarct burden (core volume >70 mL).
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.007 |
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".