‘Real-world’ comparison of first-line direct aspiration and stent retriever mechanical thrombectomy for the treatment of acute ischemic stroke in the anterior circulation: a multicenter international retrospective study
Bibliographic record
Abstract
BACKGROUND: Thrombectomy for anterior large vessel occlusion less than 24 hours since last known well is now standard of care. Certain aspects of clinical trials may limit generalizability to 'real-world' practice. OBJECTIVE: To compare revascularization rates and outcomes for direct aspiration (ADAPT) and stent retriever thrombectomy following anterior acute ischemic stroke (AIS) in a real-life setting. METHODS: Data from the most recent 20 consecutive patients with AIS treated with mechanical thrombectomy between 2015 and 2016 were collected from 15 high-volume stroke centers across North America for a total of 300 cases. Patients with proximal anterior large vessel occlusions were dichotomized by primary treatment technique. Ordinal logistic regression assessed the effects of clinical variables on patient disability using 90-day modified Rankin Scale (mRS) scores. RESULTS: Adequate revascularization (Thrombolysis in Cerebral Infarction ≥2b) was ultimately achieved in 91.2% of first-line direct aspiration (ADAPT) cases with an average of 1.9±1.9 passes and in 87.5% of stent retriever cases with an average of 1.7±1.0 passes. Time from groin puncture to revascularization was shorter for ADAPT cases. The mean 90-day mRS score for both groups was 3.0±2.4. Number of passes using primary technique, and postintervention intracranial hemorrhage, were significant predictors of 90-day mRS scores after ADAPT, while age and preprocedure mRS score were predictive of outcomes following first-line stent retriever. CONCLUSIONS: Our data show similar adequate revascularization rates and 90-day functional outcomes for first-line direct aspiration and stent retrievers for anterior large vessel occlusion in a real-world setting. These results support the findings of other prospective trials evaluating the two techniques.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".