GR.1 Standardized approach to direct first pass aspiration technique for endovascular thrombectomy: description and initial experience with CANADAPT
Bibliographic record
Abstract
Background: Endovascular thrombectomy (EVT) is standard of care for acute ischemic stroke. There is growing evidence that A Direct Aspiration first Pass Technique (ADAPT) is a safe, efficient and effective approach for EVT, offering several advantages. This study describes initial institutional experience in the use of a standardized aspiration only technique: CANADAPT. Methods: Single center prospective cohort study was performed on patients treated for large/medium vessel ischemic stroke. A sequential stepwise aspiration only technique was applied, CANADAPT, consisting of three maneuvers, A, B and C. The reperfusion success rate, number of passes, use of rescue technique, complication rate and procedural cost was determined. Results: 22 patients were included representing M1 (77%), M1/2 (9%), carotid-T (9%) and basilar (5%) occlusions. First pass recanalization was achieved in 50% of patients. A further 4 patients had successful reperfusion with a second pass (total 68% success). 7 patients had stent rescue technique (SOLUMBRA). Of these, 5 patients (22% of total) had successful reperfusion. The cost per procedure was $6,630 ± 1069 for CANADAPT, and $13,530 ± 2706 for SOLUMBRA. Conclusions: CANADAPT represents a standardized approach to aspiration only thrombectomy. This study demonstrates the safety, efficiency and efficacy of this technique in EVT.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".