Abstract P504: Outcomes and Predictors of Successful First Pass in MCA Occlusions Using ADAPT Thrombectomy Technique - Insights From STAR
Bibliographic record
Abstract
Introduction: Successful first pass (SFP) has been identified as a key benchmark of the success of mechanical thrombectomy (MT). However, studies that evaluate the predictors and outcomes of SFP using ADAPT (A Direct Aspiration first Pass Technique) are limied by the small number of patients or single center design. Methods: We used data from the prospectively collected data from 28 stroke centers that are included in the Stroke Thrombectomy and Aneurysm Registry (STAR). Patients with middle cerebral artery (MCA) occlusions at the level of M1 or M2 segments were included. SFP was defined by achieving modified Thrombolysis in Cerebral Infarction (mTICI) score≥2b with a single aspiration attempt. A multivariable logistic regression analysis was used to assess the predictors of SFP and evaluate the relationship between SFP and favorable 90-day outcome (90-day modified Rankin scale ≤2). Results: Out of 6123 patients included in STAR, 1002 (16.4%) underwent MT of M1 or M2 occlusion using ADAPT technique. SFP was achieved in 390 (38.9%) patients. SFP patients were older (72 vs. 69, P=0.007), had higher Alberta Stroke Program Early CT Score (ASPECTS) on presentation (9 vs. 8, P=0.018) (Table 1). On multivariable analysis, neither age (aOR 1.006, 95% CI 0.996-1.016, P=0.252) nor ASPECTS (aOR 1.055, 95% CI 0.976-1.141, P=0.179) were independent predictor of SFP. Importantly, SFP was independently associated with favorable 90-day outcome (aOR 2.769, 95% CI 1.988-3.858, P<0.001) after controlling for age, sex, ASPECTS, history of atrial fibrillation, NIHSS on presentation, onset to groin time and IV-tPA. Conclusion: In this cohort of patients with M1 or M2 occlsuion undergoing MT using ADAPT technique, patients who had SFP were older and had better ASPECTS. However, both age and ASPECTS were not independently associated with SFP. Also, patients who had SFP were almost 3 times more likely to achieve favorable 90-day 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".