Thrombectomy in basilar artery occlusions: impact of number of passes and futile reperfusion
Bibliographic record
Abstract
BACKGROUND: The number of mechanical thrombectomy (MT) passes is strongly associated with angiographic reperfusion as well as clinical outcomes in patients with anterior circulation ischemic stroke. However, these associations have not been analyzed in patients with basilar artery occlusion (BAO). We investigated the influence of the number of MT passes on the degree of reperfusion and clinical outcomes, and compared outcome after ≤3 passes versus >3 passes. METHODS: We used data from the prospective multicentric Endovascular Treatment in Ischemic Stroke (ETIS) Registry at 18 sites in France. Patients with BAO treated with MT were included. The primary outcome was a favorable outcome, defined as a modified Rankin Scale score of 0-3 at 90 days. We fit mixed multiple regression models, with center as a random effect. RESULTS: We included 275 patients. Successful recanalization (modified Thrombolysis In Cerebral Infarction (mTICI) 2b-3) was achieved in 88.4%, and 41.8% had a favorable outcome. The odds ratio for favorable outcome with each pass above 1 was 0.41 (95% CI 0.23 to 0.73) and for recanalization (mTICI 2b-3) it was 0.70 (95% CI 0.57 to 0.87). In patients with ≤3 passes, the rate of favorable outcome in recanalized versus non-recanalized patients was 50.5% versus 10.0% (p=0.001), while in those with >3 passes it was 16.7% versus 15.2% (p=0.901). CONCLUSIONS: We found that BAO patients had a significant relationship between the number of MT passes and both recanalization and favorable functional outcome. We further found that the benefit of recanalization in BAO patients was significant only when recanalization was achieved within three passes, encouraging at least three passes before stopping the procedure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 teacher head, 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".