Mechanical thrombectomy for basilar artery occlusion: efficacy, outcomes, and futile recanalization in comparison with the anterior circulation
Bibliographic record
Abstract
BACKGROUND: Performing mechanical thrombectomy (MT) in patients with basilar artery occlusion (BAO) is currently not evidence-based. OBJECTIVE: To compare patients' outcome, relative merits of achieving recanalization, and predictors of futile recanalization (FR) between BAO and anterior circulation large vessel occlusion (ACLVO) MT. METHODS: In the multicenter BEYOND-SWIFT registry (NCT03496064), univariate and multivariate (displayed as adjusted Odds Ratios, aOR and 95% confidence intervals, 95%-CI) outcome comparisons between BAO (N=165) and ACLVO (N=1574) were performed. The primary outcome was favorable outcome at 90 days (modified Rankin Scale, mRS 0-2). Secondary outcome included mortality, symptomatic intracranial hemorrhage (sICH) and FR. The relative merits of achieving successful recanalization between ACLVO and BAO were evaluated with interaction terms. RESULTS: MT in BAO was more often technically effective and equally safe in regards to mortality and sICH when compared to ACLVO. When adjusting for baseline differences, there was no significant difference between BAO vs ACLVO regarding rates of favorable outcome (aOR 0.986, 95%-CI 0.553 - 1.758). However, BAO were associated with increased rates of FR (aOR 2.146, 95%-CI 1.267 - 3.633). Predictors for FR were age, stroke severity, maneuver count and intracranial stenting. No significant heterogeneity on the relative merits of achieving successful recanalization on several outcome parameters were observed when comparing BAO and ACLVO. CONCLUSIONS: In selected patients, similar outcomes can be achieved in BAO and ACLVO patients treated with MT. Randomized controlled trials comparing patient selection and interventional strategies seem warranted to avoid FR. TRIAL REGISTRATION NUMBER: NCT03496064.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".