Futile Recanalization After Endovascular Treatment in Patients With Acute Basilar Artery Occlusion
Bibliographic record
Abstract
BACKGROUND: It is estimated that >50% of acute basilar artery occlusion (ABAO) patients with successful reperfusion after endovascular treatment (EVT) have futile recanalization. However, few studies investigated the reasons behind this. OBJECTIVE: To identify the factors associated with futile recanalization in ABAO after successful reperfusion. METHODS: We recruited patients with successful reperfusion (expanded Thrombolysis In Cerebral Infarction score of ≥2b) after EVT from the Basilar Artery Occlusion Study registry. Patients were divided into meaningful recanalization (90-day modified Rankin Scale 0-3) and futile recanalization (90-day modified Rankin Scale 4-6) groups. Multivariable logistic regression analyses were used to identify the predictors of futile recanalization. RESULTS: A total of 522 patients with successful reperfusion were selected. Of these, 328 patients had futile recanalization and 194 had meaningful recanalization. Multivariable logistic regression shows that higher neutrophil-to-lymphocyte ratio ( P = .01), higher baseline National Institutes of Health Stroke Scale score ( P < .001), longer puncture to recanalization time ( P = .02), lower baseline posterior circulation Alberta Stroke Program Early CT score ( P < .001), lower posterior circulation collateral score ( P = .02), incomplete reperfusion ( P < .001), and diabetes mellitus ( P < .001) were predictors of futile recanalization. CONCLUSION: Higher neutrophil-to-lymphocyte ratio, longer puncture to recanalization time, incomplete reperfusion, stroke severity, lower baseline posterior circulation Alberta Stroke Program Early CT score, poor collaterals, and diabetes mellitus were independent predictors of futile recanalization in patients with ABAO with successful reperfusion after EVT. Moreover, multiple stent retriever passes were associated with a high proportion of futile recanalization in patients with late time windows.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".