Predictors of Futile Recanalization after Mechanical Thrombectomy for Embolism-Related Large Vessel Occlusion in the Anterior Circulation
Bibliographic record
Abstract
Objective: Futile recanalization (FR)-a poor functional outcome despite successful reperfusion after mechanical thrombectomy (MT)-remains a significant issue in acute ischemic stroke owing to large vessel occlusion. This study aimed to identify predictors of FR, focusing on CT perfusion (CTP) parameters using our institutional retrospective data. Methods: Patients who underwent MT at our institution between April 2015 and February 2023 were retrospectively reviewed. FR was defined as a 90-day modified Rankin Scale (mRS) score of 3-6 despite successful reperfusion (modified thrombolysis in cerebral infarction ≥2b). Patients with internal carotid artery (ICA) or M1 segment of the middle cerebral artery occlusion, pre-stroke mRS 0-2, stroke etiology classified as cardioembolic or embolic stroke of undetermined source, and available CTP were included. The ischemic core was defined as cerebral blood volume (CBV) <1.0 mL/100 g on CTP, and the Alberta Stroke Program Early CT Score (ASPECTS) was also evaluated. Clinical, imaging, and procedural variables were compared between the FR group and those with a favorable outcome (mRS 0-2) after successful reperfusion. Multivariable logistic regression was performed, including imaging markers and variables with p <0.1 in univariate analyses as covariates. Receiver-operating characteristic (ROC) analyses determined thresholds for ASPECTS and CBV-defined core volume, followed by sensitivity analyses. Results: A total of 531 patients underwent MT during the study period, of whom 136 met the inclusion criteria (mean age 78 ± 11 years, 70 women, 46 ICA occlusions, median ASPECTS 9; interquartile range, 7-10). FR was observed in 69 patients (50.8%). Compared with the favorable outcome group, the FR group had significantly older age, higher baseline NIHSS scores, higher prevalence of diabetes mellitus, lower ASPECTS, larger CBV-defined core volumes, and a greater total number of device passes. Multivariable logistic regression identified older age, higher NIHSS, diabetes mellitus, and a greater total number of device passes as consistently independent predictors of FR. ROC analysis identified CBV-defined core volume ≥28.5 mL as an independent predictor of FR (area under the curve [AUC] 0.62, p = 0.013; adjusted odds ratio [aOR] 3.09, 95% confidence interval [CI] 1.23-8.28; p = 0.02); this association remained significant at ≥30 mL (aOR 2.82, 95% CI 1.14-7.33; p = 0.02) but not at ≥40 mL. ASPECTS ≤8 was also associated with FR (AUC 0.64, p = 0.002; aOR 2.92, 95% CI 1.20-7.44; p = 0.02). Conclusion: Older age, baseline stroke severity, diabetes mellitus, and multiple device passes were major predictors of FR. Among imaging markers, a CBV-defined core volume of approximately 30 mL emerged as a clinically relevant threshold associated with increased FR risk. These findings suggest that integrating clinical, procedural, and imaging factors may help optimize patient selection, although validation in larger, multicenter studies is warranted.
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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) | 0.000 | 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) | 0.000 | 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".