Impact of thrombectomy techniques on outcome in medium or distal vessel occlusion: subanalysis of the DISTAL Trial
Bibliographic record
Abstract
INTRODUCTION: The optimal thrombectomy technique for medium/distal vessel occlusions (MDVOs) remains uncertain. OBJECTIVE: To compare the safety and efficacy of aspiration thrombectomy (ADAPT) versus stent retriever thrombectomy (SR only) versus a primary combined approach (PCA). PATIENTS AND METHODS: In this post hoc analysis of the DISTAL Trial, patients treated with first-line ADAPT, SR only, or PCA were included. The primary outcome was successful reperfusion (modified Thrombolysis in Cerebral Infarction 2b-3). Secondary outcomes included functional outcome (modified Rankin Scale score at 90 days) and intracranial hemorrhage. Statistical analysis was performed using mixed-effects logistic regression models. RESULTS: Of 222 patients treated with thrombectomy, 36 underwent ADAPT, 37 SR only, and 149 a PCA as first-line strategy. The median number of thrombectomy passes was 1 (IQR 1-2). Final successful reperfusion was achieved in 76.5% with first-line ADAPT, in 61.1% with first-line SR only, and in 82.4% with first-line PCA. First pass successful reperfusion was achieved in 44.4% with ADAPT, 59.5% with SR only, and 66.4% with PCA. PCA was associated with higher first pass reperfusion rates compared with ADAPT (aOR=2.37, 95% CI 1.13 to 5.05, P=0.024). There were no significant differences in functional outcomes or safety endpoints among the techniques. ADAPT resulted in numerically more favorable functional outcome. PCA resulted in numerically higher numbers of symptomatic intracranial hemorrhage. DISCUSSION AND CONCLUSION: Final successful reperfusion rate after PCA was higher than after SR only. Functional and safety outcomes were not significantly different. Further research is warranted, including individual patient data meta-analyses and data on novel aspiration devices not used in this trial.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".