Stent retriever size and outcomes after anterior circulation occlusion thrombectomy
Bibliographic record
Abstract
BACKGROUND: The impact of stent retriever size on mechanical thrombectomy (MT) outcomes remains uncertain. We aim to clarify the influence of stent retriever size on MT outcomes by analyzing data from two national prospective registries. METHODS: A retrospective analysis was performed on data from the French and German MT registries including consecutive patients with anterior circulation large vessel occlusion who underwent Solitaire stent retriever MT with or without additional aspiration. Efficacy outcomes were successful reperfusion and complete reperfusion. Safety outcomes included any intracerebral hemorrhage (ICH) and symptomatic intracerebral hemorrhage (sICH). RESULTS: Complete reperfusion was lower in the 4×20 mm stent retriever group than in the 4×40 mm stent retriever group (47% vs 53%; OR 0.61, P=0.0039). Successful reperfusion did not differ between the 4×20 mm and 4×40 mm stent retriever groups (89% vs 93%; OR 0.69, P=0.25). There was no difference between the 6×30/6×40 mm and 4×20 mm stents, and there was no difference in functional outcomes between the groups. In terms of safety, any ICH was lower in the 4×20 mm group than in the 4×40 mm group (20% vs 36%; OR 0.60, P=0.0095). Symptomatic ICH was lower in the 4×20 mm group than in the 4×40 mm group (5% vs 10%; OR 0.58, P=0.086), but the difference did not reach statistical significance. Mortality was lower in the 4×20 mm than in the 6×40 mm group (26% vs 33%; OR 0.70, P=0.044). When compared according to occlusion location, the results were overall similar. CONCLUSION: This study suggests that longer and larger stent retrievers lead to a higher reperfusion rate but also a higher rate of hemorrhagic complications. Overall, the size of the stent did not affect functional outcomes.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".