Supplementary Material for: Adjustment of Stent Retriever Length to Clot Extent Affects First-Pass Reperfusion in Endovascular Treatment of Acute Ischemic Stroke
Bibliographic record
Abstract
Background: Stent retriever technology has evolved, and significantly longer devices have become available for mechanical thrombectomy (MT) of large cerebral vessel occlusions in ischemic stroke. We hypothesized that increased stent retriever length may improve the rate of complete angiographic reperfusion and decrease the respective number of attempts, resulting in a better clinical outcome. Methods: Retrospective analysis of patients with large vessel occlusion in the anterior and posterior circulation treated with stent retriever MT. The study group was dichotomized into short (20 mm) and long (>20 mm) retrievers using propensity matching. In the anterior circulation, the clot burden score was evaluated. Primary end points were first-pass modified thrombolysis in cerebral infarction (mTICI) 3 reperfusion and first-pass mTICI ≥ 2b reperfusion, and the secondary end point was functional independence (defined as modified Rankin Scale score 0–2) at discharge and 90 days. Results: Overall, 394 patients were included in the analysis. In the anterior circulation, short stent retrievers had a significantly higher rate of first-pass reperfusion in cases with low clot burden (mTICI 3: 27% vs. 17%; p = 0.009; mTICI ≥ 2b: 42 vs. 30%; p = 0.005) and in middle cerebral artery occlusions (mTICI ≥ 2b: 51 vs. 41%; p = 0.024). Higher rates of favorable outcome at discharge and 90 days were observed for the short stent retriever group (p < 0.001). Conclusion: Stent retriever length should be adjusted to clot burden score and vessel occlusion site.
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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 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.800 | 0.166 |
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".