Abstract 36: Endovascular Thrombectomy Beyond 24 Hours From Last Known Well: <i>A Pooled Multicenter International Cohort</i>
Bibliographic record
Abstract
Background: Limited data are available on endovascular thrombectomy (EVT) efficacy and safety in large vessel occlusion (LVO) patients presenting >24hr from last known well (LKW). We compared outcomes between patients receiving EVT and best medical management (MM) in a multicenter international cohort. Methods: Consecutive patients with anterior circulation LVO presenting >24h after LKW from 13 centers from 7/2012-4/2021 were analyzed. Multivariable models for 90d mRS distribution and symptomatic ICH were adjusted for age, NIHSS, glucose, IV tPA, transfer status, clot location, time from LKW, CT ASPECTS and ischemic core (rCBF<30%) and Tmax >6s volumes. Results: Of 240 patients with a median (IQR) LKW to presentation 28.3h (24.9-38.2), 153 (64%) received EVT. Baseline characteristics were similar except for NIHSS (EVT: 13 (8-20) vs MM: 17 (10-22), p=0.005), CT ASPECTS (EVT: 8(6-9) vs MM: 4(3-6), p<0.001) and ischemic core 2.5(0-13) vs 15(0-71) mL, p<0.001. EVT was associated with a better shift in 90d mRS (acOR: 2.45, 95% CI=1.42-4.22, p=0.001), higher functional independence (42% vs 10%, aOR: 4.84, 95% CI=2.02-11.64, p<0.001) and numerically lower mortality (22% vs 42%, aOR: 0.50, 95% CI=0.23-1.06, p=0.071), Fig 1A. However, EVT was associated with numerically higher sICH (5.5% vs 0%, p=0.10). Following EVT, 82% achieved successful reperfusion (mTICI 2b-3), which was associated with better shift in 90d mRS (acOR: 5.82, 95% CI: 1.77-19.10, p=0.004), higher functional independence (44% vs 22%, aOR: 5.03, 95% CI: 0.87-29.12, p=0.07) and lower mortality (20% vs 52%, aOR: 0.08, 95% CI: 0.01-0.57, p=0.01), Fig 1B. Conclusions: EVT may be associated with better functional outcomes, despite numerically increased risk of sICH in patients presenting with anterior circulation LVO beyond 24 hours. Further prospective studies are warranted.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".