Endovascular vs Medical Management for Late Anterior Large Vessel Occlusion With Prestroke Disability: Analysis of CLEAR and RESCUE-Japan
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Current guidelines do not address recommendations for mechanical thrombectomy (MT) in the extended time window (>6 hours after time last seen well [TLSW]) for large vessel occlusion (LVO) patients with preexisting modified Rankin Scale (mRS) > 1. In this study, we evaluated the outcomes of MT vs medical management in patients with prestroke disability presenting in the 6- to 24-hour time window with acute LVO. METHODS: We analyzed a multinational cohort (61 sites, 6 countries from 2014 to 2020) of patients with prestroke (or baseline) mRS 2 to 4 and anterior circulation LVO treated 6-24 hours from TLSW. Patients treated in the extended time window with MT vs medical management were compared using multivariable logistic regression and inverse probability of treatment weighting (IPTW). The primary outcome was the return of Rankin (ROR, return to prestroke mRS by 90 days). RESULTS: Of 554 included patients (448 who underwent MT), the median age was 82 years (interquartile range [IQR] 72-87) and the National Institutes of Health Stroke Scale (NIHSS) was 18 (IQR 13-22). In both MV logistic regression and IPTW analysis, MT was associated with higher odds of ROR (adjusted OR [aOR] 3.96, 95% CI 1.78-8.79 and OR 3.10, 95% CI 1.20-7.98, respectively). Among other factors, premorbid mRS 4 was associated with higher odds of ROR (aOR, 3.68, 95% CI 1.97-6.87), while increasing NIHSS (aOR 0.90, 95% CI 0.86-0.94) and decreasing Alberta Stroke Program Early Computed Tomography Scale score (aOR per point 0.86, 95% CI 0.75-0.99) were associated with lower odds of ROR. Age, intravenous thrombolysis, and occlusion location were not associated with ROR. DISCUSSION: In patients with preexisting disability presenting in the 6- to 24-hour time window, MT is associated with a higher probability of returning to baseline function compared with medical management. CLASSIFICATION OF EVIDENCE: This investigation's results provide Class III evidence that in patients with preexisting disability presenting 6-24 hours from the TLSW and acute anterior LVO stroke, there may be a benefit of MT over medical management in returning to baseline function.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".