Outcomes of mechanical thrombectomy in anticoagulated patients with acute distal and medium vessel stroke
Bibliographic record
Abstract
Abstract Background: Stroke remains a major health concern globally, with oral anticoagulants widely prescribed for stroke prevention. The efficacy and safety of mechanical thrombectomy (MT) in anticoagulated patients with distal medium vessel occlusions (DMVO) are not well understood. Methods: This retrospective analysis involved 1282 acute ischemic stroke (AIS) patients who underwent MT in 37 centers across North America, Asia, and Europe from September 2017 to July 2023. Data on demographics, clinical presentation, treatment specifics, and outcomes were collected. The primary outcomes were functional outcomes at 90 days post-MT, measured by modified Rankin Scale (mRS) scores. Secondary outcomes included reperfusion rates, mortality, and hemorrhagic complications. Results: Of the patients, 223 (34%) were on anticoagulation therapy. Anticoagulated patients were older (median age 78 vs 74 years; p < 0.001) and had a higher prevalence of atrial fibrillation (77% vs 26%; p < 0.001). Their baseline National Institutes of Health Stroke Scale (NIHSS) scores were also higher (median 12 vs 9; p = 0.002). Before propensity score matching (PSM), anticoagulated patients had similar rates of favorable 90-day outcomes (mRS 0–1: 30% vs 37%, p = 0.1; mRS 0–2: 47% vs 50%, p = 0.41) but higher mortality (26% vs 17%, p = 0.008). After PSM, there were no significant differences in outcomes between the two groups. Conclusion: Anticoagulated patients undergoing MT for AIS due to DMVO did not show significant differences in 90-day mRS outcomes, reperfusion, or hemorrhage compared to non-anticoagulated patients after adjustment for covariates.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".