Clinical effectiveness of endovascular stroke treatment in the early and extended time windows
Bibliographic record
Abstract
Background The clinical efficacy of mechanical thrombectomy has been unequivocally demonstrated in multiple randomized clinical trials. However, these studies were performed in carefully selected centers and utilized strict inclusion criteria. Aim We aimed to assess the clinical effectiveness of mechanical thrombectomy in a prospective registry. Methods A total of 2008 patients from 76 sites across 12 countries were enrolled in a prospective open-label mechanical thrombectomy registry. Patients were categorized into the corresponding cohorts of the SWIFT-Prime, DAWN, and DEFUSE 3 trials according to the basic demographic and clinical criteria without considering specific parenchymal imaging findings. Baseline and outcome variables were compared across the corresponding groups. Results As compared to the treated patients in the actual trials, registry-derived patients tended to be younger and had lower baseline ASPECTS. In addition, time to treatment was earlier and the use of intravenous tissue plasminogen activator (IV-tPA) and general anesthesia were higher in DAWN- and DEFUSE-3 registry derived patients versus their corresponding trials. Reperfusion rates were higher in the registry patients. The rates of 90-day good outcome (mRS0-2) in registry-derived patients were comparable to those of the patients treated in the corresponding randomized clinical trials (SWIFT-Prime, 64.5% vs. 60.2%; DAWN, 50.4% vs. 48.6%; Beyond-DAWN: 52.4% vs. 48.6%; DEFUSE 3, 52% vs. 44.6%, respectively; all P > 0.05). Registry-derived patients had significant less disability than the corresponding randomized clinical trial controls (ordinal modified Rankin Scale (mRS) shift odds ratio (OR), P < 0.05 for all). Conclusion Our study provides favorable generalizability data for the safety and efficacy of thrombectomy in the “real-world” setting and supports that patients may be safely treated outside the constraints of randomized clinical trials.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".