Optimizing Reperfusion Trials: A Consensus Research Roadmap From the STAIR XIII Conference
Bibliographic record
Abstract
The STAIR (Stroke Treatment Academic Industry Roundtable) sponsored a workshop during the STAIR XIII conference in Washington, DC on March 27 to 28, 2025, to develop consensus recommendations, particularly regarding research priorities and design elements for trials of reperfusion therapies. This forum brought together stroke neurologists, neuroradiologists, neuroimaging research scientists, members of the National Institute of Neurological Disorders and Stroke, and industry representatives to discuss future developments in reperfusion therapies. The reperfusion trials session summarized and compared recent acute stroke trials. The workshop developed consensus recommendations for research priorities and trial design challenges. Given that the majority of patients eligible for reperfusion therapies present initially to primary stroke centers, developing research networks that allow trials to be conducted in the transfer setting and overcome the logistical challenges in such centers was identified as a key priority. A particular focus was the definition and investigation of microvascular reperfusion and the no-reflow phenomenon. Potential trial paradigms to advance the field were discussed. Recent acute stroke clinical trials have extended the scope of intravenous thrombolytics and endovascular thrombectomy. Recruitment for future trials at both primary and comprehensive stroke centers, in addition to standard of care, poses challenges, particularly for novel thrombolytics. Recommendations for enhancing stroke imaging research and the definition of macrovascular versus microvascular reperfusion are provided.
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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 | 0.506 | 0.388 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.009 | 0.013 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.029 | 0.024 |
| Open science | 0.015 | 0.030 |
| Research integrity | 0.041 | 0.057 |
| Insufficient payload (model declined to judge) | 0.014 | 0.009 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".