A randomized pragmatic care trial on endovascular acute stroke interventions (EASI): criticisms, responses, and ethics of integrating research and clinical care
Bibliographic record
Abstract
BACKGROUND: The Endovascular Acute Stroke Intervention (EASI) trial was conceived as a pragmatic care trial, designed to integrate trial methods with clinical practice. Reporting the EASI experience was met with objections and criticisms during peer review concerning both scientific and ethical issues. Our goal is to discuss these criticisms in order to promote the pragmatic approach of care trials in outcome-based medical care. METHODS: The comments and criticisms of 11 reviewers from 5 journals were collected and analyzed. The EASI protocol was also compared to the protocols of seven thrombectomy trials using the pragmatic-explanatory continuum indicator summary (PRECIS). RESULTS: Main criticisms of EASI concerned selection criteria that were judged to be too vague and too inclusive, brain and vascular imaging methods that were not sufficiently prescribed by protocol, lack of blinding of outcome assessment, and lack of power. EASI was at the pragmatic end of the spectrum of thrombectomy trials. CONCLUSION: The pragmatic care trial methodology is not currently well-established. More work needs to be done to integrate scientific methods and ethical care in the best medical interest of current patients.
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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 | 0.741 | 0.865 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.022 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.012 | 0.010 |
| 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; 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".