Non-Inferiority Trials in Stroke Research: What Are They, and How Should We Interpret Them?
Bibliographic record
Abstract
Randomized clinical trials are important in both clinical and academic stroke communities with increasing numbers of new design concepts emerging. One of the "less traditional" designs that have gained increasing interest in the last decade is non-inferiority trials. Whilst the concept might appear straightforward, the design and interpretation of non-inferiority trials can be challenging. In this review, we will use exemplars from clinical trials in the stroke field to provide an overview of the advantages and limitations of non-inferiority trials and how they should be interpreted in stroke research.
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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 | 0.376 | 0.586 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.009 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.016 | 0.017 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.012 | 0.018 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".