Ethical and Methodological Issues Surrounding the Use of Appropriate Comparators in Orthopaedic Surgery Randomized Controlled Trials
Bibliographic record
Abstract
Although randomized controlled trials (RCTs) have the ability to provide researchers with more concrete evidence than that of their nonrandomized counterparts, conducting an RCT brings with it many ethical and methodological considerations. It is understood that in order to progress knowledge, and create new knowledge to benefit future patients, research must include human subjects; however, the desire to further knowledge must be placed second to the safety and respect for trial participants. An important ethical and methodological step in the design of any trial once the intervention is established is the selection of the comparator treatment. This is especially a topic of interest in orthopaedic surgery trials, in which a placebo comparator is not always possible and, arguably, sometimes never ethical. We review the use of different comparators in the treatment of orthopaedic surgery injuries and conditions, taking into consideration methodological and ethical issues. Comparators assessed are established treatments, standard-of-care treatments, conservative treatments, placebos, and sham surgeries.
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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 | 0.757 | 0.861 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.012 | 0.008 |
| Bibliometrics | 0.009 | 0.015 |
| Science and technology studies | 0.004 | 0.020 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.010 | 0.007 |
| Research integrity | 0.019 | 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".