The Canadian Orthopaedic Trauma Society
Bibliographic record
Abstract
Aims This study reviews the past 30 years of research from the Canadian Orthopedic Trauma Society (COTS), to identify predictive factors that delay or accelerate the course of randomized controlled trials in orthopaedic trauma. Methods We conducted a methodological review of all papers published through the Canadian Orthopaedic Trauma Society or its affiliates. Data abstracted included: year of publication; journal of publication; study type; number of study sites; sample size; and achievement of sample size goals. Information about the study timelines was also collected, including: the date of study proposal to COTS; date recruitment began; date recruitment ended; and date of publication. Results In total, 22 studies have been published through the COTS working group, 13 of which are randomized controlled trials (RCTs). In total, 1,423 individual patients have been involved in COTS studies, a mean of 110 patients per trial (22 to 424). Each study was conducted across a mean of approximately six centres (1 to 11) and took nearly ten years (mean 119.9 months (59 to 188)) from presentation of concept to publication. The mean length of enrolment was 63 months (26 to 113) and the mean time from cessation of enrolment to publication 51 months (19 to 78). Regardless of sample size, the only factor associated with a decreased length of enrolment was a higher number of clinical sites (p = 0.041). Neither study sample size nor length of enrolment were associated with total time to publication. Conclusion Over the last three decades, COTS has developed a multinational strategy to produce high-quality evidence in the field of orthopaedic trauma through 13 multicentre RCTs. Future efficiencies can be realized by recruitment of more clinical sites, improving connectivity between the sites, and the promotion of national streamlined ethics processes. Cite this article: Bone Joint J 2021;103-B(5):898–901.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.187 | 0.035 |
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".