The state of trial registrations in the field of Orthopaedics in years 2015–2020. A meta-epidemiological study
Bibliographic record
Abstract
Objective: To assess the extent and trends in registration of Orthopaedic randomized clinical trials (RCTs) between 2015 and 2020. Design: Epidemiological study. Primary publications of RCTs published in top Orthopaedic journals (ISI Journal Citation Reports 2019 rankings) between 2015 and 2020 were included in this meta-epidemiological study with no restrictions on patient population, intervention/control groups or outcome type. Independent reviewers in pairs were involved in RCT selection and data extraction. The proportion of RCTs published that were registered (prospectively or retrospectively) or not registered were reported using counts and percentages stratified by years for each journal. Results: A total of 474 primary RCTs were considered eligible. We identified 157 out of 474 RCTs (33% of RCTs across journals) that were reported to have been registered prospectively.The proportion of prospective RCT registrations had increased by 40% (10%-50%) between 2015 and 2020. On the other hand, the proportion of RCTs with no registrations were reduced by 29% (50%-21%) between 2015 and 2020. Conclusion: Prospective RCT registration in the past 5 years in the field of orthopaedic has increased, but 2/3 of published RCTs still failed to report prospective registration.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | MetaresearchMeta-epidemiology (broad)Meta-epidemiology (narrow) Domain: Reporting · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| gpt | MetaresearchMeta-epidemiology (broad) Domain: Reporting · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | medium |
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 | 0.206 | 0.298 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.029 |
| Bibliometrics | 0.018 | 0.017 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".