A Quality Assessment of Randomized Clinical Trials in Pediatric Orthopaedics
Bibliographic record
Abstract
The promotion and practice of evidence-based medicine necessitates a critical evaluation of medical literature, including the criterion standard of randomized clinical trials (RCTs). Recent studies have examined the quality of RCTs in various surgical specialties, but no study has focused on pediatric orthopaedics. The purpose of this study was to assess and describe the quality of RCTs published in the last 10 years in journals with high clinical impact in pediatric orthopaedics. All of the RCTs in pediatric orthopaedics published in 5 well-recognized journals between 1995 and 2005 were reviewed using the Detsky Quality Assessment Scale. The mean percentage score on the Detsky scale was 53% (95% confidence interval, 46%-60%). Only 7 (19%) of the articles satisfied the threshold for a satisfactory level of methodological quality (Detsky >75%). Most RCTs in pediatric orthopaedics that are published in well-recognized peer-reviewed journals demonstrate substantial deficiencies in methodological quality. Particular areas of weakness include inadequate rigor and reporting of randomization methods, use of inappropriate or poorly described outcome measures, inadequate description of inclusion and exclusion criteria, and inappropriate statistical analysis. Further efforts are necessary to improve the conduct and reporting of clinical trials in this field to avoid inadvertent misinformation of the clinical community.
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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 | 0.681 | 0.881 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.016 |
| Bibliometrics | 0.019 | 0.019 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| 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".