Evidence-based Recommendations for Pediatric Orthopaedic Practice
Bibliographic record
Abstract
BACKGROUND: Evidence-based medicine has become the cornerstone to guide clinical practice decision-making. Evidence-based medicine integrates the strongest available evidence with clinical expertise to make decisions about clinical care. The quality of the evidence depends upon the soundness of the study methodology to allow for meaningful interpretation of the clinical results. The purpose of this review is to analyze the methodological design and clinical findings of published pediatric orthopaedic studies to determine their ability to change or influence clinical practice. METHODS: This is the first in a series of evidence-based reviews in pediatric orthopaedics. The pediatric orthopaedic literature was reviewed for randomized controlled trials (RCTs) published in 2013 to 2014. Two RCTs were selected from the Journal of Bone and Joint Surgery for in depth methodological review and analysis. Methodological reviews were performed by 2 orthopaedic surgeons with advanced research degrees. Following this, 2 clinical experts reviewed the articles to rate the clinical impact or value of each study. Methodological and clinical reviews were compiled, and a final recommendation on impact to change clinical practice was made based on both review components at the consensus of the panel. RESULTS: The first study reviewed investigated the impact of physical therapy on function following supracondylar humeral fractures in children. The reviewers deemed the superiority study to of sound design, and conclusions appropriate for the methodology used and clinical findings. The results do not compel a recommendation to change clinical practice. The second study investigated the impact of Botulinum Toxin A with casting for the treatment of idiopathic toe-walking in children. Although of relatively sound design, the sample size was too small to appropriately perform some statistical comparisons. No recommendation to change clinical practice could be made. CONCLUSION: Both RCTs reviewed were superiority studies with a negative result. No recommendation to change clinical practice could be made. SIGNIFICANCE: Interpretation of superiority studies with nonsignificant findings must be done with caution. The findings of both of these RCTs highlight the need for more noninferiority trials in the pediatric orthopaedic literature in order to appropriately demonstrate no difference between 2 treatment options.
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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 | 0.081 | 0.404 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.011 |
| Bibliometrics | 0.026 | 0.014 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.015 | 0.008 |
| Research integrity | 0.020 | 0.018 |
| Insufficient payload (model declined to judge) | 0.024 | 0.010 |
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".