Conservative versus Surgical Treatment of Pediatric Both-Bone Forearm Fractures: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Treatment of both-bone forearm fractures (BBFF) in skeletally immature patients includes surgical and conservative strategies; however, there is no literature-supported consensus on which provides optimal patient outcomes. This systematic review and meta-analysis compares the outcomes of surgical versus conservative treatment in the management of BBFF in skeletally immature patients. A search of Medline, Scopus, PubMed, and CENTRAL databases was performed from inception to August 2024. Studies included reported outcomes for BBFF treated surgically (intramedullary nailing, plating) or conservatively (casting) and were selected per PRISMA guidelines. Statistical analyses were conducted using DataParty, which utilizes Python 3.8.10. A total of 25 studies with 1187 patients (surgical: 837; conservative: 350) were included. Patients in the surgical group had a mean age of 8.59 years, while those treated conservatively averaged 10.92 years. The complication rate was higher in the conservative group (43%, 95% CI [0.33, 0.52]) compared to the surgical group (16%, 95% CI [0.07, 0.27]), with high heterogeneity observed in the surgical group (I² = 93%). The union rate was 100% in the conservative group and 99% in the surgical group, with minimal heterogeneity (I² = 0% and 13%, respectively). Excellent price grading was reported in 83% of cases managed conservatively (95% CI [0.73, 0.91]) and 77% of surgically treated cases (95% CI [0.59, 0.91]), with high heterogeneity (I² = 77% and 91%, respectively). In conclusion, surgical treatment of BBFF may reduce complication rates compared to conservative management. Future high-quality trials are warranted to further clarify management guidelines for pediatric BBFF.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.031 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".