Surgical and Conservative Management are Both Effective for Pediatric Both Bone Forearm Fractures: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
< .001). Despite this, union rates were 100% in both groups. Both conservative and surgical management of pediatric BBFFs yielded high union rates and excellent functional outcomes. Surgical treatment demonstrated lower complication and redisplacement rates but was associated with a longer time to union. These findings suggest that surgical treatment may be preferable for reducing redisplacement and the need for additional interventions in older children with reduced remodeling potential. Key Concepts: (1)Both conservative and surgical treatment of pediatric both bone forearm fractures result in excellent functional outcomes and 100% union rates, which supports the effectiveness of both approaches in skeletally immature patients.(2)Surgical management is associated with significantly lower rates of redisplacement (3% vs 26%) as well as lower need for additional interventions (5% vs 14%) compared to conservative treatment, highlighting its benefit in maintaining fracture stability.(3)Although the time to union was longer with surgical treatment (8.26 vs 6.50 weeks), this did not negatively impact final functional outcomes.(4)Age-related remodeling potential remains a key determinant in treatment selection, with conservative treatment more suitable for younger children and surgical treatment preferable in older children with diminished remodeling capacity. Level of Evidence: III.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.017 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".