A Prospective Study of Pediatric Hand Fractures and Review of the Literature
Bibliographic record
Abstract
OBJECTIVE: Hand fractures represent a leading cause of morbidity in children. However, little information exists correlating the mechanisms and environment of injury with outcomes and treatments. We examine the demographics, etiology, anatomic location, mechanism, and management of pediatric hand fractures in our center's hand unit. METHODS: We conducted a prospective observational study on all children with acute hand fractures evaluated in the Plastic Surgery Emergency Clinic during a 3-month period in 2010. Data pertaining to demographics, referral patterns, injury pattern, clinical outcomes, and other factors related to hand fractures were then analyzed and interpreted. RESULTS: Most children were referred by our institution's emergency department. More than 60% were boys, and nearly half were between 10 and 15 years old. The right and left hands were injured at equal rates. Most of the injuries (90%) occurred in the afternoon or evening. More than 85% occurred in urban, rather than rural, environments. Crush injuries were the leading cause in toddlers, whereas sports-related injuries became the major cause of injury in older groups. Proximal phalanges were the most common bone injured, and the fifth digit was the most commonly injured digit. More than 80% of the fractures were managed nonsurgically. CONCLUSIONS: The pattern of pediatric hand fracture in different age groups is highlighted in this article. The observations from this study will hopefully encourage further review with a larger cohort and a focus on preventative measures for pediatric hand fractures.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".