Pediatric Forefoot Fractures
Bibliographic record
Abstract
BACKGROUND: Forefoot fractures account for 6% to 10% of fractures in children, and although the majority heals with supportive treatment, complications may lead to pain and disability. No previous study in children has evaluated complication risk in the emergency department based on initial assessment characteristics. STUDY OBJECTIVES: The study aim was to identify the radiological and clinical variables that increase the complication rate of pediatric forefoot fractures. This may help emergency physicians refer patients who require more thorough follow-up or surgical intervention. METHODS: We evaluated 497 forefoot fractures on initial presentation to a pediatric emergency department at the Children's Hospital at London Health Science Centre over a 6-year period. We collected variables such as degree of angulation, displacement, number of concurrent fractures, and demographic data such as age and sex. We then determined the variables associated with complications by reviewing each patient's chart. RESULTS: Overall, there was a 6.4% complication rate. Analysis identified sex as an important predictor of complications. Females, although representing approximately one third of the sample, represented nearly two thirds of the cases with complicated outcomes (P = 0.001; odds ratio [OR], 4.67). Increased number of fractures was also significant (P = 0.01; OR, 2.41) as was increasing age (P = 0.01; OR, 1.17) and patients who chose to return to the emergency department (P < 0.05; OR, 5.282). Lateral angulation/displacement and anteroposterior angulation/displacement were not associated with increased complications. CONCLUSION: Identifying features, such as female sex, increasing age, multiple fractures, and return to emergency departments for repeat visits, may help guide the emergency physician on whom to refer for specialized care.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".