Predictors of Osteochondral Fractures Following Patellar Dislocation in the Pediatric Emergency Department
Bibliographic record
Abstract
BACKGROUND: Patellar dislocations are frequently seen in the emergency department (ED). Almost all children with a reduced patellar dislocation will have a knee radiography, while only 10% have a fracture identified on x-ray. OBJECTIVE: The primary purpose of the study was to identify factors predicting osteochondral fractures among children with patellar dislocation reduced in the ED. METHODS: This was a retrospective cohort study of all children aged between 1 and 18 years old with patellar dislocation who needed a reduction in a tertiary care pediatric ED between 2019 and 2024. The primary outcome was the presence of a fracture identified by radiology (x-ray or MRI) during ED visit or follow-up at the orthopedic clinic. Multiple independent variables were evaluated as potential predictors. These were related to the patient (age, sex, previous patellar dislocation), the accident, and the physical examination before and after reduction, as well as finding at the follow-up at the orthopedic clinic. All charts were evaluated using a standardized form, and 10% were evaluated in duplicate to ensure interrater reliability. The primary analysis was the association between the independent variable and fracture using logistic regression. RESULTS: There was a total of 316 diagnoses of patellar luxation in 276 children with a median age of 14 years. Ninety-six children had their patellar dislocation reduced at the ED and were included in the study, of whom 19 (20%) had a fracture. Of all variables tested, only the persistence of knee swelling at orthopedic follow-up was associated with a higher risk of fracture (OR: 13.39; 95% CI: 1.70-105.32). CONCLUSION: Approximately 20% of children who needed a reduction in the ED for patellar dislocation had a fracture. Persistent knee swelling at follow-up is a potential predictor of fracture.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".