Incidence of secondary interventions after early spica casting for diaphyseal femur fractures in young children
Bibliographic record
Abstract
BACKGROUND: Children aged 6 months to 5 years with diaphyseal femur fractures are typically treated with spica casting, as recommended by the American Association of Orthopaedic Surgeons clinical practice guideline. We aimed to determine the incidence of secondary interventions after early spica casting for femur fractures in children aged 6 years or less. METHODS: This was a retrospective cohort study of patients aged 6 years or less with diaphyseal femur fractures treated with early spica casting at a single Canadian tertiary care, level 1 trauma pediatric centre between January 2005 and May 2015. RESULTS: A total of 246 patients were included (190 boys [77.2%] and 56 girls [22.8%] with a mean age of 2.28 yr [standard deviation (SD) 1.35 yr]). Nine patients (3.7%) required early secondary interventions (cast wedging in 8 and flexible intramedullary nail fixation in 1). At last follow-up, 51 patients (20.7%) had clinically measurable limb length discrepancy (LLD) (mean 9.4 mm [SD 3-25 mm]), and 1 patient (0.4%) had mild clinical valgus deformity. Older, heavier patients with initial fracture shortening of 20 mm or more had a higher likelihood of developing a clinically measurable LLD. No patient required surgical intervention after fracture union to correct acquired LLD or angular deformity. CONCLUSION: Early spica casting for diaphyseal femoral fractures in children aged 6 years or younger had a low rate of complications and return to the operating room, Although 21% of patients had a clinically measurable LLD at last follow-up, no patient required secondary intervention after fracture union to correct acquired LLD or angular deformity. These findings have relevance for the Canadian health care system, especially during the COVID-19 pandemic.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".