Factors affecting management of children’s low-risk distal radius fractures in the emergency department: a population-based retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Ten randomized controlled trials over the last 2 decades support treating low-risk pediatric distal radius fractures with removable immobilization and without physician follow-up. We aimed to determine the proportion of these fractures being treated without physician follow-up and to determine whether different hospital and physician types are treating these injuries differently. METHODS: We conducted a retrospective population-based cohort study using ICES data. We included children aged 2-14 years (2-12 yr for girls and 2-14 yr for boys) with distal radius fractures having had no reduction or operation within a 6-week period, and who received treatment in Ontario emergency departments from 2003 to 2015. Proportions of patients receiving orthopedic, primary care and no follow-up were determined. Multivariable log-binomial regression was used to quantify associations between hospital and physician type and management. RESULTS: = 14 742) fractures were treated without physician follow-up, with the proportion of physician follow-up consistent across all years of the study. Treatment in a small hospital emergency department (risk ratio [RR] 1.86, 95% confidence interval [CI] 1.72-2.01), treatment by a pediatrician (RR 1.22, 95% CI 1.11-1.34) or treatment by a subspecialty pediatric emergency medicine-trained physician (RR 1.73, 95% CI 1.56-1.92) were most likely to result in no follow-up. INTERPRETATION: While small hospital emergency departments, pediatricians and pediatric emergency medicine specialists were most likely to manage low-risk distal radius fractures without follow-up, the majority of these fractures in Ontario were not managed according to the latest research evidence. Canadian guidelines are required to improve care of these fractures and to reduce the substantial overutilization of physician resources we observed.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".