Association Between Severity of Musculoskeletal Injury and Risk of Subsequent Injury in Children and Adolescents on the Basis of Parental Recall
Bibliographic record
Abstract
OBJECTIVES: To describe the frequency of subsequent injuries in children who were seen at an emergency department (ED) for a musculoskeletal injury and to explore factors associated with sustaining a subsequent injury within a year. DESIGN: This was a prospective cohort study of children aged 1 through 17 years who sought care at an ED for an injury. Subsequent injuries were assessed through telephone interviews. SETTING: Subjects were recruited from a national database of childhood injury after they presented to a hospital ED at 1 of the 2 pediatric trauma centers in Montreal, Quebec. PATIENTS/ PARTICIPANTS: A consecutive sample of 7640 children aged 1 through 17 years who sought care for a fracture or a soft-tissue injury to an arm or a leg; 6182 completed both telephone interviews (80.9% response rate). Main Exposure Having a more severe injury was defined in 2 ways: (1) fracture of a limb or (2) injury that required follow-up or admission. Main Outcome Measure Having a subsequent injury during 12-month follow-up. RESULTS: Subjects with an index fracture were at lower risk of subsequent injury than were those with a soft-tissue injury (13.5% compared with 17.7%; adjusted odds ratio, 0.74; 95% confidence interval, 0.63-0.87). Subjects whose injury needed a follow-up were also at lower risk of subsequent injury than those whose injury was treated only in the ED (17.7% compared with 14.3%; adjusted odds ratio, 0.79; 95% confidence interval, 0.67-0.93) as were those who were admitted (17.7% compared with 8.7%; adjusted odds ratio, 0.51; 95% confidence interval, 0.26-0.99). CONCLUSIONS: Having had a severe musculoskeletal injury may be associated with a decreased risk of subsequent injury in children and adolescents. A possible explanation could be reduced exposure to risk.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".