Risk of Recurrent Fracture: A Population-Based Study
Bibliographic record
Abstract
OBJECTIVES: To determine if children who sustain a fracture in childhood had an increased rate of fracture later in childhood or early adulthood. The a priori null hypothesis was that children who sustained a fracture would not have an increased rate of future fractures compared with children who did not sustain a fracture when controlling for important covariates. METHODS: This is a population-based retrospective cohort study using health care databases in Ontario. Approximately 2.5 million healthy children aged 0 to 15 years living in Ontario, Canada between April 1, 2003, and March 31, 2004, were included and followed for 7 years. The exposure was occurrence of any fracture during a 1-year baseline period. The main outcome was any fractures during a 7-year follow-up period. RESULTS: < .0001) during the follow-up period after adjustment for sex, rurality, history of previous fracture, and the occurrence of other injuries (head and soft-tissue). CONCLUSIONS: The occurrence of a fracture during childhood was associated with an increased rate of future fractures compared with children who did not suffer a fracture. Attempting to improve childhood bone health by targeting children who present to a fracture clinic with multiple fracture risk factors may be a useful strategy for secondary prevention of fractures and may have beneficial effects on long-term bone health.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".