Fragility fracture identifies patients at imminent risk for subsequent fracture: real-world retrospective database study in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: The secondary fracture prevention gap in the osteoporosis field has been previously described as a 'crisis'. Closing this gap is increasingly important in the context of accumulating evidence showing that an incident fragility fracture is associated with an increased risk of subsequent fracture within 1-2 years, known as imminent fracture risk. The objective of this study was to use health services data to characterize the time between index fragility fractures occurring at different osteoporotic sites and subsequent fractures. METHODS: This retrospective observational study used de-identified health services data from the publicly funded healthcare system in Ontario, the largest province of Canada. Patients aged > 65 with an index fragility fracture occurring between 2011 and 2015 were identified from the ICES Data Repository using International Classification of Diseases (ICD)-10 codes. We examined median time to subsequent fragility fractures for osteoporotic fracture sites until the end of follow-up (2017). BMD assessment and use of osteoporosis therapies following index fracture were also characterized. RESULTS: Among 115,776 patients with an index fragility fracture, 17.8% incurred a second fragility fracture. Median time between index and second fracture occurring at any site was 555 days (interquartile range: 236-955). For each index fracture site examined, median time from index to second fracture was < 2 years. The proportion of patients with BMD assessment was 10.3% ≤1 year prior to and 16.4% ≤1 year post index fracture. The proportion of patients receiving osteoporosis therapy was 29.8% ≤1 year prior, 34.6% ≤1 year post, and 25.9% > 3 years post index fracture. CONCLUSIONS: This cohort of Canadian patients aged > 65 years who experienced a fragility fracture at any site are at imminent risk of experiencing subsequent fracture within the next 2 years and should be proactively assessed and treated.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.010 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".