The Risk of Hip Fractures in Older Individuals With Diabetes
Bibliographic record
Abstract
OBJECTIVE: Compared with men and women without diabetes, individuals with type 2 diabetes have higher bone mineral density (BMD). However, they may still be at increased risk for hip fractures. Using population-based Ontario health care data, we compared the risk of hip fractures among men and women with and without diabetes. RESEARCH DESIGN AND METHODS: Using a retrospective cohort design, we identified Ontario residents aged > or =66 years with diabetes from a validated registry from 1994 to 1995 (n = 197,412) and followed them for their first hip fracture until 31 March 2003 (mean 6.1-year follow-up). Hip fracture rates were compared with those of age-matched Ontario residents without diabetes (n = 401,400), and results were stratified by sex and adjusted for age and other covariates. RESULTS: Compared with individuals without diabetes, individuals with diabetes had greater comorbidity, were less likely to have had a BMD test, and were more likely to be taking medications that increase risk of falling and decrease BMD. After adjusting for these differences and age, we found that diabetes increased fracture risk in both men (hazard ratio 1.18 [95% CI 1.12-1.24], P < 0.0001) and women (1.11 [1.08-1.15], P < 0.0001). CONCLUSIONS: Men and women with diabetes have a higher risk of hip fractures compared with individuals without diabetes. Further research to elucidate the mechanisms underlying this increased risk of fracture is needed, as well as increased attention to fracture prevention strategies in patients with diabetes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".