Fractures are increased and bisphosphonate use decreased in individuals with insulin-dependent diabetes: a 10 year cohort study
Bibliographic record
Abstract
BACKGROUND: Individuals with diabetes have been found previously to be at increased risk of non-traumatic fracture. However, it is unclear if these individuals are being identified and treated for osteoporosis. METHODS: 7753 Canadians over 50 years of age were followed prospectively for 10 years. 606/7753 (7.8%) of had diabetes; 98 were insulin-dependent and 508 were not. Using a cox proportional hazards model, we assessed the association between diabetes status and incident non-traumatic fracture. Using logistic regression we identified factors associated with bisphosphonate use over the 10 year period of study. RESULTS: Mean (SD) age of participants was 66.7(9.4) years and 72% were female. Those with diabetes had higher BMD T-scores at baseline, with a mean (SD) femoral neck T-Score of -0.97 (1.06), compared to -1.24 (0.99) in the general cohort. The adjusted hazard ratio (HR) for incident non-traumatic fracture in individuals with insulin-dependent diabetes over the 10 year study period was 2.50 (95% confidence interval [CI] 1.60, 3.90; p < 0.001). Despite this increased fracture rate, individuals with diabetes (insulin-dependent or non-insulin-dependent) were less likely to be on bisphosphonate therapy at any point over 10 years of prospective follow up compared to other CaMos subjects (odds ratio [OR]: 0.59; 95% CI 0.46-0.75, p < 0.001). CONCLUSIONS: Despite the increased risk of non-traumatic fracture associated with insulin-dependent diabetes, we that found individuals with diabetes are less likely to be treated with a bisphosphonate than those without diabetes. These findings point to a possible care gap in the treatment of non-traumatic fractures in individuals with diabetes in Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".