Frailty and Risk of Fractures in Patients With Type 2 Diabetes
Bibliographic record
Abstract
OBJECTIVE We aimed to explore whether frailty was associated with fracture risk and whether frailty could modify the propensity of type 2 diabetes toward increased risk of fractures. RESEARCH DESIGN AND METHODS Data were from a prospective cohort study. Our primary outcome was time to the first incident clinical fragility fracture; secondary outcomes included time to hip fracture and to clinical spine fracture. Frailty status was measured by a Frailty Index (FI) of deficit accumulation. The Cox model incorporating an interaction term (frailty × diabetes) was used for analyses. RESULTS The analysis included 3,149 (70% women) participants; 138 (60% women) had diabetes. Higher bone mineral density and FI were observed in participants with diabetes compared with control subjects. A significant relationship between the FI and the risk of incident fragility fractures was found, with a hazard ratio (HR) of 1.02 (95% CI 1.01–1.03) and 1.19 (95% CI 1.10–1.33) for per-0.01 and per-0.10 FI increase, respectively. The interaction was also statistically significant (P = 0.018). The HR for per-0.1 increase in the FI was 1.33 for participants with diabetes and 1.19 for those without diabetes if combining the estimate for the FI itself with the estimate from the interaction term. No evidence of interaction between frailty and diabetes was found for risk of hip and clinical spine fractures. CONCLUSIONS Participants with type 2 diabetes were significantly frailer than individuals without diabetes. Frailty increases the risk of fragility fracture and enhances the effect of diabetes on fragility fractures. Particular attention should be paid to diabetes as a risk factor for fragility fractures in those who are frail.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".