Bibliographic record
Abstract
PURPOSE OF REVIEW: Type 1 (T1D) and 2 diabetes (T2D) are associated with increased risk of fracture independent of bone mineral density (BMD). Fracture risk prediction tools can identify individuals at highest risk, and therefore, most likely to benefit from antifracture therapy. This review summarizes recent advances in fracture prediction tools as applied to individuals with diabetes. RECENT FINDINGS: The Fracture Risk Assessment (FRAX) tool, Garvan Fracture Risk Calculator (FRC), and QFracture tool are validated tools for fracture risk prediction. FRAX is most widely used internationally, and considers T1D (but not T2D) under secondary osteoporosis disorders. FRAX underestimates fracture risk in both T1D and T2D. Trabecular bone score and other adjustments for T2D-associated risk improve FRAX-based estimations. Similar adjustments for T1D are not identified. Garvan FRC does not incorporate diabetes as an input but does includes falls. Garvan FRC slightly underestimates osteoporotic fracture risk in women with diabetes. QFracture incorporates both T1D and T2D and falls as input variables, but has not been directly validated in individuals with diabetes. SUMMARY: Further research is needed to validate and compare available fracture prediction tools and their performance in individuals with diabetes.
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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) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.003 |
| 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".