Inflammatory bowel disease and the risk of fracture after controlling for FRAX
Bibliographic record
Abstract
Subjects with inflammatory bowel disease (IBD) are at increased risk for hip and other major osteoporotic fractures. However, previous analyses have not fully accounted for differences in bone mineral density (BMD) and other clinical factors that affect the risk of fracture. The World Health Organization Fracture Risk Assessment tool (FRAX) can be used to predict the 10-year fracture risk from BMD and clinical risk factors. A population-based database containing clinical information on all IBD subjects in the province of Manitoba, Canada, was linked with the Manitoba Bone Mineral Density Database, which contains results of all dual X-ray absorptiometry (DXA) scans in the province. FRAX probabilities were calculated for all subjects aged 50 years or more undergoing baseline DXA testing. Subjects were followed for occurrence of major osteoporotic fractures (MOF; hip, clinical spine, wrist, humerus). Cox proportional hazards models were used to determine whether IBD was independently predictive of MOF or hip fracture. After controlling for FRAX fracture probability computed with BMD, IBD was not associated with a significantly increased risk for MOF (hazard ratio [HR] = 1.12, 95% confidence interval [CI], 0.83-1.55) but was associated with an increased risk for hip fracture (HR = 2.14; 95% CI, 1.26-3.65). The addition of femoral neck T-score to FRAX probability without knowledge of BMD had a negligible effect on the estimated HRs for IBD, suggesting that IBD mediates any effect on fracture risk independently of femoral neck BMD. After controlling for FRAX probability, subjects with IBD are not at an increased risk for overall MOF, but may be at increased risk of hip fracture.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".