Risk factors and management of osteoporosis in inflammatory bowel disease
Bibliographic record
Abstract
PURPOSE OF REVIEW: To provide a synopsis on established and new research evaluating bone disease in patients with inflammatory bowel disease (IBD). RECENT FINDINGS: Persons with IBD, including Crohn's disease and ulcerative colitis are believed to be at high risk for osteoporosis and fracture. As osteoporosis is clinically silent and persons with IBD are not universally screened, the burden of bone disease in IBD has been difficult to accurately assess. It is also unclear whether bone disease is due to inflammatory activity, medication use, poor nutrient intake/absorption, or body habitus characteristics. Recent studies using population-wide databases of bone mineral density (BMD) analyses suggest that Crohn's disease is responsible for a small effect on BMD after adjusting for other risk factors for low BMD, whereas ulcerative colitis does not appear to confer an independent risk. Furthermore, IBD does not appear to be a risk for overall fracture once controlling for factors which are associated with both IBD and fracture risk. The ability to assess BMD on incidentally performed computed tomography scans may allow detection of low BMD in IBD patients. SUMMARY: Although reduced BMD and fracture are more common in persons with IBD, the precise burden is not well characterized. Also, the relative impact of IBD-associated factors and IBD-specific inflammation on bone health is still uncertain.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".