Bone health in patients with inflammatory bowel disease
Bibliographic record
Abstract
Patients with inflammatory bowel disease (IBD) are prone to reduced bone mineral density and elevated overall fracture risk. Osteopenia affects up to 40% of patients with IBD (high regional variability). Besides disease activity, IBD specialists must consider possible side effects of medication and the presence of associated diseases and extraintestinal manifestations. Osteopenia and osteoporosis remain frequent problems in patients with IBD and are often underestimated because of widely differing screening and treatment practices. Malnutrition, chronic intestinal inflammation and corticosteroid intake are the major pathophysiological factors contributing to osteoporosis. Patients with IBD are screened for osteoporosis using dual-energy X-ray absorptiometry (DXA), which is recommended for all patients with a prolonged disease course of more than three months, with repeated corticosteroid administration, aged >40 years with a high FRAX risk score or aged <40 years with multiple risk factors. From a therapeutic perspective, besides good disease control, vitamin D supplementation and glucocorticoid sparing, several specific osteological options are available: bisphosphonates, receptor activator of nuclear factor kappa-B ligand (RANKL) inhibitors (denosumab), parathyroid hormone (PTH) analogues and selective estrogen receptor modulators. This review provides an overview of the pathophysiology, diagnosis, prevention and treatment of IBD-associated bone loss.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".