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Record W2022719586 · doi:10.1097/mog.0000000000000037

Risk factors and management of osteoporosis in inflammatory bowel disease

2014· review· en· W2022719586 on OpenAlexaff
Laura E. Targownik, Çharles N. Bernstein, William D. Leslie

Bibliographic record

VenueCurrent Opinion in Gastroenterology · 2014
Typereview
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineOsteoporosisUlcerative colitisInflammatory bowel diseaseDiseaseBone mineralCrohn's diseaseInternal medicinePopulationFRAXBone densityOsteoporotic fractureEnvironmental health

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.396
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.056
GPT teacher head0.389
Teacher spread0.333 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreReview

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".

Quick stats

Citations61
Published2014
Admission routes1
Has abstractyes

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