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Record W4391873550 · doi:10.1093/jcag/gwad061.243

A243 BONE MINERAL DENSITY AND DIETARY BONE NUTRIENTS DIFFER IN PATIENTS WITH CROHN'S DISEASE STRICTURES

2024· article· en· W4391873550 on OpenAlexaff
A Macci, Jawad Basit, Rachel E. Klassen, Ryan E. Rosentreter, Kaina Bindra, Brendan Cord Lethebe, Steven K. Boyd, Emma O. Billington, M Raman, Lauren A. Burt, Cathy Lu

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsAlberta Health ServicesUniversity of Calgary
Fundersnot available
KeywordsBone mineralCrohn's diseaseMedicineDiseaseNutrientInternal medicineGastroenterologyDentistryOsteoporosisBiology

Abstract

fetched live from OpenAlex

Abstract Background Crohn’s disease (CD) phenotypes include inflammatory (non-stricture) and stricture behaviours. Strictures are bowel narrowing’s that may lead to obstructions and subsequent dietary restrictions to prevent blockages. Bone mineral density (BMD) in CD is affected by many factors including corticosteroid use, CD itself, but also dietary changes. Clinical gold standard for measuring BMD is by dual x-ray absorptiometry (DXA) scans. High-resolution peripheral quantitative computed tomography (HR-pQCT), a more precise imaging modality assesses volumetric BMD, bone geometry and bone microarchitecture. We aim to compare dietary intake, and bone quality in both stricture and non-stricture CD. Aims To identify nutritional patterns, bone quality differences and deficiencies between two subtypes of CD; including energy intake, dietary components and/or micronutrients Methods Individuals (≥55 years old) with ileal CD strictures (fixed, angulated bowel or thickened bowel with pre-stenotic dilation on diagnostic imaging), or inflammatory CD were prospectively recruited. Patients with short gut, celiac disease, dysphagia history were excluded. All patients completed DXA hip and spine scans and HR-pQCT radius and tibia scans. Dietary assessment questionnaires (Automated Self-Administered 24-hour Dietary Assessment Tool (ASA24), and Diet History Questionnaire III for food frequency over the past year were completed. Results 56 (27 inflammatory (48% female, mean age 64.2, BMI 28.7, 16 years CD duration) and 29 strictures (45% female, mean age 65.9, BMI 27.3, 25 years CD duration, 15 (51.7%) prior bowel resection) were included. 31/56 (55.4%) patients were on biologics and 11 (19.5%) had past corticosteroid exposure. DXA-based BMD for stricture versus non-stricture CD patients was not significantly different at the hip or spine. However, HR-pQCT-based radial total BMD (p=0.03), cortical thickness (p=0.01) and cortical area (p=0.04) were lower in stricture than non-stricture patients.11 (7 stricture, 4 inflammatory) patients with past steroids consumed more dairy (p=0.01), vitamin D (p = 0.04), and calcium (p=0.03) than other CD patients. Stricture patients had significantly less consumption of vitamin K (p=0.001), vegetables (p=0.02), calcium (p=0.03), and dairy (p=0.03). Conclusions Patients with CD strictures have lower BMD and cortical bone quality at the radius than those without strictures. Patients with CD strictures also consume significantly less vitamin K, calcium, and dairy, all vital dietary components to prevent OP, compared to non-stricture patients. Overall, the skeletal fracture risk is likely much greater in CD patients with strictures than without, due to greater inherent bone fragility, and less consumption of key nutrition building blocks of bones. Funding Agencies Koopmans Memorial Research Fund

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.003
GPT teacher head0.181
Teacher spread0.178 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2024
Admission routes1
Has abstractyes

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