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Record W4407285686 · doi:10.1093/jcag/gwae059.189

A189 IMPACT OF PHYSICAL ACTIVITY AND MEDICATIONS ON BODY COMPOSITION DYNAMICS IN PEDIATRIC IBD PATIENTS: A PROSPECTIVE STUDY

2025· article· en· W4407285686 on OpenAlexaffabout
L Djani, Kathleen J. Orius, Nikita Neale, L Dehbidi Assadzadeh, Grace Tongue, F Huang, Xiaoling Yang, J Bouthot, Colette Deslandres, Prévost Jantchou

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2025
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversité LavalUniversité de Montréal
Fundersnot available
KeywordsMedicineProspective cohort studyComposition (language)Dynamics (music)PsychologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background Although inflammatory bowel disease (IBD) severity is associated with decreased body mass index (BMI) in pediatric patients, many of them gain weight during follow-up. Physical activity levels (PAL) are associated with lower BMI dynamics while overweight/obesity worsen health outcomes in children. Few studies have explored BMI evolution and its related factors in this population. Aims To investigate BMI dynamics in children with IBD from diagnosis to last follow-up and assess the impact of PAL, disease phenotype/activity, and medication on BMI changes. Methods Pediatric IBD patients prospectively completed the Canadian Health Measure Survey quarterly for one year to assess PAL and were classified into three groups based on PAL (sedentary, moderately active or extremely/vigorously active). Clinical disease activity was classified using physician global assessment, PUCAI and sPCDAI. BMI was assessed at each visit. Results A total of 256 patients (56% male, median age 14y [IQR (interquartile range): 13-16]) were included. At diagnosis, 56% were normal weight, 38% underweight, 5% overweight, and 2% obese. By the first visit, 74% were normal weight, 4% underweight, 17% overweight, and 5% obese. The median time from diagnosis to the first study visit was 29 months [IQR: 7-44] during which patients gained a mean of 2.97 (95% CI: 2.64;3.31) BMI points. The following factors were associated with BMI gain: disease duration (Pearson Coefficient Correlation [95% CI]:0.42 [0.31;0.51]), age at diagnosis (-0.13 [-0.25; -0.01]), BMI at diagnosis (-0.23 [-0.34; -0.11]), BMI z-scores at diagnosis (-0.32 [-0.42; -0.20]) and higher age at inclusion (0.20 [0.08;0.31]). In a multivariate logistic regression, we found that being underweight compared to normal weight (adjusted odds ratio (aOR) =0.15 [0.06; 0.39]) and exposition to anti-TNFα (aOR = (3.89 [1.17; 12.97]) were independently associated to the risk for overweight/obesity during follow-up. Conclusions We observed a 15% increase in overweight/obesity prevalence and a 34% decrease in underweight prevalence in patients over the studied interval. BMI gain was significantly linked to exposure to anti-TNFa, warranting further investigations. Table 1. Mean BMI Differences Between Diagnosis and First Study Visit Funding Agencies None

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)0.001
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 score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.356
Teacher spread0.345 · 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
Published2025
Admission routes2
Has abstractyes

Explore more

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