A54 DIETARY COMPONENTS ARE ASSOCIATED WITH FECAL CALPROTECTIN IN ULCERATIVE COLITIS
Notice bibliographique
Résumé
Abstract Background Ulcerative colitis (UC) is thought to arise from dysregulated immune responses due to intestinal dysbiosis and altered epithelial barrier function. Dietary components may affect the gut microbiome and contribute to either inflammation or its resolution. The relationship between diet and disease activity in UC warrants further investigation. Aims This prospective cohort study explored the relationship between dietary components, and markers of disease activity: fecal calprotectin (FCP) and partial Mayo score (PMS) in patients with UC. Methods 40 participants were recruited from University of Calgary IBD clinics. Study staff obtained two 24-hour diet recalls using the validated automated self administered (ASA)-24 and captured PMS at baseline (T1) and follow-up at week 12 (T2). FCP samples were collected at T1 and T2. Diet variables included adjusted macro/micronutrients (n=44), food groups (n=36) and the validated Canadian healthy eating index-2009 (CHEI) where higher scores reflect healthier intake. CHEI captures intake of dark green and orange foods (DGO) and moderation scoring (MOD) of saturated fats (SF), sodium and added sugars. Higher CHEI scores result from increased intake of DGO and lower intake of SF, sodium and added sugars (higher MOD score). Associations with outcome variables were examined at T1 and T2 individually and across both timepoints (BT). Mixed effect logistic regression models identified relationships between dietary variables, FCP and PMS. Models were adjusted for age, sex, BMI, medications, probiotics, and for repeated measures in both timepoint analyses. Results A positive association was identified between FCP as a continuous variable and SF (T1:Coef=0.22, p_adj=0.02) and a negative association identified between FCP with citrus/melon/berries (BT:Coef=-1.01, p_adj =0.04), total sugars (BT:Coef=-0.06, p_adj=0.025) and HEI (BT:Coef=-0.13, p_adj =0.06 and T1 coef=-0.18, p_adj =7.0 e-5). FCP increased as SF (-0.30,p_adj=0.01), DGO (-0.60, p_adj=0.02), and MOD (-0.21, p_adj=0.02) scores decreased. The presence of inflammation (as a binary variable, FCP >250) was negatively associated with higher fiber intake (BT: Odds Ratio (OR)= 0.016, CI(0.001,0.40) p_adj=0.08). For PMS as a continuous variable, HEI had a negative association with PMS (T2: -0.05, p_adj=0.06). With PMS as a discrete score (remission=PMS<2) there was no significant association with any diet components. Conclusions This study suggests that a healthier diet, both in overall pattern and specific dietary components, was associated with lower FCP and PMS. Our findings related to SF, citrus/melons/berries, and DGO parallel the IOIBD dietary guidelines. Future research should explore through controlled intervention studies whether modifying dietary patterns and components independently reduces disease activity. Funding Agencies Crohn’s and Colitis Foundation
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».