P0604 Frequency and Analysis of Deep Remission in Patients with Ulcerative Colitis: A Single-Center Retrospective Study
Notice bibliographique
Résumé
Abstract Background Ulcerative Colitis (UC) is an inflammatory bowel disease affecting the colon and rectum, marked by periods of exacerbation and remission. Achieving deep remission is characterized by the absence of symptoms, normalized inflammatory markers, and endoscopic healing, which is linked to an improved long-term outcome. However, identifying the factors that contribute to deep remission remain important due to the variability in treatment responses and clinical presentations. The objective of this study was to assess the frequency of deep remission in patients with UC and to analyze the demographic and clinical factors associated with achieving this level of remission. Methods A retrospective study of 94 UC patients at the IBD Clinic of the General Hospital of Mexico analyzed medical records to assess demographic and clinical variables, including age, gender, disease extent, age at diagnosis, extraintestinal manifestations (EIMs), and treatments. Disease severity was evaluated using the Truelove and Witts scale (clinical), the Mayo sub-score (endoscopic), and the Riley index (histological). Patients were classified as being in deep remission if they achieved clinical, endoscopic, and histological remission, with normalized biochemical markers (C-reactive protein and fecal calprotectin). Statistical analyses, including chi-square tests and T-tests, were performed using SPSS version 29. Results Among the 94 patients studied, 18 (19.1%) achieved deep remission. In terms of gender, 38.9% of patients with deep remission were male and 61.1% were female, with no significant differences compared to patients without deep remission (p = 0.425). The mean age of patients with deep remission was higher (46.11 ± 13.26 years) compared to those without deep remission (40.66 ± 12.55 years), though this difference was not statistically significant (p = 0.091). Age at diagnosis was similar between both groups (35.83 ± 14.04 years vs. 34.76 ± 12.23 years, p = 0.785). Most patients in both groups were classified as E3 according to the Montreal classification, with no significant differences (p = 0.774). The use of conventional treatment was similar in both groups (77.7% vs. 64.4%, p = 0.423), while biological therapy was more common in patients without deep remission (35.5% vs. 22.2%, p = 0.217). Extraintestinal manifestations were more common in patients with deep remission (38.9% vs. 26.3%, p = 0.306). Conclusion In this study, 19.1% of patients with UC achieved deep remission. No significant differences were found in demographic or clinical factors. These results suggest that the factors evaluated were not significantly associated with deep remission in this cohort, underscoring the need to explore other potential determinants of remission in UC. References 1.Sands BE, Peyrin-Biroulet L, Loftus EV, Danese S, Colombel JF, Török HP, et al. Vedolizumab versus Adalimumab for Moderate-to-Severe Ulcerative Colitis. N Engl J Med. 2019;381(13):1215–26. 2.Turner D, Ricciuto A, Lewis A, D’Amico F, Dhaliwal J, Griffiths AM, et al. STRIDE-II: An Update on the Selecting Therapeutic Targets in Inflammatory Bowel Disease (IBD) Consensus Guidelines from the International Organization for the Study of IBD (IOIBD). J Crohns Colitis. 2021;15(6):881–93. 3.Dignass A, Eliakim R, Magro F, Maaser C, Chowers Y, Geboes K, et al. Second European Evidence-Based Consensus on the Diagnosis and Management of Ulcerative Colitis Part 2: Current Management. J Crohns Colitis. 2012;6(10):991–1030. 4.Dulai PS, Singh S, Casteele NV, Boland BS, Jairath V, Feagan BG, et al. Development and Validation of a Novel Clinical Scoring Tool to Predict Outcomes with Biological Therapy in Patients with Ulcerative Colitis. Aliment Pharmacol Ther. 2018;47(5):714–22. 5. Lichtenstein GR, Loftus EV, Isaacs KL, Regueiro MD, Gerson LB, Sands BE. ACG Clinical Guideline: Management of Crohn’s Disease in Adults. Am J Gastroenterol. 2018;113(4):481–517. 6.Harbord M, Eliakim R, Bettenworth D, Karmiris K, Katsanos KH, Kopylov U, et al. Third European Evidence-based Consensus on Diagnosis and Management of Ulcerative Colitis. Part 2: Current Management. J Crohns Colitis. 2017;11(7):769–84. 7.Colombel JF, Narula N, Peyrin-Biroulet L. Management Strategies to Improve Outcomes of Patients with Inflammatory Bowel Diseases. Gastroenterology. 2017;152(2):351–61. 8.Hanauer SB, Sandborn WJ, Lichtenstein GR, Rubin DT. The Management of Ulcerative Colitis: Current Treatment Approaches. Clin Gastroenterol Hepatol (2005).
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) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».