P0604 Frequency and Analysis of Deep Remission in Patients with Ulcerative Colitis: A Single-Center Retrospective Study
Bibliographic record
Abstract
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).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".