P831 Clinical factors associated with severity in patients with Inflammatory Bowel Disease in Brazil (On Behalf of GEDIIB)
Bibliographic record
Abstract
Abstract Background Brazil has shown an increase in Inflammatory Bowel Disease (IBD) cases. GEDIIB (Brazilian Organization of Crohn’s Disease and Colitis) established a data platform to create a national registry of IBD patients. The study aimed to characterize the profile of IBD patients and identify clinical factors associated with IBD severity. Methods A cohort study was conducted between Jul/20 and Aug/22. Data obtained from medical records and/or directly from patients were registered via REDCap. Local institutional review boards approved the study protocol. We designed a population-based risk model aimed at stratifying severe disease based on one or more outcome variables: previous hospitalization, surgery, and biologics. Univariate and bivariate analyses and Poisson modeling were used. Results A total of 1,179 patients were included: 600 (51%) with ulcerative colitis (UC), 568 (48%) with Crohn’s Disease (CD), and 11 (0.9%) with indeterminate colitis. The mean age was 34.4±14.7y, 59% female, 73% Caucasian, and 85.3% non-smoker. Regarding the initial symptoms, 42% presented diarrhea, 38% abdominal pain, and 20% weight loss. The age of IBD symptom onset ranged from 1-87 years (32.3±14.4). According to the Montreal classification of CD, A1: 5%, A2: 63%, A3: 32%; L1: 29.7%, L2: 14.3%, L3: 41.2%, B1: 32%, B2: 26.7%, B3: 11.3%; perianal 15.5%. In UC, 46.3% presented pancolitis and 30% left-sided colitis. Only 3.9% were malnourished, 30.9% were overweight, and 18% were obese. The main extraintestinal manifestations were rheumatologic (21%). Regarding medical treatment, 68.1% of the patients received biologics (45% Infliximab, 29% Adalimumab, 9.7% Vedolizumab, and 8.8% Ustekinumab), 67% salicylates, 47.6% immunosuppressors, and 0.8% Tofacitinib. Of those submitted to surgery (34.1%, n=439), 54% were elective versus 46% urgent; most procedures (80%) were open/laparotomy, while 20% were laparoscopic. Of those, 8.5% were colectomy. The presence of CD, pancolitis, the absence of (isolated) proctitis, younger age (<20 years), rheumatologic manifestations, and no history of smoking were found to be independent risk factors. Conclusion This is the first epidemiological study using the national patient registry organized by GEDIIB. The profile of patients with severe disease is consistent with the data in the literature, characterized by younger age, greater extent of disease, and extraintestinal manifestations. Further epidemiological studies should be encouraged to guide national policies aimed at the early diagnosis and treatment of IBD.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".