Clinical Phenotype and Disease Course of Inflammatory Bowel Disease in Iran: Results of the Iranian Registry of Crohn’s and Colitis (IRCC)
Bibliographic record
Abstract
BACKGROUND: Data on the epidemiology of inflammatory bowel disease (IBD) in the Middle East are scarce. We aimed to describe the clinical phenotype, disease course, and medication usage of IBD cases from Iran in the Middle East. METHODS: We conducted a cross-sectional study of registered IBD patients in the Iranian Registry of Crohn's and Colitis (IRCC) from 2017 until 2022. We collected information on demographic characteristics, past medical history, family history, disease extent and location, extra-intestinal manifestations, IBD medications, and activity using the IBD-control-8 questionnaire and the Manitoba IBD index, admissions history, history of colon cancer, and IBD-related surgeries. RESULTS: In total, 9746 patients with ulcerative colitis (UC) (n=7793), and Crohn's disease (CD) (n=1953) were reported. The UC to CD ratio was 3.99. The median age at diagnosis was 29.2 (IQR: 22.6,37.6) and 27.6 (IQR: 20.6,37.6) for patients with UC and CD, respectively. The male-to-female ratio was 1.28 in CD patients. A positive family history was observed in 17.9% of UC patients. The majority of UC patients had pancolitis (47%). Ileocolonic involvement was the most common type of involvement in CD patients (43.7%), and the prevalence of stricturing behavior was 4.6%. A prevalence of 0.3% was observed for colorectal cancer among patients with UC. Moreover,15.2% of UC patients and 38.4% of CD patients had been treated with anti-tumor necrosis factor (anti-TNF). CONCLUSION: In this national registry-based study, there are significant differences in some clinical phenotypes such as the prevalence of extra-intestinal manifestations and treatment strategies such as biological use in different geographical locations.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".