P-072 Evolution of Clinical Behavior in Crohn’s Disease
Bibliographic record
Abstract
Definition of Crohn’s disease (CD) phenotypes is important to define care strategies for the patients. The aim of this study was to evaluate the patient’s long-term evolution of their phenotypes, determining the main predictive factors for this evolution in a cohort with CD in southern Brazil. Data of 179 patients were retrospectively collected from a prospective database. Montreal Classification was used. Kaplan-Meier curve was used to estimate the cumulative probability of developing a complication. Cox’s Regression for multivariate analyses was applied. Research approved by the Institutional Review Board. Female: 54.2%. At diagnosis: mean age: 32.7 year (±13.7); phenotype distribution at diagnosis: age A1 = 11.2%, A2 = 60.3%, A3 = 28.5%; location: L1 = 23.5%, L2 = 26.8%, L3 = 37.4%, L4 = 2.8%, L1L4 = 6.7%, L2L4 = 1.7%, L3L4 = 1.1%; behavior: B1 = 60.3%, B2 = 26.8%, B3 = 12.9%; median follow-up time: 73.0 months (32.5–118.7). Change in behavior: from B1 to B2 26.8% and to B3 2.8%. Behavior at the end of follow-up period: inflammatory 42.5%, stricturing 43.0%, penetrating 14.5%. Perianal disease: 46.4%. Cumulative probability of being complication-free in 5, 10 and 20 years was 88.4%, 65% and 47.3%, respectively. Significant associations after multivariate analysis with complicated disease: localized disease in L1 and L4, age at diagnosis less than 17 year; stricturing: localized disease in L1 and L4, use of biological therapy, granuloma; perianal disease: age at diagnosis less than 17 years, use of immunosuppressive therapy. Clinical behavior changed over time, change to stricturing pattern was the most frequent complication; penetrating pattern remained stable throughout the patients’ disease. Age at diagnosis and location of the disease were determinants of clinical behavior modification.
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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 | 0.003 |
| 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) | 0.003 | 0.001 |
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".