Factors Associated with Fistulizing Crohn’s Disease in Children at Diagnosis: A Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: Perianal manifestations are common at diagnosis of Crohn's Disease and include perianal fistulas, abscesses, fissures, and inflammatory anal skin tags. Perianal fistulizing Crohn's disease (PFCD), involving fistulas and abscesses, is associated with a poor prognosis in children.This study aimed to identify the factors associated with PFCD at diagnosis. Secondary aims were to: assess factors associated with the severity of PFCD according to the Van Assche score, characterize the prevalence of perianal Crohn's disease in a Canadian cohort, and evaluate its management at diagnosis. METHODS: We collected data from patients aged 4-18 years diagnosed with Crohn's disease between 2009 and 2021 at our IBD center who underwent perineal magnetic resonance imaging within three months of diagnosis. Perianal Crohn's disease was assessed clinically and through MRI results. RESULTS: Among 489 patients (57.9% male, median age 13.8 years), 229 (46.8%) had perianal Crohn's disease. Perianal fistulizing Crohn's disease was identified in 115 patients (23.5%), including 13.0% without any clinical signs. The median Van Assche score was 13.0 in patients with PFCD versus 2.0 in those without. Male sex, granulomas on intestinal biopsies, and anal fissures were associated with both the presence and increased severity of PFCD. CONCLUSION: This study emphasizes the importance of performing perianal MRI early at the diagnosis as occult perianal fistulizing Crohn's disease may be discovered. Male sex, granulomas on intestinal biopsies and anal fissures were associated both with the presence of PFCD and increased severity.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".