The Impact of Integrating Pelvic Magnetic Resonance Imaging at Diagnosis on Early Detection of Perianal Crohn's Disease in Pediatrics
Bibliographic record
Abstract
INTRODUCTION: Perianal Crohn's disease (CD) can be a severe manifestation of pediatric CD. Earlier detection may alter outcomes. The aim of this study was to determine if performing pelvic magnetic resonance imaging (MRI) on newly diagnosed pediatric patients with CD would identify asymptomatic perianal CD and lead to earlier biologic use and less perianal surgery. METHODS: Patients were prospectively enrolled into the Edmonton Pediatric Inflammatory Bowel Disease Clinic registry (baseline pelvic MRI since 2018). A retrospective review (2018-2023) was performed. A blinded radiologist re-read the positive MRIs using St. James and Parks criteria. RESULTS: One hundred thirty-nine patients were included (median age 13 [interquartile range 11-16, range 6-18]). Overall, 19% (n = 27/139) had subclinical perianal disease (MR+/asymptomatic [ASx]). For patients who were both asymptomatic and had a normal perianal examination (n = 86/139, 62%), their subclinical perianal disease rate was similar at 20% (n = 17/86). Compared with MR-/ASx, MR+/ASx patients had a relative risk of 1.40 (95% confidence interval [CI] 1.18-1.68) and 1.32 (95% CI 1.17-1.52) of starting a biologic at 6 and 12 months, respectively. MR+/Sx needed the most and earliest perianal surgery, but MR+/ASx also had higher rates and faster time to perianal surgery than MR-/ASx ( P = 0.02). Perianal side branch fistula was a predictor of surgery (odds ratio 107.6, [95% CI 16.9-2,178] P < 0.0001). DISCUSSION: One in 5 newly diagnosed pediatric patients with CD had subclinical perianal disease, even when having a normal perianal physical examination. These patients needed more and earlier perianal surgery and had higher biologic use despite their perianal disease being subclinical. Adding routine MR imaging at the time of pediatric CD diagnosis may help inform treatment decisions and improve these outcomes.
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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 | 0.004 | 0.024 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".