Diagnosing Crohn’s disease in presumed cryptoglandular perianal fistulas: an expert Delphi consensus on early identification of patients at risk of Crohn’s disease in perianal fistulas (PREFAB)
Bibliographic record
Abstract
BACKGROUND: The aim of this Delphi study was to reach consensus on a new clinical decision tool to help identify or exclude Crohn's disease (CD) in patients with perianal fistula(s) (PAF). METHODS: A panel of international experts in the field of proctology/inflammatory bowel disease was invited to participate. In the first round (electronic survey), participants were asked to anonymously provide their opinion probing (1) the relevance and use of clinical characteristics suggestive of underlying CD, (2) the use of fecal calprotectin (FCP) for screening for CD, and (3) on the diagnostic work-up for CD in PAF patients with raised clinical suspicion. In the second/third round (virtual consensus meetings), statements were paired/revised and presented in final sets of statements. Consensus was predefined as ≥70% (dis)agreement. RESULTS: Final consensus was reached on 12 statements, including screening of all PAF patients (regardless of the complexity, biological behavior, and co-existent perianal symptoms) and referral of PAF patients for a colonoscopy in case of elevated FCP levels (≥150 mcg/g) and/or in case of one clinical major criterion (defined as: unintentional weight loss, unexplained diarrhea, PSC, UC, >1 internal fistula openings, fistula involving other organs (vagina/bladder), recurrent fistulation (after initial healing), proctitis, and anal stenosis). Also, clinical (fistula-)characteristics that warrant raised suspicion for CD and an algorithm on the diagnostic work-/follow-up of patients with raised suspicion were defined. CONCLUSION: International consensus was reached on a new, clinical decision tool, including a practical and relevant algorithm for finding/excluding CD in PAF patients.
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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 | 0.145 | 0.095 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| 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".