ESPGHAN Revised Porto Criteria for the Diagnosis of Inflammatory Bowel Disease in Children and Adolescents
Bibliographic record
Abstract
BACKGROUND: The diagnosis of pediatric-onset inflammatory bowel disease (PIBD) can be challenging in choosing the most informative diagnostic tests and correctly classifying PIBD into its different subtypes. Recent advances in our understanding of the natural history and phenotype of PIBD, increasing availability of serological and fecal biomarkers, and the emergence of novel endoscopic and imaging technologies taken together have made the previous Porto criteria for the diagnosis of PIBD obsolete. METHODS: We aimed to revise the original Porto criteria using an evidence-based approach and consensus process to yield specific practice recommendations for the diagnosis of PIBD. These revised criteria are based on the Paris classification of PIBD and the original Porto criteria while incorporating novel data, such as for serum and fecal biomarkers. A consensus of at least 80% of participants was achieved for all recommendations and the summary algorithm. RESULTS: The revised criteria depart from existing criteria by defining 2 categories of ulcerative colitis (UC, typical and atypical); atypical phenotypes of UC should be treated as UC. A novel approach based on multiple criteria for diagnosing IBD-unclassified (IBD-U) is proposed. Specifically, these revised criteria recommend upper gastrointestinal endoscopy and ileocolonscopy for all suspected patients with PIBD, with small bowel imaging (unless typical UC after endoscopy and histology) by magnetic resonance enterography or wireless capsule endoscopy. CONCLUSIONS: These revised Porto criteria for the diagnosis of PIBD have been developed to meet present challenges and developments in PIBD and provide up-to-date guidelines for the definition and diagnosis of the IBD spectrum.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".