The Medical Management of Paediatric Crohn’s Disease: an ECCO-ESPGHAN Guideline Update
Bibliographic record
Abstract
OBJECTIVE: We aimed to provide an evidence-supported update of the ECCO-ESPGHAN guideline on the medical management of paediatric Crohn's disease [CD]. METHODS: We formed 10 working groups and formulated 17 PICO-structured clinical questions [Patients, Intervention, Comparator, and Outcome]. A systematic literature search from January 1, 1991 to March 19, 2019 was conducted by a medical librarian using MEDLINE, EMBASE, and Cochrane Central databases. A shortlist of 30 provisional statements were further refined during a consensus meeting in Barcelona in October 2019 and subjected to a vote. In total 22 statements reached ≥ 80% agreement and were retained. RESULTS: We established that it was key to identify patients at high risk of a complicated disease course at the earliest opportunity, to reduce bowel damage. Patients with perianal disease, stricturing or penetrating behaviour, or severe growth retardation should be considered for up-front anti-tumour necrosis factor [TNF] agents in combination with an immunomodulator. Therapeutic drug monitoring to guide treatment changes is recommended over empirically escalating anti-TNF dose or switching therapies. Patients with low-risk luminal CD should be induced with exclusive enteral nutrition [EEN], or with corticosteroids when EEN is not an option, and require immunomodulator-based maintenance therapy. Favourable outcomes rely on close monitoring of treatment response, with timely adjustments in therapy when treatment targets are not met. Serial faecal calprotectin measurements or small bowel imaging [ultrasound or magnetic resonance enterography] are more reliable markers of treatment response than clinical scores alone. CONCLUSIONS: We present state-of-the-art guidance on the medical treatment and long-term management of children and adolescents with CD.
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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 | 0.015 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".