Primary sclerosing cholangitis in children with inflammatory bowel disease: An ESPGHAN position paper from the Hepatology Committee and the IBD Porto group
Bibliographic record
Abstract
OBJECTIVE: We aimed to provide an evidence-supported approach to diagnose, monitor, and treat children with inflammatory bowel disease (IBD) and primary sclerosing cholangitis (PSC). METHODS: The core group formulated seven PICO-structured clinical questions. A systematic literature search from inception to December 2022 was conducted by a medical librarian using MEDLINE and EMBASE. Core messages from the literature were phrased as position statements and then circulated to a sounding board composed of international experts in pediatric gastroenterology and hepatology, histopathology, adult gastroenterology and hepatology, radiology, and surgery. Statements reaching at least 80% agreement were considered as final. The other statements were refined and then subjected to a second online vote or rejection. RESULTS: Regular screening for gamma-glutamyltransferase (GGT) is essential for detecting possible biliary disease in children with IBD. MR cholangiopancreatography is the radiological modality of choice for establishing the diagnosis of PSC. Liver biopsy is relevant in the evaluation of small duct PSC or autoimmune hepatitis. Children who do not have known IBD at the time of PSC diagnosis should undergo initial screening with fecal calprotectin for asymptomatic colitis, and then at least once yearly thereafter. Children with a cholestatic liver enzyme profile can be considered for treatment with ursodeoxycholic acid and can continue if there is a meaningful reduction or normalization in GGT. Oral vancomycin may have a beneficial effect on GGT and intestinal inflammation, but judicious use is recommended due to the lack of long-term studies. Children with PSC-IBD combined with convincing features of autoimmune hepatitis may benefit from corticosteroids and antimetabolites. CONCLUSIONS: We present state-of-the-art guidance on the diagnostic criteria, follow-up strategies, and therapeutic strategies and point out research gaps in children and adolescents with PSC-IBD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".