Oral Vancomycin, Ursodeoxycholic Acid, or No Therapy for Pediatric Primary Sclerosing Cholangitis: A Matched Analysis
Bibliographic record
Abstract
BACKGROUND AND AIMS: Many children with primary sclerosing cholangitis (PSC) receive oral vancomycin therapy (OVT) or ursodeoxycholic acid (UDCA). There is a paucity of data on whether these medications improve outcomes. APPROACH AND RESULTS: We analyzed retrospective data from the Pediatric PSC Consortium. Children treated with OVT were matched 1:1:1 to those treated with UDCA or managed with observation (no treatment) based on the closest propensity score, ensuring similar baseline characteristics. Two hundred sixty-four patients (88 each with OVT, UDCA, or observation) had matching propensity scores and were similar in demographics, phenotype, immunosuppression, baseline biochemistry, and hepatic fibrosis. After 1 year in an intention-to-treat analysis, all outcome metrics were similar regardless of treatment group. In OVT, UDCA, and untreated groups, respectively: Gamma-glutamyltransferase normalized in 53%, 49%, and 52% (P = not significant [NS]), liver fibrosis stage was improved in 20%, 13%, and 18% and worsened in 11%, 29%, and 18% (P = NS), and the 5-year probability of liver transplant listing was 21%, 10%, and 12% (P = NS). Favorable outcome was associated with having a mild phenotype of PSC and minimal hepatic fibrosis. CONCLUSIONS: We presented the largest-ever description of outcomes on OVT in PSC and compared them to carefully matched patients on UDCA or no therapy. Neither OVT nor UDCA showed improvement in outcomes compared to a strategy of observation. Patients progressed to end-stage liver disease at similar rates. Spontaneous normalization of biochemistry is common in children receiving no therapy, particularly in the majority of children with a mild phenotype and an early stage of disease. Placebo-controlled treatment trials are needed to identify effective treatments for pediatric PSC.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".