Serum bile acids as a prognostic biomarker in biliary atresia following Kasai portoenterostomy
Bibliographic record
Abstract
BACKGROUND AND AIMS: In biliary atresia, serum bilirubin is commonly used to predict outcomes after Kasai portoenterostomy (KP). Infants with persistently high levels invariably need liver transplant, but those achieving normalized levels have a less certain disease course. We hypothesized that serum bile acid levels could help predict outcomes in the latter group. APPROACH AND RESULTS: Participants with biliary atresia from the Childhood Liver Disease Research Network were included if they had normalized bilirubin levels 6 months after KP and stored serum samples from the 6-month post-KP clinic visit ( n = 137). Bile acids were measured from the stored serum samples and used to divide participants into ≤40 μmol/L ( n = 43) or >40 μmol/L ( n = 94) groups. At 2 years of age, the ≤40 μmol/L compared with >40 μmol/L group had significantly lower total bilirubin, aspartate aminotransferase, alanine aminotransferase, gamma-glutamyltransferase, bile acids, and spleen size, as well as significantly higher albumin and platelet counts. Furthermore, during 734 person-years of follow-up, those in the ≤40 μmol/L group were significantly less likely to develop splenomegaly, ascites, gastrointestinal bleeding, or clinically evident portal hypertension. The ≤40 μmol/L group had a 10-year cumulative incidence of liver transplant/death of 8.5% (95% CI: 1.1%-26.1%), compared with 42.9% (95% CI: 28.6%-56.4%) for the >40 μmol/L group ( p = 0.001). CONCLUSIONS: Serum bile acid levels may be a useful prognostic biomarker for infants achieving normalized bilirubin levels after KP.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".