Does Adjuvant Steroid Therapy Post-Kasai Portoenterostomy Improve the Outcome of Biliary Atresia? A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: The role of adjuvant steroid therapy in the postoperative management of patients with biliary atresia (BA) is unclear. OBJECTIVE: To systematically review the literature and perform a meta-analysis to determine the efficacy of adjuvant steroid therapy post-Kasai portoenterostomy (KP) on BA outcome. METHODS: A systematic review and meta-analysis of randomized trials and⁄or observational studies that examined the role of steroids on BA outcomes published between January 1969 and June 2010 was conducted. Studies were identified using the Medline, PubMed, EMBASE and Cochrane databases. RESULTS: Sixteen observational studies and one randomized controlled trial (RCT) were found. Four of the 16 observational studies (160 participants) and the RCT (73 participants) met the entry criteria and were eligible to be included in the analysis. There was no statistically significant difference in the effect of steroids either on normalizing serum bilirubin levels at six months (pooled OR 1.48 [95% CI 0.67 to 3.28]) or in delaying the need for early liver transplantation (within the first year post-KP (pooled OR 0.59 [95% CI 0.21 to 1.72]). CONCLUSION: The present meta-analysis did not find a significant effect of steroid over standard therapy, either in normalizing serum bilirubin levels at six months or at delaying the need for early liver transplantation post-KP. RCT studies of sufficient size and comprehensive design using high-dose steroids are needed to determine the effectiveness of steroids on the short and intermediate post-KP outcomes for BA patients.
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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 | 0.017 | 0.046 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.040 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".