Bibliographic record
Abstract
BACKGROUND: Liver transplantation has become a widely accepted form of treatment for numerous end-stage liver diseases. Bile acids may decrease the degree of allograft rejection after liver transplantation by changing the expression of major histocompatibility complex class molecules in bile duct epithelium and central vein endothelium. OBJECTIVES: To assess the beneficial and harmful effects of bile acids for liver-transplanted patients. SEARCH STRATEGY: We performed searches of the Cochrane Hepato-Biliary Group Trials Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, and EMBASE to April 2003. We also searched The Chinese Biomedical Database to May 2002. SELECTION CRITERIA: Randomised clinical trials comparing any dose of bile acids or duration of treatment in liver-transplanted patients versus placebo, no intervention, or another intervention. We included randomised clinical trials irrespective of blinding, language, and publication status. DATA COLLECTION AND ANALYSIS: W Chen extracted the data and C Gluud validated them. We evaluated the methodological quality of the trials from the method for generation of the allocation sequence, allocation concealment, double blinding, and follow-up. We used the intention-to-treat principle to perform meta-analyses and presented the outcomes as relative risk (RR) or weighted mean difference (WMD), both with 95% confidence intervals (CI). MAIN RESULTS: We identified seven randomised trials (six evaluating ursodeoxycholic acid versus placebo or no intervention and one evaluating tauro-ursodeoxycholic acid versus no intervention) with a total of 335 liver-transplanted patients. The administration of bile acids began one day or more after liver transplantation. All patients received the standard triple-drug immunosuppressive regimen (steroids, azathioprine, and cyclosporine or tacrolimus) to suppress the allograft rejection response after liver transplantation. Bile acids did not significantly reduce all-cause mortality, mortality related to allograft rejection, retransplantation, acute cellular rejection, or number of patients with steroid-resistant rejection. Bile acids significantly reduced the number of patients who had chronic rejection in a fixed-effect model but not in a random-effects model. Bile acids were safe and well tolerated by liver-transplanted patients. AUTHORS' CONCLUSIONS: Bile acids do not seem to have significant beneficial effects in liver-transplanted 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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".