Postoperative Outcomes Following Liver Transplantation for Wilson's Disease: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
ABSTRACT Background Liver transplant is indicated in patients with Wilson's disease for acute hepatic failure, advanced cirrhosis, and disease refractory to chelation therapy. This study aims to systematically review data about overall morbidity, hepatic, neuropsychiatric, and survival outcomes following liver transplantation for Wilson disease. Methods MEDLINE, Embase, and Central were searched from inception until July 2023. Peer‐reviewed articles and published abstracts evaluating patients diagnosed with Wilson's disease and undergoing any type of liver transplant as a result of the disease were eligible for inclusion. A restricted maximum likelihood random effects model was used to generate the pooled proportion of each outcome. The risk of bias for each included observational study was assessed using the Methodological Index for Non‐Randomized Studies tool. Results A total of 39 studies met all inclusion criteria. All studies were observational. Specific indications for liver transplant were most commonly acute liver failure (36.73%), chronic liver failure (45.02%), and acute‐on‐chronic liver failure (8.35%). The pooled proportions of mortality at 30 days, 1, and 5 years were 0.10 (95% CI 0.08, 0.13; I 2 = 16%), 0.11 (95% CI 0.09, 0.14; I 2 = 37%), and 0.15 (95% CI 0.11, 0.20; I 2 = 81%), respectively. The postoperative complication with the greatest prevalence was biopsy‐proven acute rejection with a pooled proportion of 0.20 (95% CI 0.12, 0.31; I 2 = 84%). The mean MINORS score for risk of bias for all studies was 8.19. Conclusion Overall, reporting quality and consistency of outcomes included in the studies was poor as assessed using the MINORS score. Pooled proportions for 30‐day, 1‐ and 5‐year mortality are similar, suggesting most postoperative deaths are acute in nature. Future research should incorporate objective measures and the reporting of standardized parameters to allow more robust comparisons between studies.
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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 | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.031 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".