Outcomes of Adult Liver Retransplantation: A Canadian National Database Analysis
Bibliographic record
Abstract
Background. Liver retransplantation remains as the only treatment for graft failure. This investigation aims to assess the incidence, post‐transplant outcomes, and risk factors in liver retransplantation recipients in Canada. Materials and Methods. The Canadian Organ Replacement Register was used to obtain and analyse data on all adult liver retransplant recipients, matched donors, transplant-specific variables, and post‐transplant outcomes from January 2000 to December 2018. Results. 377 (6.5%) patients underwent liver retransplantation. Autoimmune liver disease and hepatitis C virus (HCV) were the most common underlying diagnoses. Graft failure was 7.9% and 12.5%, and overall survival was 77.1% and 65.6% at 1 year and 5 years, respectively. In contrast to recipients receiving their first graft transplant, the retransplantation group had a significantly higher incidence of graft failure p < 0.001 and lower overall survival p < 0.001 . The graft failure and patient survival rates were comparable between second transplant and repeat retransplant recipients. Furthermore, there were no differences in graft failure and patient survival when stratified according to time to retransplantation. Recipient and donor age (HR = 1.12, p = 0.011 ; HR = 1.09, p = 0.008 ), recipient HCV status (HR = 1.81, p = 0.014 ), and donor cytomegalovirus status (HR = 4.10, p = 0.006 ) were predictors of patient mortality. Conclusion. This analysis of liver retransplantation demonstrates that this is a safe treatment for early and late graft failure. Furthermore, even in patients requiring more than two grafts, similar outcomes to initial retransplantation can be achieved with careful selection.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.014 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".