Financial, policy, and ethical barriers to the expansion of living donor liver transplant: Meeting report from a living donor liver transplant consensus conference
Bibliographic record
Abstract
INTRODUCTION: In October 2021, the American Society of Transplantation (AST) hosted a virtual consensus conference aimed at identifying and addressing barriers to the broader, safe expansion of living donor liver transplantation (LDLT) throughout the United States (US). METHODS: A multidisciplinary group of LDLT experts convened to address issues related to financial implications on the donor, transplant center crisis management, regulatory and oversight policies, and ethical considerations by assessing the relative significance of issues in preventing LDLT growth, with proposed strategies to overcome barriers. RESULTS: Living liver donors endure multiple obstacles including financial instability, loss of job security, and potential morbidity. These concerns, along with other center, state, and federal specific policies can be perceived as significant barriers to expanding LDLT. Donor safety is of paramount importance to the transplant community; however, regulatory and oversight policies aimed at ensuring donor safety can be viewed as ambiguous and complicated leading to time-consuming evaluations that may deter donor motivation and program expansion. CONCLUSION: Transplant programs need to establish appropriate crisis management plans to mitigate potential negative donor outcomes and ensure program viability and stability. Finally, ethical aspects, including informed consent for high-risk recipients and use of non-directed donors, can be perceived as additional barriers to expanding LDLT.
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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 | 0.072 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.015 | 0.017 |
| Insufficient payload (model declined to judge) | 0.003 | 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".