Ethical Issues in Normothermic Regional Perfusion in Controlled Organ Donation After Determination of Death by Circulatory Criteria: A Scoping Review
Bibliographic record
Abstract
Normothermic regional perfusion (NRP) is a surgical technique that can improve the quality and number of organs recovered for donation after the determination of death by circulatory criteria. Despite its promise, adoption of NRP has been hindered because of unresolved ethical issues. To inform stakeholders, this scoping review provides an impartial overview of the major ethical controversies surrounding NRP. We undertook this review according to a modified 5-step methodology proposed by Arksey and O'Malley. Publications were retrieved through MEDLINE and Embase. Gray literature was sourced from Canadian organ donation organizations, English-language organ donation organization websites, and through our research networks. Three reviewers independently screened all documents for inclusion, extracted data, and participated in content analysis. Disagreements were resolved through consensus meetings. Seventy-one documents substantively engaging with ethical issues in NRP were included for full-text analysis. We identified 6 major themes encompassing a range of overlapping ethical debates: (1) the compatibility of NRP with the dead donor rule, the injunction that organ recovery cannot cause death, (2) the risk of donor harm posed by NRP, (3) uncertainties regarding consent requirements for NRP, (4) risks to stakeholder trust posed by NRP, (5) the implications of NRP for justice, and (6) NRP's potential to benefits of NRP for stakeholders. We found no agreement on the ethical permissibility of NRP. However, some debates may be resolved through additional empirical study. As decision-makers contemplate the adoption of NRP, it is critical to address the ethical issues facing the technique to ensure stakeholder trust in deceased donation and transplantation systems is preserved.
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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 | 0.148 | 0.404 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.015 | 0.017 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".