Reply: The urgent need for consensus around organ donation after assisted dying
Bibliographic record
Abstract
To the editor, Regarding our study on “Liver Transplantation after Medical Assistance in Dying (MAiD)”, Drs. Berry and Kotha raise ethical and geopolitical considerations related to transplantation from donation after MAiD. Encouraging discourse among stakeholders, including policymakers, the public, ethicists, legal experts, and the medical community, is crucial.1 Jurisdictions practicing transplant after MAiD in Canada have undergone rigorous policy development. Public trust in transplantation is sacrosanct, warranting distance between transplant surgeons and donation decision-making. Surgeon involvement due to MAiD’s contentious nature may risk declining trust.2 Assuming a link between MAiD and donation/transplantation is perilous and false. Organ procurement in MAiD follows a process similar to donation after circulatory determination of death. MAiD medications are administered, circulatory death is established, and a 5-minute “hands-off” period precedes organ procurement. Organ donation in MAiD cases does not cause or hasten death and is not a means of euthanasia.3 Donation after circulatory determination of death requires first-person consent following rigorous MAiD approval. Patients must provide informed consent as per current Canadian legislation enacted in 2016. Patients can independently choose MAiD or organ donation after death, irrespective of death’s imminence. These decisions remain mutually exclusive.4 Only 57 out of 10,064 MAiD cases in Canada in 2021 were eligible for organ donation, representing a mere 0.5% of recipients. This underscores the minimal intersection between MAiD and organ donation, challenging the claim of a variation in practice. We acknowledge the sensitivity surrounding MAiD and its diverse perspectives. MAiD’s objective is not to facilitate organ transplantation but to make an autonomous choice driven by individual circumstances, beliefs, and end-of-life wishes. The question remains whether moral repugnance in MAiD hinders life-saving organ transplantation.5
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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 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.036 | 0.052 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".