The authority of next-of-kin in explicit and presumed consent systems for deceased organ donation: an analysis of 54 nations
Bibliographic record
Abstract
BACKGROUND: The degree of involvement by the next-of-kin in deceased organ procurement worldwide is unclear. We investigated the next-of-kin's authority in the procurement process in nations with either explicit or presumed consent. METHODS: We collected data from 54 nations, 25 with presumed consent and 29 with explicit consent. We characterized the authority of the next-of-kin in the decision to donate deceased organs. Specifically, we examined whether the next-of-kin's consent to procure organs was always required and whether the next-of-kin were able to veto procurement when the deceased had expressed a wish to donate. RESULTS: The next-of-kin are involved in the organ procurement process in most nations regardless of the consent principle and whether the wishes of the deceased to be a donor were expressed or unknown. Nineteen of the 25 nations with presumed consent provide a method for individuals to express a wish to be a donor. However, health professionals in only four of these nations responded that they do not override a deceased's expressed wish because of a family's objection. Similarly, health professionals in only four of the 29 nations with explicit consent proceed with a deceased's pre-existing wish to be a donor and do not require next-of-kin's consent, but caveats still remain for when this is done. CONCLUSIONS: The next-of-kin have a considerable influence on the organ procurement process in both presumed and explicit consent nations.
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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 | 0.017 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".