The authority of next-of-kin in explicit and presumed consent systems for deceased organ donation: an analysis of 54 nations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it