Bibliographic record
Abstract
BACKGROUND: Pre-emptive kidney transplantation for end-stage kidney disease in children has many advantages and may lead to the consideration of marginal parent donors. METHODS: Using the example of the transplant of a kidney with medullary sponge disease from a parent to the child, we review the ethical framework for working up such donors. RESULTS: The four principles of health ethics include autonomy (the right of the patient to retain control over his/her own body); beneficence (healthcare providers must do all they can do to benefit the patient in each situation); non-maleficence ("first do no harm"-providers must consider whether other people or society could be harmed by a decision made, even if it is made for the benefit of an individual patient) and justice (there should be an element of fairness in all medical decisions). Highly motivated donors may derive significant psychological benefit from their donation and may thus be willing to incur more risk. The transplantation team and, ideally, an independent donor advocate team must make a judgment about the acceptability of the risk-benefit ratio for particular potential donors, who must also make their own assessment. The transplantation team and donor advocate team must be comfortable with the risk-benefit ratio before proceeding. CONCLUSIONS: An independent donor advocacy team that focuses on the donor needs is needed with sufficient multidisciplinary ethical, social, and psychological expertise. The decision to accept or reject the donor should be within the authority of the independent donor advocacy team and not the providers or the donor.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.031 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".