The World's Youngest Cadaveric Kidney Transplant: Medical, Surgical and Ethical Issues
Bibliographic record
Abstract
BACKGROUND: We report here the first successful transplant from a preterm cadaveric donor. This was performed in November 1994. The donor, who had been born at about 33 weeks of gestation, was diagnosed as having agenesis of the corpus callosum. The transplant was carried out 10 days after the donor's birth. The recipient was a 17-month-old boy with a diagnosis of Denys-Drash syndrome (WT1 mutation). METHOD: We describe and analyze the ethical, social, cultural, medical and surgical issues encountered and how these were addressed. The major issue of determining death in a beating heart, very young donor was dealt with in the absence of worldwide experience and guidelines. RESULTS: The transplanted recipient has lived with the grafted pair of kidneys for more then 22 years. He has led a relatively normal life. CONCLUSIONS: It is possible for immature preterm deceased donor kidneys to be transplanted into a 17-month-old recipient and for the grafted kidneys to grow with the recipient and function for 22 years. There were challenges in ethically determining the death of the donor, in surgical techniques to obviate potential surgical complications, and in postoperative care of the recipient, but these were managed successfully.
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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".