Dual kidney transplants from adult marginal donors: Review and perspective
Bibliographic record
Abstract
The practice of dual kidney transplantation (DKT) from adult marginal deceased donors (MDDs) dates back to the mid-1990s with initial pioneering experiences reported by the Stanford and Maryland groups, at which time the primary indication was estimated insufficient nephron mass from older donors. Multiple subsequent studies of short and long-term success have been reported focusing on three major aspects of DKT: Identifying appropriate selection criteria and developing scoring systems based on pre- and post-donation factors; refining technical aspects; and analyzing mid-term outcomes. The number of adult DKTs performed in the United States has declined in the past decade and only about 60 are performed annually. For adult deceased donor kidneys meeting double allocation criteria, > 60% are ultimately not transplanted. Deceased donors with limited renal functional capacity represent a large proportion of potential kidneys doomed to either discard or non-recovery. However, DKT may reduce organ discard and optimize the use of kidneys from MDDs. In an attempt to promote utilization of MDD kidneys, the United Network for Organ Sharing introduced new allocation guidelines pursuant to DKT in 2019. The purpose of this review is to chronicle the history of DKT and identify opportunities to improve utilization of MDD kidneys through DKT.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".