Living Donor Age and Kidney Allograft Half-Life
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Living donor paired exchange programs assume that kidneys from living donors are of comparable quality and anticipated longevity. This study determined actual allograft t(1/2) within different recipient age groups (10-year increments) as a function of donor age (5-year increments), and juxtaposed these results against the probabilities of deceased donor transplantation, and exclusion from transplantation (death or removal from the wait-list). DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Data from the US Renal Data System (transplant dates 1988-2003 with follow-up through September 2007) were used to determine allograft t(1/2), whereas data from patients on the United Network for Organ Sharing waiting list between 2003 and 2005 (with follow-up through February 2010) were used to determine wait-list outcomes. RESULTS: With the exception of recipients aged 18-39 years, who had the best outcomes with donors aged 18-39 years, living donor age between 18 and 64 years had minimal effect on allograft t(1/2) (difference of 1-2 years with no graded association). The probability of deceased donor transplantation after 3 years of wait-listing ranged from 21% to 66% by blood type and level of sensitization, whereas the probability of being excluded from transplantation ranged from 6% to 27% by age, race, and primary renal disease. CONCLUSIONS: With the exception of recipients aged 18-39 years, living donor age between 18 and 64 years has minimal effect on allograft survival.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".