Income of Living Kidney Donors and the Income Difference Between Living Kidney Donors and Their Recipients in the United States
Bibliographic record
Abstract
Disincentives for living kidney donation are common but are poorly understood. We studied 54 483 living donor kidney transplants in the United States between 2000 and 2009, limiting to those with valid zip code data to allow determination of median household income by linkage to the 2000 U.S. Census. We then determined the income and income difference of donors and recipients. The median household income in donors and recipients was $46 334 ±$17 350 and $46 439 ±$17 743, respectively. Donation-related expenses consume ≥ 1 month's income in 76% of donors. The mean ± standard deviation income difference between recipients and donors in transplants involving a wealthier recipient was $22 760 ± 14 792 and in 90% of transplants the difference was <$40 000 dollars. The findings suggest that the capacity for donors to absorb the financial consequences of donation, or of recipients to reimburse allowable expenses, is limited. There were few transplants with a large difference in recipient and donor income, suggesting that the scope and value of any payment between donors and recipients is likely to be small. We conclude that most donors and recipients have similar modest incomes, suggesting that the costs of donation are a significant burden in the majority of living donor transplants.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".