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Income of Living Kidney Donors and the Income Difference Between Living Kidney Donors and Their Recipients in the United States

2012· article· en· W1485059053 on OpenAlexafffund
John S. Gill, Lianne Barnieh, Jianghu Dong, Caren Rose, Olwyn Johnston, Marcello Tonelli, Scott Klarenbach

Bibliographic record

VenueAmerican Journal of Transplantation · 2012
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsAlberta Kidney Disease NetworkUniversity of AlbertaUniversity of CalgaryCentre for Advancing Health OutcomesUniversity of British Columbia
FundersAlberta Heritage Foundation for Medical ResearchUniversity of AlbertaGovernment of Canada
KeywordsDonationMedicineKidney donationPaymentDemographyHousehold incomeSignificant differenceKidney transplantationTransplantationSurgeryInternal medicineEconomicsFinanceEconomic growthGeography

Abstract

fetched live from OpenAlex

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. 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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.324

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.252
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations46
Published2012
Admission routes2
Has abstractyes

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