Financial Costs Incurred by Living Kidney Donors: A Prospective Cohort Study
Bibliographic record
Abstract
Background Approximately 40% of the kidneys for transplant worldwide come from living donors. Despite advantages of living donor transplants, rates have stagnated in recent years. One possible barrier may be costs related to the transplant process that potential willing donors may incur for travel, parking, accommodation, and lost productivity. Methods To better understand and quantify the financial costs incurred by living kidney donors, we conducted a prospective cohort study, recruiting 912 living kidney donors from 12 transplant centers across Canada between 2009 and 2014; 821 of them completed all or a portion of the costing survey. We report microcosted total, out-of-pocket, and lost productivity costs (in 2016 Canadian dollars) for living kidney donors from donor evaluation start to 3 months after donation. We examined costs according to ( 1 ) the donor’s relationship with their recipient, including spousal (donation to a partner), emotionally related nonspousal (friend, step-parent, in law), or genetically related; and ( 2 ) donation type (directed, paired kidney, or nondirected). Results Living kidney donors incurred a median (75th percentile) of $1254 ($2589) in out-of-pocket costs and $0 ($1908) in lost productivity costs. On average, total costs were $2226 higher in spousal compared with emotionally related nonspousal donors ( P =0.02) and $1664 higher in directed donors compared with nondirected donors ( P <0.001). Total costs (out-of-pocket and lost productivity) exceeded $5500 for 205 (25%) donors. Conclusions Our results can be used to inform strategies to minimize the financial burden of living donation, which may help improve the donation experience and increase the number of living donor kidney 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 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".