Suitability to Donate and Attitude Toward Living Kidney Donation in Older Adults: Results from the BIS Study
Bibliographic record
Abstract
Background: Guidelines differ regarding thresholds of glomerular filtration rate (GFR) and albuminuria (ACR) to accept living kidney donation (LKD). We aimed to assess the proportion of community-dwelling older adults suitable to LKD according to different GFR and ACR thresholds, and their attitude towards LKD. Methods: We used data from the BIS-study, a cohort of adults aged ≥70 years. Kidney-related contraindications to LKD were defined using KDIGO (high and low GFR thresholds of 90 and 60ml/min/1.73m2 using the EKFC equation based on creatinine and cystatin C, respectively; LKD can be discussed between these thresholds) and British Transplantation Society (BTS; age- and sex-specific GFR thresholds) guidelines. The ACR thresholds were 30mg/g (low threshold for both guidelines), 100mg/g (high KDIGO threshold), and 300mg/g (high BTS threshold). Participants' attitude towards LKD was asked at the first follow-up visit. Results: Among the 2069 participants (median age 80 years, 53% women, median estimated GFR 63ml/min/1.73m2), none had an estimated GFR above the high KDIGO GFR threshold at baseline. Considering the combination of other GFR and ACR thresholds, prevalence of renal contraindication to LKD ranged from 38 to 54%. Ninety-three percent of participants presented ≥1 non-kidney-related contraindication to LKD, among which heart failure, coronary artery disease, and cancer were the most frequent. Prevalence of suitability to LKD ranged from 0 to 6%, depending on combinations of thresholds of GFR and ACR. After an 8-year follow-up period, 11 to 16% of participants suitable to LKD at baseline maintained their suitability criteria, 6 to 11% had died, and none of them developed CKD stage 4-5. Overall, 73% of all participants agreed to donate a kidney to a relative, but this percentage rose to 85 to 87% in participants suitable to LKD. Conclusions: Most older adults were theoretically willing to donate a kidney to a relative. Regardless of the low percentage of participants without any contraindication to LKD, their absolute sample size could be an opportunity to increase the number of kidney donors at the population level. To this purpose, the choice of GFR and ACR thresholds may be crucial. Funding: Government Support - Non-U.S.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".