Accepting Kidneys from Older Living Donors: Impact on Transplant Recipient Outcomes
Bibliographic record
Abstract
Older living kidney donors are regularly accepted. Better knowledge of recipient outcomes is needed to inform this practice. This retrospective cohort study observed kidney allograft recipients from Ontario, Canada between January 2000 and March 2008. Donors to these recipients were older living (≥ 60 years), younger living, or standard criteria deceased (SCD). Review of medical records and electronic healthcare data were used to perform survival analysis. Recipients received 73 older living, 1187 younger living and 1400 SCD kidneys. Recipients of older living kidneys were older than recipients of younger living kidneys. Baseline glomerular filtration rate (eGFR) of older kidneys was 13 mL/min per 1.73 m² lower than younger kidneys. Median follow-up time was 4 years. The primary outcome of total graft loss was not significantly different between older and younger living kidney recipients [adjusted hazard ratio, HR (95%CI): 1.56 (0.98-2.49)]. This hazard ratio was not proportional and increased with time. Associations were not modified by recipient age or donor eGFR. There was no significant difference in total graft loss comparing older living to SCD kidney recipients [HR: 1.29 (0.80-2.08)]. In light of an observed trend towards potential differences beyond 4 years, uncertainty remains, and extended follow-up of this and other cohorts is warranted.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".