Donor Age, Donor-Recipient Size Mismatch, and Kidney Graft Survival
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Small donor and/or kidney sizes relative to recipient size are associated with a higher risk of kidney allograft failure. Donor and recipient ages are associated with graft survival and may modulate the relationship between size mismatch and the latter. The aim of this study was to determine whether the association between donor-recipient size mismatch and graft survival differs by donor and recipient age. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENT: We performed a retrospective cohort study of first adult deceased donor kidney transplantations performed between 2000 and 2018 recorded in the Scientific Registry of Transplant Recipients. We used multivariable Cox proportional hazards models to assess the association between donor-recipient body surface area ratio and death-censored graft survival, defined as return to dialysis or retransplantation. We considered interactions between donor-recipient body surface area ratio and each of recipient and donor age. RESULTS: =0.04). The magnitude of the association between severe size mismatch (donor-recipient body surface area ratio <0.80 versus ≥1.00) and death-censored graft survival was stronger with older donor age and recipient age. In all recipient age categories except the youngest (18-30 years), 5- and 10-year graft survival rates were similar or better with a size-mismatched donor aged <40 years than a nonsize-mismatched donor aged 40 years or older. CONCLUSIONS: The association of donor-recipient size mismatch on long-term graft survival is modulated by recipient and donor age. Size-mismatched kidneys yield excellent graft survival when the donor is young. Donor age was more strongly associated with graft survival than size mismatch.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".