Increasing the use of marginal kidneys in Manitoba’s older-adult end-stage renal disease population: survival and cost-utility implications
Bibliographic record
Abstract
Kidney transplantation is the optimal treatment for patients with end-stage kidney disease, offering increased survival and reduced costs in comparison to dialysis. Transplant programs worldwide have increasingly relied upon organs from deceased donors to increase the supply of viable transplantable kidneys as current supply is unable to meet demand. The implications of transplantation with marginal kidneys, defined by a Kidney Donor Profile Index (KDPI) ≥86 from both an economic and patient survival perspective has not been assessed in the Canadian context. The purpose of this project is to describe the survival implications and cost-utility of increasing the use of marginal kidneys in Manitoba’s older-adult end-stage renal-disease patient population. We constructed a cost-utility model with microsimulation from the perspective of the Canadian single payer health system for incident transplant waitlisted patients aged 60 and over. Patients were followed for 10 years from date of waitlisting. We included Manitoba specific data pertaining to potential KDPI ≥86 kidney supply, transplant ineligibility, receiving a transplant, and death on the waitlist. Remaining model inputs were sourced from the literature. Our analysis compared the intervention (Marginal Kidney scenario) to usual care (Status Quo scenario). All costs are presented in 2019 Canadian dollars. The ten-year mean cost and quality-adjusted life years (QALYs) per patient in the Marginal Kidney scenario were estimated at $362,116.54 (SD: $149,037.69) and 4.52 (SD: 1.84). In the Status Quo scenario, the mean cost and QALYs per patient were estimated at $365,624.71 (SD: $152,647.93) and 4.35 (SD: 1.81). The incremental cost-utility ratio between the two scenarios was estimated at -$20,573.03. At ten years., 60.1% of the cohort in the Marginal Kidney scenario remained alive, compared to 56.7% in the Status Quo scenario. Mean survival for marginal kidney recipients and transplant-naïve patients were 115.59 and 80.37 months respectively. Increasing the use of marginal kidneys in Manitoba’s end-stage renal-disease population aged 60 and over may offer cost savings, increased quality-of-life, and increased survival in comparison to usual care. Further research is needed regarding the effects of human leukocyte antigen mismatches, differences by blood-type, the allowance for multiple transplants, and preemptive transplantation on costs, QALYs, and survival.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".