Expanding Access to High KDPI Kidney Transplant for Recipients Aged 60 y and Older: Cost Utility and Survival
Bibliographic record
Abstract
Background: Modern organ allocation systems are tasked with equitably maximizing the utility of transplanted organs. Increasing the use of deceased donor organs at risk of discard may be a cost-effective strategy to improve overall transplant benefit. We determined the survival implications and cost utility of increasing the use of marginal kidneys in an older adult Canadian population of patients with end-stage kidney disease. Methods: 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 y and older. A kidney donor profile index score of ≥86 was considered a marginal kidney. Donor- and recipient-level characteristics encompassed in the kidney donor profile index and estimated posttransplant survival scores were used to derive survival posttransplant. Patients were followed up for 10 y from the date of waitlist initiation. Our analysis compared the routine use of marginal kidneys (marginal kidney scenario) with the current practice of limited use (status quo scenario). Results: The 10-y mean cost and quality-adjusted life-years per patient in the marginal kidney scenario were estimated at $379 485.33 (SD: $156 872.49) and 4.77 (SD: 1.87). In the status quo scenario, the mean cost and quality-adjusted life-years per patient were $402 937.68 (SD: $168 508.85) and 4.37 (SD: 1.87); thus, the intervention was considered dominant. At 10 y, 62.8% and 57.0% of the respective cohorts in the marginal kidney and status quo scenarios remained alive. Conclusions: Increasing the use of marginal kidneys in patients with end-stage kidney disease aged 60 y and older may offer cost savings, improved quality of life, and greater patient survival in comparison with usual care.
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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) | 0.000 | 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".