ArticleTransplantation2019
Evaluation of Accepting Kidneys of Varying Quality for Transplantation or Expedited Placement With Decision Trees.
Article in Transplantation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence-driven kidney organ allocation: systematic review of clinical outcome prediction, ethical frameworks, and decision-making algorithms.BMC nephrology · 2025Pooled it
- The impact of simultaneous batch turn downs and targeted kidney utilization decisions on patient survival.PloS one · 2026Article
- Review
- Present and Future Applications of Artificial Intelligence in Kidney Transplantation.Journal of clinical medicine · 2024Review
- Predicting Kidney Transplantation Outcomes from Donor and Recipient Characteristics at Time Zero: Development of a Mobile Application for Nephrologists.Journal of clinical medicine · 2024Article
- Considerable Variability Among Transplant Nephrologists in Judging Deceased Donor Kidney Offers.Kidney international reports · 2023Article
- Machine Learning Support for Decision-Making in Kidney Transplantation: Step-by-step Development of a Technological Solution.JMIR medical informatics · 2022Article
- Patient and Clinician Perceptions of Informed Consent and Decision Making About Accepting KDPI > 85 Kidneys.Transplantation direct · 2022Article
- Designing a Liver Transplant Patient and Family Decision Support Tool for Organ Offer Decisions.Transplantation direct · 2021Article
- Acute Kidney Injury (AKI) before and after Kidney Transplantation: Causes, Medical Approach, and Implications for the Long-Term Outcomes.Journal of clinical medicine · 2021Review
- Functional status-based risk-benefit analyses of high-KDPI kidney transplant versus dialysis.Transplant international : official journal of the European Society for Organ Transplantation · 2019Article
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Authors and funding
7 authors.
Funding
Abstract
backgroundUnderutilization of marginal-quality kidneys for transplantation produced ideas of expediting kidney placement for populations with decreased opportunities of receiving transplants. Such policies can be less efficacious for specific individuals and should be scrutinized until the decision-making for accepting marginal-quality organs, which has relied on experiential judgment, is better understood at the individual level. There exist rigorous tools promoting personalized decisions with useful and objective information.
methodsThis article introduces a decision-tree methodology that analyzes a patient's dilemma: to accept a kidney offer now or reject it. The methodology calculates the survival benefit of accepting a kidney given a certain quality now and the survival benefit of rejecting it. Survival benefit calculation accounts for patients' and donors' characteristics and transplant centers' and organ procurement organizations' performances and incorporates patients' perceived transplant and dialysis utilities. Valuations of rejecting an offer are contingent on future opportunities and subject to uncertainty in the timing of successive kidney offers and their quality and donor characteristics.
resultsThe decision tree was applied to a realistic patient profile as a demonstration. The tool was tested on 1000 deceased-donor kidney offers in 2016. Evaluating up to 1 year of future offers, the tool attains 61% accuracy, with transplant utility of 1.0 and dialysis utility of 0.5. The accuracy reveals potential bias in kidney offer acceptance/rejection at transplant centers.
conclusionsThe decision-tree tool presented could aid personalized transplant decision-making in the future by providing patients with calculated, individualized survival benefits between accepting and rejecting a kidney offer.
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