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Kidney allocation rules simulator

2022-06Journal article Restricted access
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dc.contributor.authorLima, Bruno A.
dc.contributor.authorHenriques, Teresa S.
dc.contributor.authorAlves, Helena
dc.date.accessioned2023-03-24T10:40:05Z
dc.date.available2023-03-24T10:40:05Z
dc.date.issued2022-06
dc.description.abstractThe greatest challenge of any kidney transplant program lies in finding enough organ donors (in number and quality) for all waitlisted transplant candidates. Unfortunately, we must resign ourselves to a manifestly insufficient supply of organs for the current demand. Furthermore we must be able to predict kidney transplant success at organ allocation if we want to minimize the number of patients who return to an already overcrowded waiting list for transplantation. Therefore, the definition of deceased donors' kidney allocation rules on transplantation must be supported by simulations that allow foreseeing, as much as possible, the consequences of these rules. Here we present the Kidney Allocation Rules Simulator (KARS) application that enables testing different kidney transplant allocation' systems with different donors and transplant candidates' datasets. In this application, it is possible to simulate allocation rules implemented in Portugal, in the United Kingdom, in countries within Eurtotransplant, and a previously suggested color priority system. As inputs, this application needs three data files: a file with transplant candidates' information, a file with candidates' anti-HLA antibodies, and a file with donors' information. As output, we will have a file with donor-recipient pairs selected according to the kidney allocation system simulated. When seeking waste reduction while ensuring a fair distribution of organs from deceased donors, the definition of rules selecting donor-recipient pairs in renal transplantation must be based on evidence supported by data. On the continuously changing process for a better distribution of an increasingly scarce resource must, we must be able to predict transplant outcomes when defining the best allocation rules.pt_PT
dc.description.sponsorshipThis project received the “Antonio Morais Sarmento” research grant from the Portuguese Society of Transplantation.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationTranspl Immunol. 2022 Jun;72:101578. doi: 10.1016/j.trim.2022.101578. Epub 2022 Mar 9pt_PT
dc.identifier.doi10.1016/j.trim.2022.101578pt_PT
dc.identifier.issn0966-3274
dc.identifier.urihttp://hdl.handle.net/10400.18/8601
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0966327422000521pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectKidney Transplantationpt_PT
dc.subjectClinical Decision-makingpt_PT
dc.subjectAllocation Systempt_PT
dc.titleKidney allocation rules simulatorpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.startPage101578pt_PT
oaire.citation.titleTransplant Immunologypt_PT
oaire.citation.volume72pt_PT
rcaap.embargofctAcesso de acordo com política editorial da revista.pt_PT
rcaap.rightsembargoedAccesspt_PT
rcaap.typearticlept_PT

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