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Prediction of delayed graft function using different scoring algorithms: A single-center experience

AIM: To compare the performance of 3 published delayed graft function (DGF) calculators that compute the theoretical risk of DGF for each patient. METHODS: This single-center, retrospective study included 247 consecutive kidney transplants from a deceased donor. These kidney transplantations were pe...

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Autores principales: Michalak, Magda, Wouters, Kristien, Fransen, Erik, Hellemans, Rachel, Van Craenenbroeck, Amaryllis H, Couttenye, Marie M, Bracke, Bart, Ysebaert, Dirk K, Hartman, Vera, De Greef, Kathleen, Chapelle, Thiery, Roeyen, Geert, Van Beeumen, Gerda, Emonds, Marie-Paule, Abramowicz, Daniel, Bosmans, Jean-Louis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5661123/
https://www.ncbi.nlm.nih.gov/pubmed/29104860
http://dx.doi.org/10.5500/wjt.v7.i5.260
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author Michalak, Magda
Wouters, Kristien
Fransen, Erik
Hellemans, Rachel
Van Craenenbroeck, Amaryllis H
Couttenye, Marie M
Bracke, Bart
Ysebaert, Dirk K
Hartman, Vera
De Greef, Kathleen
Chapelle, Thiery
Roeyen, Geert
Van Beeumen, Gerda
Emonds, Marie-Paule
Abramowicz, Daniel
Bosmans, Jean-Louis
author_facet Michalak, Magda
Wouters, Kristien
Fransen, Erik
Hellemans, Rachel
Van Craenenbroeck, Amaryllis H
Couttenye, Marie M
Bracke, Bart
Ysebaert, Dirk K
Hartman, Vera
De Greef, Kathleen
Chapelle, Thiery
Roeyen, Geert
Van Beeumen, Gerda
Emonds, Marie-Paule
Abramowicz, Daniel
Bosmans, Jean-Louis
author_sort Michalak, Magda
collection PubMed
description AIM: To compare the performance of 3 published delayed graft function (DGF) calculators that compute the theoretical risk of DGF for each patient. METHODS: This single-center, retrospective study included 247 consecutive kidney transplants from a deceased donor. These kidney transplantations were performed at our institution between January 2003 and December 2012. We compared the occurrence of observed DGF in our cohort with the predicted DGF according to three different published calculators. The accuracy of the calculators was evaluated by means of the c-index (receiver operating characteristic curve). RESULTS: DGF occurred in 15.3% of the transplants under study. The c index of the Irish calculator provided an area under the curve (AUC) of 0.69 indicating an acceptable level of prediction, in contrast to the poor performance of the Jeldres nomogram (AUC = 0.54) and the Chapal nomogram (AUC = 0.51). With the Irish algorithm the predicted DGF risk and the observed DGF probabilities were close. The mean calculated DGF risk was significantly different between DGF-positive and DGF-negative subjects (P < 0.0001). However, at the level of the individual patient the calculated risk of DGF overlapped very widely with ranges from 10% to 51% for recipients with DGF and from 4% to 56% for those without DGF. The sensitivity, specificity and positive predictive value of a calculated DGF risk ≥ 30% with the Irish nomogram were 32%, 91% and 38%. CONCLUSION: Predictive models for DGF after kidney transplantation are performant in the population in which they were derived, but less so in external validations.
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spelling pubmed-56611232017-11-03 Prediction of delayed graft function using different scoring algorithms: A single-center experience Michalak, Magda Wouters, Kristien Fransen, Erik Hellemans, Rachel Van Craenenbroeck, Amaryllis H Couttenye, Marie M Bracke, Bart Ysebaert, Dirk K Hartman, Vera De Greef, Kathleen Chapelle, Thiery Roeyen, Geert Van Beeumen, Gerda Emonds, Marie-Paule Abramowicz, Daniel Bosmans, Jean-Louis World J Transplant Retrospective Cohort Study AIM: To compare the performance of 3 published delayed graft function (DGF) calculators that compute the theoretical risk of DGF for each patient. METHODS: This single-center, retrospective study included 247 consecutive kidney transplants from a deceased donor. These kidney transplantations were performed at our institution between January 2003 and December 2012. We compared the occurrence of observed DGF in our cohort with the predicted DGF according to three different published calculators. The accuracy of the calculators was evaluated by means of the c-index (receiver operating characteristic curve). RESULTS: DGF occurred in 15.3% of the transplants under study. The c index of the Irish calculator provided an area under the curve (AUC) of 0.69 indicating an acceptable level of prediction, in contrast to the poor performance of the Jeldres nomogram (AUC = 0.54) and the Chapal nomogram (AUC = 0.51). With the Irish algorithm the predicted DGF risk and the observed DGF probabilities were close. The mean calculated DGF risk was significantly different between DGF-positive and DGF-negative subjects (P < 0.0001). However, at the level of the individual patient the calculated risk of DGF overlapped very widely with ranges from 10% to 51% for recipients with DGF and from 4% to 56% for those without DGF. The sensitivity, specificity and positive predictive value of a calculated DGF risk ≥ 30% with the Irish nomogram were 32%, 91% and 38%. CONCLUSION: Predictive models for DGF after kidney transplantation are performant in the population in which they were derived, but less so in external validations. Baishideng Publishing Group Inc 2017-10-24 2017-10-24 /pmc/articles/PMC5661123/ /pubmed/29104860 http://dx.doi.org/10.5500/wjt.v7.i5.260 Text en ©The Author(s) 2017. Published by Baishideng Publishing Group Inc. All rights reserved. http://creativecommons.org/licenses/by-nc/4.0/ Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
spellingShingle Retrospective Cohort Study
Michalak, Magda
Wouters, Kristien
Fransen, Erik
Hellemans, Rachel
Van Craenenbroeck, Amaryllis H
Couttenye, Marie M
Bracke, Bart
Ysebaert, Dirk K
Hartman, Vera
De Greef, Kathleen
Chapelle, Thiery
Roeyen, Geert
Van Beeumen, Gerda
Emonds, Marie-Paule
Abramowicz, Daniel
Bosmans, Jean-Louis
Prediction of delayed graft function using different scoring algorithms: A single-center experience
title Prediction of delayed graft function using different scoring algorithms: A single-center experience
title_full Prediction of delayed graft function using different scoring algorithms: A single-center experience
title_fullStr Prediction of delayed graft function using different scoring algorithms: A single-center experience
title_full_unstemmed Prediction of delayed graft function using different scoring algorithms: A single-center experience
title_short Prediction of delayed graft function using different scoring algorithms: A single-center experience
title_sort prediction of delayed graft function using different scoring algorithms: a single-center experience
topic Retrospective Cohort Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5661123/
https://www.ncbi.nlm.nih.gov/pubmed/29104860
http://dx.doi.org/10.5500/wjt.v7.i5.260
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