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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...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2017
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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. |
format | Online Article Text |
id | pubmed-5661123 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
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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