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Kinetic GFR Outperforms CKD-EPI for Slow Graft Function Prediction in the Immediate Postoperative Period Following Kidney Transplantation
Background: Rapid identification of patients at high risk for slow graft function (SGF) is of major importance in the immediate period following renal graft transplantation, both for early therapeutic decisions and long-term prognosis. Due to the high variability of serum creatinine levels after sur...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7763889/ https://www.ncbi.nlm.nih.gov/pubmed/33322021 http://dx.doi.org/10.3390/jcm9124003 |
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author | Dash, Jonathan Verissimo, Thomas Faivre, Anna Berchtold, Lena Berney, Thierry Pugin, Jérôme de Seigneux, Sophie Legouis, David |
author_facet | Dash, Jonathan Verissimo, Thomas Faivre, Anna Berchtold, Lena Berney, Thierry Pugin, Jérôme de Seigneux, Sophie Legouis, David |
author_sort | Dash, Jonathan |
collection | PubMed |
description | Background: Rapid identification of patients at high risk for slow graft function (SGF) is of major importance in the immediate period following renal graft transplantation, both for early therapeutic decisions and long-term prognosis. Due to the high variability of serum creatinine levels after surgery, glomerular filtration rate (GFR) estimation is challenging. In this situation, kinetic estimated GFR (KeGFR) equations are interesting tools but have never been assessed for the identification of SGF patients. Methods: We conducted a single-center retrospective cohort study, including all consecutive kidney allograft recipients in the University Hospitals of Geneva from 2008 to 2016. GFR was estimated using both CKD-EPI and KeGFR formulae. Their accuracies for SGF prediction were compared. Patients were followed up for one year after transplantation. Results: A total of 326 kidney recipients were analyzed. SGF occurred in 76 (23%) patients. KeGFR estimation stabilized from the day following kidney transplantation, more rapidly than CKD-EPI. Discrimination ability for SGF prediction was better for KeGFR than CKD-EPI (AUC 0.82 and 0.66, p < 0.001, respectively). Conclusion: KeGFR computed from the first day after renal transplantation was able to predict SGF with good discrimination, outperforming CKD-EPI estimation. SGF patients had lower renal graft function overall at the one-year follow up. |
format | Online Article Text |
id | pubmed-7763889 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-77638892020-12-27 Kinetic GFR Outperforms CKD-EPI for Slow Graft Function Prediction in the Immediate Postoperative Period Following Kidney Transplantation Dash, Jonathan Verissimo, Thomas Faivre, Anna Berchtold, Lena Berney, Thierry Pugin, Jérôme de Seigneux, Sophie Legouis, David J Clin Med Article Background: Rapid identification of patients at high risk for slow graft function (SGF) is of major importance in the immediate period following renal graft transplantation, both for early therapeutic decisions and long-term prognosis. Due to the high variability of serum creatinine levels after surgery, glomerular filtration rate (GFR) estimation is challenging. In this situation, kinetic estimated GFR (KeGFR) equations are interesting tools but have never been assessed for the identification of SGF patients. Methods: We conducted a single-center retrospective cohort study, including all consecutive kidney allograft recipients in the University Hospitals of Geneva from 2008 to 2016. GFR was estimated using both CKD-EPI and KeGFR formulae. Their accuracies for SGF prediction were compared. Patients were followed up for one year after transplantation. Results: A total of 326 kidney recipients were analyzed. SGF occurred in 76 (23%) patients. KeGFR estimation stabilized from the day following kidney transplantation, more rapidly than CKD-EPI. Discrimination ability for SGF prediction was better for KeGFR than CKD-EPI (AUC 0.82 and 0.66, p < 0.001, respectively). Conclusion: KeGFR computed from the first day after renal transplantation was able to predict SGF with good discrimination, outperforming CKD-EPI estimation. SGF patients had lower renal graft function overall at the one-year follow up. MDPI 2020-12-10 /pmc/articles/PMC7763889/ /pubmed/33322021 http://dx.doi.org/10.3390/jcm9124003 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Dash, Jonathan Verissimo, Thomas Faivre, Anna Berchtold, Lena Berney, Thierry Pugin, Jérôme de Seigneux, Sophie Legouis, David Kinetic GFR Outperforms CKD-EPI for Slow Graft Function Prediction in the Immediate Postoperative Period Following Kidney Transplantation |
title | Kinetic GFR Outperforms CKD-EPI for Slow Graft Function Prediction in the Immediate Postoperative Period Following Kidney Transplantation |
title_full | Kinetic GFR Outperforms CKD-EPI for Slow Graft Function Prediction in the Immediate Postoperative Period Following Kidney Transplantation |
title_fullStr | Kinetic GFR Outperforms CKD-EPI for Slow Graft Function Prediction in the Immediate Postoperative Period Following Kidney Transplantation |
title_full_unstemmed | Kinetic GFR Outperforms CKD-EPI for Slow Graft Function Prediction in the Immediate Postoperative Period Following Kidney Transplantation |
title_short | Kinetic GFR Outperforms CKD-EPI for Slow Graft Function Prediction in the Immediate Postoperative Period Following Kidney Transplantation |
title_sort | kinetic gfr outperforms ckd-epi for slow graft function prediction in the immediate postoperative period following kidney transplantation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7763889/ https://www.ncbi.nlm.nih.gov/pubmed/33322021 http://dx.doi.org/10.3390/jcm9124003 |
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