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Predictive features of chronic kidney disease in atypical haemolytic uremic syndrome

Chronic kidney disease (CKD) is a frequent and serious complication of atypical haemolytic uremic syndrome (aHUS). We aimed to develop a simple accurate model to predict the risk of renal dysfunction in aHUS based on clinical and biological features available at hospital admission. Renal function at...

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Autores principales: Jamme, Matthieu, Raimbourg, Quentin, Chauveau, Dominique, Seguin, Amélie, Presne, Claire, Perez, Pierre, Gobert, Pierre, Wynckel, Alain, Provôt, François, Delmas, Yahsou, Mousson, Christiane, Servais, Aude, Vrigneaud, Laurence, Veyradier, Agnès, Rondeau, Eric, Coppo, Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5436831/
https://www.ncbi.nlm.nih.gov/pubmed/28542627
http://dx.doi.org/10.1371/journal.pone.0177894
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author Jamme, Matthieu
Raimbourg, Quentin
Chauveau, Dominique
Seguin, Amélie
Presne, Claire
Perez, Pierre
Gobert, Pierre
Wynckel, Alain
Provôt, François
Delmas, Yahsou
Mousson, Christiane
Servais, Aude
Vrigneaud, Laurence
Veyradier, Agnès
Rondeau, Eric
Coppo, Paul
author_facet Jamme, Matthieu
Raimbourg, Quentin
Chauveau, Dominique
Seguin, Amélie
Presne, Claire
Perez, Pierre
Gobert, Pierre
Wynckel, Alain
Provôt, François
Delmas, Yahsou
Mousson, Christiane
Servais, Aude
Vrigneaud, Laurence
Veyradier, Agnès
Rondeau, Eric
Coppo, Paul
author_sort Jamme, Matthieu
collection PubMed
description Chronic kidney disease (CKD) is a frequent and serious complication of atypical haemolytic uremic syndrome (aHUS). We aimed to develop a simple accurate model to predict the risk of renal dysfunction in aHUS based on clinical and biological features available at hospital admission. Renal function at 1-year follow-up, based on an estimated glomerular filtration rate < 60mL/min/1.73m(2) as assessed by the Modification of Diet in Renal Disease equation, was used as an indicator of significant CKD. Prospectively collected data from a cohort of 156 aHUS patients who did not receive eculizumab were used to identify predictors of CKD. Covariates associated with renal impairment were identified by multivariate analysis. The model performance was assessed and a scoring system for clinical practice was constructed from the regression coefficient. Multivariate analyses identified three predictors of CKD: a high serum creatinine level, a high mean arterial pressure and a mildly decreased platelet count. The prognostic model had a good discriminative ability (area under the curve = .84). The scoring system ranged from 0 to 5, with corresponding risks of CKD ranging from 18% to 100%. This model accurately predicts development of 1-year CKD in patients with aHUS using clinical and biological features available on admission. After further validation, this model may assist in clinical decision making.
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spelling pubmed-54368312017-05-27 Predictive features of chronic kidney disease in atypical haemolytic uremic syndrome Jamme, Matthieu Raimbourg, Quentin Chauveau, Dominique Seguin, Amélie Presne, Claire Perez, Pierre Gobert, Pierre Wynckel, Alain Provôt, François Delmas, Yahsou Mousson, Christiane Servais, Aude Vrigneaud, Laurence Veyradier, Agnès Rondeau, Eric Coppo, Paul PLoS One Research Article Chronic kidney disease (CKD) is a frequent and serious complication of atypical haemolytic uremic syndrome (aHUS). We aimed to develop a simple accurate model to predict the risk of renal dysfunction in aHUS based on clinical and biological features available at hospital admission. Renal function at 1-year follow-up, based on an estimated glomerular filtration rate < 60mL/min/1.73m(2) as assessed by the Modification of Diet in Renal Disease equation, was used as an indicator of significant CKD. Prospectively collected data from a cohort of 156 aHUS patients who did not receive eculizumab were used to identify predictors of CKD. Covariates associated with renal impairment were identified by multivariate analysis. The model performance was assessed and a scoring system for clinical practice was constructed from the regression coefficient. Multivariate analyses identified three predictors of CKD: a high serum creatinine level, a high mean arterial pressure and a mildly decreased platelet count. The prognostic model had a good discriminative ability (area under the curve = .84). The scoring system ranged from 0 to 5, with corresponding risks of CKD ranging from 18% to 100%. This model accurately predicts development of 1-year CKD in patients with aHUS using clinical and biological features available on admission. After further validation, this model may assist in clinical decision making. Public Library of Science 2017-05-18 /pmc/articles/PMC5436831/ /pubmed/28542627 http://dx.doi.org/10.1371/journal.pone.0177894 Text en © 2017 Jamme et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Jamme, Matthieu
Raimbourg, Quentin
Chauveau, Dominique
Seguin, Amélie
Presne, Claire
Perez, Pierre
Gobert, Pierre
Wynckel, Alain
Provôt, François
Delmas, Yahsou
Mousson, Christiane
Servais, Aude
Vrigneaud, Laurence
Veyradier, Agnès
Rondeau, Eric
Coppo, Paul
Predictive features of chronic kidney disease in atypical haemolytic uremic syndrome
title Predictive features of chronic kidney disease in atypical haemolytic uremic syndrome
title_full Predictive features of chronic kidney disease in atypical haemolytic uremic syndrome
title_fullStr Predictive features of chronic kidney disease in atypical haemolytic uremic syndrome
title_full_unstemmed Predictive features of chronic kidney disease in atypical haemolytic uremic syndrome
title_short Predictive features of chronic kidney disease in atypical haemolytic uremic syndrome
title_sort predictive features of chronic kidney disease in atypical haemolytic uremic syndrome
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5436831/
https://www.ncbi.nlm.nih.gov/pubmed/28542627
http://dx.doi.org/10.1371/journal.pone.0177894
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