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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Main Authors: Matthieu Jamme, Quentin Raimbourg, Dominique Chauveau, Amélie Seguin, Claire Presne, Pierre Perez, Pierre Gobert, Alain Wynckel, François Provôt, Yahsou Delmas, Christiane Mousson, Aude Servais, Laurence Vrigneaud, Agnès Veyradier, Eric Rondeau, Paul Coppo, French Thrombotic Microangiopathies Reference Centre
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2017-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5436831?pdf=render
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spelling doaj-faaec435d4624cfd8f8a21d8416e2ff72020-11-25T02:12:28ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01125e017789410.1371/journal.pone.0177894Predictive features of chronic kidney disease in atypical haemolytic uremic syndrome.Matthieu JammeQuentin RaimbourgDominique ChauveauAmélie SeguinClaire PresnePierre PerezPierre GobertAlain WynckelFrançois ProvôtYahsou DelmasChristiane MoussonAude ServaisLaurence VrigneaudAgnès VeyradierEric RondeauPaul CoppoFrench Thrombotic Microangiopathies Reference CentreChronic 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/1.73m2 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.http://europepmc.org/articles/PMC5436831?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Matthieu Jamme
Quentin Raimbourg
Dominique Chauveau
Amélie Seguin
Claire Presne
Pierre Perez
Pierre Gobert
Alain Wynckel
François Provôt
Yahsou Delmas
Christiane Mousson
Aude Servais
Laurence Vrigneaud
Agnès Veyradier
Eric Rondeau
Paul Coppo
French Thrombotic Microangiopathies Reference Centre
spellingShingle Matthieu Jamme
Quentin Raimbourg
Dominique Chauveau
Amélie Seguin
Claire Presne
Pierre Perez
Pierre Gobert
Alain Wynckel
François Provôt
Yahsou Delmas
Christiane Mousson
Aude Servais
Laurence Vrigneaud
Agnès Veyradier
Eric Rondeau
Paul Coppo
French Thrombotic Microangiopathies Reference Centre
Predictive features of chronic kidney disease in atypical haemolytic uremic syndrome.
PLoS ONE
author_facet Matthieu Jamme
Quentin Raimbourg
Dominique Chauveau
Amélie Seguin
Claire Presne
Pierre Perez
Pierre Gobert
Alain Wynckel
François Provôt
Yahsou Delmas
Christiane Mousson
Aude Servais
Laurence Vrigneaud
Agnès Veyradier
Eric Rondeau
Paul Coppo
French Thrombotic Microangiopathies Reference Centre
author_sort Matthieu Jamme
title 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_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_sort predictive features of chronic kidney disease in atypical haemolytic uremic syndrome.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2017-01-01
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/1.73m2 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.
url http://europepmc.org/articles/PMC5436831?pdf=render
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