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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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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