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Evaluation of 32 urine biomarkers to predict the progression of acute kidney injury after cardiac surgery

Biomarkers for acute kidney injury (AKI) have been used to predict the progression of AKI but a systematic comparison of the prognostic ability of each biomarkers alone or in combination has not been performed. In order to assess this, we measured the concentration of 32 candidate biomarkers in the...

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Autores principales: Arthur, John M., Hill, Elizabeth G., Alge, Joseph L., Lewis, Evelyn C., Neely, Benjamin A., Janech, Michael G, Tumlin, James A., Chawla, Lakhmir S., Shaw, Andrew D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3880389/
https://www.ncbi.nlm.nih.gov/pubmed/24005224
http://dx.doi.org/10.1038/ki.2013.333
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author Arthur, John M.
Hill, Elizabeth G.
Alge, Joseph L.
Lewis, Evelyn C.
Neely, Benjamin A.
Janech, Michael G
Tumlin, James A.
Chawla, Lakhmir S.
Shaw, Andrew D.
author_facet Arthur, John M.
Hill, Elizabeth G.
Alge, Joseph L.
Lewis, Evelyn C.
Neely, Benjamin A.
Janech, Michael G
Tumlin, James A.
Chawla, Lakhmir S.
Shaw, Andrew D.
author_sort Arthur, John M.
collection PubMed
description Biomarkers for acute kidney injury (AKI) have been used to predict the progression of AKI but a systematic comparison of the prognostic ability of each biomarkers alone or in combination has not been performed. In order to assess this, we measured the concentration of 32 candidate biomarkers in the urine of 95 patients with AKIN stage 1 after cardiac surgery. Urine markers were divided into eight groups based on the putative pathophysiologic mechanism they reflect. We then compared the ability of the markers alone or in combination to predict the primary outcome of worsening AKI or death (23 patients) and the secondary outcome of AKIN stage 3 or death (13 patients). IL-18 was the best predictor of both outcomes (AUC of 0.74 and 0.89). L-FABP (AUC of 0.67 and 0.85), NGAL (AUC of 0.72 and 0.83) and KIM-1 (AUC of 0.73 and 0.81) were also good predictors. Correlation between most of the markers was generally related to their predictive ability but KIM-1 had a relatively weak correlation with other markers. The combination of IL-18 and KIM-1 had a very good predictive value with an AUC of 0.93 to predict AKIN 3 or death. Thus, combination of IL-18 and KIM-1 would result in improved identification of high risk patients for enrollment in clinical trials.
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spelling pubmed-38803892014-08-01 Evaluation of 32 urine biomarkers to predict the progression of acute kidney injury after cardiac surgery Arthur, John M. Hill, Elizabeth G. Alge, Joseph L. Lewis, Evelyn C. Neely, Benjamin A. Janech, Michael G Tumlin, James A. Chawla, Lakhmir S. Shaw, Andrew D. Kidney Int Article Biomarkers for acute kidney injury (AKI) have been used to predict the progression of AKI but a systematic comparison of the prognostic ability of each biomarkers alone or in combination has not been performed. In order to assess this, we measured the concentration of 32 candidate biomarkers in the urine of 95 patients with AKIN stage 1 after cardiac surgery. Urine markers were divided into eight groups based on the putative pathophysiologic mechanism they reflect. We then compared the ability of the markers alone or in combination to predict the primary outcome of worsening AKI or death (23 patients) and the secondary outcome of AKIN stage 3 or death (13 patients). IL-18 was the best predictor of both outcomes (AUC of 0.74 and 0.89). L-FABP (AUC of 0.67 and 0.85), NGAL (AUC of 0.72 and 0.83) and KIM-1 (AUC of 0.73 and 0.81) were also good predictors. Correlation between most of the markers was generally related to their predictive ability but KIM-1 had a relatively weak correlation with other markers. The combination of IL-18 and KIM-1 had a very good predictive value with an AUC of 0.93 to predict AKIN 3 or death. Thus, combination of IL-18 and KIM-1 would result in improved identification of high risk patients for enrollment in clinical trials. 2013-09-04 2014-02 /pmc/articles/PMC3880389/ /pubmed/24005224 http://dx.doi.org/10.1038/ki.2013.333 Text en http://www.nature.com/authors/editorial_policies/license.html#terms Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Arthur, John M.
Hill, Elizabeth G.
Alge, Joseph L.
Lewis, Evelyn C.
Neely, Benjamin A.
Janech, Michael G
Tumlin, James A.
Chawla, Lakhmir S.
Shaw, Andrew D.
Evaluation of 32 urine biomarkers to predict the progression of acute kidney injury after cardiac surgery
title Evaluation of 32 urine biomarkers to predict the progression of acute kidney injury after cardiac surgery
title_full Evaluation of 32 urine biomarkers to predict the progression of acute kidney injury after cardiac surgery
title_fullStr Evaluation of 32 urine biomarkers to predict the progression of acute kidney injury after cardiac surgery
title_full_unstemmed Evaluation of 32 urine biomarkers to predict the progression of acute kidney injury after cardiac surgery
title_short Evaluation of 32 urine biomarkers to predict the progression of acute kidney injury after cardiac surgery
title_sort evaluation of 32 urine biomarkers to predict the progression of acute kidney injury after cardiac surgery
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3880389/
https://www.ncbi.nlm.nih.gov/pubmed/24005224
http://dx.doi.org/10.1038/ki.2013.333
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