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Urinary π-glutathione S-transferase Predicts Advanced Acute Kidney Injury Following Cardiovascular Surgery
Urinary biomarkers augment the diagnosis of acute kidney injury (AKI), with AKI after cardiovascular surgeries being a prototype of prognosis scenario. Glutathione S-transferases (GST) were evaluated as biomarkers of AKI. Urine samples were collected in 141 cardiovascular surgical patients and analy...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4985825/ https://www.ncbi.nlm.nih.gov/pubmed/27527370 http://dx.doi.org/10.1038/srep26335 |
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author | Shu, Kai-Hsiang Wang, Chih-Hsien Wu, Che-Hsiung Huang, Tao-Min Wu, Pei-Chen Lai, Chien-Heng Tseng, Li-Jung Tsai, Pi-Ru Connolly, Rory Wu, Vin-Cent |
author_facet | Shu, Kai-Hsiang Wang, Chih-Hsien Wu, Che-Hsiung Huang, Tao-Min Wu, Pei-Chen Lai, Chien-Heng Tseng, Li-Jung Tsai, Pi-Ru Connolly, Rory Wu, Vin-Cent |
author_sort | Shu, Kai-Hsiang |
collection | PubMed |
description | Urinary biomarkers augment the diagnosis of acute kidney injury (AKI), with AKI after cardiovascular surgeries being a prototype of prognosis scenario. Glutathione S-transferases (GST) were evaluated as biomarkers of AKI. Urine samples were collected in 141 cardiovascular surgical patients and analyzed for urinary alpha-(α-) and pi-(π-) GSTs. The outcomes of advanced AKI (KDIGO stage 2, 3) and all-cause in-patient mortality, as composite outcome, were recorded. Areas under the receiver operator characteristic (ROC) curves and multivariate generalized additive model (GAM) were applied to predict outcomes. Thirty-eight (26.9%) patients had AKI, while 12 (8.5%) were with advanced AKI. Urinary π-GST differentiated patients with/without advanced AKI or composite outcome after surgery (p < 0.05 by generalized estimating equation). Urinary π-GST predicted advanced AKI at 3 hrs post-surgery (p = 0.033) and composite outcome (p = 0.009), while the corresponding ROC curve had AUC of 0.784 and 0.783. Using GAM, the cutoff value of 14.7 μg/L for π-GST showed the best performance to predict composite outcome. The addition of π-GST to the SOFA score improved risk stratification (total net reclassification index = 0.47). Thus, urinary π-GST levels predict advanced AKI or hospital mortality after cardiovascular surgery and improve in SOFA outcome assessment specific to AKI. |
format | Online Article Text |
id | pubmed-4985825 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-49858252016-08-22 Urinary π-glutathione S-transferase Predicts Advanced Acute Kidney Injury Following Cardiovascular Surgery Shu, Kai-Hsiang Wang, Chih-Hsien Wu, Che-Hsiung Huang, Tao-Min Wu, Pei-Chen Lai, Chien-Heng Tseng, Li-Jung Tsai, Pi-Ru Connolly, Rory Wu, Vin-Cent Sci Rep Article Urinary biomarkers augment the diagnosis of acute kidney injury (AKI), with AKI after cardiovascular surgeries being a prototype of prognosis scenario. Glutathione S-transferases (GST) were evaluated as biomarkers of AKI. Urine samples were collected in 141 cardiovascular surgical patients and analyzed for urinary alpha-(α-) and pi-(π-) GSTs. The outcomes of advanced AKI (KDIGO stage 2, 3) and all-cause in-patient mortality, as composite outcome, were recorded. Areas under the receiver operator characteristic (ROC) curves and multivariate generalized additive model (GAM) were applied to predict outcomes. Thirty-eight (26.9%) patients had AKI, while 12 (8.5%) were with advanced AKI. Urinary π-GST differentiated patients with/without advanced AKI or composite outcome after surgery (p < 0.05 by generalized estimating equation). Urinary π-GST predicted advanced AKI at 3 hrs post-surgery (p = 0.033) and composite outcome (p = 0.009), while the corresponding ROC curve had AUC of 0.784 and 0.783. Using GAM, the cutoff value of 14.7 μg/L for π-GST showed the best performance to predict composite outcome. The addition of π-GST to the SOFA score improved risk stratification (total net reclassification index = 0.47). Thus, urinary π-GST levels predict advanced AKI or hospital mortality after cardiovascular surgery and improve in SOFA outcome assessment specific to AKI. Nature Publishing Group 2016-08-16 /pmc/articles/PMC4985825/ /pubmed/27527370 http://dx.doi.org/10.1038/srep26335 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Shu, Kai-Hsiang Wang, Chih-Hsien Wu, Che-Hsiung Huang, Tao-Min Wu, Pei-Chen Lai, Chien-Heng Tseng, Li-Jung Tsai, Pi-Ru Connolly, Rory Wu, Vin-Cent Urinary π-glutathione S-transferase Predicts Advanced Acute Kidney Injury Following Cardiovascular Surgery |
title | Urinary π-glutathione S-transferase Predicts Advanced Acute Kidney Injury Following Cardiovascular Surgery |
title_full | Urinary π-glutathione S-transferase Predicts Advanced Acute Kidney Injury Following Cardiovascular Surgery |
title_fullStr | Urinary π-glutathione S-transferase Predicts Advanced Acute Kidney Injury Following Cardiovascular Surgery |
title_full_unstemmed | Urinary π-glutathione S-transferase Predicts Advanced Acute Kidney Injury Following Cardiovascular Surgery |
title_short | Urinary π-glutathione S-transferase Predicts Advanced Acute Kidney Injury Following Cardiovascular Surgery |
title_sort | urinary π-glutathione s-transferase predicts advanced acute kidney injury following cardiovascular surgery |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4985825/ https://www.ncbi.nlm.nih.gov/pubmed/27527370 http://dx.doi.org/10.1038/srep26335 |
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