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Preoperative risk assessment improves biomarker detection for predicting acute kidney injury after cardiac surgery
BACKGROUND: Although urinary neutrophil gelatinase-associated lipocalin (NGAL) has emerged as a promising biomarker for the early detection of kidney injury, previous studies of adult patients who underwent cardiac surgery have reported only moderate discrimination. The age, creatinine, and ejection...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6122821/ https://www.ncbi.nlm.nih.gov/pubmed/30180211 http://dx.doi.org/10.1371/journal.pone.0203447 |
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author | Lee, Cheng-Chia Chang, Chih-Hsiang Chen, Shao-Wei Fan, Pei-Chun Chang, Su-Wei Chen, Yi-Ting Nan, Yu-Yun Lin, Pyng-Jing Tsai, Feng-Chun |
author_facet | Lee, Cheng-Chia Chang, Chih-Hsiang Chen, Shao-Wei Fan, Pei-Chun Chang, Su-Wei Chen, Yi-Ting Nan, Yu-Yun Lin, Pyng-Jing Tsai, Feng-Chun |
author_sort | Lee, Cheng-Chia |
collection | PubMed |
description | BACKGROUND: Although urinary neutrophil gelatinase-associated lipocalin (NGAL) has emerged as a promising biomarker for the early detection of kidney injury, previous studies of adult patients who underwent cardiac surgery have reported only moderate discrimination. The age, creatinine, and ejection fraction (ACEF) score is a preoperative validated risk model with satisfactory accuracy for predicting AKI following cardiac surgery. It remains unknown whether combining preoperative risk assessment through ACEF scores followed by urinary NGAL test in a population of high-risk individuals is an optimal approach with improved predictive performance. MATERIAL AND METHODS: A total of 177 consecutive patients who underwent cardiac surgery were enrolled. Clinical characteristics, prognostic model scores, and outcomes were assessed. Urinary NGAL were examined within 6 hours after cardiac surgery. Patients were stratified according to preoperative ACEF scores, and comparisons were made using the area under the receiver operator characteristic curve (AUROC) for the prediction of AKI. RESULTS: A total of 45.8% (81/177) of the patients had AKI. As expected, patients with ACEF scores ≥ 1.1 were older and more likely to have class III or IV heart failure. They were also more likely to have diabetes mellitus, myocardial infarction, and peripheral arterial disease. Urinary NGAL alone moderately predicted AKI, with an AUROC of 0.732. Risk stratification by ACEF scores ≥ 1.1 substantially improved the AUROC of urinary NGAL to 0.873 (95% confidence interval, 0.784–0.961; P < .001). CONCLUSIONS: Risk stratification by preoperative ACEF scores ≥ 1.1, followed by postoperative urinary NGAL, provides more satisfactory risk discrimination than does urinary NGAL alone for the early detection of AKI after cardiac surgery. Future studies should investigate whether this strategy could improve the outcomes and cost-effectiveness of care in patients undergoing cardiac surgery. |
format | Online Article Text |
id | pubmed-6122821 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-61228212018-09-16 Preoperative risk assessment improves biomarker detection for predicting acute kidney injury after cardiac surgery Lee, Cheng-Chia Chang, Chih-Hsiang Chen, Shao-Wei Fan, Pei-Chun Chang, Su-Wei Chen, Yi-Ting Nan, Yu-Yun Lin, Pyng-Jing Tsai, Feng-Chun PLoS One Research Article BACKGROUND: Although urinary neutrophil gelatinase-associated lipocalin (NGAL) has emerged as a promising biomarker for the early detection of kidney injury, previous studies of adult patients who underwent cardiac surgery have reported only moderate discrimination. The age, creatinine, and ejection fraction (ACEF) score is a preoperative validated risk model with satisfactory accuracy for predicting AKI following cardiac surgery. It remains unknown whether combining preoperative risk assessment through ACEF scores followed by urinary NGAL test in a population of high-risk individuals is an optimal approach with improved predictive performance. MATERIAL AND METHODS: A total of 177 consecutive patients who underwent cardiac surgery were enrolled. Clinical characteristics, prognostic model scores, and outcomes were assessed. Urinary NGAL were examined within 6 hours after cardiac surgery. Patients were stratified according to preoperative ACEF scores, and comparisons were made using the area under the receiver operator characteristic curve (AUROC) for the prediction of AKI. RESULTS: A total of 45.8% (81/177) of the patients had AKI. As expected, patients with ACEF scores ≥ 1.1 were older and more likely to have class III or IV heart failure. They were also more likely to have diabetes mellitus, myocardial infarction, and peripheral arterial disease. Urinary NGAL alone moderately predicted AKI, with an AUROC of 0.732. Risk stratification by ACEF scores ≥ 1.1 substantially improved the AUROC of urinary NGAL to 0.873 (95% confidence interval, 0.784–0.961; P < .001). CONCLUSIONS: Risk stratification by preoperative ACEF scores ≥ 1.1, followed by postoperative urinary NGAL, provides more satisfactory risk discrimination than does urinary NGAL alone for the early detection of AKI after cardiac surgery. Future studies should investigate whether this strategy could improve the outcomes and cost-effectiveness of care in patients undergoing cardiac surgery. Public Library of Science 2018-09-04 /pmc/articles/PMC6122821/ /pubmed/30180211 http://dx.doi.org/10.1371/journal.pone.0203447 Text en © 2018 Lee 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 Lee, Cheng-Chia Chang, Chih-Hsiang Chen, Shao-Wei Fan, Pei-Chun Chang, Su-Wei Chen, Yi-Ting Nan, Yu-Yun Lin, Pyng-Jing Tsai, Feng-Chun Preoperative risk assessment improves biomarker detection for predicting acute kidney injury after cardiac surgery |
title | Preoperative risk assessment improves biomarker detection for predicting acute kidney injury after cardiac surgery |
title_full | Preoperative risk assessment improves biomarker detection for predicting acute kidney injury after cardiac surgery |
title_fullStr | Preoperative risk assessment improves biomarker detection for predicting acute kidney injury after cardiac surgery |
title_full_unstemmed | Preoperative risk assessment improves biomarker detection for predicting acute kidney injury after cardiac surgery |
title_short | Preoperative risk assessment improves biomarker detection for predicting acute kidney injury after cardiac surgery |
title_sort | preoperative risk assessment improves biomarker detection for predicting acute kidney injury after cardiac surgery |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6122821/ https://www.ncbi.nlm.nih.gov/pubmed/30180211 http://dx.doi.org/10.1371/journal.pone.0203447 |
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