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Comparative accuracy of biomarkers for the prediction of hospital-acquired acute kidney injury: a systematic review and meta-analysis
BACKGROUND: Several biomarkers have been proposed to predict the occurrence of acute kidney injury (AKI); however, their efficacy varies between different trials. The aim of this study was to compare the predictive performance of different candidate biomarkers for AKI. METHODS: In this systematic re...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9652605/ https://www.ncbi.nlm.nih.gov/pubmed/36371256 http://dx.doi.org/10.1186/s13054-022-04223-6 |
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author | Pan, Heng-Chih Yang, Shao-Yu Chiou, Terry Ting-Yu Shiao, Chih-Chung Wu, Che-Hsiung Huang, Chun-Te Wang, Tsai-Jung Chen, Jui-Yi Liao, Hung-Wei Chen, Sheng-Yin Huang, Tao-Min Yang, Ya-Fei Lin, Hugo You-Hsien Chan, Ming-Jen Sun, Chiao-Yin Chen, Yih-Ting Chen, Yung-Chang Wu, Vin-Cent |
author_facet | Pan, Heng-Chih Yang, Shao-Yu Chiou, Terry Ting-Yu Shiao, Chih-Chung Wu, Che-Hsiung Huang, Chun-Te Wang, Tsai-Jung Chen, Jui-Yi Liao, Hung-Wei Chen, Sheng-Yin Huang, Tao-Min Yang, Ya-Fei Lin, Hugo You-Hsien Chan, Ming-Jen Sun, Chiao-Yin Chen, Yih-Ting Chen, Yung-Chang Wu, Vin-Cent |
author_sort | Pan, Heng-Chih |
collection | PubMed |
description | BACKGROUND: Several biomarkers have been proposed to predict the occurrence of acute kidney injury (AKI); however, their efficacy varies between different trials. The aim of this study was to compare the predictive performance of different candidate biomarkers for AKI. METHODS: In this systematic review, we searched PubMed, Medline, Embase, and the Cochrane Library for papers published up to August 15, 2022. We selected all studies of adults (> 18 years) that reported the predictive performance of damage biomarkers (neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), liver-type fatty acid-binding protein (L-FABP)), inflammatory biomarker (interleukin-18 (IL-18)), and stress biomarker (tissue inhibitor of metalloproteinases-2 × insulin-like growth factor-binding protein-7 (TIMP-2 × IGFBP-7)) for the occurrence of AKI. We performed pairwise meta-analyses to calculate odds ratios (ORs) and 95% confidence intervals (CIs) individually. Hierarchical summary receiver operating characteristic curves (HSROCs) were used to summarize the pooled test performance, and the Grading of Recommendations, Assessment, Development and Evaluations criteria were used to appraise the quality of evidence. RESULTS: We identified 242 published relevant studies from 1,803 screened abstracts, of which 110 studies with 38,725 patients were included in this meta-analysis. Urinary NGAL/creatinine (diagnostic odds ratio [DOR] 16.2, 95% CI 10.1–25.9), urinary NGAL (DOR 13.8, 95% CI 10.2–18.8), and serum NGAL (DOR 12.6, 95% CI 9.3–17.3) had the best diagnostic accuracy for the risk of AKI. In subgroup analyses, urinary NGAL, urinary NGAL/creatinine, and serum NGAL had better diagnostic accuracy for AKI than urinary IL-18 in non-critically ill patients. However, all of the biomarkers had similar diagnostic accuracy in critically ill patients. In the setting of medical and non-sepsis patients, urinary NGAL had better predictive performance than urinary IL-18, urinary L-FABP, and urinary TIMP-2 × IGFBP-7: 0.3. In the surgical patients, urinary NGAL/creatinine and urinary KIM-1 had the best diagnostic accuracy. The HSROC values of urinary NGAL/creatinine, urinary NGAL, and serum NGAL were 91.4%, 85.2%, and 84.7%, respectively. CONCLUSIONS: Biomarkers containing NGAL had the best predictive accuracy for the occurrence of AKI, regardless of whether or not the values were adjusted by urinary creatinine, and especially in medically treated patients. However, the predictive performance of urinary NGAL was limited in surgical patients, and urinary NGAL/creatinine seemed to be the most accurate biomarkers in these patients. All of the biomarkers had similar predictive performance in critically ill patients. Trial registration CRD42020207883, October 06, 2020. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13054-022-04223-6. |
format | Online Article Text |
id | pubmed-9652605 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-96526052022-11-14 Comparative accuracy of biomarkers for the prediction of hospital-acquired acute kidney injury: a systematic review and meta-analysis Pan, Heng-Chih Yang, Shao-Yu Chiou, Terry Ting-Yu Shiao, Chih-Chung Wu, Che-Hsiung Huang, Chun-Te Wang, Tsai-Jung Chen, Jui-Yi Liao, Hung-Wei Chen, Sheng-Yin Huang, Tao-Min Yang, Ya-Fei Lin, Hugo You-Hsien Chan, Ming-Jen Sun, Chiao-Yin Chen, Yih-Ting Chen, Yung-Chang Wu, Vin-Cent Crit Care Research BACKGROUND: Several biomarkers have been proposed to predict the occurrence of acute kidney injury (AKI); however, their efficacy varies between different trials. The aim of this study was to compare the predictive performance of different candidate biomarkers for AKI. METHODS: In this systematic review, we searched PubMed, Medline, Embase, and the Cochrane Library for papers published up to August 15, 2022. We selected all studies of adults (> 18 years) that reported the predictive performance of damage biomarkers (neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), liver-type fatty acid-binding protein (L-FABP)), inflammatory biomarker (interleukin-18 (IL-18)), and stress biomarker (tissue inhibitor of metalloproteinases-2 × insulin-like growth factor-binding protein-7 (TIMP-2 × IGFBP-7)) for the occurrence of AKI. We performed pairwise meta-analyses to calculate odds ratios (ORs) and 95% confidence intervals (CIs) individually. Hierarchical summary receiver operating characteristic curves (HSROCs) were used to summarize the pooled test performance, and the Grading of Recommendations, Assessment, Development and Evaluations criteria were used to appraise the quality of evidence. RESULTS: We identified 242 published relevant studies from 1,803 screened abstracts, of which 110 studies with 38,725 patients were included in this meta-analysis. Urinary NGAL/creatinine (diagnostic odds ratio [DOR] 16.2, 95% CI 10.1–25.9), urinary NGAL (DOR 13.8, 95% CI 10.2–18.8), and serum NGAL (DOR 12.6, 95% CI 9.3–17.3) had the best diagnostic accuracy for the risk of AKI. In subgroup analyses, urinary NGAL, urinary NGAL/creatinine, and serum NGAL had better diagnostic accuracy for AKI than urinary IL-18 in non-critically ill patients. However, all of the biomarkers had similar diagnostic accuracy in critically ill patients. In the setting of medical and non-sepsis patients, urinary NGAL had better predictive performance than urinary IL-18, urinary L-FABP, and urinary TIMP-2 × IGFBP-7: 0.3. In the surgical patients, urinary NGAL/creatinine and urinary KIM-1 had the best diagnostic accuracy. The HSROC values of urinary NGAL/creatinine, urinary NGAL, and serum NGAL were 91.4%, 85.2%, and 84.7%, respectively. CONCLUSIONS: Biomarkers containing NGAL had the best predictive accuracy for the occurrence of AKI, regardless of whether or not the values were adjusted by urinary creatinine, and especially in medically treated patients. However, the predictive performance of urinary NGAL was limited in surgical patients, and urinary NGAL/creatinine seemed to be the most accurate biomarkers in these patients. All of the biomarkers had similar predictive performance in critically ill patients. Trial registration CRD42020207883, October 06, 2020. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13054-022-04223-6. BioMed Central 2022-11-12 /pmc/articles/PMC9652605/ /pubmed/36371256 http://dx.doi.org/10.1186/s13054-022-04223-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Pan, Heng-Chih Yang, Shao-Yu Chiou, Terry Ting-Yu Shiao, Chih-Chung Wu, Che-Hsiung Huang, Chun-Te Wang, Tsai-Jung Chen, Jui-Yi Liao, Hung-Wei Chen, Sheng-Yin Huang, Tao-Min Yang, Ya-Fei Lin, Hugo You-Hsien Chan, Ming-Jen Sun, Chiao-Yin Chen, Yih-Ting Chen, Yung-Chang Wu, Vin-Cent Comparative accuracy of biomarkers for the prediction of hospital-acquired acute kidney injury: a systematic review and meta-analysis |
title | Comparative accuracy of biomarkers for the prediction of hospital-acquired acute kidney injury: a systematic review and meta-analysis |
title_full | Comparative accuracy of biomarkers for the prediction of hospital-acquired acute kidney injury: a systematic review and meta-analysis |
title_fullStr | Comparative accuracy of biomarkers for the prediction of hospital-acquired acute kidney injury: a systematic review and meta-analysis |
title_full_unstemmed | Comparative accuracy of biomarkers for the prediction of hospital-acquired acute kidney injury: a systematic review and meta-analysis |
title_short | Comparative accuracy of biomarkers for the prediction of hospital-acquired acute kidney injury: a systematic review and meta-analysis |
title_sort | comparative accuracy of biomarkers for the prediction of hospital-acquired acute kidney injury: a systematic review and meta-analysis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9652605/ https://www.ncbi.nlm.nih.gov/pubmed/36371256 http://dx.doi.org/10.1186/s13054-022-04223-6 |
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