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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
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.
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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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