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Biomarkers for prediction of renal replacement therapy in acute kidney injury: a systematic review and meta-analysis
PURPOSE: Acute kidney injury (AKI) frequently occurs in critically ill patients and often precipitates use of renal replacement therapy (RRT). However, the ideal circumstances for whether and when to start RRT remain unclear. We performed evidence synthesis of the available literature to evaluate th...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5861176/ https://www.ncbi.nlm.nih.gov/pubmed/29541790 http://dx.doi.org/10.1007/s00134-018-5126-8 |
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author | Klein, Sebastian J. Brandtner, Anna K. Lehner, Georg F. Ulmer, Hanno Bagshaw, Sean M. Wiedermann, Christian J. Joannidis, Michael |
author_facet | Klein, Sebastian J. Brandtner, Anna K. Lehner, Georg F. Ulmer, Hanno Bagshaw, Sean M. Wiedermann, Christian J. Joannidis, Michael |
author_sort | Klein, Sebastian J. |
collection | PubMed |
description | PURPOSE: Acute kidney injury (AKI) frequently occurs in critically ill patients and often precipitates use of renal replacement therapy (RRT). However, the ideal circumstances for whether and when to start RRT remain unclear. We performed evidence synthesis of the available literature to evaluate the value of biomarkers to predict receipt of RRT for AKI. METHODS: We conducted a PRISMA-guided systematic review and meta-analysis including all trials evaluating biomarker performance for prediction of RRT in AKI. A systematic search was applied in MEDLINE, Embase, and CENTRAL databases from inception to September 2017. All studies reporting an area under the curve (AUC) for a biomarker to predict initiation of RRT were included. RESULTS: Sixty-three studies comprising 15,928 critically ill patients (median per study 122.5 [31–1439]) met eligibility. Forty-one studies evaluating 13 different biomarkers were included. Of these biomarkers, neutrophil gelatinase-associated lipocalin (NGAL) had the largest body of evidence. The pooled AUCs for urine and blood NGAL were 0.720 (95% CI 0.638–0.803) and 0.755 (0.706–0.803), respectively. Blood creatinine and cystatin C had pooled AUCs of 0.764 (0.732–0.796) and 0.768 (0.729–0.807), respectively. For urine biomarkers, interleukin-18, cystatin C, and the product of tissue inhibitor of metalloproteinase-2 and insulin growth factor binding protein-7 showed pooled AUCs of 0.668 (0.606–0.729), 0.722 (0.575–0.868), and 0.857 (0.789–0.925), respectively. CONCLUSION: Though several biomarkers showed promise and reasonable prediction of RRT use for critically ill patients with AKI, the strength of evidence currently precludes their routine use to guide decision-making on when to initiate RRT. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00134-018-5126-8) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5861176 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-58611762018-03-22 Biomarkers for prediction of renal replacement therapy in acute kidney injury: a systematic review and meta-analysis Klein, Sebastian J. Brandtner, Anna K. Lehner, Georg F. Ulmer, Hanno Bagshaw, Sean M. Wiedermann, Christian J. Joannidis, Michael Intensive Care Med Systematic Review PURPOSE: Acute kidney injury (AKI) frequently occurs in critically ill patients and often precipitates use of renal replacement therapy (RRT). However, the ideal circumstances for whether and when to start RRT remain unclear. We performed evidence synthesis of the available literature to evaluate the value of biomarkers to predict receipt of RRT for AKI. METHODS: We conducted a PRISMA-guided systematic review and meta-analysis including all trials evaluating biomarker performance for prediction of RRT in AKI. A systematic search was applied in MEDLINE, Embase, and CENTRAL databases from inception to September 2017. All studies reporting an area under the curve (AUC) for a biomarker to predict initiation of RRT were included. RESULTS: Sixty-three studies comprising 15,928 critically ill patients (median per study 122.5 [31–1439]) met eligibility. Forty-one studies evaluating 13 different biomarkers were included. Of these biomarkers, neutrophil gelatinase-associated lipocalin (NGAL) had the largest body of evidence. The pooled AUCs for urine and blood NGAL were 0.720 (95% CI 0.638–0.803) and 0.755 (0.706–0.803), respectively. Blood creatinine and cystatin C had pooled AUCs of 0.764 (0.732–0.796) and 0.768 (0.729–0.807), respectively. For urine biomarkers, interleukin-18, cystatin C, and the product of tissue inhibitor of metalloproteinase-2 and insulin growth factor binding protein-7 showed pooled AUCs of 0.668 (0.606–0.729), 0.722 (0.575–0.868), and 0.857 (0.789–0.925), respectively. CONCLUSION: Though several biomarkers showed promise and reasonable prediction of RRT use for critically ill patients with AKI, the strength of evidence currently precludes their routine use to guide decision-making on when to initiate RRT. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00134-018-5126-8) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2018-03-14 2018 /pmc/articles/PMC5861176/ /pubmed/29541790 http://dx.doi.org/10.1007/s00134-018-5126-8 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Systematic Review Klein, Sebastian J. Brandtner, Anna K. Lehner, Georg F. Ulmer, Hanno Bagshaw, Sean M. Wiedermann, Christian J. Joannidis, Michael Biomarkers for prediction of renal replacement therapy in acute kidney injury: a systematic review and meta-analysis |
title | Biomarkers for prediction of renal replacement therapy in acute kidney injury: a systematic review and meta-analysis |
title_full | Biomarkers for prediction of renal replacement therapy in acute kidney injury: a systematic review and meta-analysis |
title_fullStr | Biomarkers for prediction of renal replacement therapy in acute kidney injury: a systematic review and meta-analysis |
title_full_unstemmed | Biomarkers for prediction of renal replacement therapy in acute kidney injury: a systematic review and meta-analysis |
title_short | Biomarkers for prediction of renal replacement therapy in acute kidney injury: a systematic review and meta-analysis |
title_sort | biomarkers for prediction of renal replacement therapy in acute kidney injury: a systematic review and meta-analysis |
topic | Systematic Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5861176/ https://www.ncbi.nlm.nih.gov/pubmed/29541790 http://dx.doi.org/10.1007/s00134-018-5126-8 |
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