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Combining renal cell arrest and damage biomarkers to predict progressive AKI in patient with sepsis
BACKGROUND: Sepsis is the most common trigger for AKI and up to 40% of mild or moderate septic AKI would progress to more severe AKI, which is associated with significantly increased risk for death and later CKD/ESRD. Early identifying high risk patients for AKI progression is a major challenge in p...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8672478/ https://www.ncbi.nlm.nih.gov/pubmed/34906098 http://dx.doi.org/10.1186/s12882-021-02611-8 |
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author | Tao, Xiaolei Chen, Chunbo Luo, Weihong Zhou, Jing Tian, Jianwei Yang, Xiaobing Hou, Fan Fan |
author_facet | Tao, Xiaolei Chen, Chunbo Luo, Weihong Zhou, Jing Tian, Jianwei Yang, Xiaobing Hou, Fan Fan |
author_sort | Tao, Xiaolei |
collection | PubMed |
description | BACKGROUND: Sepsis is the most common trigger for AKI and up to 40% of mild or moderate septic AKI would progress to more severe AKI, which is associated with significantly increased risk for death and later CKD/ESRD. Early identifying high risk patients for AKI progression is a major challenge in patients with septic AKI. METHODS: This is a prospective, multicenter cohort study which enrolled adult patients with sepsis and initially developed stage 1 or 2 AKI in the intensive care unit from January 2014 to March 2018. AKI was diagnosed and staged according to 2012 KDIGO-AKI guidelines. Renal cell arrest biomarkers (urinary TIMP2*IGFBP7, u[TIMP-2]*[IGFBP7]) and renal damage biomarkers (urinary KIM-1[uKIM-1] and urinary IL-18 [uIL-18]) were measured at time of AKI clinical diagnosis, and the performance of biomarkers for predicting septic AKI progression alone or in combination were evaluated. The primary outcome was AKI progression defined as worsening of AKI stage. The secondary outcome was AKI progression with subsequent death during hospitalization. RESULTS: Among 433 screened patients, 149 patients with sepsis and stage 1 or 2 AKI were included, in which 63 patients developed progressive AKI and 49 patients subsequently died during hospitalization. u[TIMP-2]*[IGFBP7], uKIM-1 and uIL-18 independently predicted the progression of septic AKI in which u[TIMP-2]*[IGFBP7] showed the greatest AUC (0.745; 95%CI, 0.667-0.823) as compared to uKIM-1 (AUC 0.719; 95%CI 0.638-0.800) and uIL-18 (AUC 0.619; 95%CI 0.525-0.731). Combination of u[TIMP-2]*[IGFBP7] with uKIM-1 improved the performance of predicting septic AKI progression with AUC of 0.752. u[TIMP-2]*[IGFBP7], alone or combined with uKIM-1/uIL-18, improved the risk reclassification over the clinical risk factor model alone both for the primary and secondary outcomes, as evidenced by significant category-free net reclassification index. CONCLUSIONS: Combination of renal cell arrest and damage biomarkers enhanced the prediction of AKI progression in patients with sepsis and improved risk reclassification over the clinical risk factors. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12882-021-02611-8. |
format | Online Article Text |
id | pubmed-8672478 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-86724782021-12-15 Combining renal cell arrest and damage biomarkers to predict progressive AKI in patient with sepsis Tao, Xiaolei Chen, Chunbo Luo, Weihong Zhou, Jing Tian, Jianwei Yang, Xiaobing Hou, Fan Fan BMC Nephrol Research Article BACKGROUND: Sepsis is the most common trigger for AKI and up to 40% of mild or moderate septic AKI would progress to more severe AKI, which is associated with significantly increased risk for death and later CKD/ESRD. Early identifying high risk patients for AKI progression is a major challenge in patients with septic AKI. METHODS: This is a prospective, multicenter cohort study which enrolled adult patients with sepsis and initially developed stage 1 or 2 AKI in the intensive care unit from January 2014 to March 2018. AKI was diagnosed and staged according to 2012 KDIGO-AKI guidelines. Renal cell arrest biomarkers (urinary TIMP2*IGFBP7, u[TIMP-2]*[IGFBP7]) and renal damage biomarkers (urinary KIM-1[uKIM-1] and urinary IL-18 [uIL-18]) were measured at time of AKI clinical diagnosis, and the performance of biomarkers for predicting septic AKI progression alone or in combination were evaluated. The primary outcome was AKI progression defined as worsening of AKI stage. The secondary outcome was AKI progression with subsequent death during hospitalization. RESULTS: Among 433 screened patients, 149 patients with sepsis and stage 1 or 2 AKI were included, in which 63 patients developed progressive AKI and 49 patients subsequently died during hospitalization. u[TIMP-2]*[IGFBP7], uKIM-1 and uIL-18 independently predicted the progression of septic AKI in which u[TIMP-2]*[IGFBP7] showed the greatest AUC (0.745; 95%CI, 0.667-0.823) as compared to uKIM-1 (AUC 0.719; 95%CI 0.638-0.800) and uIL-18 (AUC 0.619; 95%CI 0.525-0.731). Combination of u[TIMP-2]*[IGFBP7] with uKIM-1 improved the performance of predicting septic AKI progression with AUC of 0.752. u[TIMP-2]*[IGFBP7], alone or combined with uKIM-1/uIL-18, improved the risk reclassification over the clinical risk factor model alone both for the primary and secondary outcomes, as evidenced by significant category-free net reclassification index. CONCLUSIONS: Combination of renal cell arrest and damage biomarkers enhanced the prediction of AKI progression in patients with sepsis and improved risk reclassification over the clinical risk factors. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12882-021-02611-8. BioMed Central 2021-12-15 /pmc/articles/PMC8672478/ /pubmed/34906098 http://dx.doi.org/10.1186/s12882-021-02611-8 Text en © The Author(s) 2021 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 Article Tao, Xiaolei Chen, Chunbo Luo, Weihong Zhou, Jing Tian, Jianwei Yang, Xiaobing Hou, Fan Fan Combining renal cell arrest and damage biomarkers to predict progressive AKI in patient with sepsis |
title | Combining renal cell arrest and damage biomarkers to predict progressive AKI in patient with sepsis |
title_full | Combining renal cell arrest and damage biomarkers to predict progressive AKI in patient with sepsis |
title_fullStr | Combining renal cell arrest and damage biomarkers to predict progressive AKI in patient with sepsis |
title_full_unstemmed | Combining renal cell arrest and damage biomarkers to predict progressive AKI in patient with sepsis |
title_short | Combining renal cell arrest and damage biomarkers to predict progressive AKI in patient with sepsis |
title_sort | combining renal cell arrest and damage biomarkers to predict progressive aki in patient with sepsis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8672478/ https://www.ncbi.nlm.nih.gov/pubmed/34906098 http://dx.doi.org/10.1186/s12882-021-02611-8 |
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