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A nomogram incorporating functional and tubular damage biomarkers to predict the risk of acute kidney injury for septic patients

BACKGROUND: Combining tubular damage and functional biomarkers may improve prediction precision of acute kidney injury (AKI). Serum cystatin C (sCysC) represents functional damage of kidney, while urinary N-acetyl-β-D-glucosaminidase (uNAG) is considered as a tubular damage biomarker. So far, there...

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Autores principales: Ma, Jianchao, Deng, Yujun, Lao, Haiyan, Ouyang, Xin, Liang, Silin, Wang, Yifan, Yao, Fen, Deng, Yiyu, Chen, Chunbo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8120900/
https://www.ncbi.nlm.nih.gov/pubmed/33985459
http://dx.doi.org/10.1186/s12882-021-02388-w
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author Ma, Jianchao
Deng, Yujun
Lao, Haiyan
Ouyang, Xin
Liang, Silin
Wang, Yifan
Yao, Fen
Deng, Yiyu
Chen, Chunbo
author_facet Ma, Jianchao
Deng, Yujun
Lao, Haiyan
Ouyang, Xin
Liang, Silin
Wang, Yifan
Yao, Fen
Deng, Yiyu
Chen, Chunbo
author_sort Ma, Jianchao
collection PubMed
description BACKGROUND: Combining tubular damage and functional biomarkers may improve prediction precision of acute kidney injury (AKI). Serum cystatin C (sCysC) represents functional damage of kidney, while urinary N-acetyl-β-D-glucosaminidase (uNAG) is considered as a tubular damage biomarker. So far, there is no nomogram containing this combination to predict AKI in septic cohort. We aimed to compare the performance of AKI prediction models with or without incorporating these two biomarkers and develop an effective nomogram for septic patients in intensive care unit (ICU). METHODS: This was a prospective study conducted in the mixed medical-surgical ICU of a tertiary care hospital. Adults with sepsis were enrolled. The patients were divided into development and validation cohorts in chronological order of ICU admission. A logistic regression model for AKI prediction was first constructed in the development cohort. The contribution of the biomarkers (sCysC, uNAG) to this model for AKI prediction was assessed with the area under the receiver operator characteristic curve (AUC), continuous net reclassification index (cNRI), and incremental discrimination improvement (IDI). Then nomogram was established based on the model with the best performance. This nomogram was validated in the validation cohort in terms of discrimination and calibration. The decision curve analysis (DCA) was performed to evaluate the nomogram’s clinical utility. RESULTS: Of 358 enrolled patients, 232 were in the development cohort (69 AKI), while 126 in the validation cohort (52 AKI). The first clinical model included the APACHE II score, serum creatinine, and vasopressor used at ICU admission. Adding sCysC and uNAG to this model improved the AUC to 0.831. Furthermore, incorporating them significantly improved risk reclassification over the predictive model alone, with cNRI (0.575) and IDI (0.085). A nomogram was then established based on the new model including sCysC and uNAG. Application of this nomogram in the validation cohort yielded fair discrimination with an AUC of 0.784 and good calibration. The DCA revealed good clinical utility of this nomogram. CONCLUSIONS: A nomogram that incorporates functional marker (sCysC) and tubular damage marker (uNAG), together with routine clinical factors may be a useful prognostic tool for individualized prediction of AKI in septic patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12882-021-02388-w.
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spelling pubmed-81209002021-05-17 A nomogram incorporating functional and tubular damage biomarkers to predict the risk of acute kidney injury for septic patients Ma, Jianchao Deng, Yujun Lao, Haiyan Ouyang, Xin Liang, Silin Wang, Yifan Yao, Fen Deng, Yiyu Chen, Chunbo BMC Nephrol Research BACKGROUND: Combining tubular damage and functional biomarkers may improve prediction precision of acute kidney injury (AKI). Serum cystatin C (sCysC) represents functional damage of kidney, while urinary N-acetyl-β-D-glucosaminidase (uNAG) is considered as a tubular damage biomarker. So far, there is no nomogram containing this combination to predict AKI in septic cohort. We aimed to compare the performance of AKI prediction models with or without incorporating these two biomarkers and develop an effective nomogram for septic patients in intensive care unit (ICU). METHODS: This was a prospective study conducted in the mixed medical-surgical ICU of a tertiary care hospital. Adults with sepsis were enrolled. The patients were divided into development and validation cohorts in chronological order of ICU admission. A logistic regression model for AKI prediction was first constructed in the development cohort. The contribution of the biomarkers (sCysC, uNAG) to this model for AKI prediction was assessed with the area under the receiver operator characteristic curve (AUC), continuous net reclassification index (cNRI), and incremental discrimination improvement (IDI). Then nomogram was established based on the model with the best performance. This nomogram was validated in the validation cohort in terms of discrimination and calibration. The decision curve analysis (DCA) was performed to evaluate the nomogram’s clinical utility. RESULTS: Of 358 enrolled patients, 232 were in the development cohort (69 AKI), while 126 in the validation cohort (52 AKI). The first clinical model included the APACHE II score, serum creatinine, and vasopressor used at ICU admission. Adding sCysC and uNAG to this model improved the AUC to 0.831. Furthermore, incorporating them significantly improved risk reclassification over the predictive model alone, with cNRI (0.575) and IDI (0.085). A nomogram was then established based on the new model including sCysC and uNAG. Application of this nomogram in the validation cohort yielded fair discrimination with an AUC of 0.784 and good calibration. The DCA revealed good clinical utility of this nomogram. CONCLUSIONS: A nomogram that incorporates functional marker (sCysC) and tubular damage marker (uNAG), together with routine clinical factors may be a useful prognostic tool for individualized prediction of AKI in septic patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12882-021-02388-w. BioMed Central 2021-05-13 /pmc/articles/PMC8120900/ /pubmed/33985459 http://dx.doi.org/10.1186/s12882-021-02388-w 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
Ma, Jianchao
Deng, Yujun
Lao, Haiyan
Ouyang, Xin
Liang, Silin
Wang, Yifan
Yao, Fen
Deng, Yiyu
Chen, Chunbo
A nomogram incorporating functional and tubular damage biomarkers to predict the risk of acute kidney injury for septic patients
title A nomogram incorporating functional and tubular damage biomarkers to predict the risk of acute kidney injury for septic patients
title_full A nomogram incorporating functional and tubular damage biomarkers to predict the risk of acute kidney injury for septic patients
title_fullStr A nomogram incorporating functional and tubular damage biomarkers to predict the risk of acute kidney injury for septic patients
title_full_unstemmed A nomogram incorporating functional and tubular damage biomarkers to predict the risk of acute kidney injury for septic patients
title_short A nomogram incorporating functional and tubular damage biomarkers to predict the risk of acute kidney injury for septic patients
title_sort nomogram incorporating functional and tubular damage biomarkers to predict the risk of acute kidney injury for septic patients
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8120900/
https://www.ncbi.nlm.nih.gov/pubmed/33985459
http://dx.doi.org/10.1186/s12882-021-02388-w
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