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Development and validation of a nomogram to predict the risk of renal replacement therapy among acute kidney injury patients in intensive care unit

BACKGROUND: There are no universally accepted indications to initiate renal replacement therapy (RRT) among patients with acute kidney injury (AKI). This study aimed to develop a nomogram to predict the risk of RRT among AKI patients in intensive care unit (ICU). METHODS: In this retrospective cohor...

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Autores principales: Peng, Jiang-Chen, Wu, Yan, Xing, Shun-Peng, Zhu, Ming-Li, Gao, Yuan, Li, Wen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Nature Singapore 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10581925/
https://www.ncbi.nlm.nih.gov/pubmed/37498349
http://dx.doi.org/10.1007/s10157-023-02383-5
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author Peng, Jiang-Chen
Wu, Yan
Xing, Shun-Peng
Zhu, Ming-Li
Gao, Yuan
Li, Wen
author_facet Peng, Jiang-Chen
Wu, Yan
Xing, Shun-Peng
Zhu, Ming-Li
Gao, Yuan
Li, Wen
author_sort Peng, Jiang-Chen
collection PubMed
description BACKGROUND: There are no universally accepted indications to initiate renal replacement therapy (RRT) among patients with acute kidney injury (AKI). This study aimed to develop a nomogram to predict the risk of RRT among AKI patients in intensive care unit (ICU). METHODS: In this retrospective cohort study, we extracted AKI patients from Medical Information Mart for Intensive Care III (MIMIC-III) database. Patients were randomly divided into a training cohort (70%) and a validation cohort (30%). Multivariable logistic regression based on Akaike information criterion was used to establish the nomogram. The discrimination and calibration of the nomogram were evaluated by Harrell’s concordance index (C-index) and Hosmer–Lemeshow (HL) test. Decision curve analysis (DCA) was performed to evaluate clinical application. RESULTS: A total of 7413 critically ill patients with AKI were finally enrolled. 514 (6.9%) patients received RRT after ICU admission. 5194 (70%) patients were in the training cohort and 2219 (30%) patients were in the validation cohort. Nine variables, namely, age, hemoglobin, creatinine, blood urea nitrogen and lactate at AKI detection, comorbidity of congestive heart failure, AKI stage, and vasopressor use were included in the nomogram. The predictive model demonstrated satisfying discrimination and calibration with C-index of 0.938 (95% CI, 0.927–0.949; HL test, P = 0.430) in training set and 0.935 (95% CI, 0.919–0.951; HL test, P = 0.392) in validation set. DCA showed a positive net benefit of our nomogram. CONCLUSION: The nomogram developed in this study was highly accurate for RRT prediction with potential application value. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10157-023-02383-5.
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spelling pubmed-105819252023-10-19 Development and validation of a nomogram to predict the risk of renal replacement therapy among acute kidney injury patients in intensive care unit Peng, Jiang-Chen Wu, Yan Xing, Shun-Peng Zhu, Ming-Li Gao, Yuan Li, Wen Clin Exp Nephrol Original Article BACKGROUND: There are no universally accepted indications to initiate renal replacement therapy (RRT) among patients with acute kidney injury (AKI). This study aimed to develop a nomogram to predict the risk of RRT among AKI patients in intensive care unit (ICU). METHODS: In this retrospective cohort study, we extracted AKI patients from Medical Information Mart for Intensive Care III (MIMIC-III) database. Patients were randomly divided into a training cohort (70%) and a validation cohort (30%). Multivariable logistic regression based on Akaike information criterion was used to establish the nomogram. The discrimination and calibration of the nomogram were evaluated by Harrell’s concordance index (C-index) and Hosmer–Lemeshow (HL) test. Decision curve analysis (DCA) was performed to evaluate clinical application. RESULTS: A total of 7413 critically ill patients with AKI were finally enrolled. 514 (6.9%) patients received RRT after ICU admission. 5194 (70%) patients were in the training cohort and 2219 (30%) patients were in the validation cohort. Nine variables, namely, age, hemoglobin, creatinine, blood urea nitrogen and lactate at AKI detection, comorbidity of congestive heart failure, AKI stage, and vasopressor use were included in the nomogram. The predictive model demonstrated satisfying discrimination and calibration with C-index of 0.938 (95% CI, 0.927–0.949; HL test, P = 0.430) in training set and 0.935 (95% CI, 0.919–0.951; HL test, P = 0.392) in validation set. DCA showed a positive net benefit of our nomogram. CONCLUSION: The nomogram developed in this study was highly accurate for RRT prediction with potential application value. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10157-023-02383-5. Springer Nature Singapore 2023-07-27 2023 /pmc/articles/PMC10581925/ /pubmed/37498349 http://dx.doi.org/10.1007/s10157-023-02383-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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/) .
spellingShingle Original Article
Peng, Jiang-Chen
Wu, Yan
Xing, Shun-Peng
Zhu, Ming-Li
Gao, Yuan
Li, Wen
Development and validation of a nomogram to predict the risk of renal replacement therapy among acute kidney injury patients in intensive care unit
title Development and validation of a nomogram to predict the risk of renal replacement therapy among acute kidney injury patients in intensive care unit
title_full Development and validation of a nomogram to predict the risk of renal replacement therapy among acute kidney injury patients in intensive care unit
title_fullStr Development and validation of a nomogram to predict the risk of renal replacement therapy among acute kidney injury patients in intensive care unit
title_full_unstemmed Development and validation of a nomogram to predict the risk of renal replacement therapy among acute kidney injury patients in intensive care unit
title_short Development and validation of a nomogram to predict the risk of renal replacement therapy among acute kidney injury patients in intensive care unit
title_sort development and validation of a nomogram to predict the risk of renal replacement therapy among acute kidney injury patients in intensive care unit
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10581925/
https://www.ncbi.nlm.nih.gov/pubmed/37498349
http://dx.doi.org/10.1007/s10157-023-02383-5
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