Development and Validation of a Prediction Model for Acute Kidney Injury Among Patients With Acute Decompensated Heart Failure

Background: Acute kidney injury is an adverse event that carries significant morbidity among patients with acute decompensated heart failure (ADHF). We planned to develop a parsimonious model that is simple enough to use in clinical practice to predict the risk of acute kidney injury (AKI) occurrenc...

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Autores principales:	Lei Wang, Yun-Tao Zhao
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	acute decompensated heart failure acute kidney injury prediction model B-type natriuretic peptide acute cardiorenal syndrome Diseases of the circulatory (Cardiovascular) system RC666-701
Acceso en línea:	https://doaj.org/article/4ec9788f4c614071944471e8c79c2480
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spelling	oai:doaj.org-article:4ec9788f4c614071944471e8c79c24802021-11-15T05:46:09ZDevelopment and Validation of a Prediction Model for Acute Kidney Injury Among Patients With Acute Decompensated Heart Failure2297-055X10.3389/fcvm.2021.719307https://doaj.org/article/4ec9788f4c614071944471e8c79c24802021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fcvm.2021.719307/fullhttps://doaj.org/toc/2297-055XBackground: Acute kidney injury is an adverse event that carries significant morbidity among patients with acute decompensated heart failure (ADHF). We planned to develop a parsimonious model that is simple enough to use in clinical practice to predict the risk of acute kidney injury (AKI) occurrence.Methods: Six hundred and fifty patients with ADHF were enrolled in this study. Data for each patient were collected from medical records. We took three different approaches of variable selection to derive four multivariable logistic regression model. We selected six candidate predictors that led to a relatively stable outcome in different models to derive the final prediction model. The prediction model was verified through the use of the C-Statistics and calibration curve.Results: Acute kidney injury occurred in 42.8% of the patients. Advanced age, diabetes, previous renal dysfunction, high baseline creatinine, high B-type natriuretic peptide, and hypoalbuminemia were the strongest predictors for AKI. The prediction model showed moderate discrimination C-Statistics: 0.766 (95% CI, 0.729–0.803) and good identical calibration.Conclusion: In this study, we developed a prediction model and nomogram to estimate the risk of AKI among patients with ADHF. It may help clinical physicians detect AKI and manage it promptly.Lei WangYun-Tao ZhaoFrontiers Media S.A.articleacute decompensated heart failureacute kidney injuryprediction modelB-type natriuretic peptideacute cardiorenal syndromeDiseases of the circulatory (Cardiovascular) systemRC666-701ENFrontiers in Cardiovascular Medicine, Vol 8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	acute decompensated heart failure acute kidney injury prediction model B-type natriuretic peptide acute cardiorenal syndrome Diseases of the circulatory (Cardiovascular) system RC666-701
spellingShingle	acute decompensated heart failure acute kidney injury prediction model B-type natriuretic peptide acute cardiorenal syndrome Diseases of the circulatory (Cardiovascular) system RC666-701 Lei Wang Yun-Tao Zhao Development and Validation of a Prediction Model for Acute Kidney Injury Among Patients With Acute Decompensated Heart Failure
description	Background: Acute kidney injury is an adverse event that carries significant morbidity among patients with acute decompensated heart failure (ADHF). We planned to develop a parsimonious model that is simple enough to use in clinical practice to predict the risk of acute kidney injury (AKI) occurrence.Methods: Six hundred and fifty patients with ADHF were enrolled in this study. Data for each patient were collected from medical records. We took three different approaches of variable selection to derive four multivariable logistic regression model. We selected six candidate predictors that led to a relatively stable outcome in different models to derive the final prediction model. The prediction model was verified through the use of the C-Statistics and calibration curve.Results: Acute kidney injury occurred in 42.8% of the patients. Advanced age, diabetes, previous renal dysfunction, high baseline creatinine, high B-type natriuretic peptide, and hypoalbuminemia were the strongest predictors for AKI. The prediction model showed moderate discrimination C-Statistics: 0.766 (95% CI, 0.729–0.803) and good identical calibration.Conclusion: In this study, we developed a prediction model and nomogram to estimate the risk of AKI among patients with ADHF. It may help clinical physicians detect AKI and manage it promptly.
format	article
author	Lei Wang Yun-Tao Zhao
author_facet	Lei Wang Yun-Tao Zhao
author_sort	Lei Wang
title	Development and Validation of a Prediction Model for Acute Kidney Injury Among Patients With Acute Decompensated Heart Failure
title_short	Development and Validation of a Prediction Model for Acute Kidney Injury Among Patients With Acute Decompensated Heart Failure
title_full	Development and Validation of a Prediction Model for Acute Kidney Injury Among Patients With Acute Decompensated Heart Failure
title_fullStr	Development and Validation of a Prediction Model for Acute Kidney Injury Among Patients With Acute Decompensated Heart Failure
title_full_unstemmed	Development and Validation of a Prediction Model for Acute Kidney Injury Among Patients With Acute Decompensated Heart Failure
title_sort	development and validation of a prediction model for acute kidney injury among patients with acute decompensated heart failure
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/4ec9788f4c614071944471e8c79c2480
work_keys_str_mv	AT leiwang developmentandvalidationofapredictionmodelforacutekidneyinjuryamongpatientswithacutedecompensatedheartfailure AT yuntaozhao developmentandvalidationofapredictionmodelforacutekidneyinjuryamongpatientswithacutedecompensatedheartfailure
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Development and Validation of a Prediction Model for Acute Kidney Injury Among Patients With Acute Decompensated Heart Failure

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