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Development and validation of a prediction model for the early occurrence of acute kidney injury in patients with acute pancreatitis

BACKGROUND: Acute pancreatitis (AP) is associated with a high incidence of acute kidney injury (AKI). This study aimed to develop a nomogram for predicting the early onset of AKI in AP patients admitted to the intensive care unit. METHOD: Clinical data for 799 patients diagnosed with AP were extract...

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Autores principales: Wu, Simin, Zhou, Qin, Cai, Yang, Duan, Xiangjie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10071964/
https://www.ncbi.nlm.nih.gov/pubmed/36999227
http://dx.doi.org/10.1080/0886022X.2023.2194436
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author Wu, Simin
Zhou, Qin
Cai, Yang
Duan, Xiangjie
author_facet Wu, Simin
Zhou, Qin
Cai, Yang
Duan, Xiangjie
author_sort Wu, Simin
collection PubMed
description BACKGROUND: Acute pancreatitis (AP) is associated with a high incidence of acute kidney injury (AKI). This study aimed to develop a nomogram for predicting the early onset of AKI in AP patients admitted to the intensive care unit. METHOD: Clinical data for 799 patients diagnosed with AP were extracted from the Medical Information Mart for Intensive Care IV database. Eligible AP patients were randomly divided into training and validation cohorts. The independent prognostic factors for the early development of AKI in AP patients were determined using the all-subsets regression method and multivariate logistic regression. A nomogram was constructed for predicting the early occurrence of AKI in AP patients. The performance of the nomogram was evaluated based on the area under the receiver operating characteristic curve (AUC), calibration curves and decision curve analysis (DCA). RESULTS: Seven independent prognostic factors were identified as predictive factors for early onset AKI in AP patients. The AUC of the nomogram in the training and validation cohorts were 0.795 (95% CI, 0.758–0.832) and 0.772 (95% CI, 0.711–0.832), respectively. The AUC of the nomogram was higher compared with that of the BISAP, Ranson, APACHE II scores. Further, the calibration curve revealed that the predicted outcome was in agreement with the actual observations. Finally, the DCA curves showed that the nomogram had a good clinical applicability value. CONCLUSION: The constructed nomogram showed a good predictive ability for the early occurrence of AKI in AP patients.
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spelling pubmed-100719642023-04-05 Development and validation of a prediction model for the early occurrence of acute kidney injury in patients with acute pancreatitis Wu, Simin Zhou, Qin Cai, Yang Duan, Xiangjie Ren Fail Clinical Study BACKGROUND: Acute pancreatitis (AP) is associated with a high incidence of acute kidney injury (AKI). This study aimed to develop a nomogram for predicting the early onset of AKI in AP patients admitted to the intensive care unit. METHOD: Clinical data for 799 patients diagnosed with AP were extracted from the Medical Information Mart for Intensive Care IV database. Eligible AP patients were randomly divided into training and validation cohorts. The independent prognostic factors for the early development of AKI in AP patients were determined using the all-subsets regression method and multivariate logistic regression. A nomogram was constructed for predicting the early occurrence of AKI in AP patients. The performance of the nomogram was evaluated based on the area under the receiver operating characteristic curve (AUC), calibration curves and decision curve analysis (DCA). RESULTS: Seven independent prognostic factors were identified as predictive factors for early onset AKI in AP patients. The AUC of the nomogram in the training and validation cohorts were 0.795 (95% CI, 0.758–0.832) and 0.772 (95% CI, 0.711–0.832), respectively. The AUC of the nomogram was higher compared with that of the BISAP, Ranson, APACHE II scores. Further, the calibration curve revealed that the predicted outcome was in agreement with the actual observations. Finally, the DCA curves showed that the nomogram had a good clinical applicability value. CONCLUSION: The constructed nomogram showed a good predictive ability for the early occurrence of AKI in AP patients. Taylor & Francis 2023-03-30 /pmc/articles/PMC10071964/ /pubmed/36999227 http://dx.doi.org/10.1080/0886022X.2023.2194436 Text en © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
spellingShingle Clinical Study
Wu, Simin
Zhou, Qin
Cai, Yang
Duan, Xiangjie
Development and validation of a prediction model for the early occurrence of acute kidney injury in patients with acute pancreatitis
title Development and validation of a prediction model for the early occurrence of acute kidney injury in patients with acute pancreatitis
title_full Development and validation of a prediction model for the early occurrence of acute kidney injury in patients with acute pancreatitis
title_fullStr Development and validation of a prediction model for the early occurrence of acute kidney injury in patients with acute pancreatitis
title_full_unstemmed Development and validation of a prediction model for the early occurrence of acute kidney injury in patients with acute pancreatitis
title_short Development and validation of a prediction model for the early occurrence of acute kidney injury in patients with acute pancreatitis
title_sort development and validation of a prediction model for the early occurrence of acute kidney injury in patients with acute pancreatitis
topic Clinical Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10071964/
https://www.ncbi.nlm.nih.gov/pubmed/36999227
http://dx.doi.org/10.1080/0886022X.2023.2194436
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