Diabetes Mellitus as a Risk Factor for Progression from Acute Kidney Injury to Acute Kidney Disease: A Specific Prediction Model

Huanhuan Zhao,1– 5,* Lulu Liang,1– 5,* Shaokang Pan,1 Zhenjie Liu,1 Yan Liang,1 Yingjin Qiao,1 Dongwei Liu,1– 5 Zhangsuo Liu1– 5 1Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, People’s Republic of...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Zhao H, Liang L, Pan S, Liu Z, Liang Y, Qiao Y, Liu D
Formato:	article
Lenguaje:	EN
Publicado:	Dove Medical Press 2021
Materias:	diabetes mellitus acute kidney injury anemia oliguria nomogram Specialties of internal medicine RC581-951
Acceso en línea:	https://doaj.org/article/bd7b163608534e04b25dfb91ae85e7c7
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:bd7b163608534e04b25dfb91ae85e7c7
record_format	dspace
spelling	oai:doaj.org-article:bd7b163608534e04b25dfb91ae85e7c72021-12-02T16:51:44ZDiabetes Mellitus as a Risk Factor for Progression from Acute Kidney Injury to Acute Kidney Disease: A Specific Prediction Model1178-7007https://doaj.org/article/bd7b163608534e04b25dfb91ae85e7c72021-05-01T00:00:00Zhttps://www.dovepress.com/diabetes-mellitus-as-a-risk-factor-for-progression-from-acute-kidney-i-peer-reviewed-fulltext-article-DMSOhttps://doaj.org/toc/1178-7007Huanhuan Zhao,1– 5,* Lulu Liang,1– 5,* Shaokang Pan,1 Zhenjie Liu,1 Yan Liang,1 Yingjin Qiao,1 Dongwei Liu,1– 5 Zhangsuo Liu1– 5 1Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, People’s Republic of China; 2Research Institute of Nephrology, Zhengzhou University, Zhengzhou, 450052, People’s Republic of China; 3Research Center for Kidney Disease, Zhengzhou, 450052, Henan Province, People’s Republic of China; 4Key Laboratory of Precision Diagnosis and Treatment for Chronic Kidney Disease in Henan Province, Zhengzhou, 450052, People’s Republic of China; 5Core Unit of National Clinical Medical Research Center of Kidney Disease, Zhengzhou, 450052, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zhangsuo Liu; Dongwei LiuDepartment of Nephrology, The First Affiliated Hospital of Zhengzhou University, No. 1, Jianshe East Road, Zhengzhou, 450052, Henan Province, People’s Republic of ChinaTel +86-0371-66295921Email Lzs58055@163.com; dongweiliu01@163.comPurpose: Acute kidney injury is very common in hospitalized patients and carries a significant risk of mortality. Although timely intervention may improve patient prognosis, studies on the development of acute kidney disease in patients with acute kidney injury remain scarce. Thus, we constructed a prediction model to identify patients likely to develop acute kidney disease.Patients and Methods: Among 474 patients screened for eligibility, 261 were enrolled and randomly divided into training (185 patients) and independent validation cohorts (76 patients). Least absolute shrinkage and selection operator regression and multivariate logistic regression analyses were used to select features and build a nomogram incorporating the selected predictors: diabetes, anemia, oliguria, and peak creatinine. Calibration, discrimination, and the clinical usefulness of the model were assessed using calibration plots, the C-index, receiver operating characteristic curves, and decision curve analysis.Results: Diabetes was significantly associated with the presence of AKD. Peak creatinine, oliguria, and anemia also contributed to the progression of acute kidney injury. The model displayed good predictive power with a C-index of 0.834 and an AUC of 0.834 (95% confidence interval (CI): 0.773– 0.895) in the training cohort and a C-index of 0.851 and an AUC of 0.851 (95% CI: 0.753– 0.949) in the validation cohort. The calibration curves also showed that the model had a medium ability to predict acute kidney disease risk. Decision curve analysis showed that the nomogram was clinically useful when interventions were decided at the possibility threshold of 22%.Conclusion: This novel prediction nomogram may allow for convenient prediction of acute kidney disease in patients with acute kidney injury, which may help to improve outcomes.Keywords: diabetes mellitus, acute kidney injury, anemia, oliguria, nomogramZhao HLiang LPan SLiu ZLiang YQiao YLiu DLiu ZDove Medical Pressarticlediabetes mellitusacute kidney injuryanemiaoligurianomogramSpecialties of internal medicineRC581-951ENDiabetes, Metabolic Syndrome and Obesity: Targets and Therapy, Vol Volume 14, Pp 2367-2379 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	diabetes mellitus acute kidney injury anemia oliguria nomogram Specialties of internal medicine RC581-951
spellingShingle	diabetes mellitus acute kidney injury anemia oliguria nomogram Specialties of internal medicine RC581-951 Zhao H Liang L Pan S Liu Z Liang Y Qiao Y Liu D Liu Z Diabetes Mellitus as a Risk Factor for Progression from Acute Kidney Injury to Acute Kidney Disease: A Specific Prediction Model
description	Huanhuan Zhao,1– 5,* Lulu Liang,1– 5,* Shaokang Pan,1 Zhenjie Liu,1 Yan Liang,1 Yingjin Qiao,1 Dongwei Liu,1– 5 Zhangsuo Liu1– 5 1Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, People’s Republic of China; 2Research Institute of Nephrology, Zhengzhou University, Zhengzhou, 450052, People’s Republic of China; 3Research Center for Kidney Disease, Zhengzhou, 450052, Henan Province, People’s Republic of China; 4Key Laboratory of Precision Diagnosis and Treatment for Chronic Kidney Disease in Henan Province, Zhengzhou, 450052, People’s Republic of China; 5Core Unit of National Clinical Medical Research Center of Kidney Disease, Zhengzhou, 450052, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zhangsuo Liu; Dongwei LiuDepartment of Nephrology, The First Affiliated Hospital of Zhengzhou University, No. 1, Jianshe East Road, Zhengzhou, 450052, Henan Province, People’s Republic of ChinaTel +86-0371-66295921Email Lzs58055@163.com; dongweiliu01@163.comPurpose: Acute kidney injury is very common in hospitalized patients and carries a significant risk of mortality. Although timely intervention may improve patient prognosis, studies on the development of acute kidney disease in patients with acute kidney injury remain scarce. Thus, we constructed a prediction model to identify patients likely to develop acute kidney disease.Patients and Methods: Among 474 patients screened for eligibility, 261 were enrolled and randomly divided into training (185 patients) and independent validation cohorts (76 patients). Least absolute shrinkage and selection operator regression and multivariate logistic regression analyses were used to select features and build a nomogram incorporating the selected predictors: diabetes, anemia, oliguria, and peak creatinine. Calibration, discrimination, and the clinical usefulness of the model were assessed using calibration plots, the C-index, receiver operating characteristic curves, and decision curve analysis.Results: Diabetes was significantly associated with the presence of AKD. Peak creatinine, oliguria, and anemia also contributed to the progression of acute kidney injury. The model displayed good predictive power with a C-index of 0.834 and an AUC of 0.834 (95% confidence interval (CI): 0.773– 0.895) in the training cohort and a C-index of 0.851 and an AUC of 0.851 (95% CI: 0.753– 0.949) in the validation cohort. The calibration curves also showed that the model had a medium ability to predict acute kidney disease risk. Decision curve analysis showed that the nomogram was clinically useful when interventions were decided at the possibility threshold of 22%.Conclusion: This novel prediction nomogram may allow for convenient prediction of acute kidney disease in patients with acute kidney injury, which may help to improve outcomes.Keywords: diabetes mellitus, acute kidney injury, anemia, oliguria, nomogram
format	article
author	Zhao H Liang L Pan S Liu Z Liang Y Qiao Y Liu D Liu Z
author_facet	Zhao H Liang L Pan S Liu Z Liang Y Qiao Y Liu D Liu Z
author_sort	Zhao H
title	Diabetes Mellitus as a Risk Factor for Progression from Acute Kidney Injury to Acute Kidney Disease: A Specific Prediction Model
title_short	Diabetes Mellitus as a Risk Factor for Progression from Acute Kidney Injury to Acute Kidney Disease: A Specific Prediction Model
title_full	Diabetes Mellitus as a Risk Factor for Progression from Acute Kidney Injury to Acute Kidney Disease: A Specific Prediction Model
title_fullStr	Diabetes Mellitus as a Risk Factor for Progression from Acute Kidney Injury to Acute Kidney Disease: A Specific Prediction Model
title_full_unstemmed	Diabetes Mellitus as a Risk Factor for Progression from Acute Kidney Injury to Acute Kidney Disease: A Specific Prediction Model
title_sort	diabetes mellitus as a risk factor for progression from acute kidney injury to acute kidney disease: a specific prediction model
publisher	Dove Medical Press
publishDate	2021
url	https://doaj.org/article/bd7b163608534e04b25dfb91ae85e7c7
work_keys_str_mv	AT zhaoh diabetesmellitusasariskfactorforprogressionfromacutekidneyinjurytoacutekidneydiseaseaspecificpredictionmodel AT liangl diabetesmellitusasariskfactorforprogressionfromacutekidneyinjurytoacutekidneydiseaseaspecificpredictionmodel AT pans diabetesmellitusasariskfactorforprogressionfromacutekidneyinjurytoacutekidneydiseaseaspecificpredictionmodel AT liuz diabetesmellitusasariskfactorforprogressionfromacutekidneyinjurytoacutekidneydiseaseaspecificpredictionmodel AT liangy diabetesmellitusasariskfactorforprogressionfromacutekidneyinjurytoacutekidneydiseaseaspecificpredictionmodel AT qiaoy diabetesmellitusasariskfactorforprogressionfromacutekidneyinjurytoacutekidneydiseaseaspecificpredictionmodel AT liud diabetesmellitusasariskfactorforprogressionfromacutekidneyinjurytoacutekidneydiseaseaspecificpredictionmodel AT liuz diabetesmellitusasariskfactorforprogressionfromacutekidneyinjurytoacutekidneydiseaseaspecificpredictionmodel
_version_	1718382940340092928

Diabetes Mellitus as a Risk Factor for Progression from Acute Kidney Injury to Acute Kidney Disease: A Specific Prediction Model

Ejemplares similares