A diagnostic model for minimal change disease based on biological parameters
Background Minimal change disease (MCD) is a kind of nephrotic syndrome (NS). In this study, we aimed to establish a mathematical diagnostic model based on biological parameters to classify MCD. Methods A total of 798 NS patients were divided into MCD group and control group. The comparison of biolo...
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doaj-583d06c12f234059b46f98a0ad1d3f522020-11-25T00:00:23ZengPeerJ Inc.PeerJ2167-83592018-01-016e423710.7717/peerj.4237A diagnostic model for minimal change disease based on biological parametersHanyu Zhu0Qiuxia Han1Dong Zhang2Yong Wang3Jing Gao4Wenjia Geng5Xiaoli Yang6Xiangmei Chen7Department of Nephrology, Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, National Clinical Research Center of Kidney Diseases, Beijing Key Laboratory of Kidney Disease, Beijing, ChinaDepartment of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Nephrology, Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, National Clinical Research Center of Kidney Diseases, Beijing Key Laboratory of Kidney Disease, Beijing, ChinaDepartment of Nephrology, Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, National Clinical Research Center of Kidney Diseases, Beijing Key Laboratory of Kidney Disease, Beijing, ChinaDepartment of Clinical Biochemistry, Chinese PLA General Hospital, Beijing, ChinaDepartment of Nephrology, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, ChinaDepartment of Nephrology, Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, National Clinical Research Center of Kidney Diseases, Beijing Key Laboratory of Kidney Disease, Beijing, ChinaDepartment of Nephrology, Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, National Clinical Research Center of Kidney Diseases, Beijing Key Laboratory of Kidney Disease, Beijing, ChinaBackground Minimal change disease (MCD) is a kind of nephrotic syndrome (NS). In this study, we aimed to establish a mathematical diagnostic model based on biological parameters to classify MCD. Methods A total of 798 NS patients were divided into MCD group and control group. The comparison of biological indicators between two groups were performed with t-tests. Logistic regression was used to establish the diagnostic model, and the diagnostic value of the model was estimated using receiver operating characteristic (ROC) analysis. Results Thirteen indicators including Anti-phospholipase A2 receptor (anti-PLA2R) (P = 0.000), Total protein (TP) (P = 0.000), Albumin (ALB) (P = 0.000), Direct bilirubin (DB) (P = 0.002), Creatinine (Cr) (P = 0.000), Total cholesterol (CH) (P = 0.000), Lactate dehydrogenase (LDH) (P = 0.007), High density lipoprotein cholesterol (HDL) (P = 0.000), Low density lipoprotein cholesterol (LDL) (P = 0.000), Thrombin time (TT) (P = 0.000), Plasma fibrinogen (FIB) (P = 0.000), Immunoglobulin A (IgA) (P = 0.008) and Complement 3 (C3) (P = 0.019) were significantly correlated with MCD. Furthermore, the area under ROC curves of CH, HDL, LDL, TT and FIB were more than 0.70. Logistic analysis demonstrated that CH and TT were risk factors for MCD. According to the ROC of “CH+TT”, the AUC was 0.827, with the sensitivity of 83.0% and the specificity of 69.8% (P = 0.000). Conclusion The established diagnostic model with CH and TT could be used for classified diagnosis of MCD.https://peerj.com/articles/4237.pdfMinimal change diseaseDiagnostic modelBiological parameters |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hanyu Zhu Qiuxia Han Dong Zhang Yong Wang Jing Gao Wenjia Geng Xiaoli Yang Xiangmei Chen |
spellingShingle |
Hanyu Zhu Qiuxia Han Dong Zhang Yong Wang Jing Gao Wenjia Geng Xiaoli Yang Xiangmei Chen A diagnostic model for minimal change disease based on biological parameters PeerJ Minimal change disease Diagnostic model Biological parameters |
author_facet |
Hanyu Zhu Qiuxia Han Dong Zhang Yong Wang Jing Gao Wenjia Geng Xiaoli Yang Xiangmei Chen |
author_sort |
Hanyu Zhu |
title |
A diagnostic model for minimal change disease based on biological parameters |
title_short |
A diagnostic model for minimal change disease based on biological parameters |
title_full |
A diagnostic model for minimal change disease based on biological parameters |
title_fullStr |
A diagnostic model for minimal change disease based on biological parameters |
title_full_unstemmed |
A diagnostic model for minimal change disease based on biological parameters |
title_sort |
diagnostic model for minimal change disease based on biological parameters |
publisher |
PeerJ Inc. |
series |
PeerJ |
issn |
2167-8359 |
publishDate |
2018-01-01 |
description |
Background Minimal change disease (MCD) is a kind of nephrotic syndrome (NS). In this study, we aimed to establish a mathematical diagnostic model based on biological parameters to classify MCD. Methods A total of 798 NS patients were divided into MCD group and control group. The comparison of biological indicators between two groups were performed with t-tests. Logistic regression was used to establish the diagnostic model, and the diagnostic value of the model was estimated using receiver operating characteristic (ROC) analysis. Results Thirteen indicators including Anti-phospholipase A2 receptor (anti-PLA2R) (P = 0.000), Total protein (TP) (P = 0.000), Albumin (ALB) (P = 0.000), Direct bilirubin (DB) (P = 0.002), Creatinine (Cr) (P = 0.000), Total cholesterol (CH) (P = 0.000), Lactate dehydrogenase (LDH) (P = 0.007), High density lipoprotein cholesterol (HDL) (P = 0.000), Low density lipoprotein cholesterol (LDL) (P = 0.000), Thrombin time (TT) (P = 0.000), Plasma fibrinogen (FIB) (P = 0.000), Immunoglobulin A (IgA) (P = 0.008) and Complement 3 (C3) (P = 0.019) were significantly correlated with MCD. Furthermore, the area under ROC curves of CH, HDL, LDL, TT and FIB were more than 0.70. Logistic analysis demonstrated that CH and TT were risk factors for MCD. According to the ROC of “CH+TT”, the AUC was 0.827, with the sensitivity of 83.0% and the specificity of 69.8% (P = 0.000). Conclusion The established diagnostic model with CH and TT could be used for classified diagnosis of MCD. |
topic |
Minimal change disease Diagnostic model Biological parameters |
url |
https://peerj.com/articles/4237.pdf |
work_keys_str_mv |
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