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Establishment of a novel nomogram for the clinically diagnostic prediction of minimal change disease, −a common cause of nephrotic syndrome

BACKGROUND: Minimal change disease (MCD) is one of the major causes of nephrotic syndrome (NS). A confirmed MCD diagnosis mainly depends on renal biopsy at present, which is an invasive procedure with many potential risks. The overall incidence of complications caused by renal biopsy procedures has...

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Autores principales: Yan, Gaofei, Liu, Guanzhi, Tian, Xuefei, Tian, Lifang, Wang, Hao, Ren, Peiyao, Ma, Xiaotao, Fu, Rongguo, Chen, Zhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7490860/
https://www.ncbi.nlm.nih.gov/pubmed/32928127
http://dx.doi.org/10.1186/s12882-020-02058-3
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author Yan, Gaofei
Liu, Guanzhi
Tian, Xuefei
Tian, Lifang
Wang, Hao
Ren, Peiyao
Ma, Xiaotao
Fu, Rongguo
Chen, Zhao
author_facet Yan, Gaofei
Liu, Guanzhi
Tian, Xuefei
Tian, Lifang
Wang, Hao
Ren, Peiyao
Ma, Xiaotao
Fu, Rongguo
Chen, Zhao
author_sort Yan, Gaofei
collection PubMed
description BACKGROUND: Minimal change disease (MCD) is one of the major causes of nephrotic syndrome (NS). A confirmed MCD diagnosis mainly depends on renal biopsy at present, which is an invasive procedure with many potential risks. The overall incidence of complications caused by renal biopsy procedures has been reported as approximately 11 and 6.6% outside and within China, respectively. Unfortunately, there is currently no noninvasive procedure or practical classification method for distinguishing MCD from other primary glomerular diseases available. METHOD: A total of 1009 adult patients who underwent renal biopsy between January 2017 and November 2019 were enrolled in this study. Twenty-five parameters extracted from patient demographics, clinical manifestations, and laboratory test results were statistically analysed. LASSO regression analysis was further performed on these parameters. The parameters with the highest area under the curve (AUC) were selected and used to establish a logistic diagnostic prediction model. RESULTS: Of the 25 parameters, 14 parameters were significantly different (P < 0.05). MCD patients were mostly younger (36 (22, 55) vs. 41 (28.75, 53)) and male (59% vs. 52%) and had lower levels of diastolic blood pressure (DBP) (79 (71, 85.5) vs. 80 (74, 89)) and IgG (5.42 (3.17, 6.36) vs. 9.38 (6.79, 12.02)) and higher levels of IgM (1.44 (0.96, 1.88) vs. 1.03 (0.71, 1.45)) and IgE (160 (46.7, 982) vs. 47.3 (19, 126)) than those in the non-MCD group. Using the LASSO model, we established a classifier for adults based on four parameters: DBP and the serum levels of IgG, IgM, IgE. We were able to clinically classify adult patients with NS into MCD and non-MCD using this model. The validation accuracy of the logistic regression model was 0.88. A nomogram based on these four classifiers was developed for clinical use that could predict the probability of MCD in adult patients with NS. CONCLUSIONS: A LASSO model can be used to distinguish MCD from other primary glomerular diseases in adult patients with NS. Combining the model and the nomogram potentially provides a novel and valuable approach for nephrologists to diagnose MCD, avoiding the complications caused by renal biopsy.
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spelling pubmed-74908602020-09-16 Establishment of a novel nomogram for the clinically diagnostic prediction of minimal change disease, −a common cause of nephrotic syndrome Yan, Gaofei Liu, Guanzhi Tian, Xuefei Tian, Lifang Wang, Hao Ren, Peiyao Ma, Xiaotao Fu, Rongguo Chen, Zhao BMC Nephrol Technical Advance BACKGROUND: Minimal change disease (MCD) is one of the major causes of nephrotic syndrome (NS). A confirmed MCD diagnosis mainly depends on renal biopsy at present, which is an invasive procedure with many potential risks. The overall incidence of complications caused by renal biopsy procedures has been reported as approximately 11 and 6.6% outside and within China, respectively. Unfortunately, there is currently no noninvasive procedure or practical classification method for distinguishing MCD from other primary glomerular diseases available. METHOD: A total of 1009 adult patients who underwent renal biopsy between January 2017 and November 2019 were enrolled in this study. Twenty-five parameters extracted from patient demographics, clinical manifestations, and laboratory test results were statistically analysed. LASSO regression analysis was further performed on these parameters. The parameters with the highest area under the curve (AUC) were selected and used to establish a logistic diagnostic prediction model. RESULTS: Of the 25 parameters, 14 parameters were significantly different (P < 0.05). MCD patients were mostly younger (36 (22, 55) vs. 41 (28.75, 53)) and male (59% vs. 52%) and had lower levels of diastolic blood pressure (DBP) (79 (71, 85.5) vs. 80 (74, 89)) and IgG (5.42 (3.17, 6.36) vs. 9.38 (6.79, 12.02)) and higher levels of IgM (1.44 (0.96, 1.88) vs. 1.03 (0.71, 1.45)) and IgE (160 (46.7, 982) vs. 47.3 (19, 126)) than those in the non-MCD group. Using the LASSO model, we established a classifier for adults based on four parameters: DBP and the serum levels of IgG, IgM, IgE. We were able to clinically classify adult patients with NS into MCD and non-MCD using this model. The validation accuracy of the logistic regression model was 0.88. A nomogram based on these four classifiers was developed for clinical use that could predict the probability of MCD in adult patients with NS. CONCLUSIONS: A LASSO model can be used to distinguish MCD from other primary glomerular diseases in adult patients with NS. Combining the model and the nomogram potentially provides a novel and valuable approach for nephrologists to diagnose MCD, avoiding the complications caused by renal biopsy. BioMed Central 2020-09-14 /pmc/articles/PMC7490860/ /pubmed/32928127 http://dx.doi.org/10.1186/s12882-020-02058-3 Text en © The Author(s) 2020 Open AccessThis 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/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Technical Advance
Yan, Gaofei
Liu, Guanzhi
Tian, Xuefei
Tian, Lifang
Wang, Hao
Ren, Peiyao
Ma, Xiaotao
Fu, Rongguo
Chen, Zhao
Establishment of a novel nomogram for the clinically diagnostic prediction of minimal change disease, −a common cause of nephrotic syndrome
title Establishment of a novel nomogram for the clinically diagnostic prediction of minimal change disease, −a common cause of nephrotic syndrome
title_full Establishment of a novel nomogram for the clinically diagnostic prediction of minimal change disease, −a common cause of nephrotic syndrome
title_fullStr Establishment of a novel nomogram for the clinically diagnostic prediction of minimal change disease, −a common cause of nephrotic syndrome
title_full_unstemmed Establishment of a novel nomogram for the clinically diagnostic prediction of minimal change disease, −a common cause of nephrotic syndrome
title_short Establishment of a novel nomogram for the clinically diagnostic prediction of minimal change disease, −a common cause of nephrotic syndrome
title_sort establishment of a novel nomogram for the clinically diagnostic prediction of minimal change disease, −a common cause of nephrotic syndrome
topic Technical Advance
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7490860/
https://www.ncbi.nlm.nih.gov/pubmed/32928127
http://dx.doi.org/10.1186/s12882-020-02058-3
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