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Exploration of pathological prediction of chronic kidney diseases by a novel theory of bi-directional probability
In the clinic, the pathological types of chronic kidney diseases (CKD) are considered references for choosing treatment protocols. From a statistical viewpoint, a non-invasive method to predict pathological types of CKD is a focus of our work. In the current study, following a frequency analysis of...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4997332/ https://www.ncbi.nlm.nih.gov/pubmed/27557856 http://dx.doi.org/10.1038/srep32151 |
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author | Yang, Yuan Luo, Min Xiao, Li Zhu, Xue-jing Wang, Chang Fu, Xiao Yuan, Shu-guang Xiao, Fang Liu, Hong Dong, Zheng Liu, Fu-you Sun, Lin |
author_facet | Yang, Yuan Luo, Min Xiao, Li Zhu, Xue-jing Wang, Chang Fu, Xiao Yuan, Shu-guang Xiao, Fang Liu, Hong Dong, Zheng Liu, Fu-you Sun, Lin |
author_sort | Yang, Yuan |
collection | PubMed |
description | In the clinic, the pathological types of chronic kidney diseases (CKD) are considered references for choosing treatment protocols. From a statistical viewpoint, a non-invasive method to predict pathological types of CKD is a focus of our work. In the current study, following a frequency analysis of the clinical indices of 588 CKD patients in the department of nephrology, a third-grade class-A hospital, a novel theory is proposed: “bi-directional cumulative probability dichotomy”. Further, two models for the prediction and differential diagnosis of CKD pathological type are established. The former indicates an occurrence probability of the pathological types, and the latter indicates an occurrence of CKD pathological type according to logistic binary regression. To verify the models, data were collected from 135 patients, and the results showed that the highest accuracy rate on membranous nephropathy (MN-100%), followed by IgA nephropathy (IgAN-83.33%) and mild lesion type (MLN-73.53%), whereas lower prediction accuracy was observed for mesangial proliferative glomerulonephritis (0%) and focal segmental sclerosis type (21.74%). The models of bi-directional probability prediction and differential diagnosis indicate a good prediction value in MN, IgAN and MLN and may be considered alternative methods for the pathological discrimination of CKD patients who are unable to undergo renal biopsy. |
format | Online Article Text |
id | pubmed-4997332 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-49973322016-09-01 Exploration of pathological prediction of chronic kidney diseases by a novel theory of bi-directional probability Yang, Yuan Luo, Min Xiao, Li Zhu, Xue-jing Wang, Chang Fu, Xiao Yuan, Shu-guang Xiao, Fang Liu, Hong Dong, Zheng Liu, Fu-you Sun, Lin Sci Rep Article In the clinic, the pathological types of chronic kidney diseases (CKD) are considered references for choosing treatment protocols. From a statistical viewpoint, a non-invasive method to predict pathological types of CKD is a focus of our work. In the current study, following a frequency analysis of the clinical indices of 588 CKD patients in the department of nephrology, a third-grade class-A hospital, a novel theory is proposed: “bi-directional cumulative probability dichotomy”. Further, two models for the prediction and differential diagnosis of CKD pathological type are established. The former indicates an occurrence probability of the pathological types, and the latter indicates an occurrence of CKD pathological type according to logistic binary regression. To verify the models, data were collected from 135 patients, and the results showed that the highest accuracy rate on membranous nephropathy (MN-100%), followed by IgA nephropathy (IgAN-83.33%) and mild lesion type (MLN-73.53%), whereas lower prediction accuracy was observed for mesangial proliferative glomerulonephritis (0%) and focal segmental sclerosis type (21.74%). The models of bi-directional probability prediction and differential diagnosis indicate a good prediction value in MN, IgAN and MLN and may be considered alternative methods for the pathological discrimination of CKD patients who are unable to undergo renal biopsy. Nature Publishing Group 2016-08-25 /pmc/articles/PMC4997332/ /pubmed/27557856 http://dx.doi.org/10.1038/srep32151 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Yang, Yuan Luo, Min Xiao, Li Zhu, Xue-jing Wang, Chang Fu, Xiao Yuan, Shu-guang Xiao, Fang Liu, Hong Dong, Zheng Liu, Fu-you Sun, Lin Exploration of pathological prediction of chronic kidney diseases by a novel theory of bi-directional probability |
title | Exploration of pathological prediction of chronic kidney diseases by a novel theory of bi-directional probability |
title_full | Exploration of pathological prediction of chronic kidney diseases by a novel theory of bi-directional probability |
title_fullStr | Exploration of pathological prediction of chronic kidney diseases by a novel theory of bi-directional probability |
title_full_unstemmed | Exploration of pathological prediction of chronic kidney diseases by a novel theory of bi-directional probability |
title_short | Exploration of pathological prediction of chronic kidney diseases by a novel theory of bi-directional probability |
title_sort | exploration of pathological prediction of chronic kidney diseases by a novel theory of bi-directional probability |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4997332/ https://www.ncbi.nlm.nih.gov/pubmed/27557856 http://dx.doi.org/10.1038/srep32151 |
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