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Establishment of a clinical diagnostic model for gouty arthritis based on the serum biochemical profile: A case-control study

The disease progression of gouty arthritis (GA) is relatively clear, with the 4 stages of hyperuricemia (HUA), acute gouty arthritis (AGA), gouty arthritis during the intermittent period (GIP), and chronic gouty arthritis (CGA). This paper attempts to construct a clinical diagnostic model based on b...

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Autores principales: Lyu, Shang, Ding, Ruowen, Yang, Shilin, Chen, Wanyuan, Rao, Yi, OuYang, Hui, Liu, Peng, Feng, Yulin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8078334/
https://www.ncbi.nlm.nih.gov/pubmed/33879701
http://dx.doi.org/10.1097/MD.0000000000025542
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author Lyu, Shang
Ding, Ruowen
Yang, Shilin
Chen, Wanyuan
Rao, Yi
OuYang, Hui
Liu, Peng
Feng, Yulin
author_facet Lyu, Shang
Ding, Ruowen
Yang, Shilin
Chen, Wanyuan
Rao, Yi
OuYang, Hui
Liu, Peng
Feng, Yulin
author_sort Lyu, Shang
collection PubMed
description The disease progression of gouty arthritis (GA) is relatively clear, with the 4 stages of hyperuricemia (HUA), acute gouty arthritis (AGA), gouty arthritis during the intermittent period (GIP), and chronic gouty arthritis (CGA). This paper attempts to construct a clinical diagnostic model based on blood routine test data, in order to avoid the need for bursa fluid examination and other tedious steps, and at the same time to predict the development direction of GA. Serum samples from 579 subjects were collected within 3 years in this study and were divided into a training set (n = 379) and validation set (n = 200). After a series of multivariate statistical analyses, the serum biochemical profile was obtained, which could effectively distinguish different stages of GA. A clinical diagnosis model based on the biochemical index of the training set was established to maximize the probability of the stage as a diagnosis, and the serum biochemical data from 200 patients were used for validation. The total area under the curve (AUC) of the clinical diagnostic model was 0.9534, and the AUCs of the 5 models were 0.9814 (Control), 0.9288 (HUA), 0.9752 (AGA), 0.9056 (GIP), and 0.9759 (CGA). The kappa coefficient of the clinical diagnostic model was 0.80. This clinical diagnostic model could be applied clinically and in research to improve the accuracy of the identification of the different stages of GA. Meanwhile, the serum biochemical profile revealed by this study could be used to assist the clinical diagnosis and prediction of GA.
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spelling pubmed-80783342021-04-27 Establishment of a clinical diagnostic model for gouty arthritis based on the serum biochemical profile: A case-control study Lyu, Shang Ding, Ruowen Yang, Shilin Chen, Wanyuan Rao, Yi OuYang, Hui Liu, Peng Feng, Yulin Medicine (Baltimore) 4100 The disease progression of gouty arthritis (GA) is relatively clear, with the 4 stages of hyperuricemia (HUA), acute gouty arthritis (AGA), gouty arthritis during the intermittent period (GIP), and chronic gouty arthritis (CGA). This paper attempts to construct a clinical diagnostic model based on blood routine test data, in order to avoid the need for bursa fluid examination and other tedious steps, and at the same time to predict the development direction of GA. Serum samples from 579 subjects were collected within 3 years in this study and were divided into a training set (n = 379) and validation set (n = 200). After a series of multivariate statistical analyses, the serum biochemical profile was obtained, which could effectively distinguish different stages of GA. A clinical diagnosis model based on the biochemical index of the training set was established to maximize the probability of the stage as a diagnosis, and the serum biochemical data from 200 patients were used for validation. The total area under the curve (AUC) of the clinical diagnostic model was 0.9534, and the AUCs of the 5 models were 0.9814 (Control), 0.9288 (HUA), 0.9752 (AGA), 0.9056 (GIP), and 0.9759 (CGA). The kappa coefficient of the clinical diagnostic model was 0.80. This clinical diagnostic model could be applied clinically and in research to improve the accuracy of the identification of the different stages of GA. Meanwhile, the serum biochemical profile revealed by this study could be used to assist the clinical diagnosis and prediction of GA. Lippincott Williams & Wilkins 2021-04-23 /pmc/articles/PMC8078334/ /pubmed/33879701 http://dx.doi.org/10.1097/MD.0000000000025542 Text en Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0 (https://creativecommons.org/licenses/by/4.0/)
spellingShingle 4100
Lyu, Shang
Ding, Ruowen
Yang, Shilin
Chen, Wanyuan
Rao, Yi
OuYang, Hui
Liu, Peng
Feng, Yulin
Establishment of a clinical diagnostic model for gouty arthritis based on the serum biochemical profile: A case-control study
title Establishment of a clinical diagnostic model for gouty arthritis based on the serum biochemical profile: A case-control study
title_full Establishment of a clinical diagnostic model for gouty arthritis based on the serum biochemical profile: A case-control study
title_fullStr Establishment of a clinical diagnostic model for gouty arthritis based on the serum biochemical profile: A case-control study
title_full_unstemmed Establishment of a clinical diagnostic model for gouty arthritis based on the serum biochemical profile: A case-control study
title_short Establishment of a clinical diagnostic model for gouty arthritis based on the serum biochemical profile: A case-control study
title_sort establishment of a clinical diagnostic model for gouty arthritis based on the serum biochemical profile: a case-control study
topic 4100
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8078334/
https://www.ncbi.nlm.nih.gov/pubmed/33879701
http://dx.doi.org/10.1097/MD.0000000000025542
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