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Construction of Rheumatoid Arthritis Risk Prediction and Medical Image Applications from Rheumatoid Factor Levels

OBJECTIVE: To study the value of rheumatoid factor (RF) levels in the risk assessment of rheumatoid arthritis (RA) and combined hypertension and diabetes mellitus (DM) and construct RA risk prediction and medical image applications from rheumatoid factor levels. METHODS: A total of 249 RA patients w...

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Autores principales: Li, Wenrun, Bi, Sheng, Liang, Yu, Zhu, Hongyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9553335/
https://www.ncbi.nlm.nih.gov/pubmed/36238489
http://dx.doi.org/10.1155/2022/8617467
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author Li, Wenrun
Bi, Sheng
Liang, Yu
Zhu, Hongyan
author_facet Li, Wenrun
Bi, Sheng
Liang, Yu
Zhu, Hongyan
author_sort Li, Wenrun
collection PubMed
description OBJECTIVE: To study the value of rheumatoid factor (RF) levels in the risk assessment of rheumatoid arthritis (RA) and combined hypertension and diabetes mellitus (DM) and construct RA risk prediction and medical image applications from rheumatoid factor levels. METHODS: A total of 249 RA patients who were treated in the First People's Hospital of Yunnan Province, and another 149 non-RA people were selected as the controls. The clinical data and the detection results of serum circulating RF_IgA, RF_IgG, and RF_IgM were collected. The receiver operating curve (ROC) and logistic regression were used to analyze the value of RF levels in the risk assessment of RA and combined hypertension and DM. RESULTS: After adjusting for age, BMI, smoking, drinking, hypertension, and diabetes, logistic regression analysis showed that RF_IgA positive, RF_IgG positive, and RF_IgM positive were all independent risk factors for RA (P < 0.05). The area under the curve (AUC) of circulating RF_IgA, RF_IgG, and RF_IgM levels in predicting RA was 0.79 (95% CI: 0.74-0.83, P < 0.001), 0.73 (95% CI: 0.68-0.78, P < 0.001), and 0.87 (95% CI: 0.84-0.91, P < 0.001), respectively. The AUC for predicting RA was 0.88 (95% CI: 0.85-0.92, P < 0.001) when combined detection of circulating RF_IgA, RF_IgG, and RF_IgM levels in peripheral blood. After adjusting for age and sex, logistic regression analysis showed that RF_IgA positive, RF_IgG positive, and RF_IgM positive were not independent risk factors for DM in RA patients (P > 0.05). CONCLUSION: The levels of serum circulating RF_IgA, RF_IgG, and RF_IgM are valuable indicators for predicting the risk of RA, but not for the risk of RA complicated with hypertension and DM.
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spelling pubmed-95533352022-10-12 Construction of Rheumatoid Arthritis Risk Prediction and Medical Image Applications from Rheumatoid Factor Levels Li, Wenrun Bi, Sheng Liang, Yu Zhu, Hongyan Comput Math Methods Med Research Article OBJECTIVE: To study the value of rheumatoid factor (RF) levels in the risk assessment of rheumatoid arthritis (RA) and combined hypertension and diabetes mellitus (DM) and construct RA risk prediction and medical image applications from rheumatoid factor levels. METHODS: A total of 249 RA patients who were treated in the First People's Hospital of Yunnan Province, and another 149 non-RA people were selected as the controls. The clinical data and the detection results of serum circulating RF_IgA, RF_IgG, and RF_IgM were collected. The receiver operating curve (ROC) and logistic regression were used to analyze the value of RF levels in the risk assessment of RA and combined hypertension and DM. RESULTS: After adjusting for age, BMI, smoking, drinking, hypertension, and diabetes, logistic regression analysis showed that RF_IgA positive, RF_IgG positive, and RF_IgM positive were all independent risk factors for RA (P < 0.05). The area under the curve (AUC) of circulating RF_IgA, RF_IgG, and RF_IgM levels in predicting RA was 0.79 (95% CI: 0.74-0.83, P < 0.001), 0.73 (95% CI: 0.68-0.78, P < 0.001), and 0.87 (95% CI: 0.84-0.91, P < 0.001), respectively. The AUC for predicting RA was 0.88 (95% CI: 0.85-0.92, P < 0.001) when combined detection of circulating RF_IgA, RF_IgG, and RF_IgM levels in peripheral blood. After adjusting for age and sex, logistic regression analysis showed that RF_IgA positive, RF_IgG positive, and RF_IgM positive were not independent risk factors for DM in RA patients (P > 0.05). CONCLUSION: The levels of serum circulating RF_IgA, RF_IgG, and RF_IgM are valuable indicators for predicting the risk of RA, but not for the risk of RA complicated with hypertension and DM. Hindawi 2022-10-04 /pmc/articles/PMC9553335/ /pubmed/36238489 http://dx.doi.org/10.1155/2022/8617467 Text en Copyright © 2022 Wenrun Li et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Li, Wenrun
Bi, Sheng
Liang, Yu
Zhu, Hongyan
Construction of Rheumatoid Arthritis Risk Prediction and Medical Image Applications from Rheumatoid Factor Levels
title Construction of Rheumatoid Arthritis Risk Prediction and Medical Image Applications from Rheumatoid Factor Levels
title_full Construction of Rheumatoid Arthritis Risk Prediction and Medical Image Applications from Rheumatoid Factor Levels
title_fullStr Construction of Rheumatoid Arthritis Risk Prediction and Medical Image Applications from Rheumatoid Factor Levels
title_full_unstemmed Construction of Rheumatoid Arthritis Risk Prediction and Medical Image Applications from Rheumatoid Factor Levels
title_short Construction of Rheumatoid Arthritis Risk Prediction and Medical Image Applications from Rheumatoid Factor Levels
title_sort construction of rheumatoid arthritis risk prediction and medical image applications from rheumatoid factor levels
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9553335/
https://www.ncbi.nlm.nih.gov/pubmed/36238489
http://dx.doi.org/10.1155/2022/8617467
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