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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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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. |
format | Online Article Text |
id | pubmed-9553335 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
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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