Analysis of risk factors and the predictive value of a nomogram model for coronary heart disease in patients with rheumatoid arthritis

BackgroundRheumatoid arthritis (RA) is associated with an elevated risk of coronary heart disease (CHD) due to a complex interplay of traditional cardiovascular risk factors and RA-specific mechanisms. This study aimed to identify key risk factors for CHD in RA patients and develop a nomogram model...

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Main Authors: Guozhu Che, Xing Zhao, Haizhuan An, Yanyan Wang, Qianyu Guo, Ke Xu
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-06-01
Series:Frontiers in Cardiovascular Medicine
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Online Access:https://www.frontiersin.org/articles/10.3389/fcvm.2025.1558012/full
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author Guozhu Che
Xing Zhao
Haizhuan An
Yanyan Wang
Qianyu Guo
Ke Xu
author_facet Guozhu Che
Xing Zhao
Haizhuan An
Yanyan Wang
Qianyu Guo
Ke Xu
author_sort Guozhu Che
collection DOAJ
description BackgroundRheumatoid arthritis (RA) is associated with an elevated risk of coronary heart disease (CHD) due to a complex interplay of traditional cardiovascular risk factors and RA-specific mechanisms. This study aimed to identify key risk factors for CHD in RA patients and develop a nomogram model for individualized risk prediction.MethodsA retrospective study was conducted involving 258 RA patients, including 32 with CHD and 226 without CHD, admitted between January 2021 and August 2024. Demographic, clinical, and laboratory data were collected. Multivariate logistic regression analysis identified independent risk factors, which were incorporated into a nomogram model. The model's performance was evaluated using the receiver operating characteristic (ROC) curve, calibration plots, and decision curve analysis (DCA). Internal validation was performed using bootstrap resampling.ResultsKey risk factors for CHD in RA patients included hypertension, HbA1c, RA duration, carotid plaque burden, uric acid, and ECG abnormalities. The nomogram demonstrated excellent discriminative ability, with an area under the ROC curve (AUC) of 0.868 (95% CI: 0.819–0.916) and robust calibration (P = 0.908). Internal validation confirmed its reliability (AUC = 0.866). DCA indicated that the nomogram provided superior clinical utility by optimizing the net benefit across a range of threshold probabilities.ConclusionsThis study identified hypertension, elevated HbA1c, prolonged RA duration, carotid plaque burden, increased uric acid levels, and ECG abnormalities as significant risk factors for CHD in RA patients. A nomogram prediction model incorporating these factors was developed, exhibiting outstanding discriminatory and calibration capabilities.
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spelling doaj-art-1b3b6ab3acd44ea280e1f5fbce6ad1422025-08-20T02:31:13ZengFrontiers Media S.A.Frontiers in Cardiovascular Medicine2297-055X2025-06-011210.3389/fcvm.2025.15580121558012Analysis of risk factors and the predictive value of a nomogram model for coronary heart disease in patients with rheumatoid arthritisGuozhu CheXing ZhaoHaizhuan AnYanyan WangQianyu GuoKe XuBackgroundRheumatoid arthritis (RA) is associated with an elevated risk of coronary heart disease (CHD) due to a complex interplay of traditional cardiovascular risk factors and RA-specific mechanisms. This study aimed to identify key risk factors for CHD in RA patients and develop a nomogram model for individualized risk prediction.MethodsA retrospective study was conducted involving 258 RA patients, including 32 with CHD and 226 without CHD, admitted between January 2021 and August 2024. Demographic, clinical, and laboratory data were collected. Multivariate logistic regression analysis identified independent risk factors, which were incorporated into a nomogram model. The model's performance was evaluated using the receiver operating characteristic (ROC) curve, calibration plots, and decision curve analysis (DCA). Internal validation was performed using bootstrap resampling.ResultsKey risk factors for CHD in RA patients included hypertension, HbA1c, RA duration, carotid plaque burden, uric acid, and ECG abnormalities. The nomogram demonstrated excellent discriminative ability, with an area under the ROC curve (AUC) of 0.868 (95% CI: 0.819–0.916) and robust calibration (P = 0.908). Internal validation confirmed its reliability (AUC = 0.866). DCA indicated that the nomogram provided superior clinical utility by optimizing the net benefit across a range of threshold probabilities.ConclusionsThis study identified hypertension, elevated HbA1c, prolonged RA duration, carotid plaque burden, increased uric acid levels, and ECG abnormalities as significant risk factors for CHD in RA patients. A nomogram prediction model incorporating these factors was developed, exhibiting outstanding discriminatory and calibration capabilities.https://www.frontiersin.org/articles/10.3389/fcvm.2025.1558012/fullrheumatoid arthritiscoronary heart diseasenomogram modelrisk factorspredictive analysis
spellingShingle Guozhu Che
Xing Zhao
Haizhuan An
Yanyan Wang
Qianyu Guo
Ke Xu
Analysis of risk factors and the predictive value of a nomogram model for coronary heart disease in patients with rheumatoid arthritis
Frontiers in Cardiovascular Medicine
rheumatoid arthritis
coronary heart disease
nomogram model
risk factors
predictive analysis
title Analysis of risk factors and the predictive value of a nomogram model for coronary heart disease in patients with rheumatoid arthritis
title_full Analysis of risk factors and the predictive value of a nomogram model for coronary heart disease in patients with rheumatoid arthritis
title_fullStr Analysis of risk factors and the predictive value of a nomogram model for coronary heart disease in patients with rheumatoid arthritis
title_full_unstemmed Analysis of risk factors and the predictive value of a nomogram model for coronary heart disease in patients with rheumatoid arthritis
title_short Analysis of risk factors and the predictive value of a nomogram model for coronary heart disease in patients with rheumatoid arthritis
title_sort analysis of risk factors and the predictive value of a nomogram model for coronary heart disease in patients with rheumatoid arthritis
topic rheumatoid arthritis
coronary heart disease
nomogram model
risk factors
predictive analysis
url https://www.frontiersin.org/articles/10.3389/fcvm.2025.1558012/full
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