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A nomogram based on endothelial function and conventional risk factors predicts coronary artery disease in hypertensives

BACKGROUND: There is currently a lack of a precise, concise, and practical clinical prediction model for predicting coronary artery disease (CAD) in patients with essential hypertension (EH). This study aimed to construct a nomogram to predict CAD in patients with EH based on flow-mediated dilation...

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Autores principales: Huang, Xiao-Dong, Lin, Ji-Yan, Huang, Xian-Wei, Zhou, Ting-Ting, Xie, Liang-Di
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10148409/
https://www.ncbi.nlm.nih.gov/pubmed/37118701
http://dx.doi.org/10.1186/s12872-023-03235-6
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author Huang, Xiao-Dong
Lin, Ji-Yan
Huang, Xian-Wei
Zhou, Ting-Ting
Xie, Liang-Di
author_facet Huang, Xiao-Dong
Lin, Ji-Yan
Huang, Xian-Wei
Zhou, Ting-Ting
Xie, Liang-Di
author_sort Huang, Xiao-Dong
collection PubMed
description BACKGROUND: There is currently a lack of a precise, concise, and practical clinical prediction model for predicting coronary artery disease (CAD) in patients with essential hypertension (EH). This study aimed to construct a nomogram to predict CAD in patients with EH based on flow-mediated dilation (FMD) of brachial artery and traditional risk factors. METHODS: Clinical data of 1752 patients with EH were retrospectively collected. High-resolution vascular ultrasound was used to detect FMD in all patients at the Fujian Hypertension Research Institute, China. Patients were divided into two groups, i.e. training group (n = 1204, from August 2000 to December 2013) and validation group (n = 548, from January 2014 to May 2016) according to the time of enrollment. Independent predictors of CAD were analyzed by multivariable logistic regression in the training group, and a nomogram was constructed accordingly. Finally, we evaluated the discrimination, calibration, and clinical applicability of the model using the area under curve (AUC) of receiver operating characteristic analysis, calibration curve combined with Hosmer-Lemeshow test, and decision curve, respectively. RESULTS: There were 263 (21.8%) cases of EH combined with CAD in the training group. Multivariate logistic regression showed that FMD, age, duration of EH, waist circumference, and diabetes mellitus were independent influencing factors for CAD in EH patients. Smoking which was close to statistical significance (P = 0.062) was also included in the regression model to increase the accuracy. Ultimately, the nomogram for predicting CAD in EH patients was constructed according to above predictors after proper transformation. The AUC values of the training group and the validation group were 0.799 (95%CI 0.770–0.829) and 0.836 (95%CI 0.787–0.886), respectively. Calibration curve and Hosmer-Lemeshow test showed that the model had good calibration (training group: χ(2) = 0.55, P = 0.759; validation group: χ(2) = 1.62, P = 0.446). The decision curve also verified the clinical applicability of the nomogram. CONCLUSION: The nomogram based on FMD and traditional risk factors (age, duration of EH disease, smoking, waist circumference and diabetes mellitus) can predict CAD high-risk group among patients with EH.
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spelling pubmed-101484092023-04-30 A nomogram based on endothelial function and conventional risk factors predicts coronary artery disease in hypertensives Huang, Xiao-Dong Lin, Ji-Yan Huang, Xian-Wei Zhou, Ting-Ting Xie, Liang-Di BMC Cardiovasc Disord Research BACKGROUND: There is currently a lack of a precise, concise, and practical clinical prediction model for predicting coronary artery disease (CAD) in patients with essential hypertension (EH). This study aimed to construct a nomogram to predict CAD in patients with EH based on flow-mediated dilation (FMD) of brachial artery and traditional risk factors. METHODS: Clinical data of 1752 patients with EH were retrospectively collected. High-resolution vascular ultrasound was used to detect FMD in all patients at the Fujian Hypertension Research Institute, China. Patients were divided into two groups, i.e. training group (n = 1204, from August 2000 to December 2013) and validation group (n = 548, from January 2014 to May 2016) according to the time of enrollment. Independent predictors of CAD were analyzed by multivariable logistic regression in the training group, and a nomogram was constructed accordingly. Finally, we evaluated the discrimination, calibration, and clinical applicability of the model using the area under curve (AUC) of receiver operating characteristic analysis, calibration curve combined with Hosmer-Lemeshow test, and decision curve, respectively. RESULTS: There were 263 (21.8%) cases of EH combined with CAD in the training group. Multivariate logistic regression showed that FMD, age, duration of EH, waist circumference, and diabetes mellitus were independent influencing factors for CAD in EH patients. Smoking which was close to statistical significance (P = 0.062) was also included in the regression model to increase the accuracy. Ultimately, the nomogram for predicting CAD in EH patients was constructed according to above predictors after proper transformation. The AUC values of the training group and the validation group were 0.799 (95%CI 0.770–0.829) and 0.836 (95%CI 0.787–0.886), respectively. Calibration curve and Hosmer-Lemeshow test showed that the model had good calibration (training group: χ(2) = 0.55, P = 0.759; validation group: χ(2) = 1.62, P = 0.446). The decision curve also verified the clinical applicability of the nomogram. CONCLUSION: The nomogram based on FMD and traditional risk factors (age, duration of EH disease, smoking, waist circumference and diabetes mellitus) can predict CAD high-risk group among patients with EH. BioMed Central 2023-04-28 /pmc/articles/PMC10148409/ /pubmed/37118701 http://dx.doi.org/10.1186/s12872-023-03235-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Huang, Xiao-Dong
Lin, Ji-Yan
Huang, Xian-Wei
Zhou, Ting-Ting
Xie, Liang-Di
A nomogram based on endothelial function and conventional risk factors predicts coronary artery disease in hypertensives
title A nomogram based on endothelial function and conventional risk factors predicts coronary artery disease in hypertensives
title_full A nomogram based on endothelial function and conventional risk factors predicts coronary artery disease in hypertensives
title_fullStr A nomogram based on endothelial function and conventional risk factors predicts coronary artery disease in hypertensives
title_full_unstemmed A nomogram based on endothelial function and conventional risk factors predicts coronary artery disease in hypertensives
title_short A nomogram based on endothelial function and conventional risk factors predicts coronary artery disease in hypertensives
title_sort nomogram based on endothelial function and conventional risk factors predicts coronary artery disease in hypertensives
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10148409/
https://www.ncbi.nlm.nih.gov/pubmed/37118701
http://dx.doi.org/10.1186/s12872-023-03235-6
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