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Brachial-ankle pulse wave velocity trajectories in a middle-aged population

OBJECTIVE: The “trajectory” phenotype was observed in several cardiovascular risk factors with aging. We aim to identify multiple brachial-ankle Pulse Wave Velocity (baPWV) trajectory phenotypes and assess their determinants. METHODS: Among 5,182 participants with baPWV measurements (2010–2016) at n...

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Autores principales: Deng, Xuan, Song, Yongjian, Han, Xu, Chen, Xueyu, Yang, Wenyi, Wu, Shouling, Zhou, Yong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10083284/
https://www.ncbi.nlm.nih.gov/pubmed/37051065
http://dx.doi.org/10.3389/fcvm.2023.1092525
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author Deng, Xuan
Song, Yongjian
Han, Xu
Chen, Xueyu
Yang, Wenyi
Wu, Shouling
Zhou, Yong
author_facet Deng, Xuan
Song, Yongjian
Han, Xu
Chen, Xueyu
Yang, Wenyi
Wu, Shouling
Zhou, Yong
author_sort Deng, Xuan
collection PubMed
description OBJECTIVE: The “trajectory” phenotype was observed in several cardiovascular risk factors with aging. We aim to identify multiple brachial-ankle Pulse Wave Velocity (baPWV) trajectory phenotypes and assess their determinants. METHODS: Among 5,182 participants with baPWV measurements (2010–2016) at no less than three time points in Kailuan Study, we derived baPWV trajectory pattern using SAS Proc Traj program. We applied the lowest Bayesian information criterion to identify the best typing model, related the identified trajectory pattern to baseline and changes in characteristics. RESULTS: Among 5.3 ± 1.7 years follow-up, four distinct baPWV trajectories were identified as low (1,961,37.8%), medium-low (1,846,35.6%), medium-high (1,024,19.8%), and high (351,6.8%) groups. In the stepwise models, mean arterial pressure and age were the main determinators of the trajectory patterns, with a Δpseudo-R(2) of 0.335 and 0.164, respectively. With the low trajectory group as reference and multivariable adjustment, odd ratios of medium low, medium high and high associated with 1 mmHg increment of mean arterial pressure were 1.08(95%CI: 1.07–1.09), 1.13(1.12–1.14), and 1.16(1.15–1.18). The estimates for age were 1.08(1.07–1.10), 1.20(1.18–1.21) and 1.28(1.26–1.31). Additionally, baseline resting heart rate, low-density lipoprotein cholesterol, fasting blood glucose, hypersensitive C-reaction protein and uric acid, and changes in mean arterial pressure, resting heart rate, fasting blood glucose, and uric acid were positively associated with the trajectory, while BMI was negatively associated. CONCLUSIONS: The changes in baPWV overtime followed a “trajectory” pattern, mainly determined by mean arterial pressure and age.
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spelling pubmed-100832842023-04-11 Brachial-ankle pulse wave velocity trajectories in a middle-aged population Deng, Xuan Song, Yongjian Han, Xu Chen, Xueyu Yang, Wenyi Wu, Shouling Zhou, Yong Front Cardiovasc Med Cardiovascular Medicine OBJECTIVE: The “trajectory” phenotype was observed in several cardiovascular risk factors with aging. We aim to identify multiple brachial-ankle Pulse Wave Velocity (baPWV) trajectory phenotypes and assess their determinants. METHODS: Among 5,182 participants with baPWV measurements (2010–2016) at no less than three time points in Kailuan Study, we derived baPWV trajectory pattern using SAS Proc Traj program. We applied the lowest Bayesian information criterion to identify the best typing model, related the identified trajectory pattern to baseline and changes in characteristics. RESULTS: Among 5.3 ± 1.7 years follow-up, four distinct baPWV trajectories were identified as low (1,961,37.8%), medium-low (1,846,35.6%), medium-high (1,024,19.8%), and high (351,6.8%) groups. In the stepwise models, mean arterial pressure and age were the main determinators of the trajectory patterns, with a Δpseudo-R(2) of 0.335 and 0.164, respectively. With the low trajectory group as reference and multivariable adjustment, odd ratios of medium low, medium high and high associated with 1 mmHg increment of mean arterial pressure were 1.08(95%CI: 1.07–1.09), 1.13(1.12–1.14), and 1.16(1.15–1.18). The estimates for age were 1.08(1.07–1.10), 1.20(1.18–1.21) and 1.28(1.26–1.31). Additionally, baseline resting heart rate, low-density lipoprotein cholesterol, fasting blood glucose, hypersensitive C-reaction protein and uric acid, and changes in mean arterial pressure, resting heart rate, fasting blood glucose, and uric acid were positively associated with the trajectory, while BMI was negatively associated. CONCLUSIONS: The changes in baPWV overtime followed a “trajectory” pattern, mainly determined by mean arterial pressure and age. Frontiers Media S.A. 2023-03-27 /pmc/articles/PMC10083284/ /pubmed/37051065 http://dx.doi.org/10.3389/fcvm.2023.1092525 Text en © 2023 Deng, Song, Han, Chen, Yan, Wu and Zhou. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cardiovascular Medicine
Deng, Xuan
Song, Yongjian
Han, Xu
Chen, Xueyu
Yang, Wenyi
Wu, Shouling
Zhou, Yong
Brachial-ankle pulse wave velocity trajectories in a middle-aged population
title Brachial-ankle pulse wave velocity trajectories in a middle-aged population
title_full Brachial-ankle pulse wave velocity trajectories in a middle-aged population
title_fullStr Brachial-ankle pulse wave velocity trajectories in a middle-aged population
title_full_unstemmed Brachial-ankle pulse wave velocity trajectories in a middle-aged population
title_short Brachial-ankle pulse wave velocity trajectories in a middle-aged population
title_sort brachial-ankle pulse wave velocity trajectories in a middle-aged population
topic Cardiovascular Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10083284/
https://www.ncbi.nlm.nih.gov/pubmed/37051065
http://dx.doi.org/10.3389/fcvm.2023.1092525
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