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Cardiac MR modelling of systolic and diastolic blood pressure

Authors :
Samer Alabed
Pankaj Garg
Rui Li
Andrew J Swift
Ciaran Grafton-Clarke
Peter Swoboda
Rebecca Gosling
Hosamadin Assadi
Liang Zhong
Ian Halliday
Vassilios S Vassiliou
David Paul Ripley
Gareth Matthews
Xiaodan Zhao
Zia Mehmood
Bahman Kasmai
Vaishali Limbachia
Gurung-Koney Yashoda
Rob J van der Geest
Source :
Open Heart, Vol 10, Iss 2 (2023)
Publication Year :
2023
Publisher :
BMJ Publishing Group, 2023.

Abstract

Aims Blood pressure (BP) is a crucial factor in cardiovascular health and can affect cardiac imaging assessments. However, standard outpatient cardiovascular MR (CMR) imaging procedures do not typically include BP measurements prior to image acquisition. This study proposes that brachial systolic BP (SBP) and diastolic BP (DBP) can be modelled using patient characteristics and CMR data.Methods In this multicentre study, 57 patients from the PREFER-CMR registry and 163 patients from other registries were used as the derivation cohort. All subjects had their brachial SBP and DBP measured using a sphygmomanometer. Multivariate linear regression analysis was applied to predict brachial BP. The model was subsequently validated in a cohort of 169 healthy individuals.Results Age and left ventricular ejection fraction were associated with SBP. Aortic forward flow, body surface area and left ventricular mass index were associated with DBP. When applied to the validation cohort, the correlation coefficient between CMR-derived SBP and brachial SBP was (r=0.16, 95% CI 0.011 to 0.305, p=0.03), and CMR-derived DBP and brachial DBP was (r=0.27, 95% CI 0.122 to 0.403, p=0.0004). The area under the curve (AUC) for CMR-derived SBP to predict SBP>120 mmHg was 0.59, p=0.038. Moreover, CMR-derived DBP to predict DBP>80 mmHg had an AUC of 0.64, p=0.002.Conclusion CMR-derived SBP and DBP models can estimate brachial SBP and DBP. Such models may allow efficient prospective collection, as well as retrospective estimation of BP, which should be incorporated into assessments due to its critical effect on load-dependent parameters.

Details

Language :
English
ISSN :
20533624
Volume :
10
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Open Heart
Publication Type :
Academic Journal
Accession number :
edsdoj.fa7cbd2d10af43b58aba3b910e488410
Document Type :
article
Full Text :
https://doi.org/10.1136/openhrt-2023-002484