A1 Refereed original research article in a scientific journal

Impedance plethysmography-based method in the assessment of subclinical atherosclerosis




AuthorsHaapala Mira, Lyytikäinen Leo-Pekka, Peltokangas Mikko, Koivistoinen Teemu, Hutri-Kähonen Nina, Laurila Mika-Matti, Mäntysalo Matti, Raitakari Olli T, Kähonen Mika, Lehtimäki Terho, Vehkaoja Antti, Oksala Niku

PublisherELSEVIER IRELAND LTD

Publication year2021

JournalAtherosclerosis

Journal name in sourceATHEROSCLEROSIS

Journal acronymATHEROSCLEROSIS

Volume319

First page 101

Last page107

Number of pages7

ISSN0021-9150

DOIhttps://doi.org/10.1016/j.atherosclerosis.2021.01.006

Self-archived copy’s web addresshttps://research.utu.fi/converis/portal/detail/Publication/53312161


Abstract
Background and aimsThe aim of this study was to examine an association of individual and combined pulse waveform parameters derived from bioimpedance measurements, that is pulse waves from a distal impedance plethysmographic (IPG), a whole-body impedance cardiographic (ICG) and transformed distal impedance plethysmographic (tIPG) signals, with markers of subclinical atherosclerosis, i.e. carotid intima-media thickness (cIMT), brachial artery flow-mediated dilation (FMD) and carotid artery distensibility (Cdist). The level of the association was also compared for arterial pulse wave velocity (PWV) and cIMT, FMD, and Cdist.
MethodsIPG, ICG, tIPG signals were measured from 1741 Finnish adults aged 30-45 years. The association between pulse wave parameters and cIMT, FMD and Cdist was studied using bootstrapped stepwise Akaike's Information Criterion method resulting in selection of parameters other than PWV, i.e. parameters having stronger association with cIMT, FMD and Cdist than PWV, in the model. Then risk scores were calculated from the selected pulse wave parameters and their association between cIMT, FMD and Cdist was studied with multivariable linear regression analysis.
Results The risk score was found to be the third strongest predictor of subclinical atherosclerosis as indicated by cIMT measurement, the second strongest predictor of FMD and the strongest predictor of Cdist. These findings show that several individual pulse wave parameters were associated more strongly with cIMT, FMD, and Cdist than PWV when adjusted with clinical risk factors.
ConclusionsImpedance based pulse waveform analysis provides a useful tool for assessing cardiovascular risk and estimating presence of structural changes in the vasculature.

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