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contributor authorManring, Noah D.
contributor authorAl-Toki, Mouayed H.
date accessioned2022-02-04T22:19:17Z
date available2022-02-04T22:19:17Z
date copyright7/17/2020 12:00:00 AM
date issued2020
identifier issn2572-7958
identifier otherrisk_006_04_041008.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4275334
description abstractAortic compliance has been well established as an independent predictor of cardiovascular morbidity and mortality. The current “gold standard” for assessing aortic compliance is to use the carotid-femoral pulse-wave velocity (PWV) as a surrogate; however, PWV alone has been discussed in the literature as being inadequate for assessing compliance, especially for elderly patients and others who have a stiff aorta. In this paper, an equation for the aortic compliance is developed using two approaches: (1) lumped-parameter modeling based on blood-pressure data and (2) distributed modeling based on the PWV. in vitro experiments are conducted using a silicone-rubber tube which simulates the aorta, and an actual aorta harvested from a 1 year old, Holstein heifer. For both the rubber aorta and the Holstein aorta, a comparison is made between the blood-pressure model and the PWV model. In conclusion, it is shown that good agreement exists between the two models, suggesting that either model may be used depending upon the available data. Furthermore, due to differences in material properties, it is shown that the compliance of the rubber aorta increases with mean arterial pressure, while the compliance of the Holstein aorta decreases with mean arterial pressure. Clinical implications of this research are also discussed.
publisherThe American Society of Mechanical Engineers (ASME)
titleTwo Methods to Assess Aortic Compliance Using Blood Pressure and Pulse-Wave Velocity
typeJournal Paper
journal volume3
journal issue4
journal titleJournal of Engineering and Science in Medical Diagnostics and Therapy
identifier doi10.1115/1.4047575
journal fristpage044501-1
journal lastpage044501-10
page10
treeJournal of Engineering and Science in Medical Diagnostics and Therapy:;2020:;volume( 003 ):;issue: 004
contenttypeFulltext


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