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Thesis

Flow mediated dilatation over the natural history of abdominal aortic aneurysms

Abstract:

Abdominal aortic aneurysm, an abnormal dilatation of the descending aorta, disproportionately affects males and is often asymptomatic until rupture, posing major risk of mortality. The natural history varies greatly in individuals; some patients remain at subclinical aortic diameters for decades, others rapidly progress to sizes indicating surgical intervention. Surgical mortality is associated with age, so it is advantageous to predict growth of AAA. The biochemical implications of wall degradation may have systemic inflammatory effects which adversely affect the endothelium, which regulates vasomotor tone. Vasodilation is modulated by the release of nitric oxide and the measurement of flow mediated dilatation (FMD) is a widely used proxy for NO bioavailability. The goal of this study is to examine changes of FMD over time and its predictive value in AAA growth. We hypothesise that FMD correlates with future growth rate of AAAs in humans.

In FMD, ultrasonography is used to measure the diameter of an artery before and after it is subjected to shear stress through temporary limb ischaemia. No past study of AAA patients has examined serial measurements of FMD. The OxAAA study collects serial measurements on AAA patients under surveillance and undergoing surgery. FMD predicts future aneurysm growth of AAA patients and FMD deteriorates over time. Due to its non-invasive and cost effective nature, FMD is useful in predicting the growth of AAA, and has also been shown to predict cardiovascular events, serving a two-fold purpose. In clinical contexts, it may be used to foresee imminent need for AAA repair, allowing for pre-surgical lifestyle changes. FMD may also indicate future growth, allowing for less frequent surveillance and reducing costs.

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Division:
MSD
Department:
Surgical Sciences
Role:
Author

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Role:
Supervisor
Role:
Supervisor


DOI:
Type of award:
MSc by Research
Level of award:
Masters
Awarding institution:
University of Oxford


UUID:
uuid:a7910e0b-2aca-4368-a16d-2b4257114a28
Deposit date:
2017-10-19
ARK identifier:

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