Date of Award

Spring 5-25-2019

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Micro and Nanoscale Systems

First Advisor

Eric Sherer

Abstract

Abdominal aortic aneurysm (AAA) is indicated when the diameter of the abdominal aorta is larger than 30 mm. The primary risk associated with AAA is an increased risk of aortic rupture, which is fatal in 68-90% of cases. Once a patient is diagnosed with AAA, the AAA is monitored via abdominal ultrasound. The rationale for the regular surveillance is that the risk of rupture is low for AAA, less than 55 mm in size, but increases dramatically in diameter larger than 55 mm. Early surgery on patients with smaller AAA diameters (lower risk of rupture) has a higher mortality rate than taking no action. Despite numerous researches done about prediction of AAA size, there is a lack of a design that quantifies the risk of surgery and rates of rupture and mortality at surveillances and integrates it with the process of decision making. This research addresses the necessity of integrating the rupture rate in different time periods.

A Monte-Carlo simulation technique was applied to a growth model based on Bayesian Analysis to simulate 10,000 and 1,000,000 hypothetical patients. To ensure that the generated data correlated to the original data, the Cholesky decomposition was determined from the patient cohort data and applied to generation of characteristics of the hypothetical patients. The probability of each possible growth trajectory and cumulative risk of rupture is computed by Bayesian Analysis for each patient. Mortality and rupture rates are calculated individually, applying the Monte-Carlo simulation on meta-analysis paper and National Vital Statistics System data for 2014. The risk of rupture increases in patients with increase in the size and the mortality rate increases with the time.

Different protocols regarding the surgical intervention threshold, risk of surgery, and observation time limits were designed, and the effects of life expectancy simulated. Simulating all 10,000 and 1,000,000 hypothetical patients and comparing the results for different designed protocols and current available protocols in different countries, gave us a unique opportunity to analyze the effect of the surveillance and surgery decisions on patients' mortality.

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