2D fetal echocardiography (ECHO) can be used for monitoring heart development in utero. This study’s purpose is to empirically model normal fetal heart growth and function changes during development by ECHO and compare these to fetuses diagnosed with and without cardiomyopathy with diabetic mothers. There are existing mathematical models describing fetal heart development but they warrant revalidation and adjustment. 377 normal fetuses with healthy mothers, 98 normal fetuses with diabetic mothers, and 37 fetuses with cardiomyopathy and diabetic mothers had their cardiac structural dimensions, cardiothoracic ratio, valve flow velocities, and heart rates measured by fetal ECHO in a retrospective chart review. Cardiac features were fitted to linear functions, with respect to gestational age, femur length, head circumference, and biparietal diameter and z-scores were created to model normal fetal growth for all parameters. These z-scores were used to assess what metrics had no difference in means between the normal fetuses of both healthy and diabetic mothers but differed from those diagnosed with cardiomyopathy. It was found that functional metrics like mitral and tricuspid E wave and pulmonary velocity could be important predictors for cardiomyopathy when fitted by gestational age, femur length, head circumference, and biparietal diameter. Additionally, aortic and tricuspid annulus diameters when fitted to estimated gestational age showed potential to be predictors for fetal cardiomyopathy. While the metrics overlapped over their full range, combining them together may have the potential for predicting cardiomyopathy in utero. Future directions of this study will explore creating a classifier model that can predict cardiomyopathy using the metrics assessed in this study.

2D fetal echocardiography (ECHO) can be used for monitoring heart development in utero. This study’s purpose is to empirically model normal fetal heart growth and function changes during development by ECHO and compare these to fetuses diagnosed with and without cardiomyopathy with diabetic mothers. There are existing mathematical models describing fetal heart development but they warrant revalidation and adjustment. 377 normal fetuses with healthy mothers, 98 normal fetuses with diabetic mothers, and 37 fetuses with cardiomyopathy and diabetic mothers had their cardiac structural dimensions, cardiothoracic ratio, valve flow velocities, and heart rates measured by fetal ECHO in a retrospective chart review. Cardiac features were fitted to linear functions, with respect to gestational age, femur length, head circumference, and biparietal diameter and z-scores were created to model normal fetal growth for all parameters. These z-scores were used to assess what metrics had no difference in means between the normal fetuses of both healthy and diabetic mothers, but differed from those diagnosed with cardiomyopathy. It was found that functional metrics like mitral and tricuspid E wave and pulmonary velocity could be important predictors for cardiomyopathy when fitted by gestational age, femur length, head circumference, and biparietal diameter. Additionally, aortic and tricuspid annulus diameters when fitted to estimated gestational age showed potential to be predictors for fetal cardiomyopathy. While the metrics overlapped over their full range, combining them together may have the potential for predicting cardiomyopathy in utero. Future directions of this study will explore creating a classifier model that can predict cardiomyopathy using the metrics assessed in this study.

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is an enveloped single-stranded positive-sense RNA virus that originated in China and has rapidly spread worldwide. With the Delta variant arriving before many K-12 schools in Arizona resumed in-person learning for the 2021-2022 academic year, a plethora of mitigation measures were utilized by schools. Public schools in both Maricopa and Pima county without mask mandates were found to be 3.5 times more likely to have COVID-19 outbreaks in comparison to those with mask requirements at the start of the school year. In addition, when analyzing the presence of three other mitigation measures (cohorting, random testing, and use of improved air filtration), only 5.42% were found to use all four mitigation measures.

This thesis is a retrospective study analyzing data from patient implanted cardiac devices in other to determine the effect of SARS-CoV-2 on cardiac arrhythmias. This study is also the first, to the knowledge of the researchers, in which a cohort of undifferentiated hospitalized and non-hospitalized COVID patients were studied using data from cardiac implanted devices. The results from this study has shown that SARS-CoV-2 leads to statistically significant increases in arrhythmic burden, in particular increased overall arrhythmic episodes, increased VT episodes, increased AT Burden percent, and increased SVT Average Ventricular Rate, and a statistically significant decrease in VT Average Ventricular Rate.