The purpose of this study, which was done in conjunction with the Arizona Heart Foundation, was to evaluate whether pyridoxine accelerates ulcer wound healing in diabetic patients with ulcers in the lower extremities. In this study, 100 mg of pyridoxine per day was given to patients in the experimental group (while they receive normal wound treatment) while patients in the control group received normal treatment of wounds without the pyridoxine. Over time, wound healing was evaluated by photographing and then measuring the size of patients' ulcer wounds on the photographs. Results from the experimental group were compared with those of the control group to evaluate the efficacy of the pyridoxine treatment. In addition, comparisons of the healing rates were made with respect to whether the patients smoked, had hypertension or hypotension, and the patients' body mass indexes. It has been found that there was no statistically significant difference in the mean healing rates between the control groups and experimental groups. In addition, it has been found that smoking, BMI and blood pressure did not have a statistically appreciable effect on the difference in mean healing rates between the control and experimental groups. This is evidence that pyridoxine did not have a statistically significant effect on wound healing rates.

The COVID-19 pandemic has resulted in preventative measures and has led to extensive changes in lifestyle for the vast majority of the American population. As the pandemic progresses, a growing amount of evidence shows that minority groups, such as the Deaf community, are often disproportionately and uniquely affected. Deaf people are directly affected in their ability to personally socialize and continue with daily routines. More specifically, this can constitute their ability to meet new people, connect with friends/family, and to perform in their work or learning environment. It also may result in further mental health changes and an increased reliance on technology. The impact of COVID-19 on the Deaf community in clinical settings must also be considered. This includes changes in policies for in-person interpreters and a rise in telehealth. Often, these effects can be representative of the pre-existing low health literacy, frequency of miscommunication, poor treatment, and the inconvenience felt by Deaf people when trying to access healthcare. Ultimately, these effects on the Deaf community must be taken into account when attempting to create a full picture of the societal shift caused by COVID-19.

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.

As much as SARS-CoV-2 has altered the way humans live since the beginning of 2020, this virus's deadly nature has required clinical testing to meet 2020's demands of higher throughput, higher accuracy and higher efficiency. Information technology has allowed institutions, like Arizona State University (ASU), to make strategic and operational changes to combat the SARS-CoV-2 pandemic. At ASU, information technology was one of the six facets identified in the ongoing review of the ASU Biodesign Clinical Testing Laboratory (ABCTL) among business, communications, management/training, law, and clinical analysis. The first chapter of this manuscript covers the background of clinical laboratory automation and details the automated laboratory workflow to perform ABCTL’s COVID-19 diagnostic testing. The second chapter discusses the usability and efficiency of key information technology systems of the ABCTL. The third chapter explains the role of quality control and data management within ABCTL’s use of information technology. The fourth chapter highlights the importance of data modeling and 10 best practices when responding to future public health emergencies.