Congenital heart disease (CHD) is the most prevalent birth defect and is the result of multiple etiologies including genetic and environmental causes. This article reviews the genetic workup for structural CHD in the clinical setting, beginning with CHD epidemiology and etiology and then moving to genetic testing, clinical evaluation, and genetic counseling. An algorithm is presented as a guide to genetic test selection, and available tests are explained with their respective advantages and limitations. Finally, future advances are discussed. As this review focuses on structural heart disease, isolated cardiomyopathies, inherited primary arrhythmia syndromes and aortopathies are not discussed.
The exponential increase in clinical research has profoundly changed medical sciences. Evidence that has accumulated in the past three decades from clinical trials has led to the proposal that clinical care should not be based solely on clinical expertise and patient values, and should integrate robust data from systematic research. As a consequence, clinical research has become more complex and methods have become more rigorous, and evidence is usually not easily translated into clinical practice. Therefore, the instruction of clinical research methods for scientists and clinicians must adapt to this new reality. To address this challenge, a global distance-learning clinical research-training program was developed, based on collaborative learning, the pedagogical goal of which was to develop critical thinking skills in clinical research. We describe and analyze the challenges and possible solutions of this course after 5 years of experience (2008–2012) with this program. Through evaluation by students and faculty, we identified and reviewed the following challenges of our program: 1) student engagement and motivation, 2) impact of heterogeneous audience on learning, 3) learning in large groups, 4) enhancing group learning, 5) enhancing social presence, 6) dropouts, 7) quality control, and 8) course management. We discuss these issues and potential alternatives with regard to our research and background.
Sudden cardiac death (SCD) is one of the leading causes of mortality in the U.S. military and competitive athletes. In this study, we simulate how genetic screening may be implemented in the military to prevent an SCD endpoint resulting from hypertrophic cardiomyopathy (HCM). We created a logistic regression model to predict variant pathogenicity in the most common HCM associated genes MYH7 and MYBPC3. Model predictions were used in conjunction with the gnomAD database to identify frequencies of pathogenic variants. Extrapolating these variants to a military population, lives saved and cost benefit analyses were conducted for screening for HCM related to pathogenic variants in MYH7 and MYBPC3. Genetic screening for HCM followed by echocardiography in individuals with pathogenic variants is predicted to save an average of 2.9 lives per accession cohort, based on historical cohort sizes, and result in a break‐even cost of ~$7 per test. The false positives, defined as disqualified individuals for military service who do not have HCM, are predicted to be 0 individuals per accession cohort. This study suggests that the main barriers for the implementation of genetic screening for the U.S. military are the low detection rate and variant interpretation.
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