Component C South Carolina Muscular Dystrophy Surveillance, Tracking, and Research Network (SC MD STARnet) is a collaboration between the state health department and the state?s flagship university (University of South Carolina, USC). The overarching aim of this component of the project is to conduct ongoing research about of the health status, health care utilization, and public health impact of people with MD. We will estimate prevalence, survival, and track clinical indicators of care in order to understand diagnosed prevalence, disease progression, clinical care, and health status. This work will result in at least five peer reviewed publications and five national presentations to professional societies, national conferences, or other meetings that include professionals and advocates for people with MD. We will conduct longitudinal, population-based surveillance on eligible MD cases with Myotonic Dystrophy (DM), Fascioscapulohumeral (FSHD), Limb-girdle (LGMD), congenital (CMD), Emery- Dreirfuss (EDMD) and distal MD. We will follow the Duchenne/Becker MD cohort to determine if there are changes in prevalence and survival and to describe progress and care. We will also develop research methods and tools, including surveys and interviews, and conduct research with other sites and CDC. Throughout the funding cycle we will both lead projects and simultaneously act as secondary analysts on projects lead by other sites or NCBDDD.
The aim of conducting research with the subpopulations identified through surveillance is to address knowledge gaps (eg. Quality of life, pregnancy and fertility issues, and self-care issues, etc.). We will analyze, publish at least 5 manuscripts, and make at least 5 presentations about the surveillance and research findings at national meetings of clinicians, health care providers, advocates, and other interested parties.
Component C The SC MD STARnet project will analyze muscular dystrophy (MD) surveillance data and disseminate research results through peer-reviewed publications and presentations to target audiences using data from both the 2014 ? 2019 and the 2019-2024 funding cycles. We will answer questions related to the onset, course, health services utilization, disparities, and quality of life of people with the eligible MD types.
