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Researchers are assessing the prevalence of Non-alcoholic Fatty Liver Disease (NAFLD) and Nonalcoholic Steatohepatitis (NASH) in the population and assembling a well-characterized cohort of adults with NAFLD and NASH to validate models of NAFLD diagnosis and determine long-term outcomes.
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Non-Alcoholic Fatty Liver Disease (NAFLD) is the most common cause of chronic liver disease in the world and a major public health issue in the US. Recent information on the prevalence of NAFLD in general and Non-Alcoholic Steatohepatitis (NASH) with fibrosis in particular is very scarce. Such information is crucial for defining the epidemiology of NAFLD, identifying risk factors for advanced fibrosis and longitudinal outcomes. This study will enroll a random sample of adults from Olmsted County, Minnesota, to validate machine learning models for NAFLD diagnosis and disease severity. These data would be fundamental for the development of screening strategies in the community, which are urgently needed for early diagnosis of liver fibrosis and therapeutic interventions before cirrhosis develops.
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800 participants in 1 patient group
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Jessica L Olson
Data sourced from clinicaltrials.gov
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