Criteria for the progression of steatohepatosis in obese adolescents with signs of metabolic syndrome
Background. To date, obesity in adolescents is a serious problem, which is caused by the prevalence of this pathology, especially in developed countries, and the possible consequences in the future, in particular, metabolic syndrome. It was believed that metabolic syndrome is diagnosed in middle-aged people and in the elderly, but modern studies suggest that this pathology is increasingly manifested in adolescents, and the liver is a key organ of the pathogenesis of all metabolic disorders. Therefore, the study, which aims to determine the algorithm for the progression of steatohepatosis in obese adolescents with signs of metabolic syndrome, is relevant. Materials and methods. The study included 226 obese patients aged 12–18 years. To assess the functional state of the liver, clinical, laboratory and instrumental methods of research were used. The homeostasis model assessment was used as a criterion for insulin resistance. Also, serum levels of fibronectin, type IV collagen, N-terminal propeptides and C-terminal telopeptides of type I collagen were evaluated. To determine the criteria for the diagnosis of steatohepatosis in adolescents, Wald-Genkin procedure was used. Results. The results of basic researches (laboratory and instrumental) demonstrate the presence of impaired liver function in obese adolescents, which manifest themselves in the form of fatty liver disease. The revealed atherogenic dyslipidemia, presence of insulin resistance, abdominal obesity make it possible to determine the risk groups for the development of metabolic syndrome among adolescents. The diagnostic value of biochemical markers of fibrosis in non-alcoholic fatty liver disease was studied. The developed algorithm for the early diagnosis of steatohepatosis in obese adolescents confirmed its diagnostic value and reliability, which will contribute to the timely treatment of the disease and the prevention of complications. Conclusions. In the future, the use of the developed algorithm will improve the efficiency of early diagnosis of fatty liver disease, as well as the treatment and preventive measures.
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