Assessment of the risk of developing liver fibrosis in patients with non-alcoholic fatty liver disease

Abstract

The prognosis of a patient with non-alcoholic fatty liver disease (NAFLD) is directly related to the development and progression of fibrosis, which is associated with a wide comorbidity. Despite the existence of various options for assessing the risk of liver fibrosis, further development of prognostic systems that reflect the pathological mechanisms of the disease is necessary. Objective. Determination of indicators associated with the pathogenesis of the disease, which, in combination, will identify the risks of progression of fibrosis in patients with NAFLD to optimize the diagnosis of the disease. Materials and methods. An open observational case-control study was conducted in 79 patients with NAFLD, 21 of them without fibrosis (NAFLD without LF), 58 with fibrosis of varying severity (NAFLD with LF). The examination program included general clinical, laboratory, instrumental (including liver elastometry, FibroScan), histological (assessment of liver biopsy specimens), microbiological (gas chromatography–mass spectrometry of microbial markers (GC-MSM)) studies. Results. Using the logistic regression module, a model was built to assess the risk of LF in NAFLD, consisting of 4 indicators: taurocholic acid; glucose; triglycerides; total sum of microbial markers in GC-MSM. The variables included in the model reflect the mutual influence of the most important pathological factors of NAFLD and comorbid pathology. The resulting model has high sensitivity (98.28%), specificity (95.24%) and diagnostic accuracy (97.47%). For the convenience of practical application, a simplified version of the risk assessment model for LF in NAFLD was proposed depending on the number of altered risk factors. Conclusions. A model for assessing the risk of developing LF in patients with NAFLD was built, which included indicators associated with the pathogenesis of the disease. A simplified version of the model has been developed depending on the number of risk factors, the indicators of which are in the unfavorable zone.