Non-invasive Diagnostic Model of Liver Fibrosis Associated With NAFLD and Prediction of Prognosis

In a retrospective study, 200 patients with non-alcoholic fatty liver disease, fatty liver hepatitis, and fatty liver fibrosis have been identified for pathological diagnosis of liver histology and exclusion of other liver diseases. Before the liver biopsy were performed, these patients should detect liver function, coagulation function, renal function, blood glucose, blood lipids, liver elasticity measurement and imaging indicators and results, and demographic data. To evaluate the diagnostic ability of the current non-invasive diagnostic model of NAFLD fibrosis and the adaptability of model indicators to the diagnosis of enrolled patients, and to correct the indicators, including discarding unsuitable indicators and incorporating new indicators, and adjusting the diagnostic score. Establish a non-invasive diagnostic model for liver fibrosis in Beijing based on NAFLD. In a prospective observational study, 100 patients without other liver diseases and ultrasound-tested fatty liver were enrolled, and histopathological diagnosis of liver were included in the study, and liver function, coagulation function, renal function, blood glucose, and non-invasive model analysis were detected. Blood lipids, liver elasticity measurements, and imaging indicators were examined and demographic data were collected. The non-invasive diagnostic model established by retrospective study was used to diagnose fibrosis and its staging, compared with histopathological diagnosis, and adjusted the index of non-invasive diagnostic model to further revise and improve the diagnostic efficacy of the diagnostic model. Long-term follow-up observations were performed in the prospective observation cohort. The liver function, coagulation function, renal function, blood glucose, blood lipids, liver elasticity and imaging examination were performed during the observation period, and the treatment events and the progress of the patients were recorded. To explore the correlation and predictive ability of