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Create a Free AccountCirrhosis and Portal hypertension
Transient elastography in healthy subjects and factors influencing liver stiffness in non-alcoholic fatty liver disease: An Italian community-based population study
Few studies have been performed to explore parameters that influence liver stiffness measurement (LSM) using transient elastography in general population.Basal values and changes of liver stiffness predict the risk of disease progression in compensated advanced chronic liver disease
Transient elastography has been proposed as a tool to predict the risk of decompensation in patients with chronic liver disease. We aimed to identify risk groups of disease progression, using a combination of baseline liver stiffness measurement (LSM) and its change over time (delta-LSM) in patients with compensated advanced chronic liver disease (cACLD).Hemostatic balance in patients with liver cirrhosis: Report of a consensus conference
Patients with cirrhosis present with hemostatic alterations secondary to reduced availability of pro-coagulant and anti-coagulant factors. The net effect of these changes is a rebalanced hemostatic system. The Italian Association of the Study of the Liver (AISF) and the Italian Society of Internal Medicine (SIMI) promoted a consensus conference on the hemostatic balance in patients with cirrhosis. The consensus process started with the review of the literature by a scientific board of experts and ended with a formal consensus meeting in Rome in December 2014.Liver and spleen elastography using supersonic shear imaging for the non-invasive diagnosis of cirrhosis severity and oesophageal varices
Elastography is a promising non-invasive approach for assessing liver fibrosis. We assessed diagnostic performances of liver and spleen stiffness using supersonic shear imaging for diagnosing cirrhosis severity and oesophageal varices.Serum tests, liver stiffness and artificial neural networks for diagnosing cirrhosis and portal hypertension
The diagnostic performance of biochemical scores and artificial neural network models for portal hypertension and cirrhosis is not well established.
