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Summary Background Patients with nonalcoholic fatty liver disease (NAFLD) with type 2 diabetes (T2D) or other components of metabolic syndrome are at high risk for disease progression. We proposed an algorithm to identify high‐risk NAFLD patients in clinical practice using noninvasive tests (NITs). Methods Evidence about risk stratification of NAFLD using validated NITs was reviewed by a panel of NASH Experts. Using the most recent evidence regarding the performance of NITs and their application in clinical practice were used to develop an easy‐to‐use algorithm for risk stratification of NAFLD patients seen in primary care, endocrinology and gastroenterology practices. Results The proposed algorithm uses a three‐step process to identify NAFLD patients who are potentially at high risk for adverse outcomes. The first step is to use clinical data to identify most patients who are at risk for having potentially progressive NAFLD (e.g. having T2D or multiple components of metabolic syndrome). The second step is to calculate the FIB‐4 score as a NIT that can further risk stratifying individuals who are at low risk for progressive liver disease and can be managed by their primary healthcare providers to manage their cardiometabolic comorbidities. The third step is to use second‐line NITs (transient elastography or enhanced liver fibrosis tests) to identify those who at high risk for progressive liver disease and should be considered for specially care by providers with NASH expertise. Conclusions The use of this simple clinical algorithm can identify and assist in managing patients with NAFLD at high risk for adverse outcomes.

Summary Background and Aims Non‐alcoholic steatohepatitis (NASH) is the most common cause of liver disease. However, there is lack of comparison of efficacy between different NASH drug classes. We conducted a network meta‐analysis evaluating drug classes through comparing histological outcomes and targets of drugs. Approach and Results Medline, EMBASE and CENTRAL were searched for randomised controlled trials evaluating NASH drugs in biopsy‐proven NASH patients. Primary outcomes included NASH resolution without worsening of fibrosis, at least 2‐point reduction in Non‐alcoholic fatty liver disease Activity Score (NAS) without worsening of fibrosis and at least 1‐point reduction in fibrosis. Treatments were classified into inflammation, energy, bile acid and fibrosis modulators. The analysis was conducted with Bayesian network model and surface under the cumulative ranking curve (SUCRA) analysis. Among 49 included trials, treatments modulating energy (Risk ratio (RR): 1.92, Credible intervals (Crl): 1.59‐2.34) were most likely to achieve NASH resolution followed by treatments modulating fibrosis (RR 1.66, Crl: 0.65‐4.50), bile acids (RR: 1.37, Crl: 0.99‐1.92) and inflammation (RR: 1.00, Crl: 0.75‐1.33). Energy and bile acids modulation were effective in at least 2‐point NAS reduction without worsening of fibrosis (RR: 1.52, Crl 1.30‐1.77; RR: 1.69, Crl 1.41‐2.03) and at least 1‐point reduction in fibrosis (RR: 1.26, Crl:1.05‐1.49; RR: 1.54, Crl: 1.20‐1.97). Conclusions This network analysis demonstrates the relative superiority of drugs modulating energy pathways and bile acids in NASH treatment. This guides the development and selection of drugs for combination therapies.

Background and Aims: Fatty liver is the commonest liver condition globally and traditionally associated with NAFLD. A consensus meeting was held in Chicago to explore various terminologies. Herein, we explore the proposed changes in nomenclature in a population data set from the US.Approach and Results: Statistical analysis was conducted using surveyweighted analysis. Assessment of fatty liver was conducted with vibrationcontrolled transient elastography. A controlled attenuation parameter of 288 dB/m was used to identify hepatic steatosis. Patients were classified into nonalcoholic steatotic liver disease, alcohol-associated steatotic liver disease, and viral hepatitis steatotic liver disease. Liver stiffness measures at ≥ 8.8, ≥ 11.7, and ≥ 14 kPa were used to identify clinically significant fibrosis, advanced fibrosis, and cirrhosis, respectively. A total of 5102 individuals were included in the analysis. Using a survey-weighted analysis, a total of 25.43%, 6.95%, and 0.73% of the population were classified as nonalcoholic steatotic liver disease, alcohol-associated steatotic liver disease, and viral hepatitis steatotic liver disease, respectively. A sensitivity analysis at controlled attenuation parameter of 248 dB/m and fatty liver index found similar distribution. In a comparison between nonalcoholic steatotic liver disease, alcohol-associated steatotic liver disease, and viral hepatitis steatotic liver disease, there was no significant difference between the odds of advanced fibrosis and cirrhosis between groups.However, viral hepatitis steatotic liver disease individuals were found to