Non-alcoholic fatty liver disease (NAFLD) is highly prevalent globally and requires multidisciplinary care. Here, we report key findings of a NAFLD care workshop, address knowledge gaps and highlight a path to optimise healthcare resource use, to improve outcomes in patients with steatotic liver disease.

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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.

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Context While T2D is a risk factor for liver fibrosis in NAFLD, the specific contribution of insulin resistance (IR) relative to other factors is unknown. Objective Assess the impact on liver fibrosis in NAFLD of adipose tissue (Adipo-IR) and liver (HOMA-IR) IR in people with T2D and NAFLD. Design Participants were screened by elastography in the outpatient clinics for hepatic steatosis and fibrosis, including routine metabolites, cytokeratin-18 (marker of hepatocyte apoptosis/steatohepatitis), and HOMA-IR/Adipo-IR. Setting University ambulatory care practice. Participants 483 participants with T2D. Intervention Screening for steatosis and fibrosis with elastography. Main outcome measures Liver steatosis (CAP) and fibrosis (LSM) and measurements of IR (Adipo-IR, HOMA-IR) and fibrosis (cytokeratin-18). Results Clinically significant liver fibrosis (stage F ≥ 2= LSM ≥8.0 kPa) was found in 11%, having more features of the metabolic syndrome, lower adiponectin, and higher AST, ALT, liver fat and cytokeratin-18 (p < 0.05-0.01). In multivariable analysis including just clinical variables (model 1), obesity (BMI) had the strongest association with fibrosis (OR: 2.56, CI:1.87-3.50; p < 0.01). When metabolic measurements and cytokeratin-18 were included (model 2), only BMI, AST and liver fat remained significant. When fibrosis stage was adjusted for BMI, AST, and steatosis (model 3), only adipo-IR remained strongly associated with fibrosis (OR: 1.51, CI:1.05-2.16; p = 0.03), but not BMI, hepatic IR or steatosis. Conclusions These findings pinpoint to the central role of dysfunctional, insulin-resistant adipose tissue to advanced fibrosis in T2D, beyond simply BMI or steatosis. The clinical implication is that targeting adipose tissue should be the priority of treatment in NAFLD.