LIVERSTAT for risk stratification for patients with metabolic dysfunction-associated fatty liver disease.

BACKGROUND AND AIM: LIVERSTAT is an artificial intelligence-based noninvasive test devised to screen for and provide risk stratification for metabolic dysfunction-associated fatty liver disease (MAFLD) by using simple blood biomarkers and anthropometric measurements. We aimed to study LIVERSTAT in patients with MAFLD and to explore its role for the diagnosis of advanced fibrosis. METHODS: This is a retrospective study of data from MAFLD patients who underwent a liver biopsy. Patients with type 2 diabetes who underwent transient elastography and had liver stiffness measurement (LSM) < 5 kPa were included as patients with no fibrosis. Among these patients, controlled attenuation parameter <248 dB/m was considered as no steatosis. The LIVERSTAT results were generated based on a proprietary algorithm, blinded to the histological and LSM data. RESULTS: The data for 350 patients were analyzed (mean age 53 years, 45% male, advanced fibrosis 22%). The sensitivity, specificity, positive predictive value, negative predictive value, and misclassification rate of LIVERSTAT to diagnose advanced fibrosis were 90%, 50%, 30%, 95%, and 42%, respectively. The corresponding rates for Fibrosis-4 score (FIB4) were 56%, 83%, 44%, 89%, and 22%, respectively. When LSM was used as a second test, the corresponding rates for LIVERSTAT were 60%, 97%, 76%, 94%, and 8%, respectively, while the corresponding rates for FIB4 were 38%, 99%, 83%, 89%, and 11%, respectively. CONCLUSION: LIVERSTAT had a higher negative predictive value compared with FIB4 and a lower misclassification rate compared with FIB4 when used in a two-step approach in combination with LSM for the diagnosis of advanced fibrosis.

Hepatic steatosis and metabolic risk factors among patients with chronic hepatitis B: The multicentre, prospective CAP-Asia study.

We aimed to compare the severity of liver disease, metabolic profile and cardiovascular disease (CVD) risk of chronic hepatitis B (CHB) patients with and without hepatic steatosis and patients with non-alcoholic fatty liver disease (NAFLD). Patients with NAFLD and CHB were prospectively enrolled from 10 Asian centres. Fibroscan was performed for all patients and hepatic steatosis was defined based on controlled attenuation parameter >248 dB/m. CVD risk was assessed using the Framingham risk score. The data for 1080 patients were analysed (67% NAFLD, 33% CHB). A high proportion (59%) of CHB patients had hepatic steatosis. There was a significant stepwise increase in alanine aminotransferase, aspartate aminotransferase, gamma-glutamyl transpeptidase, controlled attenuation parameter and liver stiffness measurement, from CHB patients without hepatic steatosis to CHB patients with hepatic steatosis to NAFLD patients (p < 0.001 for all comparisons). There was a significant stepwise increase in the proportion of patients with metabolic syndrome and in CVD risk, with very high or extreme CVD risk seen in 20%, 48% and 61%, across the groups (p < 0.001 between CHB patients with and without hepatic steatosis and p < 0.05 between CHB patients with hepatic steatosis and NAFLD patients). In conclusion, there was a high proportion of CHB patients with hepatic steatosis, which should be diagnosed, as they may have more severe liver disease, so that this and their metabolic risk factors can be assessed and managed accordingly for a better long-term outcome.