S2425 Non-Invasive Fibrosis Scores Are Associated With Cardiovascular Risk Scores in Metabolic Dysfunction-Associated Steatotic Liver Disease

Introduction: Metabolic dysfunction-associated steatotic liver disease (MASLD) is associated with cardiovascular disease (CVD) encompassing atherosclerosis and heart failure with preserved ejection fraction (HFpEF). However, screening for CVD in MASLD patients and vice versa remains underutilized. This study explores an association between non-invasive markers of hepatic fibrosis and cardiovascular risk scores. Methods: A longitudinal registry of ambulatory MASLD patients between 2021-2024 with a TTE was assessed. Patients with an EF >50%, no prior CAD or HFpEF diagnosis were included. Non-invasive risk scores for cardiovascular events (ASCVD, PREVENT), HFpEF (H2FPEF), and fibrosis (FIB4, SAFE, NFS) were calculated with ASCVD and PREVENT scores of ≥7.5% and H2FPEF scores of >1 point considered high risk. Statistical analysis was conducted using Spearman R and Mann Whitney. Results: 189 patients with MASLD (mean age 57 years, 60% woman, mean BMI 32.2 kg/m2) were evaluated. ASCVD, PREVENT, and H2FPEF were calculated for eligible patients (n = 95, 105, and 50 respectively). Of these, 47%, 51%, and 76% were at ‘high-risk’ for ASCVD, PREVENT, and H2FPEF, respectively. FIB4, SAFE, NFS positively correlated with H2FPEF (R = 0.44, R = 0.41, R = 0.59, P < 0.05) and cardiovascular event risk scores, but more strongly with PREVENT (for ASCVD, R = 0.47, R = 0.44, R = 0.54; for PREVENT R = 0.62, R = 0.62, R = 0.66, P < 0.05). NFS showed the strongest correlation with all 3 CVD risk scores. When stratified by gender, fibrosis positively correlated with ASCVD and PREVENT in both men and women (P < 0.05). Conclusion: Non-invasive assessments of liver fibrosis in MASLD are positively associated with CVD risk scores, more statistically significantly with the PREVENT score. Association of H2FpEF scores and non-invasive assessments of liver fibrosis in MASLD suggests a possible relationship, however larger cohorts are needed to explore the predictive value.