Background Sarcopenia and spontaneous portosystemic shunts (SPSSs) are common complications of liver cirrhosis, and both are associated with higher rates of hepatic encephalopathy (HE) development in these patients. This study… Click to show full abstract
Background Sarcopenia and spontaneous portosystemic shunts (SPSSs) are common complications of liver cirrhosis, and both are associated with higher rates of hepatic encephalopathy (HE) development in these patients. This study aimed to evaluate the simultaneous impact of skeletal muscle mass and spontaneous portosystemic shunting, measured from routine diagnostic CT on outcomes in patients with liver cirrhosis. Methods Retrospective analysis of patients with cirrhosis. Skeletal muscle mass [including fat-free muscle index (FFMI) as a surrogate for sarcopenia] and total cross-sectional spontaneous portosystemic shunt area (TSA) were quantified from CT scans. The primary endpoint was the development of HE, while the secondary endpoint was 1-year mortality. Results One hundred fifty-six patients with liver cirrhosis were included. Patients with low (L-) FFMI and large (L-)TSA showed higher rates of HE development. In multivariable analysis, L-FFMI and L-TSA were independent predictors of HE development (L-FFMI HR = 2.69, CI 1.22–5.93; L-TSA, HR = 2.50, CI = 1.24–4.72) and 1-year mortality (L-FFMI, HR = 7.68, CI 1.75–33.74; L-TSA, HR = 3.05, CI 1.32–7.04). The simultaneous presence of L-FFMI and L-TSA exponentially increased the risk of HE development (HR 12.79, CI 2.93–55.86) and 1-year mortality (HR 13.66, CI 1.75–106.50). An easy sequential algorithm including FFMI and TSA identified patients with good, intermediate, and poor prognoses. Conclusion This study indicates synergy between low skeletal muscle mass and large TSA to predict exponentially increased risk of HE development and mortality in liver cirrhosis. Simultaneous screening for sarcopenia and TSA from routine diagnostic CT may help to improve the identification of high-risk patients using an easy-to-apply algorithm. Clinical Trial registration [ClinicalTrials.gov], identifier [NCT03584204].
               
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