SUMMARY
OBJECTIVE:
The aim of this study was to explore the correlation between skeletal muscle
content and the presence and severity of metabolic dysfunction-associated
fatty liver disease in patients with metabolic dysregulation in China.
METHODS:
A cross-sectional study was conducted among patients from the endocrinology
outpatient department at Ningbo First Hospital, in Ningbo, China, in April
2021. Adult patients with metabolic dysregulation who accepted FibroScan
ultrasound were included in the study. However, those without clinical data
on skeletal muscle mass were excluded. FibroScan ultrasound was used to
noninvasively evaluate metabolic dysfunction-associated fatty liver disease.
The controlled attenuation parameter was used as an evaluation index for the
severity of liver steatosis. Bioelectrical impedance analysis was used to
measure the skeletal muscle index.
RESULTS:
A total of 153 eligible patients with complete data were included in the
final analysis. As the grading of liver steatosis intensifies, skeletal
muscle index decreases (men: P
trend
<0.001, women:
P
trend
=0.001), while body mass index, blood pressure, blood
lipid, uric acid, aminotransferase, and homeostatic model assessment of
insulin resistance increase (P
trend
<0.01). After adjusting for
confounding factors, a negative association between skeletal muscle index
and the presence of metabolic dysfunction-associated fatty liver disease was
observed in men (OR=0.691, p=0.027) and women (OR=0.614, p=0.022). According
to the receiver operating characteristic curve, the best cutoff values of
skeletal muscle index for predicting the metabolic dysfunction-associated
fatty liver disease presence were 40.37% for men (sensitivity, 87.5%;
specificity, 61.5%) and 33.95% for women (sensitivity, 78.6%; specificity,
63.8%).
CONCLUSION:
Skeletal muscle mass loss among patients with metabolic dysregulation was
positively associated with metabolic dysfunction-associated fatty liver
disease severity in both sexes. The skeletal muscle index cutoff value could
be used to predict metabolic dysfunction-associated fatty liver disease.