Abstract
Aims: Our previous study validated that controlled attenuation parameter (CAP) was a sensitive surrogate marker for evaluating metabolic derangement. However, prospective studies are needed to assess its usefulness for transition of metabolic status over time. In this study, predictive effect of CAP and its change over time was investigated by following up of medical staff volunteered for MAFLD study over 3 years. Subjects and Methods: Volunteers were recruited from our hospital to undergo FibroScan examination in 2018 and followed up in 2021. Anthropometric data, CAP and hematological indices for metabolic profiles and insulin resistance were collected. Metabolic syndrome (MetS) components were scored. CAP≥238 dB/m denoted hepatic steatosis. Number of MetS component increased by 1 or more was denoted ‘progression’ , whereas decreased by 1 or more denoted ‘regression’ of metabolic status. Results: A total of 922 subjects volunteered for FibroScan examination in 2018, and 466 of them were followed in 2021. At baseline, the median age was 49.0 years, BMI was 23.3kg/m2, waist circumference was 80cm. CAP were 240 (216, 275) dB/m, LSM were 3.9 (3.4, 4.7) Kpa, 242 (51.9%) subjects were with CAP≥238 dB/m. During the follow up, 124 (26.6%) subjects had progression, while 81 (17.3%) had regression of metabolic status. Logistic regression showed that CAP at baseline [1.0 (1.001, 1.011) , P = 0.019], change in waist circumference [1.1 (1.047, 1.165) , P = 0.000] and change in CAP [1.0 (1.004, 1.0150) , P = 0.001] were independent predictors for progression. In contrast, CAP at baseline [1.012 (1.006, 1.018) , P= 0.000], change in waist circumference [0.9 (0.857, 0.967) , P = 0.002] and change in LSM [0.813 (0.667, 0.990) , P = 0.040] were significant in predicting regression of metabolic status. Conclusions: CAP at baseline, changes in CAP and waist circumference are useful surrogate markers for predicting transition of metabolic status over time. Disclosure J.Li: None. Z.Huang: None. W.Deng: None. Z.Zhang: None. Y.Li: None. Funding National Natural Science Foundation of China (82070918)
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