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A model to predict the onset of non-alcoholic fatty liver disease within 2 years in elderly adults.
Journal of Gastroenterology and Hepatology 2017 October
BACKGROUND AND AIM: Non-alcoholic fatty liver disease (NAFLD) is a common cause of chronic hepatitis, which leads to cirrhosis and hepatocellular carcinoma. However, it is difficult to identify subjects at high risk for NAFLD onset. This study aims to construct a model to predict the onset of NAFLD within 2 years in elderly adults.
METHODS: This study included and followed 3378 initial NAFLD-free subjects aged 60 years or over for 2 years, which were randomly divided into a training set and a validation set. NAFLD was diagnosed on ultrasound. Clinical and laboratory data were recorded at baseline. A model was constructed in the training set to predict the onset of NAFLD and validated in the validation set.
RESULTS: Body mass index, hemoglobin, fasting blood glucose, and triglycerides were identified as predictors for the onset of NAFLD. A risk score (R) was calculated by them. It classified the subjects into low-risk group (R ≤ -2.88), moderate-risk group (-2.88 < R ≤ -1.26), and high-risk group (R > -1.26). In the training set, 4.68% of the participants in the low-risk group, 11.59% of the participants in the moderate-risk group, and 31.02% of the participants in the high-risk group developed NAFLD. In the validation set, 5.84% of the participants in the low-risk group, 10.57% of the participants in the moderate-risk group, and 29.44% of the participants in the high-risk group developed NAFLD.
CONCLUSIONS: This study developed a model to predict the onset of NAFLD in elderly adults, which might provide indications for intervention to these subjects.
METHODS: This study included and followed 3378 initial NAFLD-free subjects aged 60 years or over for 2 years, which were randomly divided into a training set and a validation set. NAFLD was diagnosed on ultrasound. Clinical and laboratory data were recorded at baseline. A model was constructed in the training set to predict the onset of NAFLD and validated in the validation set.
RESULTS: Body mass index, hemoglobin, fasting blood glucose, and triglycerides were identified as predictors for the onset of NAFLD. A risk score (R) was calculated by them. It classified the subjects into low-risk group (R ≤ -2.88), moderate-risk group (-2.88 < R ≤ -1.26), and high-risk group (R > -1.26). In the training set, 4.68% of the participants in the low-risk group, 11.59% of the participants in the moderate-risk group, and 31.02% of the participants in the high-risk group developed NAFLD. In the validation set, 5.84% of the participants in the low-risk group, 10.57% of the participants in the moderate-risk group, and 29.44% of the participants in the high-risk group developed NAFLD.
CONCLUSIONS: This study developed a model to predict the onset of NAFLD in elderly adults, which might provide indications for intervention to these subjects.
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