%0 Journal Article
%T Predicting incident fatty liver using simple cardio-metabolic risk factors at baseline
%A Ki-Chul Sung
%A Bum-Soo Kim
%A Yong-Kyun Cho
%A Dong-il Park
%A Sookyoung Woo
%A Seonwoo Kim
%A Sarah H Wild
%A Christopher D Byrne
%J BMC Gastroenterology
%D 2012
%I BioMed Central
%R 10.1186/1471-230x-12-84
%X 2589 people with absence of fatty liver on ultrasound examination at baseline were re-examined after a mean of 4.4£¿years in a Korean occupational cohort study. Multi-variable logistic regression analyses were used to identify baseline factors that were independently associated with incident fatty liver at follow up. The diagnostic performance of thresholds of these baseline factors to identify people with incident fatty liver at follow-up was assessed using receiver operating characteristic (ROC) curves.430 incident cases of fatty liver were identified. Several factors were independently associated with incident fatty liver: increased triglyceride (per mmol/l increase) OR 1.378 [95%CIs 1.179, 1.611], p£¿<£¿0.0001; glucose (per mmol/l increase) OR 1.215 [95%CIs 1.042, 1.416], p£¿=£¿0.013; waist (per cm increase) OR 1.078 [95%CIs 1.057, 1.099], p£¿<£¿0.001; ALT (per IU/L increase) OR 1.009 [95%CIs 1.002, 1.017], p£¿=£¿0.016; and platelets (per 1x109/L increase) OR 1.004 [1.001, 1.006], p£¿=£¿0.001; were each independently associated with incident fatty liver. Binary thresholds of the five factors were applied and the area under the ROC curve for incident fatty liver was 0.75 (95%CI 0.72¨C0.78) for the combination of all five factors above these thresholds.Simple risk factors that overlap considerably with risk factors for type 2 diabetes allow identification of people at high risk of incident fatty liver at who use of hepatic imaging could be targeted.
%K Non alcoholic fatty liver disease
%K Fatty liver
%K Etiology
%K Risk prediction
%K Metabolic syndrome
%U http://www.biomedcentral.com/1471-230X/12/84/abstract