title: Identifying non-alcoholic fatty liver disease among asymptomatic overweight and obese individuals by clinical and biochemical characteristics.
abstract: OBJECTIVE
  To determine the prevalence of liver steatosis among asymptomatic individuals attending an out-patient clinic for a problem of overweight, and to define the discriminatory value of several characteristics for predicting liver steatosis among them.
  
  
  METHODS
  Consecutive patients Swith a body mass index (BMI) of > or =25 kg/m2 who consented to undergo liver ultrasound and blood tests were recruited for inclusion. Receiver operating characteristic (ROC) curves were generated and statistical indices of diagnostic performance and their corresponding 95% confidence intervals (95% CI) were computed. Logistic regression analyses were performed to determine whether a combination of characteristics could improve diagnostic accuracy.
  
  
  RESULTS
  We enrolled sixty-eight subjects (mean BMI, 37.5 kg/m2), of whom 39 (57.4%) had liver steatosis on ultrasound. Logistic regression analyses indicated that only 3 variables were significantly and independently correlated with liver steatosis: female gender, low adiponectin levels, and high insulin resistance index. A composite index for predicting liver steatosis was calculated by summing the risk factors of female gender, low adiponectin, and insulin resistance index (FAIR score). The accuracy of this score was determined by ROC analysis to be 0.85 (95% CI, 0.74-0.96; P < 0.001). The presence of two or more risk factors (FAIR score > or =2) had a sensitivity, specificity, positive predictive value, and negative predictive value of 77%, 91%, 92%, and 74%, respectively. The likelihood ratio for a positive result was 8.43.
  
  
  CONCLUSIONS
  Among asymptomatic overweight individuals attending an out-patient clinic, the prevalence of liver steatosis on ultrasound is 57%. Female gender, the insulin resistance index, and low adiponectin are significant and independent predictors of liver steatosis. A combination of these three factors allows sensitivity and specificity for non alcoholic fatty liver of 77% and 91%, respectively.
authors.affiliation: Department of Experimental Surgery, Universitair Ziekenhuis Brussel, Belgium.
authors.forename: P
authors.initials: P
authors.lastname: Haentjens
authors.forename: D
authors.initials: D
authors.lastname: Massaad
authors.forename: H
authors.initials: H
authors.lastname: Reynaert
authors.forename: E
authors.initials: E
authors.lastname: Peeters
authors.forename: A
authors.initials: A
authors.lastname: Van Meerhaeghe
authors.forename: S
authors.initials: S
authors.lastname: Vinken
authors.forename: K
authors.initials: K
authors.lastname: Poppe
authors.forename: B
authors.initials: B
authors.lastname: Velkeniers
mesh_terms: D052242:Adiponectin / Q000097:blood; D001530:Belgium / Q000453:epidemiology; D015415:Biomarkers / Q000097:blood; D015992:Body Mass Index; D016009:Chi-Square Distribution; D005234:Fatty Liver / Q000097:blood* / Q000000981:diagnostic imaging* / Q000453:epidemiology; D005260:Female; D006801:Humans; D007333:Insulin Resistance; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000150:complications*; D050177:Overweight / Q000150:complications*; D011237:Predictive Value of Tests; D015995:Prevalence; D012372:ROC Curve; D012307:Risk Factors; D012680:Sensitivity and Specificity; D012737:Sex Factors; D014463:Ultrasonography
chemical_list: D052242:Adiponectin; D015415:Biomarkers