title: [Predictors of liver fibrosis in patients with non-alcoholic fatty liver disease. The role of metabolic syndrome, insulin-resistance and inflammation].
abstract: BACKGROUND
  NAFLD (non-alcoholic fatty liver disease) reaches an high prevalence in the general population, and it is closely related to metabolic syndrome (MetS). The entity of metabolic abnormalities and the chronic inflammation seem to play a main role in the development of liver fibrosis. The aim of our study is to determine whether subjects with NAFLD and MetS have higher liver fibrosis degree when compared with NAFLD subjects without MetS, and to investigate the relations between fibrosis, MetS and its single components and inflammation.
  
  
  METHODS
  We considered 24 patients with NAFLD. Those who had viral- and alcohol- related liver disease were excluded. MetS was diagnosed according to NCEP ATP III criteria; inflammatory status was determined through C-reactive protein (PCR) assay. The peripheral insulin-resistance was assessed by calculating HOMA ir. Liver fibrosis was measured by transient elastography (Fibroscan®).
  
  
  RESULTS
  Subjects with MetS had higher HOMA ir, PCR and Fibroscan® score (log value: 0.92±0.24 KPa vs 0.73±0.2 KPa; p=0.047). The linear correlation analysis showed that Fibroscan® score was related to MetS, number of MetS components, waist circumference, HOMA ir and PCR. However the multivariate regression analysis showed that only HOMA ir (B=0.077; 95%CI: -0.002- 0.157; p=0.05) and PCR (B=0.152; 95% CI: 0.006 - 0.299; p=0.006) were independent predictors of higher Fibroscan® score.
  
  
  CONCLUSIONS
  MetS is associated to higher liver fibrosis degree in subjects with NAFLD. The insulin-resistance and inflammation seem to be the main determinants.
authors.affiliation: Unita di Medicina Predittiva, Sapienza Universita di Roma, Roma, Italy.
authors.forename: Paola
authors.initials: P
authors.lastname: Andreozzi
authors.forename: Giovanni
authors.initials: G
authors.lastname: Viscogliosi
authors.forename: Franco
authors.initials: F
authors.lastname: Colella
authors.forename: Miroslava
authors.initials: M
authors.lastname: Subic
authors.forename: Elisa
authors.initials: E
authors.lastname: Cipriani
authors.forename: Benedetta
authors.initials: B
authors.lastname: Marigliano
authors.forename: Walter
authors.initials: W
authors.lastname: Verrusio
authors.forename: Adriana
authors.initials: A
authors.lastname: Servello
authors.forename: Evaristo
authors.initials: E
authors.lastname: Ettorre
authors.forename: Vincenzo
authors.initials: V
authors.lastname: Marigliano
mesh_terms: D000368:Aged; D000465:Algorithms; D015415:Biomarkers / Q000097:blood; D015992:Body Mass Index; D002097:C-Reactive Protein / Q000276:immunology; D054459:Elasticity Imaging Techniques; D005234:Fatty Liver / Q000150:complications* / Q000378:metabolism / Q000473:pathology*; D005260:Female; D006801:Humans; D007249:Inflammation / Q000150:complications* / Q000378:metabolism / Q000473:pathology; D007333:Insulin Resistance; D008103:Liver Cirrhosis / Q000209:etiology*; D008297:Male; D024821:Metabolic Syndrome / Q000150:complications* / Q000378:metabolism / Q000473:pathology*; D008875:Middle Aged; D065626:Non-alcoholic Fatty Liver Disease; D010865:Pilot Projects; D011237:Predictive Value of Tests; D015995:Prevalence; D012044:Regression Analysis; D012307:Risk Factors; D012680:Sensitivity and Specificity; D055105:Waist Circumference
chemical_list: D015415:Biomarkers; D002097:C-Reactive Protein