title: Using an Electronic Medical Records Database to Identify Non-Traditional Cardiovascular Risk Factors in Nonalcoholic Fatty Liver Disease.
abstract: Among adults with nonalcoholic fatty liver disease (NAFLD), 25% of deaths are attributable to cardiovascular disease (CVD). CVD risk reduction in NAFLD requires not only modification of traditional CVD risk factors but identification of risk factors unique to NAFLD.
  
  
  
  In a NAFLD cohort, we sought to identify non-traditional risk factors associated with CVD. NAFLD was determined by a previously described algorithm and a multivariable logistic regression model determined predictors of CVD.
  
  
  
  Of the 8,409 individuals with NAFLD, 3,243 had CVD and 5,166 did not. On multivariable analysis, CVD among NAFLD patients was associated with traditional CVD risk factors including family history of CVD (OR 4.25, P=0.0007), hypertension (OR 2.54, P=0.0017), renal failure (OR 1.59, P=0.04), and age (OR 1.05, P<0.0001). Several non-traditional CVD risk factors including albumin, sodium, and Model for End-Stage Liver Disease (MELD) score were associated with CVD. On multivariable analysis, an increased MELD score (OR 1.10, P<0.0001) was associated with an increased risk of CVD. Albumin (OR 0.52, P<0.0001) and sodium (OR 0.96, P=0.037) were inversely associated with CVD. In addition, CVD was more common among those with a NAFLD fibrosis score >0.676 than those with a score ≤0.676 (39 vs. 20%, P<0.0001).
  
  
  
  CVD in NAFLD is associated with traditional CVD risk factors, as well as higher MELD scores and lower albumin and sodium levels. Individuals with evidence of advanced fibrosis were more likely to have CVD. These findings suggest that the drivers of NAFLD may also promote CVD development and progression.
authors.affiliation: Liver Center, Gastrointestinal Unit, Massachusetts General Hospital, Boston, MA, USA.|Harvard Medical School, Boston, MA, USA.
authors.forename: Kathleen E
authors.initials: KE
authors.lastname: Corey
authors.affiliation: Harvard Medical School, Boston, MA, USA.|Center for Systems Biology, Center for Assessment Technology and Continuous Health, Massachusetts General Hospital, Boston, MA, USA.
authors.forename: Uri
authors.initials: U
authors.lastname: Kartoun
authors.affiliation: Harvard Medical School, Boston, MA, USA.|Biostatistics Center, Massachusetts General Hospital, Boston, MA, USA.
authors.forename: Hui
authors.initials: H
authors.lastname: Zheng
authors.affiliation: Liver Center, Gastrointestinal Unit, Massachusetts General Hospital, Boston, MA, USA.|Harvard Medical School, Boston, MA, USA.
authors.forename: Raymond T
authors.initials: RT
authors.lastname: Chung
authors.affiliation: Harvard Medical School, Boston, MA, USA.|Center for Systems Biology, Center for Assessment Technology and Continuous Health, Massachusetts General Hospital, Boston, MA, USA.
authors.forename: Stanley Y
authors.initials: SY
authors.lastname: Shaw
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D002318:Cardiovascular Diseases / Q000453:epidemiology*; D015331:Cohort Studies; D016208:Databases, Factual; D057286:Electronic Health Records; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D065626:Non-alcoholic Fatty Liver Disease / Q000150:complications*; D015995:Prevalence; D012307:Risk Factors