title: Coronary disease risk prediction algorithm warranting incorporation of C-reactive protein in Turkish adults, manifesting sex difference.
abstract: OBJECTIVE
  An algorithm is needed for predicting coronary heart disease (CHD) risk in Turkish adults who have a high prevalence of metabolic syndrome (MetS).
  
  
  RESULTS
  Ten-year risk of CHD was estimated in 2232 middle-aged adults free of CHD at baseline, followed over 7.6-years. Cox proportional hazard regression was used to predict CHD. Discrimination was assessed with area under receiver operating characteristics curve (AROC). CHD developed in 302 subjects. In multivariable analysis, high-density lipoprotein (HDL)-cholesterol levels were borderline predictive in men; smoking status and HDL-and low-density lipoprotein (LDL)-cholesterol levels were not predictive in women. Age, presence of diabetes, systolic blood pressure and C-reactive protein (CRP) were predictors in both sexes, while smoking status and LDL-cholesterol were so in men only. AROC of the model was 0.789 in men, and 0.806 in women (p < 0.001 each). An algorithm using the stated seven variables was derived separately for each sex. After age adjustment, men and women in the highest quintile of risk score were significantly and 20-27-fold more likely to develop CHD than those in the lowest quintile.
  
  
  CONCLUSIONS
  In a population with prevalent MetS, low-grade inflammation is independently relevant for CHD, as are serum lipoproteins and smoking status. The derived algorithm is effective in estimating CHD risk among Turkish adults.
authors.affiliation: Department of Cardiology, Cerrahpaşa Medical Faculty, Istanbul University, Turkey. alt_onat@yahoo.com.tr
authors.forename: A
authors.initials: A
authors.lastname: Onat
authors.forename: G
authors.initials: G
authors.lastname: Can
authors.forename: G
authors.initials: G
authors.lastname: Hergenç
authors.forename: M
authors.initials: M
authors.lastname: Uğur
authors.forename: H
authors.initials: H
authors.lastname: Yüksel
mesh_terms: D000328:Adult; D000367:Age Factors; D000465:Algorithms; D015415:Biomarkers / Q000097:blood; D002097:C-Reactive Protein / Q000032:analysis*; D003327:Coronary Disease / Q000097:blood / Q000175:diagnosis / Q000208:ethnology*; D005260:Female; D006801:Humans; D007249:Inflammation / Q000208:ethnology; D008074:Lipoproteins / Q000097:blood; D008137:Longitudinal Studies; D008297:Male; D024821:Metabolic Syndrome / Q000208:ethnology; D008875:Middle Aged; D015999:Multivariate Analysis; D016017:Odds Ratio; D011237:Predictive Value of Tests; D011379:Prognosis; D016016:Proportional Hazards Models; D011446:Prospective Studies; D012372:ROC Curve; D018570:Risk Assessment; D012307:Risk Factors; D012737:Sex Factors; D012907:Smoking / Q000208:ethnology; D013997:Time Factors; D014421:Turkey / Q000453:epidemiology
chemical_list: D015415:Biomarkers; D008074:Lipoproteins; D002097:C-Reactive Protein