title: A new coronary artery disease grading system correlates with numerous routine parameters that were associated with atherosclerosis: a grading system for coronary artery disease severity.
abstract: BACKGROUND
  Several scoring systems have tried to determine the severity of coronary artery disease (CAD) to investigate the connection between CAD severity and laboratory parameters.
  
  
  METHODS
  In total, 189 male (mean age: 61.86±10.77 years) and 75 female CAD patients (mean age: 67.84±7.70 years) were recruited and underwent angiography, which determined stenosis grade, of 17 coronary segments: no points for each nonstenosed segment or only calcified segments, one point for each stenosis from <30% to <50%, two points for each stenosis from 50% to <70%, and three points for each stenosis >70%. The points were added and should represent the severity of patients' CAD.
  
  
  RESULTS
  The coronary score correlated positively with systolic blood pressure, creatinine, blood urea nitrogen, lipase, glucose, glycated hemoglobin, triglycerides, C-reactive protein, fibrinogen Clauss, and leukocytes, and correlated negatively with Cl(-), iron, and high-density lipoprotein cholesterol. Stepwise multiple regression analysis with backward elimination revealed diabetes status, sex, and fibrinogen Clauss as significant predictors of coronary score.
  
  
  CONCLUSIONS
  The coronary score delivers a quite simple but very precise tool for the quantification of CAD severity. These results show plainly the connection between CAD severity and the lipid, glucose, coagulation, and immunologic status of CAD patients, and substantiate the importance of sufficient treatment in this group of patients - in particular, CAD patients suffering from type 2 diabetes mellitus. The coronary score would offer a suitable tool for the investigation of the connection between CAD and new biomarkers. Further studies are needed to investigate the correlation of the coronary score with outcome parameters (e.g., death).
authors.affiliation: Department of Cardiology, Medical University of Vienna, Vienna, Austria.
authors.forename: Michael
authors.initials: M
authors.lastname: Sponder
authors.affiliation: Department of Medical-Chemical Laboratory Analysis, Medical University of Vienna, Vienna, Austria.
authors.forename: Monika
authors.initials: M
authors.lastname: Fritzer-Szekeres
authors.affiliation: Department of Medical-Chemical Laboratory Analysis, Medical University of Vienna, Vienna, Austria.
authors.forename: Rodrig
authors.initials: R
authors.lastname: Marculescu
authors.affiliation: Department of Clinical Pharmacology, Medical University of Vienna, Vienna, Austria.
authors.forename: Brigitte
authors.initials: B
authors.lastname: Litschauer
authors.affiliation: Department of Cardiology, Medical University of Vienna, Vienna, Austria.
authors.forename: Jeanette
authors.initials: J
authors.lastname: Strametz-Juranek
mesh_terms: D000368:Aged; D015415:Biomarkers / Q000097:blood; D001794:Blood Pressure; D015992:Body Mass Index; D017023:Coronary Angiography; D023921:Coronary Stenosis / Q000097:blood / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000503:physiopathology; D003331:Coronary Vessels / Q000000981:diagnostic imaging / Q000503:physiopathology; D005260:Female; D006339:Heart Rate; D006801:Humans; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D012307:Risk Factors; D012720:Severity of Illness Index
chemical_list: D015415:Biomarkers
keywords: angiography; atherosclerosis; coronary artery disease; diabetes mellitus; grading system