title: Usefulness of the white blood cell count as a predictor of angiographic findings in an unselected population referred for coronary angiography.
abstract: There are limited data about the relative importance of the many different but inter-related inflammatory markers with respect to their ability to independently predict the presence and extent of coronary artery disease (CAD). In addition, studies demonstrating such associations have often been conducted in well-defined populations and have excluded patients with or not adjusted for co-morbidities associated with CAD. In a cohort of 389 men who underwent coronary angiography for a variety of clinical indications and across a spectrum of risk, the following inflammatory markers were measured at baseline to determine their relative abilities to predict angiographic outcomes: C-reactive protein, myeloperoxidase, tissue inhibitor of metalloproteinase-1, erythrocyte sedimentation rate, and white blood cell (WBC) count. This analysis was done in the context of traditional CAD risk factors and other co-morbidities associated with CAD (such as morbid obesity, renal dysfunction, heart failure, and so forth). WBC count was the only marker that was independently associated with angiographically documented CAD (p = 0.0184). Further, WBC count (odds ratio 1.31, 95% confidence interval 1.05 to 1.64, p = 0.0157) and plasma myeloperoxidase (odds ratio 1.35, 95% confidence interval 1.08 to 1.69, p = 0.0090) were the only inflammatory markers that were independently predictive of the presence of multivessel disease on coronary angiography. In conclusion, these data demonstrate that a simple baseline WBC count is independently associated with angiographic CAD, and that it can predict the presence of multivessel disease, even in the context of clinical CAD risk factors and other established inflammatory markers.
authors.affiliation: Department of Medicine, State University of New York Downstate Medical Center, Brooklyn, New York, USA. ecavusoglu@aol.com
authors.forename: Erdal
authors.initials: E
authors.lastname: Cavusoglu
authors.forename: Vineet
authors.initials: V
authors.lastname: Chopra
authors.forename: Amit
authors.initials: A
authors.lastname: Gupta
authors.forename: Cyril
authors.initials: C
authors.lastname: Ruwende
authors.forename: Sunitha
authors.initials: S
authors.lastname: Yanamadala
authors.forename: Calvin
authors.initials: C
authors.lastname: Eng
authors.forename: Luther T
authors.initials: LT
authors.lastname: Clark
authors.forename: David J
authors.initials: DJ
authors.lastname: Pinsky
authors.forename: Jonathan D
authors.initials: JD
authors.lastname: Marmur
mesh_terms: D000368:Aged; D000704:Analysis of Variance; D015415:Biomarkers / Q000097:blood; D001799:Blood Sedimentation; D002097:C-Reactive Protein / Q000378:metabolism; D015897:Comorbidity; D017023:Coronary Angiography; D003324:Coronary Artery Disease / Q000097:blood* / Q000000981:diagnostic imaging* / Q000453:epidemiology / Q000503:physiopathology; D006801:Humans; D007958:Leukocyte Count; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D009195:Peroxidase / Q000097:blood; D011237:Predictive Value of Tests; D012017:Referral and Consultation; D012307:Risk Factors; D019715:Tissue Inhibitor of Metalloproteinase-1 / Q000097:blood; D016277:Ventricular Function, Left
chemical_list: D015415:Biomarkers; D019715:Tissue Inhibitor of Metalloproteinase-1; D002097:C-Reactive Protein; D009195:Peroxidase