Association between Red Blood Cell Distribution Width and Coronary Artery Calcification in Patients Undergoing

Ozgul Malcok Gürel1, Muhammed Bora Demircelik1, Mukadder Ayse Bilgic2

  • 1Department of Cardiology, School of Medicine, Turgut Ozal University, Ankara, Turkey.

Korean Circulation Journal
|September 29, 2015
PubMed

Insights

Red blood cell distribution width (RDW) independently predicts coronary artery calcification score (CACS) in patients without obvious coronary heart disease. This finding suggests RDW may serve as a valuable biomarker for coronary artery disease risk assessment.

Area of Science:

  • Cardiology
  • Hematology
  • Medical Imaging

Background:

  • Red blood cell distribution width (RDW) is linked to cardiovascular morbidity and mortality.
  • The association between RDW and coronary artery calcification score (CACS) in patients without evident coronary heart disease (CHD) remains unclear.

Purpose of the Study:

  • To investigate the relationship between RDW and CACS in individuals at low to intermediate risk for CHD.
  • To determine if RDW is an independent predictor of CACS in this population.

Main Methods:

  • A cohort of 527 patients with low-to-intermediate CHD risk but no overt disease underwent coronary CT angiography.
  • Coronary artery calcification score (CACS) was calculated and patients were stratified into CACS ≤ 100 and CACS > 100 groups.
  • Hematological parameters, including RDW, were compared between groups, and multivariate analysis was performed.

Main Results:

  • Patients with higher CACS (Group II) were older and had significantly higher Framingham Risk Scores (FRS).
  • Elevated hemoglobin, RDW, neutrophil count, and neutrophil/lymphocyte ratio were observed in Group II.
  • Multivariate analysis identified age, RDW, and FRS as independent predictors of CACS. A RDW of 13.05% best predicted CACS > 100.

Conclusions:

  • RDW is an independent predictor of CACS in patients without obvious coronary heart disease.
  • RDW may serve as a useful biomarker for predicting the severity of coronary artery disease (CAD).
Abstract

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