Predictive value of mitral annular calcification for the diagnosis of coronary artery disease in patients with dilated cardiomyopathy

Angiology. 2001 Aug;52(8):515-20. doi: 10.1177/000331970105200802.

Abstract

Mitral annulus calcification (MAC) is an independent predictor of coronary artery disease (CAD). The present study was designed to determine whether an association exists between MAC and CAD in patients with dilated cardiomyopathy. Among the 286 patients with MAC on echocardiographic examination who underwent coronary angiography, 55 patients with echocardiographic findings of dilated cardiomyopathy (group I) were compared to 60 age-matched controls without MAC and an echocardiographic diagnosis of dilated cardiomyopathy (group II) who underwent coronary angiography during the same time. There were no differences in echocardiographic findings between two groups. The prevalence of CAD was higher in group I when compared to group II (74% vs 28%, p<0.001). With regard to severity of CAD, two-vessel, three-vessel, and left main coronary artery disease were found to be significantly frequent in group I (p<0.001). Multivariate analysis revealed that MAC (p=0.001), diabetes mellitus (p=0.048), and history of anginal chest pain (p=0.009) are the independent predictors for the presence of CAD in patients with dilated cardiomyopathy. In conclusion, MAC may be a marker for the presence of coronary artery disease in patients with dilated cardiomyopathy.

Publication types

  • Comparative Study

MeSH terms

  • Aged
  • Calcinosis*
  • Cardiomyopathy, Dilated / diagnosis*
  • Cardiomyopathy, Dilated / epidemiology*
  • Case-Control Studies
  • Comorbidity
  • Coronary Angiography / methods
  • Coronary Disease / diagnosis*
  • Coronary Disease / epidemiology*
  • Echocardiography / methods
  • Female
  • Humans
  • Male
  • Middle Aged
  • Mitral Valve Stenosis / diagnosis*
  • Mitral Valve Stenosis / epidemiology*
  • Multivariate Analysis
  • Predictive Value of Tests
  • Probability
  • Prognosis
  • Reference Values
  • Risk Factors
  • Sensitivity and Specificity