open access

Vol 16, No 4 (2009)
Original articles
Published online: 2009-05-12
Submitted: 2013-01-14
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Predictors of coronary artery disease in patients with left bundle branch block who undergo myocardial perfusion imaging

Vinodh Jeevanantham, Kavitha Manne, Mohan Sengodan, James M. Haley, David H. Hsi
Cardiol J 2009;16(4):321-326.

open access

Vol 16, No 4 (2009)
Original articles
Published online: 2009-05-12
Submitted: 2013-01-14

Abstract


Background: Due to difficulties in diagnosing coronary ischemia in patients with left bundle branch block (LBBB), identifying clinical characteristics that might help to predict coronary artery disease (CAD) is important. Our study aimed to identify clinical predictors of CAD among patients with and without LBBB who undergo myocardial perfusion imaging (MPI).
Methods: All patients with LBBB who underwent MPI (LBBB group) from June 2005 to February 2007 were compared with patients with normal baseline electrocardiography who underwent treadmill MPI (non-LBBB group) during the same period.
Results: LBBB patients with CAD were younger and had lower ejection fraction (EF) compared to LBBB patients without CAD. Similarly non-LBBB patients with CAD had lower EF, but did not differ significantly in age compared to non-LBBB patients without CAD. Regression analysis among patients with LBBB showed that EF < 55% was the most significant predictor of CAD, after controlling for other factors. A regression analysis in non-LBBB patients showed that male gender and EF £ 55% were significant predictors of CAD. A regression analysis conducted in the combined data of both LBBB and non-LBBB groups showed male gender, EF £ 55% and LBBB to be the most significant predictors of CAD.
Conclusions: Patients with LBBB have a high probability of CAD based on MPI findings. Patients with LBBB and reduced EF have a much higher likelihood of CAD compared to patients without LBBB and normal EF. Further studies on early invasive approach in patients with LBBB and reduced EF seem warranted.

Abstract


Background: Due to difficulties in diagnosing coronary ischemia in patients with left bundle branch block (LBBB), identifying clinical characteristics that might help to predict coronary artery disease (CAD) is important. Our study aimed to identify clinical predictors of CAD among patients with and without LBBB who undergo myocardial perfusion imaging (MPI).
Methods: All patients with LBBB who underwent MPI (LBBB group) from June 2005 to February 2007 were compared with patients with normal baseline electrocardiography who underwent treadmill MPI (non-LBBB group) during the same period.
Results: LBBB patients with CAD were younger and had lower ejection fraction (EF) compared to LBBB patients without CAD. Similarly non-LBBB patients with CAD had lower EF, but did not differ significantly in age compared to non-LBBB patients without CAD. Regression analysis among patients with LBBB showed that EF < 55% was the most significant predictor of CAD, after controlling for other factors. A regression analysis in non-LBBB patients showed that male gender and EF £ 55% were significant predictors of CAD. A regression analysis conducted in the combined data of both LBBB and non-LBBB groups showed male gender, EF £ 55% and LBBB to be the most significant predictors of CAD.
Conclusions: Patients with LBBB have a high probability of CAD based on MPI findings. Patients with LBBB and reduced EF have a much higher likelihood of CAD compared to patients without LBBB and normal EF. Further studies on early invasive approach in patients with LBBB and reduced EF seem warranted.
Get Citation

Keywords

left bundle branch block; coronary artery disease; myocardial perfusion imaging

About this article
Title

Predictors of coronary artery disease in patients with left bundle branch block who undergo myocardial perfusion imaging

Journal

Cardiology Journal

Issue

Vol 16, No 4 (2009)

Pages

321-326

Published online

2009-05-12

Bibliographic record

Cardiol J 2009;16(4):321-326.

Keywords

left bundle branch block
coronary artery disease
myocardial perfusion imaging

Authors

Vinodh Jeevanantham
Kavitha Manne
Mohan Sengodan
James M. Haley
David H. Hsi

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