Stress-induced ST-segment deviation in relation to the presence and severity of coronary artery disease in patients with normal myocardial perfusion imaging.
OBJECTIVE
To assess the utility of stress electrocardiography (ECG) for identifying the presence and severity of obstructive coronary artery disease (CAD) defined by coronary computed tomographic angiography (CCTA) among patients with normal nuclear myocardial perfusion imaging (MPI).


METHODS
The study population comprised 119 consecutive patients with normal MPI who also underwent CCTA (interval 3.5+/-3.8 months). Stress ECG was performed at the time of MPI. CCTA and MPI were interpreted using established scoring systems, and CCTA was used to define the presence and extent of CAD, which was quantified by a coronary artery jeopardy score.


RESULTS
Within this population, 28 patients (24%) had obstructive CAD identified by CCTA. The most common CAD pattern was single-vessel CAD (61%), although proximal vessel involvement was present in 46% of patients. Patients with CAD were nearly three times more likely to have positive standard test responses (1 mm ST-segment deviation) than patients with patent coronary arteries (36 vs. 13%, P=0.007). In multivariate analysis, a positive ST-segment test response was an independent marker for CAD (odds ratio: 2.02, confidence interval: 1.09-3.78, P=0.03) even after adjustment for a composite of clinical cardiac risk factors (odds ratio: 1.85, confidence interval: 1.05-3.23, P=0.03). Despite uniformly normal MPI, mean coronary jeopardy score was three-fold higher among patients with positive compared to those with negative ST-segment response to exercise or dobutamine stress (1.9+/-2.7 vs. 0.5+/-1.4, P=0.03).


CONCLUSIONS
Stress-induced ST-segment deviation is an independent marker for obstructive CAD among patients with normal MPI. A positive stress ECG identifies patients with a greater anatomic extent of CAD as quantified by coronary jeopardy score.
Weinsaft
Jonathan W
JW
Greenberg Cardiology Division, Department of Medicine, Weill Medical College of Cornell University, New York, NY 10021, USA. jww2001@med.cornell.edu
Manoushagian
Shant J
SJ
Patel
Taral
T
Shakoor
Aqsa
A
Kim
Robert J
RJ
Mirchandani
Sunil
S
Lin
Fay
F
Wong
Franklin J
FJ
Szulc
Massimiliano
M
Okin
Peter M
PM
Kligfield
Paul D
PD
Min
James K
JK
D000368:Aged; D017023:Coronary Angiography / Q000379:methods*; D023921:Coronary Stenosis / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000209:etiology; D004562:Electrocardiography; D005080:Exercise Test; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D055414:Myocardial Perfusion Imaging; D016017:Odds Ratio; D011237:Predictive Value of Tests; D011446:Prospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D012720:Severity of Illness Index; D014057:Tomography, X-Ray Computed