z-logo
open-access-imgOpen Access
Value of Exercise ECG for Risk Stratification in Suspected or Known CAD in the Era of Advanced Imaging Technologies
Author(s) -
Jamieson M. Bourque,
George Beller
Publication year - 2015
Publication title -
jacc. cardiovascular imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.79
H-Index - 120
eISSN - 1936-878X
pISSN - 1876-7591
DOI - 10.1016/j.jcmg.2015.09.006
Subject(s) - medicine , coronary artery disease , cardiology , electrocardiography , diabetes mellitus , risk stratification , metabolic equivalent , ischemia , radiology , physical therapy , physical activity , endocrinology
Exercise stress electrocardiography (ExECG) is underutilized as the initial test modality in patients with interpretable electrocardiograms who are able to exercise. Although stress myocardial imaging techniques provide valuable diagnostic and prognostic information, variables derived from ExECG can yield substantial data for risk stratification, either supplementary to imaging variables or without concurrent imaging. In addition to exercise-induced ischemic ST-segment depression, such markers as ST-segment elevation in lead aVR, abnormal heart rate recovery post-exercise, failure to achieve target heart rate, and poor exercise capacity improve risk stratification of ExECG. For example, patients achieving ≥10 metabolic equivalents on ExECG have a very low prevalence of inducible ischemia and an excellent prognosis. In contrast, cardiac imaging techniques add diagnostic and prognostic value in higher-risk populations (e.g., poor functional capacity, diabetes, or chronic kidney disease). Optimal test selection for symptomatic patients with suspected coronary artery disease requires a patient-centered approach factoring in the risk/benefit ratio and cost-effectiveness.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom