Abstract
This study sought to determine whether the increasing difficulty of assessing wall motion (WM), Doppler coronary flow reserve on the left anterior descending coronary artery (CFR-LAD), and myocardial perfusion (MP) during stress echocardiography (SE) was justified by increasing prognostic information in patients with known or suspected coronary artery disease. The use of echocardiographic contrast agents during SE permits the assessment of both CFR-LAD and MP, but their relative incremental prognostic value is undefined. This study followed a multicenter cohort of 718 patients for 16 months after high-dose dipyridamole contrast SE for evaluation of known or suspected coronary artery disease. The ability of WM, CFR-LAD, and MP to predict cardiac events was studied by multivariable models and risk reclassification. Abnormal SE was detected as a reversible WM abnormality in 18%, reversible MP defect in 27%, and CFR-LAD <2 in 38% of subjects. Fifty cardiac events occurred (annualized event rate 6.0%). A normal MP stress test had a 1-year hard event rate of 1.2%. The C-index of outcomes prediction based on clinical data was improved with MP (p < 0.001) and WM/CFR-LAD (p = 0.037), and MP (p = 0.003) added to clinical and WM data. Net risk reclassification was improved by adding MP (p < 0.001) or CFR-LAD (net reclassification improvement p = 0.001) in addition to clinical and WM data. The model including clinical data, WM/CFR-LAD, and MP performed better than that without MP did (p = 0.012). The multiparametric assessment of WM, CFR-LAD and MP during stress testing in patients with known or suspected coronary artery disease is feasible. Contrast SE allowed better prognostication, irrespective of the use of CFR-LAD or MP. The addition of either CFR-LAD or MP assessment to standard WM analysis and clinical parameters yielded progressively higher values for the prediction of cardiac events and may be required in today's intensively treated patients undergoing SE, because their average low risk of future cardiac events requires methods with higher predictive sensitivity than that available with standalone WM assessment.
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