Abstract

Noninvasive detection of functionally significant coronary artery disease (CAD) by echocardiography remains challenging, with the need to perform stress imaging to detect ischemia. The aim of this study was to determine whether global myocardial work (MW), derived from noninvasive left ventricular (LV) pressure-strain loops at rest, can predict significant CAD in patients without regional wall motion abnormalities and preserved LV ejection fraction (EF). One hundred and fifteen patients referred for coronary angiography who had EF≥55%, no resting regional wall motion abnormalities, and no chest pain were assessed using echocardiography. Global MW was derived from noninvasive LV pressure-strain loops constructed from speckle-tracking echocardiography indexed to brachial systolic blood pressure. Global constructive work represented the sum of positive work due to myocardial shortening during systole and negative work due to lengthening during isovolumic relaxation. Global wasted work represented energy loss by myocardial lengthening in systole and shortening in isovolumic relaxation. Global MW efficiency was derived from the percentage ratio of constructive work to the sum of constructive work and wasted work. Patients with significant CAD demonstrated a significantly reduced global MW (P<.001) compared with those without CAD. Global longitudinal strain was significantly reduced (P<.001) in patients with multivessel CAD but not those with single-vessel CAD (P=.47). Receiver operating characteristic curve analysis demonstrated that global MW was the most powerful predictor of significant CAD (area under the curve=0.786) and was superior to global longitudinal strain (area under the curve=0.693). The optimal cutoff global MW value to predict significant CAD was 1,810mm Hg% (sensitivity, 92%; specificity, 51%). Noninvasive global MW derived using LV pressure-strain loops at rest is a more sensitive index than global longitudinal strain to detect significant CAD in patients with no regional wall motion abnormalities and normal EF. This is a potential valuable clinical tool to assist in the early diagnosis of CAD.

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