An echocardiographic algorithm for predicting coronary artery disease: is it time to establish one?

Abstract

Abstract Funding Acknowledgements Type of funding sources: Public hospital(s). Main funding source(s): Al-mouwasat University Hospital and University Heart Surgery Center in Damascus, Syrian Arab Republic. Background Coronary artery disease (CAD) is a major clinical issue. CAD affects left ventricular systolic, diastolic function and LV filling pressure. Echocardiography has been known as the best noninvasive way for the assessment of systolic, diastolic function and LV filling pressure. Finding a correlation between CAD and echocardiographic parameters may help in the early assessment, prognosis and treatment of CAD. Purpose Finding a correlation between coronary artery disease and echocardiographic parameters with cutoffs to use in a diagnostic algorithm. Methods 124 patients who accepted to participate for this study underwent transthoracic echocardiography immediately before their medically indicated left heart catheterization . An experienced echo cardiographer obtained mitral flow E velocity, A velocity, E/A, A duration, Av E/e", septal, lateral and mean e", pulmonary veins S velocity, D velocity, S/D, AR velocity, AR duration, AR-A duration, left atrial volume index (LAVI), tricuspid regurgitation (TR), inter ventricular septum (IVS), left inter ventricular diameter (LIVD), posterior wall diameter (PW) and some other echo parameters and assessed LV diastolic function and filling pressure according to EACVI/ASE 2016 guidelines. This study obtained angiography results and then analyzed and compared the results. Results Echo parameters that correlated with CAD were: EDT ≥ 160 (P = 0.0012 OR = 5.46), Av E/e" ≥ 7 (P = 0.0066 OR = 3.67), E ≥ 44 cm/s (P = 0.0026 OR = 10.00), A duration > 140 (P = 0.0256 OR = 10.50), E/A ≥ 1 (P = 0.0036 OR = 4.17) and AR duration ≥ 210 (P = 0.0001 OR = 85.00). When Cutoffs ≥ 3 present, the correlation with CAD was (P= < 0.0001 OR = 8.80) with diagnostic accuracy of (sensitivity = 0.76, specificity = 0.74, NPV = 0.68, PPV = 0.81). All the results are summarized in (Picture1:Tables 1 and 2). Conclusion Echo parameters (EDT, Av E/e", E velocity, A duration, E/A, AR duration) had strong correlations with the presence of coronary artery disease. The presence of three or more abnormal parameters had a significant diagnostic accuracy for CAD, and the more the abnormal parameters were positive, the higher the specificity and positive predictive value were for the diagnosis of CAD. The presence of only two abnormal parameters had a low specificity for CAD and the presence of 2016 EACVI/ASE diastolic dysfunction correlated with CAD with modest specificity which needs further assessment for the differential diagnosis. Furthermore, one or no abnormal parameters ruled out CAD with strong negative predictive value. Depending on the results of this study we kindly propose a resting echocardiographic algorithm for the diagnosis of CAD in (picture2: a proposed algorithm). Further studies should validate this algorithm and find other echo parameters especially strain echocardiography wether for resting or exercise algorithms. Abstract Tables of results Abstract Figure. A proposed algorithm