Speckle Tracking as Predictor of Coronary Artery Disease in Diabetic Female with Acute Chest Pain

Background: Cardiovascular disease is the most common reason of mortality and morbidity all-over the world and is the major complication of diabetes. Diabetes mellitus (DM) has reached epidemic proportions worldwide and the consequences of its diagnosis are as severe as a diagnosis of coronary artery disease (CAD). Females are more likely to develop atypical symptoms of coronary CAD than males later in life. Imaging of deformation by two-dimensional speckle-tracking echocardiography (2DSTE) has developed as a highly effective method for quantification of the function of myocardium. This research aimed to evaluate the accuracy of diagnosis using speckle tracking for prediction of the existence or absence of severe CAD in diabetic female with acute chest pain by using two-dimensional echocardiography. Methods: This study is a cohort prospective research which was carried out at the department of cardiology, Tanta University Hospitals and National Heart Institute from the duration of October 2019 to September 2020 on 60 diabetic female patients above 18 years old with acute chest pain may be prolonged for > 20 minutes or transient, changes in ECG in the form of depression of ST segment and/or inversion of T wave (ECG may be normal) and cardiac biomarkers (troponin and CKMB) may be elevated or normal. Results: 2D speckle tracking was good predictor for multi-vessels disease with 95% total accuracy, then for single vessels disease with 85% total accuracy and finally for double vessel disease stenosis with 80% accuracy as shown in table. Among Non-STEMI group, 2D speckle tracking was good predictor for multi-vessels disease with 95% total accuracy, then for single vessels disease with 80% total accuracy and finally for double vessel disease stenosis with 75% accuracy as shown in table. Conclusions: We found that speckle tracking is effective in predicting presence of CAD in diabetic female patients had acute chest pain and in prediction of affected vessels depending on the distribution of affected segments in longitudinal strain by GLS. In addition, it can be used as non-invasive test for patients with acute coronary syndrome.