Ekhlas Hussein
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Ekhlas Hussein has a total of 1 co-authors. Here are the top co-authors by number of shared publications:
- Hanan Ibrahim Radwan
Faculty of Medicine, Zagazig University, Cardiovascular Department, Egypt
1 shared publication
Latest Publications
- Open Access
- 1 June 2017
- Published by Springer Nature in The Egyptian Heart Journal
- Vol. 69 (2) , 95-101
Value of global longitudinal strain by two dimensional speckle tracking echocardiography in predicting coronary artery disease severity
Significant coronary artery stenosis might cause persistently impaired longitudinal left ventricle (LV) function at rest. LV global longitudinal strain (LVGLS) can be accurately assessed by 2D speckle-tracking strain echocardiography(2D-STE). We aimed to evaluate the diagnostic accuracy of LV global longitudinal strain obtained by 2D-STE in prediction of severity of CAD. Eighty patients with suspected stable angina pectoris were included. They underwent transthoracic echocardiography (TTE) to measure LV ejection fraction, 2-D-STE to measure GLS and coronary angiography (CA). The patients were divided into two groups: group 1 (58 patients) with significant (>70%) CAD, and group 2 (22 patients) with non-significant (<70%) CAD. Images were obtained in the apical long-axis, four-chamber, and two chamber views. Regional longitudinal systolic strain was measured in 17 myocardial segments and averaged to provide global longitudinal strain (LVGLS). There was significant decrease in GLS in group 1 compared to group 2 (-11.86 ± 2.89% versus -18.65 ± 0.79%, P < 0.000). The optimal cutoff value of GLS for prediction of significant CAD was -15.6% [AUC 0.88, 95% CI 0.78-0.96 p < 0.000]. The sensitivity, specificity and accuracy of GLS for detecting significant CAD were 93.1%, 81.8%,and 90% respectively.There was a significant positive correlation between GLS and EF (r = 0.33; p = 0.036).There was incremental significant decrease in GLS with increasing number of coronary vessels involved. Measurement of global longitudinal strain using 2D speckle tracking echocardiography is sensitive and accurate tool in the prediction of severe CAD.
- 1 June 2017
- Published by Springer Nature in The Egyptian Heart Journal
- Vol. 69 (2) , 95-101
Open AccessValue of global longitudinal strain by two dimensional speckle tracking echocardiography in predicting coronary artery disease severity
Significant coronary artery stenosis might cause persistently impaired longitudinal left ventricle (LV) function at rest. LV global longitudinal strain (LVGLS) can be accurately assessed by 2D speckle-tracking strain echocardiography(2D-STE). We aimed to evaluate the diagnostic accuracy of LV global longitudinal strain obtained by 2D-STE in prediction of severity of CAD. Eighty patients with suspected stable angina pectoris were included. They underwent transthoracic echocardiography (TTE) to measure LV ejection fraction, 2-D-STE to measure GLS and coronary angiography (CA). The patients were divided into two groups: group 1 (58 patients) with significant (>70%) CAD, and group 2 (22 patients) with non-significant (<70%) CAD. Images were obtained in the apical long-axis, four-chamber, and two chamber views. Regional longitudinal systolic strain was measured in 17 myocardial segments and averaged to provide global longitudinal strain (LVGLS). There was significant decrease in GLS in group 1 compared to group 2 (-11.86 ± 2.89% versus -18.65 ± 0.79%, P < 0.000). The optimal cutoff value of GLS for prediction of significant CAD was -15.6% [AUC 0.88, 95% CI 0.78-0.96 p < 0.000]. The sensitivity, specificity and accuracy of GLS for detecting significant CAD were 93.1%, 81.8%,and 90% respectively.There was a significant positive correlation between GLS and EF (r = 0.33; p = 0.036).There was incremental significant decrease in GLS with increasing number of coronary vessels involved. Measurement of global longitudinal strain using 2D speckle tracking echocardiography is sensitive and accurate tool in the prediction of severe CAD.