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Diagnostic Performance of Two-Dimensional Speckle Tracking Echocardiography for Detection of Obstructive Coronary Artery Disease: A Meta-Analysis.
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  • Arun Kannan,
  • Jaspreet Singh,
  • Vincent Sorrell,
  • Aiden Abidov
Arun Kannan
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Jaspreet Singh
The University of Arizona
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Vincent Sorrell
University of Kentucky
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Aiden Abidov
Wayne State University
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Background: Two-dimensional speckle tracking echocardiography (STE) is a quantitative myocardial strain imaging technique in evaluating global and segmental myocardial deformation. The aim of the meta-analysis was to determine the diagnostic accuracy of STE in the detection of significant coronary artery disease (CAD) in patients undergoing resting or stress echocardiography. Methods: We performed a literature search in PubMed and Medline until March 2020 for studies evaluating the role of STE in diagnosing CAD. We assessed the diagnostic performance of STE in detecting CAD by using the pooled estimate of sensitivity, specificity, likelihood ratio, diagnostic odds ratio and diagnostic accuracy. We analyzed longitudinal strain data that were reported in resting and stress echocardiography. Results: A total of 17 studies (n=1762) were included for the analysis. 12 studies (n=1239) reported global longitudinal strain (GLS) in resting echocardiography and 5 studies (n=523) reported GLS in stress echocardiography. Overall, in resting echocardiography studies, pooled GLS sensitivity and specificity for predicting obstructive CAD data were calculated to be 79% (95% confidence interval 74-83%) and 77% (95% confidence interval 72-82%), respectively. The pooled odds ratio was 13.6 (95% confidence interval 8.7-21.5). When we considered the dobutamine stress echocardiograms alone, the sensitivity and specificity in predicting obstructive CAD was 77% (95% confidence interval 59-89%) and 78% (95% confidence interval 53-92%), respectively. The odds ratio was 12.6 (95% confidence interval 2.7-58.5). Conclusions: In this meta-analysis of patients with suspected CAD, we found that STE could effectively detect obstructive CAD with a high diagnostic sensitivity, specificity and diagnostic accuracy