Echocardiography is an important cardiac imaging tool in patients with suspected cardiac disease. However, conventional echocardiography has a limited value in the diagnosis and risk stratification of suspected CAD patients as most of these patients with no previous myocardial infarction or myocardial stunning have no wall motion abnormalities at rest. So, finding another resting module to diagnose and predict the severity of CAD would be very beneficial .
Speckle tracking echocardiography (STE) is a semi-automated software that allows fast, quantitative, and angle-independent assessment of the three components of myocardial deformation, with great feasibility and reproducibility particularly of the longitudinal one. Several clinical studies confirmed the feasibility of STE-derived longitudinal strain analysis as an adjunctive method for CAD detection .
In this prospective study, we studied 70 patients aged 20–80 and collected from an outpatient cardiology clinic; echocardiography (including both conventional and STE) and coronary angiography were done for each patient, and then data was collected and analyzed.
We could identify a cutoff value of GLS with high sensitivity and specificity to detect a high SYNTAX score.
Biering-Sørensen et al. , Gaibazzi et al. , and Billehaug et al.  showed that GLS is significantly lower in patients with obstructive CAD (at least one stenosis > 50% or ≥ 70% luminal area reduction) when compared with patients with non-obstructive CAD, and our study showed similar results. And they reported that GLS values at rest have moderate diagnostic accuracy in predicting significant CAD while in our study, it had high diagnostic accuracy, as our results revealed that GLS ⩽ 16.5 can predict significant coronary artery stenosis, with sensitivity 93% and specificity 91%, while Biering-Sørensen et al.  showed that GLS ⩽ − 18.4% can predict significant coronary stenosis (> 70%), with sensitivity 74% and specificity 58%. Similarly, Gaibazzi et al.  showed that GLS ⩽ − 20.7 may predict significant coronary stenosis (> 50%), with sensitivity 81.6% and specificity 84.9%.
In Billehaug et al. , GLS measurements have moderate diagnostic accuracy in predicting significant CAD in patients presenting with chest pain. They showed that GLS cutoff value for prediction of CAD varied between − 17.4 and − 19.7% with sensitivity from 51 to 81% and specificity between 58 and 81%. The effect of diastolic function and afterload on GLS may explain this finding.
Our study showed that GLS decreased incrementally with increasing SYNTAX score which indicates increasing severity of CAD. Vrettos et al.  showed similar results when they studied 71 patients and reported that GLS values were inversely correlated to SYNTAX score values. And they showed that the GLS optimal cutoff value to detect patients with high SYNTAX score was − 13.95 (sensitivity = 71%, specificity = 90%, p < 0.001).
There was a positive correlation between high SYNTAX score and being diabetic (p = 0.007); this was also noted in Srinivasan et al.  where they observed that patients with 5–10 years of diabetes mellitus have a significant increase in the mean SYNTAX score (p = 0.019) when compared to those with less diabetes duration.
Another positive correlation was present between SYNTAX score and smoking (p = 0.001); this was found in several studies, among them El Kersh et al. , where a statistically significant correlation between age, hypertension, diabetes mellitus, dyslipidemia, and smoking with SYNTAX score was noticed (p < 0.05).
El-Sayed et al.  found that high SYNTAX score patients have higher E/A ratio and lower deceleration time (DT) when compared with the low SYNTAX score patients (p = 0.016 and p = 0.046, respectively) while our study did not reach these results as the E/A ratio was lower in the high SYNTAX group (p = 0.04).
In our study, mean GLS was lower in diabetic patients 13.7 ± 2.4 than non-diabetics 15.8 ± 2.7 (p = 0.001), and this was similar to the results of Elgohary et al.  who compared results of patients with controlled and uncontrolled diabetes and found a significant statistical difference in GLS, age, diabetic duration, 2HPP blood sugar level, and E/é ratio in patients with controlled DM compared to uncontrolled DM. Another study by Wierzbowska-Drabik et al.  showed that during DSE global and regional LV peak, systolic longitudinal strain revealed lower values in DM patients when compared to non-diabetics: 14.5 ± 3.6% vs. 17.4 ± 4.0% at rest; p = 0.0001.
On the other hand, while we found that smokers had significantly lower mean GLS (p = 0.002), Farsalinos et al.  showed no significant changes in GLS were reported when they studied myocardial function in young and healthy heavy smokers.
Our study results showed a good correlation between left ventricle EF and GLS (r = 0.25; p = 0.04), and Benyounes et al.  reported similar results when they approved that two-dimensional GLS can predict LVEF (r = − 0.53; p < 0.001). Also, Lima et al.  concluded that left ventricle EF and GLS showed a powerful correlation (r = 0.95; r2 = 0.89; p < 0.001), especially in patients with LV systolic dysfunction than those with normal LVEF.