scholarly journals INCREMENTAL PROGNOSTIC VALUE OF MYOCARDIAL PERFUSION STRESS-ECHOCARDIOGRAPHY IN PATIENTS WITH KNOWN CORONARY ARTERY DISEASE

2013 ◽  
Vol 61 (10) ◽  
pp. E821
Author(s):  
Thomas Porter ◽  
Juefei Wu ◽  
Feng Xie ◽  
Stacey Therrien ◽  
Valentina Lorenzoni ◽  
...  
Author(s):  
Lijun Qian ◽  
Feng Xie ◽  
Di Xu ◽  
T R Porter

Abstract Aims  To evaluate the prognostic value of myocardial perfusion (MP) imaging during contrast stress echocardiography (cSE) in patients with known or suspected coronary artery disease (CAD). Methods and results  A search in PubMed, Embase databases, and the Cochrane library was conducted through May 2019. The Cochran Q statistic and the I2 statistic were used to assess heterogeneity, and the results were analysed by RevMan V5.3 and Stata V15.1 software. Twelve studies (seven dipyridamole and five exercise/dobutamine) without evidence of patient overlap (same institution publishing results over a similar time period) enrolling 5953 subjects (47% female, 8–80 months of follow-up) were included in the analysis. In all studies, total adverse cardiovascular events were defined as either cardiac death, non-fatal myocardial infarction (NFMI), or need for urgent revascularization. Hazard ratios (HRs) revealed that a MP abnormality [pooled HR 4.75; 95% confidence interval (CI) 2.47–9.14] was a higher independent predictor of total events than abnormal wall motion (WM, pooled HR 2.39; 95% CI 1.58–3.61) and resting left ventricular ejection fraction (LVEF, pooled HR 1.92; 95% CI 1.44–2.55) with significant subgroup differences (P = 0.002 compared with abnormal WM and 0.01 compared with abnormal LVEF). Abnormal MP was associated with higher risks for death [Risk ratio (RR) 5.24; 95% CI 2.91–9.43], NFMI (RR 3.09; 95% CI 1.84–5.21), and need for coronary revascularization (RR 16.44; 95% CI 6.14–43.99). Conclusion  MP analysis during stress echocardiography is an effective prognostic tool in patients with known or suspected CAD and provides incremental value over LVEF and WM in predicting clinical outcomes.


Sign in / Sign up

Export Citation Format

Share Document