Background: Right ventricular longitudinal strain of free wall (RV FWLS) assessed by two-dimensional speckle-tracking echocardiography (2D-STE) is recognized as an independent predictor of poor prognosis in patients with heart failure with preserved ejection fraction (HFpEF). However, the prognostic implications of three-dimensional STE (3D-STE) parameters in patients with HFpEF have not been well-established. The purpose of our study was to determine whether 3D-STE parameters were the more powerful predictors of poor outcomes in HFpEF patients compared with 2D-STE indices. Methods: Eighty-one consecutive patients with HFpEF were studied by 2D-STE and 3D-STE. RV volumes, ejection fraction (EF) and 3D-RVFWLS were measured by 3D-STE. 2D-RVFWLS was determined by 2D-STE. Patients were followed for the primary end point of heart failure (HF)-related hospitalization and death for HF. Results: After a median follow-up period of 17 months, 39 (48%) patients reached the end point of cardiovascular events. Compared with HFpEF patients without end-point events, those with end-point events had lower RVEF and 3D-RVFWLS (P < 0.05). Separate multivariate Cox regression analyses revealed that 3D-RVFWLS (HR 5.73; 95% CI 2.77-11.85; P < 0.001), RVEF (HR 3.47; 95% CI 1.47-8.21; P = 0.005), and 2D-RVFWLS (HR 3.17; 95% CI 1.54-6.53; P = 0.002) were independent predictors of adverse outcomes. The models with 3D-RVFWLS (AIC = 246, C-index = 0.75) and RVEF (AIC = 247, C-index = 0.76) had similar predictive performance for future clinical events as with 2D-RVFWLS (AIC = 248, C-index = 0.74). Conclusions: 3D-STE parameters are powerful predictors of poor outcomes, providing a similar predictive value as 2D-STE indices in patients with HFpEF. These findings support the potential of RV 3D-STE to identify HFpEF patients at higher risk for adverse cardiac events.
Keywords: heart failure with preserved ejection fraction; prognosis; right ventricular; speckle tracking echocardiography; strain.
Copyright © 2021 Meng, Zhu, Xie, Zhang, Qian, Gao, Li, Lin, Wu, Wang, Yang, Lv, Zhang, Li and Xie.