Abstract
Background
Right ventricular (RV) function is strongly associated with outcome in heart failure. Whether it also adds important prognostic information in patients undergoing transcatheter aortic valve implantation (TAVI) is unknown.
Methods
We consecutively enrolled patients with severe aortic stenosis (AS) scheduled for TAVI and preprocedural cardiac magnetic resonance (CMR) imaging. Kaplan-Meier estimates and multivariate Cox regression analyses were used to identify factors associated with outcome. A composite of heart failure hospitalization and/or cardiovascular death was selected as primary study endpoint.
Results
423 consecutive patients (80.7±7.3 years; 48% female) were prospectively included, 201 (48%) underwent CMR imaging. 55 (27%) patients presented with RV systolic dysfunction (RVSD) defined by RV ejection fraction (RVEF) <45%. RVSD was associated with male sex (69 vs. 40%; p<0.001), New York Heart Association (NYHA) functional status (NYHA ≥ III: 89 vs. 57%; p<0.001), NT-proBNP serum levels (9365 vs. 2715 pg/mL; p<0.001), and history of atrial fibrillation (AF: 51 vs. 30%; p=0.005). On CMR, RVSD was associated with left ventricular (LV) volumes (end-diastolic: 187 vs. 137 mL, end-systolic: 119 vs. 53 mL; p<0.001) and EF (39 vs. 64%; p<0.001).
A total of 51 events (37 deaths, 14 hospitalizations for heart failure) occurred during follow-up (9.8±9 months). While LVSD (LVEF <50%) was not significantly associated with outcome (HR 0.83, 95% CI: 0.33 – 2.11; p=0.694), RVSD showed a strong and independent association with event-free survival by multivariate Cox regression analysis (HR 2.47, 95% CI: 1.07–5.73; p=0.035), which was adjusted for all relevant CMR parameters (LV volumes and EF), cardiovascular risk factors (sex, NYHA, AF, diabetes mellitus type II, use of diuretics), and routine biomarkers (NT-proBNP, creatinine).
Conclusions
RVSD rather than LVSD, as determined on CMR, is an important predictor of outcome in patients undergoing TAVI. RV function might thus add useful prognostic information on top of established risk factors.
Figure 1. Kaplan-Meier survival curves
Funding Acknowledgement
Type of funding source: None