Real-time cardiovascular magnetic resonance imaging for non-invasive characterisation of heart failure with preserved ejection fraction: final outcomes of the HFpEF stress trial

Abstract

Abstract Background The diagnosis of heart failure with preserved ejection fraction (HFpEF) remains challenging. Recently, the HFpEF Stress Trial demonstrated feasibility and accuracy of non-invasive cardiovascular magnetic resonance (CMR) real-time (RT) exercise-stress atrial function imaging for early identification of HFpEF. However, no outcome data have yet been presented. Methods The HFpEF Stress Trial (DZHK-17) prospectively recruited 75 patients with dyspnea on exertion and echocardiographic preserved EF and signs of diastolic dysfunction (E/eʹ > 8). 68 patients entered the final study cohort and were characterized as HFpEF (n = 34) or non-cardiac dyspnea (n = 34) according to pulmonary capillary wedge pressure (HFpEF: PCWP rest: ≥ 15 mmHg stress: ≥ 25 mmHg). These patients were contacted by telephone and hospital charts were reviewed. The clinical endpoint was cardiovascular events (CVE). Results Follow-up was performed after 48 months; 1 patient was lost to follow-up. HFpEF patients were more frequently compared to non-cardiac dyspnea (15 vs. 8, p = 0.059). Hospitalised patients during follow-up had higher H2FPEF scores (5 vs. 3, p < 0.001), and impaired left atrial (LA) function at rest (p ≤ 0.002) and stress (p ≤ 0.006). Impairment of CMR-derived atrial function parameters at rest and during exercise-stress (p ≤ 0.003) was associated with increased likelihood for CVE. CMR-Feature Tracking LA Es/Ee (p = 0.016/0.017) and RT-CMR derived LA long axis strain (p = 0.003) were predictors of CVE independent of the presence of atrial fibrillation. Conclusions Left atrial function emerged as the strongest predictor for 4-year outcome in the HFpEF Stress Trial. A combination of rest and exercise-stress LA function quantification allows accurate diagnostic and prognostic stratification in HFpEF. Clinicaltrials.gov: NCT03260621. Graphical abstract