BACKGROUND

The strategies for improving outcomes in heart failure with preserved ejection fraction (HFpEF) are insufficiently defined, which affects optimal patient management. The aim of the study was to compare the prognostic value of the previously validated Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) risk score with 2 approaches primarily dedicated to diagnosing HFpEF: the HFPEF score (heavy, 2 or more hypertensive drugs, atrial fibrillation, pulmonary hypertension [pulmonary artery systolic pressure >35 mm Hg], elder age >60, elevated filling pressures [E/e' > 9]) and the HFA-PEFF algorithm (Heart Failure Association diagnostic algorithm-pretest assessment; echocardiography and natriuretic peptide score; functional testing; final etiology) in patients with exertional dyspnea categorized as HFpEF.

METHODS

Clinical and biochemical variables and echocardiographic resting and exercise data from 201 enrollees were retrospectively analyzed. Participants were followed for 48 (24-60) months for HF hospitalization and cardiovascular death.

RESULTS

Seventy-four patients (36.8%) met the study outcome. In sequential Cox analysis, the addition of MAGGIC risk score, HFPEF score, and HFA-PEFF step 2 (including only resting echocardiographic evaluation) and step 3 (including also exercise diastolic data) algorithms to the base model comprising brain natriuretic peptide and peak oxygen uptake improved the predictive power for the study endpoint. Harrell's c statistic showed a greater predictive ability for the HFA-PEFF step 3 algorithm than for each of the other scores (c index 0.715 vs 0.637, 0.644, and 0.638 for MAGGIC, HFPEF, and HFA-PEFF step 2, respectively; all P < .05). No significant differences were found for other between-score comparisons.

CONCLUSION

In patients with exertional dyspnea and a possible HFpEF, the HFPEF score and HFA-PEFF algorithm limited to resting echocardiography provide prognostic value comparable to the MAGGIC risk score. Extending the HFA-PEFF algorithm with exercise diastolic data is associated with a significant improvement in risk stratification.