Abstract

AimsSeveral different diagnostic parameters can be used to assess left ventricular (LV) longitudinal systolic function, but no studies comparing their predictive value have been conducted. We sought to compare the prognostic value of LV long‐axis function parameters at rest and exercise using the population with heart failure with preserved ejection fraction (HFpEF).Methods and resultsClinical and biochemical variables were collected at baseline in 201 patients with HFpEF. Echocardiography was performed at rest and immediately after exercise, with measurement of mitral annular plane systolic excursion, systolic tissue velocity (s′), global longitudinal strain (GLS), and global longitudinal strain rate (GLSR). Participants were followed for 48 (24–60) months for heart failure hospitalization and cardiovascular death. Seventy‐four patients (36.8%) met the study endpoint. Cox regression analysis revealed that after adjustment for Meta‐Analysis Global Group in Chronic Heart Failure risk score, brain natriuretic peptide (BNP), and peak VO2, heart failure hospitalization and cardiovascular death were significantly associated with GLS at rest [hazard ratio (HR) 0.91; 95% confidence interval (CI) 0.84–0.98; P = 0.016], GLS after exercise (HR 0.84; 95% CI 0.77–0.91; P < 0.001), and GLSR after exercise (HR 0.13; 95% CI 0.04–0.48; P = 0.002). The addition of each of the following: exercise GLS and GLSR and resting GLS to the base model including Meta‐Analysis Global Group in Chronic Heart Failure, BNP, and peak VO2 improved predictive power for the study endpoint [net reclassification improvement (NRI) = 49%, P < 0.001; NRI = 42%, P = 0.004; and NRI = 38%, P = 0.009, respectively]. Exercise GLS was the only longitudinal parameter significantly improving c‐statistics of the base model (0.68 vs. 0.73; P = 0.047).ConclusionsEchocardiographic parameters of LV longitudinal function are not equipotential in predicting adverse outcomes in HFpEF. LV deformation indices, especially assessed with exercise, show the highest predictive utility independent from and incremental to clinical data and BNP.

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