Echocardiographic predictors of cardiovascular outcome in heart failure with preserved ejection fraction.

Abstract

The optimal echocardiographic predictors of cardiovascular outcome in heart failure (HF) with preserved ejection fraction (HFpEF) are unknown. We aimed to identify independent echocardiographic predictors of cardiovascular outcome in patients with HFpEF. Systematic literature search of three electronic databases was conducted from date of inception until November 2022. Hazard ratios (HRs) and their 95% confidence intervals (CIs) for echocardiographic variables from multivariate prediction models for the composite primary endpoint of cardiovascular death and HF hospitalization were pooled using a random effects meta-analysis. Specific subgroup analyses were conducted for studies that enrolled patients with acute versus chronic HF, and for those studies that included E/e', pulmonary artery systolic pressure (PASP), renal function, natriuretic peptides and diuretic use in multivariate models. Forty-six studies totalling 20 056 patients with HFpEF were included. Three echocardiographic parameters emerged as independent predictors in all subgroup analyses: decreased left ventricular (LV) global longitudinal strain (HR 1.24, 95% CI 1.10-1.39 per 5% decrease), decreased left atrial (LA) reservoir strain (HR 1.30, 95% CI 1.13-1.1.50 per 5% decrease) and lower tricuspid annular plane systolic excursion (TAPSE) to PASP ratio (HR 1.17, 95% CI 1.07-1.25 per 0.1 unit decrease). Other independent echocardiographic predictors of the primary endpoint were a higher E/e', moderate to severe tricuspid regurgitation, LV mass index and LA ejection fraction, although these variables were less robust. Impaired LV global longitudinal strain, lower LA reservoir strain and lower TAPSE/PASP ratio predict cardiovascular death and HF hospitalization in HFpEF and are independent of filling pressures, clinical characteristics and natriuretic peptides. These echocardiographic parameters reflect key functional changes in HFpEF, and should be incorporated in future prospective risk prediction models.