Prognostic utility of diastolic dysfunction and speckle tracking echocardiography in heart failure with reduced ejection fraction

Abstract

Aims: We hypothesized that grading of diastolic dysfunction (DDF) according to two DDF grading algorithms and strain imaging yields prognostic information on all-cause mortality in patients with heart failure with reduced ejection fraction (HFrEF).

Methods and results: We enrolled ambulatory HFrEF (left ventricular ejection fraction < 45%; N = 1 065) patients who underwent echocardiography and speckle tracking assessment of global longitudinal strain (GLS). Patients were stratified according to DDF grades (Grades I-III) according to two contemporary DDF grading algorithms. Prognostic performance was assessed by C-statistics. Of the originally 1 065 enrolled patients, a total of 645 (61%) patients (age: 67 ± 11 years, male: 72%, ejection fraction: 27 ± 9%) were classified according to both DDF grading algorithms. Concordance between the algorithms was moderate (kappa = 0.48) and the reclassification rate was 33%. During a median follow-up of 3.3 years (1.9, 4.7 years), 101 (16%) died from all causes. When comparing DDF Grade I vs. Grade III, both algorithms provided prognostic information [Nagueh: (hazard ratio) HR 2.09, 95% confidence interval (CI),1.32-3.31, P = 0.002; Johansen: HR 2.47, 95% CI, 1.57-3.87, P < 0.001]. However, when comparing DDF Grade II vs. Grade III, only the Johansen algorithm yielded prognostic information (Nagueh: HR 1.04, 95% CI, 0.60-1.77, P = 0.90; Johansen: HR 2.26, 95% CI, 1.35-3.77, P = 0.002). We found no difference in prognostic performance between the two algorithms (C-statistics: 0.604 vs. 0.623, P = 0.24). Assessed by C-statistics, the most powerful predictors of the endpoint from the two algorithms were E/e'-ratio (C-statistics: 0.644), tricuspid regurgitation velocity (C-statistics: 0.625) and E/A-ratio (C-statistics: 0.602). When adding GLS to a combination of these predictors, the prognostic performance increased significantly (C-statistics: 0.705 vs. C-statistics: 0.634, P = 0.028).

Conclusions: Evaluation of DDF in patients with HFrEF yields prognostic information on all-cause mortality. Furthermore, adding GLS to contemporary algorithms of DDF adds novel prognostic information.

Keywords: Diastolic dysfunction; Prognosis; Speckle tracking.

Figure 1

Study population. Flowchart showing the inclusion of patients eligible for grading of diastolic dysfunction by the two algorithms. HFrEF, heart failure with reduced ejection fraction.

Figure 2

Flowcharts of algorithms for grading of diastolic dysfunction. Study population divided into categories of diastolic dysfunction by Nagueh et al. algorithm (A) and Johansen et al. algorithm (B). E, peak transmitral early diastolic inflow velocity; e', peak early diastolic mitral annular velocity; E/A, ratio between peak transmitral early and late diastolic inflow velocity; E/e', ratio between peak transmitral early diastolic inflow velocity and peak early diastolic mitral annular velocity; TR, tricuspid regurgitation; LAVI, left atrial volume index; LAP, left atrial pressure; cTDI, color tissue Doppler imaging; pwTDI, pulsed‐wave tissue Doppler imaging; DDF, diastolic dysfunction.

Figure 3

Kaplan–Meier survival curves. Kaplan–Meier curves showing the cumulated survival of patients divided into the three different DDF grades by Nagueh et al. (A) and Johansen et al. (B).