Global longitudinal strain in heart failure with reduced ejection fraction: Prognostic relevance across disease severity as assessed by automated cluster analysis.

BACKGROUND

Ejection fraction (EF) is still widely used to categorize heart failure (HF) patients but has limitations. Global longitudinal strain (GLS) has emerged as a new prognosticator in HF, independent of EF.

AIM

We investigated the incremental predictive benefit of GLS over different risk profiles as identified by automated cluster analysis of simple echocardiographic parameters.

METHODS AND RESULTS

In 797 HFrEF patients (age 66 ± 12y; mean EF 30 ± 7%), unsupervised cluster analysis of 10 routine echocardiographic variables (without GLS) was performed. Median follow-up was 37 months. End-point was all-cause mortality. Association between risk profiles, GLS, and mortality was assessed by Cox proportional-hazard modeling with interaction term. Cluster analysis allocated patients to 3 different risk phenogroups (PG): PG-1 (mild diastolic dysfunction [DD], moderate systolic dysfunction, no pulmonary hypertension, normal right ventricular [RV] function); PG-2 (moderate DD, mild pulmonary hypertension, normal RV function); PG-3 (severe DD, advanced systolic dysfunction, pulmonary hypertension, RV dysfunction). Compared to PG-1, PG-2 and PG-3 showed increased adjusted-hazard ratio (1.71; 95% CI:1.05-2.77, P = 0.30; and 2.58; 95% CI:1.50-4.44, P < 0.001, respectively). GLS was independently associated with outcome in the whole population (adjusted-HR: 1.11; 95% CI: 1.05-1.17, P = 0.001); however, profile membership modified the relationship between GLS and outcome which was no longer significant in PG-3 (P for interaction = 0.003).

CONCLUSIONS

Within HFrEF populations, clustering of routine echocardiography parameters can automatically identify patients with different risk profiles; further assessment by GLS may be useful for patients with not advanced disease.