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.