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. 2021 Jun;23(6):973-982.
doi: 10.1002/ejhf.2169. Epub 2021 May 1.

Identification of distinct phenotypic clusters in heart failure with preserved ejection fraction

Alicia Uijl  1   2   3 , Gianluigi Savarese  2 , Ilonca Vaartjes  1 , Ulf Dahlström  4 , Jasper J Brugts  5 , Gerard C M Linssen  6 , Vanessa van Empel  7 , Hans-Peter Brunner-La Rocca  7 , Folkert W Asselbergs  3   8   9 , Lars H Lund  2   10 , Arno W Hoes  1 , Stefan Koudstaal  3   11
Affiliations

Identification of distinct phenotypic clusters in heart failure with preserved ejection fraction

Alicia Uijl et al. Eur J Heart Fail. 2021 Jun.

Abstract

Aims: We aimed to derive and validate clinically useful clusters of patients with heart failure with preserved ejection fraction (HFpEF; left ventricular ejection fraction ≥50%).

Methods and results: We derived a cluster model from 6909 HFpEF patients from the Swedish Heart Failure Registry (SwedeHF) and externally validated this in 2153 patients from the Chronic Heart Failure ESC-guideline based Cardiology practice Quality project (CHECK-HF) registry. In SwedeHF, the median age was 80 [interquartile range 72-86] years, 52% of patients were female and most frequent comorbidities were hypertension (82%), atrial fibrillation (68%), and ischaemic heart disease (48%). Latent class analysis identified five distinct clusters: cluster 1 (10% of patients) were young patients with a low comorbidity burden and the highest proportion of implantable devices; cluster 2 (30%) patients had atrial fibrillation, hypertension without diabetes; cluster 3 (25%) patients were the oldest with many cardiovascular comorbidities and hypertension; cluster 4 (15%) patients had obesity, diabetes and hypertension; and cluster 5 (20%) patients were older with ischaemic heart disease, hypertension and renal failure and were most frequently prescribed diuretics. The clusters were reproduced in the CHECK-HF cohort. Patients in cluster 1 had the best prognosis, while patients in clusters 3 and 5 had the worst age- and sex-adjusted prognosis.

Conclusions: Five distinct clusters of HFpEF patients were identified that differed in clinical characteristics, heart failure drug therapy and prognosis. These results confirm the heterogeneity of HFpEF and form a basis for tailoring trial design to individualized drug therapy in HFpEF patients.

Keywords: Clusters; Comorbidities; External validation; Heart failure with preserved ejection fraction; Latent class analysis; Phenotyping; Treatment.

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Figures

Figure 1
Figure 1
Patient comorbidity profiles within clusters in SwedeHF. Obesity: body mass index >30 kg/m2. COPD, chronic obstructive pulmonary disease.
Figure 2
Figure 2
Cumulative incidence curves for the association between clusters and outcomes in SwedeHF patients. (A) Composite outcome, (B) all‐cause mortality, (C) cardiovascular (CV) mortality, (D) heart failure (HF) hospitalization, (E) non‐CV mortality. All models are adjusted for age and sex. The composite outcome consisted of a combination of CV mortality and HF hospitalization. CI, confidence interval; HR, hazard ratio.
See this image and copyright information in PMC

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