Abstract
Introduction: Heart failure (HF) is a heterogeneous syndrome, and the specific sub-category HF with mildly reduced ejection fraction (EF) range (HFmrEF; 41–49% EF) is only recently recognised as a distinct entity. Cluster analysis can characterise heterogeneous patient populations and could serve as a stratification tool in clinical trials and for prognostication. The aim of this study was to identify clusters in HFmrEF and compare cluster prognosis. Methods and results: Latent class analysis to cluster HFmrEF patients based on their characteristics was performed in the Swedish HF registry (n = 7316). Identified clusters were validated in a Dutch cross-sectional HF registry-based dataset CHECK-HF (n = 1536). In Sweden, mortality and hospitalisation across the clusters were compared using a Cox proportional hazard model, with a Fine-Gray sub-distribution for competing risks and adjustment for age and sex. Six clusters were discovered with the following prevalence and hazard ratio with 95% confidence intervals (HR [95%CI]) vs. cluster 1: 1) low-comorbidity (17%, reference), 2) ischaemic-male (13%, HR 0.9 [95% CI 0.7–1.1]), 3) atrial fibrillation (20%, HR 1.5 [95% CI 1.2–1.9]), 4) device/wide QRS (9%, HR 2.7 [95% CI 2.2–3.4]), 5) metabolic (19%, HR 3.1 [95% CI 2.5–3.7]) and 6) cardio-renal phenotype (22%, HR 2.8 [95% CI 2.2–3.6]). The cluster model was robust between both datasets. Conclusion: We found robust clusters with potential clinical meaning and differences in mortality and hospitalisation. Our clustering model could be valuable as a clinical differentiation support and prognostic tool in clinical trial design.
| Original language | English |
|---|---|
| Pages (from-to) | 83-90 |
| Number of pages | 8 |
| Journal | International Journal of Cardiology |
| Volume | 386 |
| Early online date | 16 May 2023 |
| DOIs | |
| Publication status | Published - 1 Sept 2023 |
Bibliographical note
Funding Information:This study was supported by grants to LHL's institution from the Swedish Research Council [grants 2013–23897–104604-23 and 523–2014-2336], the Swedish Heart Lung Foundation [grants 20150557 and 20170841], and the Stockholm County Council [grant 20140220, 20170112]. F. W. Asselbergs is supported by UCL Hospitals NIHR Biomedical Research Centre . I. Vaartjes is supported by the Dutch Heart Foundation , as part of “Facts and Figures”.
Funding Information:
LHL reports personal fees from Merck, grants and personal fees from Boehringer Ingelheim, personal fees from Sanofi, grants and personal fees from Vifor-Fresenius, personal fees from AstraZeneca, grants and personal fees from Relypsa, personal fees from Bayer, grants from Boston Scientific, grants and personal fees from Novartis, personal fees from Pharmacosmos, personal fees from Abbott, grants and personal fees from Mundipharma, personal fees from Medscape, outside the submitted work.
Funding Information:
The Swedish Heart Failure Registry is funded by the Swedish National Board of Health and Welfare, the Swedish Association of Local Authorities and Regions, the Swedish Society of Cardiology, and the Swedish Heart-Lung Foundation. Servier, the Netherlands, partially funded the inclusion of data and software program for CHECK-HF. The CHECK-HF steering committee (JB, GL, HPBLR, AH) received no funding for this project. The current study was initiated by the authors and was designed, conducted, interpreted, and reported independently of the sponsor. This work has received support from the EU/EFPIA Innovative Medicines Initiative 2 Joint Undertaking BigData@Heart grant n° 116074.
Publisher Copyright:
© 2023 The Author(s)