Cargando…
Identification of distinct phenotypic clusters in heart failure with preserved ejection fraction
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...
Autores principales: | , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Ltd.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8359985/ https://www.ncbi.nlm.nih.gov/pubmed/33779119 http://dx.doi.org/10.1002/ejhf.2169 |
_version_ | 1783737650238193664 |
---|---|
author | Uijl, Alicia Savarese, Gianluigi Vaartjes, Ilonca Dahlström, Ulf Brugts, Jasper J. Linssen, Gerard C.M. van Empel, Vanessa Brunner‐La Rocca, Hans‐Peter Asselbergs, Folkert W. Lund, Lars H. Hoes, Arno W. Koudstaal, Stefan |
author_facet | Uijl, Alicia Savarese, Gianluigi Vaartjes, Ilonca Dahlström, Ulf Brugts, Jasper J. Linssen, Gerard C.M. van Empel, Vanessa Brunner‐La Rocca, Hans‐Peter Asselbergs, Folkert W. Lund, Lars H. Hoes, Arno W. Koudstaal, Stefan |
author_sort | Uijl, Alicia |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8359985 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley & Sons, Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-83599852021-08-17 Identification of distinct phenotypic clusters in heart failure with preserved ejection fraction Uijl, Alicia Savarese, Gianluigi Vaartjes, Ilonca Dahlström, Ulf Brugts, Jasper J. Linssen, Gerard C.M. van Empel, Vanessa Brunner‐La Rocca, Hans‐Peter Asselbergs, Folkert W. Lund, Lars H. Hoes, Arno W. Koudstaal, Stefan Eur J Heart Fail HFpEF AND MACHINE LEARNING 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. John Wiley & Sons, Ltd. 2021-05-01 2021-06 /pmc/articles/PMC8359985/ /pubmed/33779119 http://dx.doi.org/10.1002/ejhf.2169 Text en © 2021 The Authors. European Journal of Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | HFpEF AND MACHINE LEARNING Uijl, Alicia Savarese, Gianluigi Vaartjes, Ilonca Dahlström, Ulf Brugts, Jasper J. Linssen, Gerard C.M. van Empel, Vanessa Brunner‐La Rocca, Hans‐Peter Asselbergs, Folkert W. Lund, Lars H. Hoes, Arno W. Koudstaal, Stefan Identification of distinct phenotypic clusters in heart failure with preserved ejection fraction |
title | Identification of distinct phenotypic clusters in heart failure with preserved ejection fraction |
title_full | Identification of distinct phenotypic clusters in heart failure with preserved ejection fraction |
title_fullStr | Identification of distinct phenotypic clusters in heart failure with preserved ejection fraction |
title_full_unstemmed | Identification of distinct phenotypic clusters in heart failure with preserved ejection fraction |
title_short | Identification of distinct phenotypic clusters in heart failure with preserved ejection fraction |
title_sort | identification of distinct phenotypic clusters in heart failure with preserved ejection fraction |
topic | HFpEF AND MACHINE LEARNING |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8359985/ https://www.ncbi.nlm.nih.gov/pubmed/33779119 http://dx.doi.org/10.1002/ejhf.2169 |
work_keys_str_mv | AT uijlalicia identificationofdistinctphenotypicclustersinheartfailurewithpreservedejectionfraction AT savaresegianluigi identificationofdistinctphenotypicclustersinheartfailurewithpreservedejectionfraction AT vaartjesilonca identificationofdistinctphenotypicclustersinheartfailurewithpreservedejectionfraction AT dahlstromulf identificationofdistinctphenotypicclustersinheartfailurewithpreservedejectionfraction AT brugtsjasperj identificationofdistinctphenotypicclustersinheartfailurewithpreservedejectionfraction AT linssengerardcm identificationofdistinctphenotypicclustersinheartfailurewithpreservedejectionfraction AT vanempelvanessa identificationofdistinctphenotypicclustersinheartfailurewithpreservedejectionfraction AT brunnerlaroccahanspeter identificationofdistinctphenotypicclustersinheartfailurewithpreservedejectionfraction AT asselbergsfolkertw identificationofdistinctphenotypicclustersinheartfailurewithpreservedejectionfraction AT lundlarsh identificationofdistinctphenotypicclustersinheartfailurewithpreservedejectionfraction AT hoesarnow identificationofdistinctphenotypicclustersinheartfailurewithpreservedejectionfraction AT koudstaalstefan identificationofdistinctphenotypicclustersinheartfailurewithpreservedejectionfraction |