Simplification of a registry-based algorithm for ejection fraction prediction in heart failure patients: Applicability in cardiology centres of the Netherlands
A simple algorithm based on routine clinical characteristics can help discern HF phenotypes in non-cardiology datasets and research settings such as research on primary care data, where measurements of EF is often not available.
Authors
- Elisa Dal Canto (ORCID: https://orcid.org/0000-0001-8999-9946)
- Igor I. Tulevski (ORCID: https://orcid.org/0000-0002-8507-1531)
- Pim van der Harst (ORCID: https://orcid.org/0000-0002-2713-686X)
- G. Aernout Somsen (ORCID: https://orcid.org/0000-0001-5690-4429)
- Folkert W. Asselbergs (ORCID: https://orcid.org/0000-0002-1692-8669)
- N. Charlotte Onland‐Moret (ORCID: https://orcid.org/0000-0002-2360-913X)
- Leonard Hofstra (ORCID: https://orcid.org/0000-0003-4432-4720)
- Sophie H. Bots (ORCID: https://orcid.org/0000-0002-4483-5582)
- Alicia Uijl (ORCID: https://orcid.org/0000-0003-2835-7741)
- Hester M. den Ruijter (ORCID: https://orcid.org/0000-0001-9762-014X)
Institutions
- Utrecht University (NL)
- Karolinska Institutet (SE)
- University Medical Center Utrecht (NL)
- University of Amsterdam (NL)
Publication Details
- Journal
- PLoS ONE
- Published
- 2024-11-05
- DOI
- https://doi.org/10.1371/journal.pone.0310023
- Citations
- 1
- Primary Topic
- Heart Failure Treatment and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.40
Funders
- Dutch Cardiovascular Alliance
- Fondation Leducq