Predicting survival in heart failure : a risk score based on 39 372 patients from 30 studies
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Authors
Pocock, Stuart J.
Ariti, Cono A.
McMurray, John J.V.
Maggioni, A.P.
Køber, Lars
Squire, I.B.
Swedberg, Karl
Dobson, Joanna
Poppe, K.K.
Whalley, Gillian
Doughty, Robert N.
Ariti, Cono A.
McMurray, John J.V.
Maggioni, A.P.
Køber, Lars
Squire, I.B.
Swedberg, Karl
Dobson, Joanna
Poppe, K.K.
Whalley, Gillian
Doughty, Robert N.
Author ORCID Profiles (clickable)
Degree
Grantor
Date
2012-10-24
Supervisors
Type
Journal Article
Ngā Upoko Tukutuku (Māori subject headings)
Keyword
heart failure
meta-analysis
prognostic model
mortality
meta-analysis
prognostic model
mortality
ANZSRC Field of Research Code (2020)
Citation
Pocock, S.J. (2012) Predicting survival in heart failure : a risk score based on 39 372 patients from 30 studies. European Heart Journal 24 Ocotober 2012
Abstract
Aims: Using a large international database from multiple cohort studies, the aim is to create a generalizable easily used risk score for mortality in patients with heart failure (HF). Methods and results: Using a large international database from multiple cohort studies, the aim is to create a generalizable easily used risk score for mortality in patients with heart failure (HF). In patients with HF of both reduced and preserved EF, the influences of readily available predictors of mortality can be quantified in an integer score accessible by an easy-to-use website www.heartfailurerisk.org. The score has the potential for widespread implementation in a clinical setting
Publisher
Oxford University Press
Permanent link
Link to ePress publication
DOI
doi:10.1093/eurheartj/ehs337
Copyright holder
Oxford University Press
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