Evidence map›Paper›PMID 38780153›Full record

ArticleJournal of the American Heart Association2024

Ten-Year Risk Equations for Incident Heart Failure in Established Atherosclerotic Cardiovascular Disease Populations.

Luke P Dawson, Melinda J Carrington, Tilahun Haregu, Shane Nanayakkara, Garry Jennings, Anthony Dart, Dion Stub, Michael Inouye, David Kaye

Abstract readValidation Study
In one paragraph

Article in Journal of the American Heart Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. A Genetic Test to Identify People at High Risk of Heart Failure.International journal of molecular sciences · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Luke P DawsonDepartment of Cardiology The Alfred Hospital Melbourne Victoria Australia.ORCID 0000-0003-3789-5808
Melinda J CarringtonBaker Heart and Diabetes Institute Melbourne Victoria Australia.ORCID 0000-0003-3865-1645
Tilahun HareguDepartment of Cardiology The Alfred Hospital Melbourne Victoria Australia.ORCID 0000-0002-8797-0469
Shane NanayakkaraDepartment of Cardiology The Alfred Hospital Melbourne Victoria Australia.ORCID 0000-0002-0146-6588
Garry JenningsDepartment of Cardiology The Alfred Hospital Melbourne Victoria Australia.ORCID 0000-0002-7865-5483
Anthony DartDepartment of Cardiology The Alfred Hospital Melbourne Victoria Australia.ORCID 0000-0003-1360-3778
Dion StubDepartment of Cardiology The Alfred Hospital Melbourne Victoria Australia.ORCID 0000-0001-8686-2709
Michael InouyeBaker Heart and Diabetes Institute Melbourne Victoria Australia.ORCID 0000-0001-9413-6520
David KayeDepartment of Cardiology The Alfred Hospital Melbourne Victoria Australia.ORCID 0000-0003-4058-0372

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTen-year risk equations for incident heart failure (HF) are available for the general population, but not for patients with established atherosclerotic cardiovascular disease (ASCVD), which is highly prevalent in HF cohorts. This study aimed to develop and validate 10-year risk equations for incident HF in patients with known ASCVD. METHODS AND

resultsTen-year risk equations for incident HF were developed using the United Kingdom Biobank cohort (recruitment 2006-2010) including participants with established ASCVD but free from HF at baseline. Model performance was validated using the Australian Baker Heart and Diabetes Institute Biobank cohort (recruitment 2000-2011) and compared with the performance of general population risk models. Incident HF occurred in 13.7% of the development cohort (n=31 446, median 63 years, 35% women, follow-up 10.7±2.7 years) and in 21.3% of the validation cohort (n=1659, median age 65 years, 25% women, follow-up 9.4±3.7 years). Predictors of HF included in the sex-specific models were age, body mass index, systolic blood pressure (treated or untreated), glucose (treated or untreated), cholesterol, smoking status, QRS duration, kidney disease, myocardial infarction, and atrial fibrillation. ASCVD-HF equations had good discrimination and calibration in development and validation cohorts, with superior performance to general population risk equations.

conclusionsASCVD-specific 10-year risk equations for HF outperform general population risk models in individuals with established ASCVD. The ASCVD-HF equations can be calculated from readily available clinical data and could facilitate screening and preventative treatment decisions in this high-risk group.

Indexed as

AtherosclerosisHeart FailureAgedAustraliaFemaleHumansIncidenceMaleMiddle AgedReproducibility of ResultsRisk AssessmentRisk FactorsTime FactorsUnited Kingdomatherosclerotic cardiovascular diseaseheart failurepredictionrisk equations

Identifiers

PMID38780153
PMCPMC11255645

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.