Evidence map›Paper›PMID 40528830›Full record

ArticleESC heart failure2025

Identification, characterisation and outcomes of pre-atrial fibrillation in heart failure with reduced ejection fraction.

Anna Helbitz, Ramesh Nadarajah, Lan Mu, Harriet Larvin, Hesham Ismail, Ali Wahab, Patrick Thompson, Peter Harrison, Mohammad Harris, Tobin Joseph and 6 more

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in ESC heart failure, 2025. 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. Article
  2. Article
  3. Article
  4. 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

16 authors.

Anna HelbitzFaculty of Medicine and Health, University of Leeds, Leeds, UK.ORCID https://orcid.org/0009-0000-8783-6617
Ramesh NadarajahLeeds Institute of Data Analytics, University of Leeds, Leeds, UK.ORCID https://orcid.org/0000-0001-9895-9356
Lan MuWolfson Institute of Population Health, Queen Mary, University of London, London, UK.
Harriet LarvinWolfson Institute of Population Health, Queen Mary, University of London, London, UK.
Hesham IsmailDepartment of Cardiology, Leeds Teaching Hospitals NHS Trust, Leeds, UK.
Ali WahabLeeds Institute of Data Analytics, University of Leeds, Leeds, UK.
Patrick ThompsonLeeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK.
Peter HarrisonLeeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK.
Mohammad HarrisLeeds Institute of Data Analytics, University of Leeds, Leeds, UK.
Tobin JosephLeeds Institute of Data Analytics, University of Leeds, Leeds, UK.
Sven PleinLeeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK.
Mark PetrieInstitute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.
Marco MetraInstitute of Cardiology, ASST Spedali Civili di Brescia and Department of Medical and Surgical Specialties, Radiological Sciences, and Public Health, University of Brescia, Brescia, Italy.
Jianhua WuWolfson Institute of Population Health, Queen Mary, University of London, London, UK.
Peter SwobodaDepartment of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK.
Chris P GaleLeeds Institute of Data Analytics, University of Leeds, Leeds, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsAtrial fibrillation (AF) in heart failure with reduced ejection fraction (HFrEF) has prognostic implications. Using a machine learning algorithm (FIND-AF), we aimed to explore clinical events and the cardiac magnetic resonance (CMR) characteristics of the pre-AF phenotype in HFrEF. METHODS AND

resultsA cohort of individuals aged ≥18 years with HFrEF without AF from the MATCH 1 and MATCH 2 studies (2018-2024) stratified by FIND-AF score. All received cardiac magnetic resonance using Cvi42 software for volumetric and T1/T2. The primary outcome was time to a composite of MACE inclusive of heart failure hospitalisation, myocardial infarction, stroke and all-cause mortality. Secondary outcomes included the association between CMR findings and FIND-AF score. Of 385 patients [mean age 61.7 (12.6) years, 39.0% women] with a median 2.5 years follow-up, the primary outcome occurred in 58 (30.2%) patients in the high FIND-AF risk group and 23 (11.9%) in the low FIND-AF risk group (hazard ratio 3.25, 95% CI 2.00-5.28, P < 0.001). Higher FIND-AF score was associated with higher indexed left ventricular mass (β = 4.7, 95% CI 0.5-8.9), indexed left atrial volume (β = 5.9, 95% CI 2.2-9.6), higher indexed left ventricular end-diastolic volume (β = 9.55, 95% CI 1.37-17.74, P = 0.022), native T1 signal (β = 18.0, 95% CI 7.0-29.1) and extracellular volume (β = 1.6, 95% CI 0.6-2.5).

conclusionsA pre-AF HFrEF subgroup with distinct CMR characteristics and poor prognosis may be identified, potentially guiding interventions to reduce clinical events.

Indexed as

Atrial FibrillationHeart FailureStroke VolumeVentricular Function, LeftAgedFemaleFollow-Up StudiesHumansMagnetic Resonance Imaging, CineMaleMiddle AgedPrognosisRetrospective StudiesAtrial fibrillationCardiovascular magnetic resonanceHeart failureMortalityPrediction

Identifiers

PMID40528830
PMCPMC12450782

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.