Identification, Characterisation and Outcomes of Pre-Atrial Fibrillation in Heart Failure with Reduced Ejection Fraction

A Helbitz; Ramesh Nadarajah; Lan Mu; Harriet Larvin; Hesham Ismail; Ali Wahab; Peter Harrison; Mohammad Harris; Tobin Joseph; Sven Plein; Mark C. Petrie; Marco Metra; Jianhua Wu; Peter Swoboda; Chris P Gale

doi:10.1002/ehf2.15347

June 18, 2025ESC Heart FailureOpen Access

Identification, Characterisation and Outcomes of Pre-Atrial Fibrillation in Heart Failure with Reduced Ejection Fraction

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Why the study?

AF in HFrEF has prognostic implications, but clinical events and CMR characteristics of the pre-AF phenotype identified by the FIND-AF machine learning algorithm were not well defined.

Does a high FIND-AF risk score predict a composite of MACE in adults with HFrEF without atrial fibrillation?

Structured PICO

Does a high FIND-AF risk score predict a composite of MACE in adults with HFrEF without atrial fibrillation?

P

Population

385 adults (aged ≥18 years) with heart failure with reduced ejection fraction (HFrEF) without atrial fibrillation from the MATCH 1 and MATCH 2 studies, mean age 61.7, 39.0% women.

I

Intervention

High risk score on the FIND-AF machine learning algorithm

C

Comparator

Low risk score on the FIND-AF machine learning algorithm

O

Outcome

Time to a composite of MACE inclusive of heart failure hospitalisation, myocardial infarction, stroke and all-cause mortalitycomposite

Implication

A machine learning algorithm (FIND-AF) can identify a pre-atrial fibrillation phenotype in HFrEF patients that is associated with distinct adverse CMR characteristics and a significantly higher risk of major adverse cardiovascular events.

Abstract

AIMS: Atrial 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 RESULTS: A 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). CONCLUSIONS: A pre-AF HFrEF subgroup with distinct CMR characteristics and poor prognosis may be identified, potentially guiding interventions to reduce clinical events.