Prediction of AF in Heart Failure With Preserved Ejection Fraction: Incremental Value of Left Atrial Strain

This study sought to identify the factors associated with incident atrial fibrillation (AF) in a well-characterized heart failure with preserved ejection fraction (HFpEF) population, with special focus on left atrial (LA) strain.

AF is associated with HFpEF, with adverse consequences. Effective risk evaluation might allow the initiation of protective strategies.

Clinical evaluation and echocardiography, including measurements of peak atrial longitudinal strain (PALS), peak atrial contraction strain (PACS), and LA volume index (LAVI), were obtained in 170 patients with symptomatic HFpEF (mean age, 65 ± 8 years), free of baseline AF. AF was identified by standard 12-lead electrocardiogram, review of relevant medical records (including Holter documentation), and surveillance with a portable single-lead electrocardiogram device over 2 weeks. Results were validated in the 103 patients with HFpEF from the Karolinska-Rennes (KaRen) study.

Over a median follow-up of 49 months, incident AF was identified in 39 patients (23%). Patients who developed AF were older; had higher clinical risk scores, brain natriuretic peptide, creatinine, LAVI, and LV mass; lower LA strain and exercise capacity; and more impaired LV diastolic function. PACS, PALS, and LAVI were the most predictive parameters for AF (area under receiver-operating characteristic curve: 0.76 for PACS, 0.71 for PALS, and 0.72 for LAVI). Nested Cox regression models showed that the predictive value of PACS and PALS was independent from and incremental to clinical data, LAVI, and E/e' ratio. Classification and regression trees analysis identified PACS ≤12.7%, PALS ≤29.4%, and LAVI >34.3 ml/m² as discriminatory nodes for AF, with a 33-fold greater hazard of AF (p < 0.001) in patients categorized as high risk. The classification and regression trees algorithm discriminated high and low AF risk in the validation cohort.

PACS and PALS provide incremental predictive information about incident AF in HFpEF. The inclusion of these LA strain components to the diagnostic algorithm may help guide screening and further monitoring for AF risk in this population.