Mobile app-based symptom-rhythm correlation assessment in patients with persistent atrial fibrillation

Abstract

BackgroundThe assessment of symptom-rhythm correlation (SRC) in patients with persistent atrial fibrillation (AF) is challenging. Therefore, we performed a novel mobile app-based approach to assess SRC in persistent AF. MethodsConsecutive persistent AF patients planned for electrical cardioversion (ECV) used a mobile app to record a 60-s photoplethysmogram (PPG) and report symptoms once daily and in case of symptoms for four weeks prior and three weeks after ECV. Within each patient, SRC was quantified by the SRC-index defined as the sum of symptomatic AF recordings and asymptomatic non-AF recordings divided by the sum of all recordings. ResultsOf 88 patients (33% women, age 68 ± 9 years) included, 78% reported any symptoms during recordings. The overall SRC-index was 0.61 (0.44–0.79). The study population was divided into SRC-index tertiles: low (<0.47), medium (0.47–0.73) and high (≥0.73). Patients within the low (vs high) SRC-index tertile had more often heart failure and diabetes mellitus (both 24.1% vs 6.9%). Extrasystoles occurred in 19% of all symptomatic non-AF PPG recordings. Within each patient, PPG recordings with the highest (vs lowest) tertile of pulse rates conferred an increased risk for symptomatic AF recordings (odds ratio [OR] 1.26, 95% coincidence interval [CI] 1.04–1.52) and symptomatic non-AF recordings (OR 2.93, 95% CI 2.16–3.97). Pulse variability was not associated with reported symptoms. ConclusionsIn patients with persistent AF, SRC is relatively low. Pulse rate is the main determinant of reported symptoms. Further studies are required to verify whether integrating mobile app-based SRC assessment in current workflows can improve AF management.