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

Background: The 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.Methods: Consecutive 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.Results: Of 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 (= 0.73). 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.Conclusions: In 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

Mobile health solutions for atrial fibrillation detection and management: a systematic review

AimWe aimed to systematically review the available literature on mobile Health (mHealth) solutions, including handheld and wearable devices, implantable loop recorders (ILRs), as well as mobile platforms and support systems in atrial fibrillation (AF) detection and management.MethodsThis systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. The electronic databases PubMed (NCBI), Embase (Ovid), and Cochrane were searched for articles published until 10 February 2021, inclusive. Given that the included studies varied widely in their design, interventions, comparators, and outcomes, no synthesis was undertaken, and we undertook a narrative review.ResultsWe found 208 studies, which were deemed potentially relevant. Of these studies included, 82, 46, and 49 studies aimed at validating handheld devices, wearables, and ILRs for AF detection and/or management, respectively, while 34 studies assessed mobile platforms/support systems. The diagnostic accuracy of mHealth solutions differs with respect to the type (handheld devices vs wearables vs ILRs) and technology used (electrocardiography vs photoplethysmography), as well as application setting (intermittent vs continuous, spot vs longitudinal assessment), and study population.ConclusionWhile the use of mHealth solutions in the detection and management of AF is becoming increasingly popular, its clinical implications merit further investigation and several barriers to widespread mHealth adaption in healthcare systems need to be overcome

Does gut microbiota affect atrial rhythm? Causalities and speculations

Dietary intake has been shown to change the composition of gut microbiota and some changes in microbiota (dysbiosis) have been linked to diabetes, hypertension, and obesity, which are established risk factors for atrial fibrillation (AF). In addition, intestinal dysbiosis generates microbiota-derived bioactive metabolites that might exert proarrhythmic actions. Although emerging preclinical investigations and clinical observational cohort studies suggest a possible role of gut dysbiosis in AF promotion, the exact mechanisms through which dysbiosis contributes to AF remain unclear. This Viewpoint article briefly reviews evidence suggesting that abnormalities in the intestinal microbiota play an important and little-recognized role in the pathophysiology of AF and that an improved understanding of this role may open up new possibilities in the management of AF

Does gut microbiota affect atrial rhythm? Causalities and speculations

Dietary intake has been shown to change the composition of gut microbiota and some changes in microbiota (dysbiosis) have been linked to diabetes, hypertension, and obesity, which are established risk factors for atrial fibrillation (AF). In addition, intestinal dysbiosis generates microbiota-derived bioactive metabolites that might exert proarrhythmic actions. Although emerging preclinical investigations and clinical observational cohort studies suggest a possible role of gut dysbiosis in AF promotion, the exact mechanisms through which dysbiosis contributes to AF remain unclear. This Viewpoint article briefly reviews evidence suggesting that abnormalities in the intestinal microbiota play an important and little-recognized role in the pathophysiology of AF and that an improved understanding of this role may open up new possibilities in the management of AF

Atrial fibrillation: epidemiology, screening and digital health.

Atrial fibrillation (AF) is highly prevalent with a lifetime risk of about 1 in 3-5 individuals after the age of 45 years. Between 2010 and 2019, the global prevalence of AF has risen markedly from 33.5 million to 59 million individuals living with AF. Early detection of AF and implementation of appropriate treatment could reduce the frequency of complications associated with AF. International AF management guidelines recommend opportunistic and systematic screening for AF, but additional data are needed. Digital approaches and pathways have been proposed for early detection and for the transition to early AF management. Mobile health (mHealth) devices provide an opportunity for digital screening and should be part of novel models of care delivery based on integrated AF care pathways. For a broad implementation of mHealth-based, integrated care for patients with chronic diseases as AF, further high quality evidence is necessary. In this review, we present an overview of the present data on epidemiology, screening techniques, and the contribution of digital health solutions to the integrated management of AF. We also provide a systemic review on current data of digital and integrated AF management

Adiposity-associated atrial fibrillation: molecular determinants, mechanisms, and clinical significance

Obesity is an important contributing factor to the pathophysiology of atrial fibrillation (AF) and its complications by causing systemic changes, such as altered haemodynamic, increased sympathetic tone, and low-grade chronic inflammatory state. In addition, adipose tissue is a metabolically active organ that comprises various types of fat deposits with discrete composition and localization that show distinct functions. Fatty tissue differentially affects the evolution of AF, with highly secretory active visceral fat surrounding the heart generally having a more potent influence than the rather inert subcutaneous fat. A variety of proinflammatory, profibrotic, and vasoconstrictive mediators are secreted by adipose tissue, particularly originating from cardiac fat, that promote atrial remodelling and increase the susceptibility to AF. In this review, we address the role of obesity-related factors and in particular specific adipose tissue depots in driving AF risk. We discuss the distinct effects of key secreted adipokines from different adipose tissue depots and their participation in cardiac remodelling. The possible mechanistic basis and molecular determinants of adiposity-related AF are discussed, and finally, we highlight important gaps in current knowledge, areas requiring future investigation, and implications for clinical management