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.

Coronavirus disease 2019 (COVID-19) is a novel, highly transmittable and severe strain disease, which has rapidly spread worldwide. Despite epidemiological evidence linking COVID-19 with cardiovascular diseases, little is known about whether and how COVID-19 influences atrial fibrillation (AF), the most prevalent arrhythmia in clinical practice. Here, we review the available evidence for prevalence and incidence of AF in patients infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and discuss disease management approaches and potential treatment options for COVID-19 infected AF patients.

Recent preclinical and observational cohort studies have implicated imbalances in gut microbiota composition as a contributor to atrial fibrillation (AF). The gut microbiota is a complex and dynamic ecosystem containing trillions of microorganisms, which produces bioactive metabolites influencing host health and disease development. In addition to host-specific determinants, lifestyle-related factors such as diet and drugs are important determinants of the gut microbiota composition. In this review, we discuss the evidence suggesting a potential bidirectional association between AF and gut microbiota, identifying gut microbiota-derived metabolites as possible regulators of the AF substrate. We summarize the effect of gut microbiota on the development and progression of AF risk factors, including heart failure, hypertension, obesity, and coronary artery disease. We also discuss the potential anti-arrhythmic effects of pharmacological and diet-induced modifications of gut microbiota composition, which may modulate and prevent the progression to AF. Finally, we highlight important gaps in knowledge and areas requiring future investigation. Although data supporting a direct relationship between gut microbiota and AF are very limited at the present time, emerging preclinical and clinical research dealing with mechanistic interactions between gut microbiota and AF is important as it may lead to new insights into AF pathophysiology and the discovery of novel therapeutic targets for AF.

Aims: TeleCheck-AF is a multicentre international project initiated to maintain care delivery for patients with atrial fibrillation (AF) during COVID-19 through teleconsultations supported by an on-demand photoplethysmography-based heart rate and rhythm monitoring app (FibriCheck®). We describe the characteristics, inclusion rates, and experiences from participating centres according the TeleCheck-AF infrastructure as well as characteristics and experiences from recruited patients. Methods and results: Three surveys exploring centre characteristics (n = 25), centre experiences (n = 23), and patient experiences (n = 826) were completed. Self-reported patient characteristics were obtained from the app. Most centres were academic (64%) and specialized public cardiology/district hospitals (36%). Majority of the centres had AF outpatient clinics (64%) and only 36% had AF ablation clinics. The time required to start patient inclusion and total number of included patients in the project was comparable for centres experienced (56%) or inexperienced in mHealth use. Within 28 weeks, 1930 AF patients were recruited, mainly for remote AF control (31% of patients) and AF ablation follow-up (42%). Average inclusion rate was highest during the lockdown restrictions and reached a steady state at a lower level after easing the restrictions (188 vs. 52 weekly recruited patients). Majority (>80%) of the centres reported no problems during the implementation of the TeleCheck-AF approach. Recruited patients [median age 64 (55–71), 62% male] agreed that the FibriCheck® app was easy to use (94%). Conclusion: Despite different health care settings and mobile health experiences, the TeleCheck-AF approach could be set up within an extremely short time and easily used in different European centres during COVID-19.

Objective: We aimed to identify predictors of left atrial appendage (LAA) thrombus in patients with atrial fibrillation (AF) and to enhance the prognostic value of the CHA₂DS₂-VASc score.Methods: Derivation cohort included 1033 consecutive AF patients referred for catheter ablation or direct current cardioversion, in whom transoesophageal echocardiography (TOE) was performed prior to the procedure. Logistic regression analysis was used to identify predictors of LAA thrombus on TOE. Receiver operating characteristic (ROC) curves were constructed to compare the newly developed score with the CHA₂DS₂and CHA₂DS₂-VASc scores in the derivation and the validation (n=320) cohort.Results: On TOE, LAA thrombus was present in 59 (5.7%) patients in the derivation cohort. Aside from variables encompassed by the CHA₂DS₂-VASc score, LAA thrombus predictors included AF type (persistent/’permanent’ vs paroxysmal) and renal dysfunction. These predictors were incorporated into the CHA₂DS₂-VASc score. In ROC analysis, area under the curve (AUC) for the new score (CHA₂DS₂-VASc-RAF score) was significantly higher (0.81) than those for the CHA₂DS₂and CHA₂DS₂-VASc scores (0.71 and 0.70, respectively). In the validation cohort, the CHA₂DS₂-VASc-RAF score also performed significantly better (AUC of 0.88) than the CHA₂DS₂and CHA₂DS₂-VASc scores (AUC of 0.63 and 0.60, respectively).Conclusion: In real-world AF patients with majority on oral anticoagulation, LAA thrombus was found in approximately 6%. Two variables not included in the CHA₂DS₂-VASc score (AF type and renal dysfunction) proved strong, independent predictors of LAA thrombus and might improve thromboembolic risk stratification.

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.