Clinical, biomarker, and genetic predictors of specific types of atrial fibrillation in a community-based cohort: data of the PREVEND study

Aggressive Rhythm Control Strategy in Atrial Fibrillation Patients Presenting at the Emergency Department: The HEROMEDICUS Study Design and Initial Results

Atrial fibrillation has progressively become a more common reason for emergency department visits, representing 0.5% of presenting reasons. Registry data have indicated that about 60% of atrial fibrillation patients who present to the emergency department are admitted, emphasizing the need for more efficient management of atrial fibrillation in the acute phase. Management of atrial fibrillation in the setting of the emergency department varies between countries and healthcare systems. The most plausible reason to justify a conservative rather than an aggressive strategy in the management of atrial fibrillation is the absence of specific guidelines from diverse societies. Several trials of atrial fibrillation treatment strategies, including cardioversion, have demonstrated that atrial fibrillation in the emergency department can be treated safely and effectively, avoiding admission. In the present study, we present the epidemiology and characteristics of atrial fibrillation patients presenting to the emergency department, as well as the impact of diverse management strategies on atrial-fibrillation-related hospital admissions. Lastly, the design and initial data of the HEROMEDICUS protocol will be presented, which constitutes an electrophysiology-based aggressive rhythm control strategy in patients with atrial fibrillation in the emergency department setting.

Impact of atrial fibrillation on 1-year outcome in patients with implantable cardioverter defibrillator or cardiac resynchronization therapy with defibrillator: results from the German DEVICE Registry

Background

Atrial fibrillation (AF) is a cardiac arrhythmia frequently documented in patients requiring implantable cardioverter defibrillators (ICDs) and/or cardiac resynchronization therapy with defibrillator (CRT-D). Patients with diagnosed AF at the point of ICD or CRT-D implantation may have an impaired follow-up outcome.

Methods

The German DEVICE I-II registry is a nationwide prospective multicentre database of patients implanted with ICD and CRT-D with clinical follow-up data. We analysed a 1-year follow up of implanted patients with AF and with sinus rhythm (SR).

Results

A total of 4,929 ICD/CRT patients are included in the present analysis: 946 (19.2%) were in AF and 3,983 (80.8%) were SR at time of device implantation. AF patients had a significantly more comorbid profile including older age {72 [interquartile range (IQR), 66-77] vs. 66 (IQR, 56-73) years; P<0.001}, and higher rate of patients with left ventricular ejection fraction <30% (68.2% vs. 61.0%; P<0.001), peripheral artery disease (4.5% vs. 2.7%; P=0.002), diabetes (33.6% vs. 25.5%; P<0.001), hypertension (58.4% vs. 51.1%; P<0.001) and renal failure (22.6% vs. 15.3%; P<0.001). The intra-hospital complication rate was 4.3% in the AF and 3.6% in the SR group (P=0.38). In 1-year follow-up AF patients experienced a significantly higher rate of defibrillator shocks (25% vs. 15.3%; P<0.001). One-year estimated mortality was 10.8% in the AF and 5.9% in the SR group (P<0.001), while estimated 1-year major adverse cardiac and cerebrovascular events (MACCE) rate was 11.2% vs. 7.0% (P<0.001). The effects of AF on electrical shocks and mortality persisted after adjusting for age, sex, advanced New York Heart Association (NYHA) class, severely impaired left ventricular ejection fraction (LVEF), coronary artery disease (CAD), chronic obstructive pulmonary disease (COPD), diabetes mellitus (DM), chronic renal failure (CRF), QRS duration, and type of indication for electronic device implantation.

Conclusions

Our clinical data on an extended cohort of contemporary patients confirm the significant impact of AF, and its associated comorbidities, upon mortality and major adverse events after implantation of ICD/CRT.

Atrial fibrillation patterns and their cardiovascular risk profiles in the general population: the Rotterdam study

BACKGROUND

Clinical guidelines categorize atrial fibrillation (AF) based on the temporality of AF events. Due to its dependence on event duration, this classification is not applicable to population-based cohort settings. We aimed to develop a simple and standardized method to classify AF patterns at population level. Additionally, we compared the longitudinal trajectories of cardiovascular risk factors preceding the AF patterns, and between men and women.

METHODS

Between 1990 and 2014, participants from the population-based Rotterdam study were followed for AF status, and categorized into 'single-documented AF episode', 'multiple-documented AF episodes', or 'long-standing persistent AF'. Using repeated measurements we created linear mixed-effects models to assess the longitudinal evolution of risk factors prior to AF diagnosis.

RESULTS

We included 14,061 participants (59.1% women, mean age 65.4 ± 10.2 years). After a median follow-up of 9.4 years (interquartile range 8.27), 1,137 (8.1%) participants were categorized as 'single-documented AF episode', 208 (1.5%) as 'multiple-documented AF episodes', and 57 (0.4%) as 'long-standing persistent AF'. In men, we found poorer trajectories of weight and waist circumference preceding 'long-standing persistent AF' as compared to the other patterns. In women, we found worse trajectories of all risk factors between 'long-standing persistent AF' and the other patterns.

CONCLUSION

We developed a standardized method to classify AF patterns in the general population. Participants categorized as 'long-standing persistent AF' showed poorer trajectories of cardiovascular risk factors prior to AF diagnosis, as compared to the other patterns. Our findings highlight sex differences in AF pathophysiology and provide insight into possible risk factors of AF patterns.

Molecular Insights in Atrial Fibrillation Pathogenesis and Therapeutics: A Narrative Review

The prevalence of atrial fibrillation (AF) is bound to increase globally in the following years, affecting the quality of life of millions of people, increasing mortality and morbidity, and beleaguering health care systems. Increasingly effective therapeutic options against AF are the constantly evolving electroanatomic substrate mapping systems of the left atrium (LA) and ablation catheter technologies. Yet, a prerequisite for better long-term success rates is the understanding of AF pathogenesis and maintenance. LA electrical and anatomical remodeling remains in the epicenter of current research for novel diagnostic and treatment modalities. On a molecular level, electrical remodeling lies on impaired calcium handling, enhanced inwardly rectifying potassium currents, and gap junction perturbations. In addition, a wide array of profibrotic stimuli activates fibroblast to an increased extracellular matrix turnover via various intermediaries. Concomitant dysregulation of the autonomic nervous system and the humoral function of increased epicardial adipose tissue (EAT) are established mediators in the pathophysiology of AF. Local atrial lymphomononuclear cells infiltrate and increased inflammasome activity accelerate and perpetuate arrhythmia substrate. Finally, impaired intracellular protein metabolism, excessive oxidative stress, and mitochondrial dysfunction deplete atrial cardiomyocyte ATP and promote arrhythmogenesis. These overlapping cellular and molecular alterations hinder us from distinguishing the cause from the effect in AF pathogenesis. Yet, a plethora of therapeutic modalities target these molecular perturbations and hold promise in combating the AF burden. Namely, atrial selective ion channel inhibitors, AF gene therapy, anti-fibrotic agents, AF drug repurposing, immunomodulators, and indirect cardiac neuromodulation are discussed here.

A Review on the State of the Art in Atrial Fibrillation Detection Enabled by Machine Learning

Atrial Fibrillation (AF) the most commonly occurring type of cardiac arrhythmia is one of the main causes of morbidity and mortality worldwide. The timely diagnosis of AF is an equally important and challenging task because of its asymptomatic and episodic nature. In this paper, state-of-the-art ECG data-based machine learning models and signal processing techniques applied for auto diagnosis of AF are reviewed. Moreover, key biomarkers of AF on ECG and the common methods and equipment used for the collection of ECG data are discussed. Besides that, the modern wearable and implantable ECG sensing technologies used for gathering AF data are presented briefly. In the end, key challenges associated with the development of auto diagnosis solutions of AF are also highlighted. This is the first review paper of its kind that comprehensively presents a discussion on all these aspects related to AF auto-diagnosis in one place. It is observed that there is a dire need for low energy and low cost but accurate auto diagnosis solutions for the proactive management of AF.

Atrial fibrillation: A review of modifiable risk factors and preventive strategies

Atrial fibrillation (AF), as the most common cardiac arrhythmia worldwide, is associated with increased mortality and morbidity. Successful therapeutic strategies have been introduced so far, but they are associated with significant costs. Therefore, identification of modifiable risk factors of AF and the development of appropriate preventive strategies may play a substantial role in promoting community health and reducing health care system costs. Modifiable cardiovascular risk factors including obesity, hypertension, diabetes mellitus, obstructive sleep apnea, alcohol consumption, smoking, and sedentary lifestyles have been proposed as possible contributors to the development and progression of AF. In this review, we discuss the role of modifiable risk factors in the development and management of AF and the evidence for the underlying mechanism for each of the potential risk factor.

Sleep Disorders and Atrial Fibrillation: Current Situation and Future Directions

Atrial fibrillation (AF) is a growing health problem worldwide. In recent years, there has been a rising interest in the relationship between sleep disorders and AF. Several studies have reported higher prevalence and incidence rates of AF in patients with obstructive sleep apnea-hypopnea syndrome (OSAHS). However, some believe that OSAHS is not a risk factor for AF; but AF, by itself, is regarded as one of the possible triggers for OSAHS. In this study, the related literature investigating the association between OSAHS and AF was reviewed, and then the possible mechanisms of this interplay were discussed. To conclude, recommendations for further research in this field were presented to researchers and some points were highlighted for physicians.