Silent atrial fibrillation: epidemiology, diagnosis, and clinical impact

Factors Affecting Late Atrial Fibrillation and Its Association With Coronary Artery Bypass Outcomes

BACKGROUND

Although predictors and outcomes of postoperative atrial fibrillation (POAF) are well studied, evidence is lacking concerning postdischarge late/recurrent atrial fibrillation (AF). This study evaluated factors affecting late/recurrent AF and its association with coronary artery bypass grafting (CABG) outcomes in a real-world setting.

METHODS

From 2012 through 2016, 5175 patients were included. Independent factors associated with late/recurrent AF were identified in a competing risk setting. Cox proportional hazard regression was used to evaluate the association between late/recurrent AF and study outcomes, consisting of all-cause mortality, major adverse cardio-cerebrovascular events, acute coronary syndrome, cerebrovascular events, and heart failure admissions.

RESULTS

During a median follow-up of 60 months (quartile 1-quartile 3, 59.3-60.7 months), late/recurrent AF developed in 85 patients (1.64%). Independent factors associated with late/recurrent AF were age (subdistribution hazard ratio [sHR], 1.04; 95% CI, 1.02-1.07), left-ventricular ejection fraction (sHR, 0.97; 95% CI, 0.95-0.99), length of stay (sHR, 1.02; 95% CI, 1.01-1.04), and POAF (sHR, 4.02; 95% CI, 2.50-6.45). Late/recurrent AF was not significantly associated with all-cause mortality and major adverse cardio-cerebrovascular events at unadjusted or adjusted levels (adjusted hazard ratio, 0.80 [95% CI, 0.50-1.28] and 0.74 [95% CI, 0.48-1.13], respectively). Nevertheless, it significantly increased the unadjusted risk of cerebrovascular events (hazard ratio, 2.28; 95% CI, 01.07-4.87), which disappeared after adjustments.

CONCLUSIONS

Patients with advanced age, a lower left-ventricular ejection fraction, and POAF are more likely to have late/recurrent clinical AF. Albeit counterintuitive, late/recurrent AF was not independently associated with worse midterm post-CABG outcomes. These observations need to be further elucidated in larger-scale studies and interpreted in the context of a developing country with limited resources for late AF surveillance.

Cardiac Blood-Based Biomarkers of Myocardial Stress as Predictors of Atrial Fibrillation Development in Patients With Embolic Stroke of Undetermined Source/Cryptogenic Stroke: A Systematic Review and Meta-Analysis

BACKGROUND AND PURPOSE

Undiagnosed atrial fibrillation (AF) is a major risk factor for stroke that can go unnoticed in individuals with embolic stroke of undetermined source (ESUS) or cryptogenic stroke (CS). Early detection is critical for stroke prognosis and secondary prevention. This study aimed to determine if blood biomarkers of myocardial stress can accurately predict AF in patients with ESUS/CS, which would allow the identification of those who would benefit from closer monitoring.

METHODS

In February 2023 we performed a systematic date-unrestricted search of three databases for studies on patients with ESUS/CS who were subsequently diagnosed with AF. We examined the relationships between AF and serum myocardial stress markers such as brain natriuretic peptide (BNP), N-terminal-pro-BNP (NT-proBNP), midregional proatrial natriuretic peptide, and troponin.

RESULTS

Among the 1,527 studies reviewed, 23 eligible studies involving 6,212 participants, including 864 with AF, were analyzed. A meta-analysis of 9 studies indicated that they demonstrated a clear association between higher NT-proBNP levels and an increased risk of AF, with adjusted and raw data indicating 3.06- and 9.03-fold higher AF risks, respectively. Lower NT-proBNP levels had a pooled negative predictive value of 91.7%, indicating the potential to rule out AF with an 8% false-negative rate.

CONCLUSIONS

Further research is required to fully determine the potential of biomarkers for AF detection after stroke, as results from previous studies lack homogeneity. However, lower NT-proBNP levels have potential in ruling out AF in patients with ESUS/CS. Combining them with other relevant biomarkers may enhance the precision of identifying patients who will not benefit from extended monitoring, which would optimize resource allocation and patient care.

Deep learning evaluation of echocardiograms to identify occult atrial fibrillation

Atrial fibrillation (AF) often escapes detection, given its frequent paroxysmal and asymptomatic presentation. Deep learning of transthoracic echocardiograms (TTEs), which have structural information, could help identify occult AF. We created a two-stage deep learning algorithm using a video-based convolutional neural network model that (1) distinguished whether TTEs were in sinus rhythm or AF and then (2) predicted which of the TTEs in sinus rhythm were in patients who had experienced AF within 90 days. Our model, trained on 111,319 TTE videos, distinguished TTEs in AF from those in sinus rhythm with high accuracy in a held-out test cohort (AUC 0.96 (0.95-0.96), AUPRC 0.91 (0.90-0.92)). Among TTEs in sinus rhythm, the model predicted the presence of concurrent paroxysmal AF (AUC 0.74 (0.71-0.77), AUPRC 0.19 (0.16-0.23)). Model discrimination remained similar in an external cohort of 10,203 TTEs (AUC of 0.69 (0.67-0.70), AUPRC 0.34 (0.31-0.36)). Performance held across patients who were women (AUC 0.76 (0.72-0.81)), older than 65 years (0.73 (0.69-0.76)), or had a CHA2DS2VASc ≥2 (0.73 (0.79-0.77)). The model performed better than using clinical risk factors (AUC 0.64 (0.62-0.67)), TTE measurements (0.64 (0.62-0.67)), left atrial size (0.63 (0.62-0.64)), or CHA2DS2VASc (0.61 (0.60-0.62)). An ensemble model in a cohort subset combining the TTE model with an electrocardiogram (ECGs) deep learning model performed better than using the ECG model alone (AUC 0.81 vs. 0.79, p = 0.01). Deep learning using TTEs can predict patients with active or occult AF and could be used for opportunistic AF screening that could lead to earlier treatment.

The Cost of Atrial Fibrillation: A Systematic Review

OBJECTIVES

Atrial fibrillation (AF) is the most common cardiac arrhythmia, with an increasing incidence and prevalence because of progressively aging populations. Costs related to AF are both direct and indirect. This systematic review aims to identify the main cost drivers of the illness, assess the potential economic impact resulting from changes in care strategies, and propose interventions where they are most needed.

METHODS

A systematic literature search of the PubMed and Scopus databases was performed to identify analytical observational studies defining the cost of illness in cases of AF. The search strategy was based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 recommendations.

RESULTS

Of the 944 articles retrieved, 24 met the inclusion criteria. These studies were conducted in several countries. All studies calculated the direct medical costs, whereas 8 of 24 studies assessed indirect costs. The median annual direct medical cost per patient, considering all studies, was €9409 (13 333 US dollars in purchasing power parities), with a very large variability due to the heterogeneity of different analyses. Hospitalization costs are generally the main cost drivers. Comorbidities and complications, such as stroke, considerably increase the average annual direct medical cost of AF.

CONCLUSIONS

In most of the analyzed studies, inpatient care cost represents the main component of the mean direct medical cost per patient. Stroke and heart failure are responsible for a large share of the total costs; therefore, implementing guidelines to manage comorbidities in AF is a necessary step to improve health and mitigate healthcare costs.

Correlates and consequences of atrial fibrillation in a prospective study of 25 000 participants in the China Kadoorie Biobank

Aims

The prevalence of atrial fibrillation (AF) is positively correlated with prior cardiovascular diseases (CVD) and CVD risk factors but is lower in Chinese than Europeans despite their higher burden of CVD. We examined the prevalence and prognosis of AF and other electrocardiogram (ECG) abnormalities in the China Kadoorie Biobank.

Methods and results

A random sample of 25 239 adults (mean age 59.5 years, 62% women) had a 12-lead ECG recorded and interpreted using a Mortara VERITAS™ algorithm in 2013-14. Participants were followed up for 5 years for incident stroke, ischaemic heart disease, heart failure (HF), and all CVD, overall and by CHA2DS2-VASc scores, age, sex, and area. Overall, 1.2% had AF, 13.6% had left ventricular hypertrophy (LVH), and 28.1% had ischaemia (two-thirds of AF cases also had ischaemia or LVH). The prevalence of AF increased with age, prior CVD, and levels of CHA₂DS₂-VASc scores (0.5%, 1.3%, 2.1%, 2.9%, and 4.4% for scores <2, 2, 3, 4, and ≥5, respectively). Atrial fibrillation was associated with two-fold higher hazard ratios (HR) for CVD (2.15; 95% CI, 1.71-2.69) and stroke (1.88; 1.44-2.47) and a four-fold higher HR for HF (3.79; 2.21-6.49). The 5-year cumulative incidence of CVD was comparable for AF, prior CVD, and CHA₂DS₂-VASc scores ≥ 2 (36.7% vs. 36.2% vs. 37.7%, respectively) but was two-fold greater than for ischaemia (19.4%), LVH (18.0%), or normal ECG (14.1%), respectively.

Conclusion

The findings highlight the importance of screening for AF together with estimation of CHA₂DS₂-VASc scores for prevention of CVD in Chinese adults.

Ratio of early transmitral inflow velocity to early diastolic strain rate predicts atrial fibrillation following acute myocardial infarction

The ratio of early transmitral filling velocity to early diastolic strain rate (E/SRe) has been proposed as a new non-invasive measurement of left ventricular filling pressure. We aimed to investigate the ability of E/SRe to predict atrial fibrillation (AF) after ST-elevation myocardial infarction (STEMI). This was a prospective cohort study of patients (n = 369) with STEMI. Patients underwent an echocardiographic examination a median of two days after pPCI. By echocardiography, transmitral early filling velocity (E) was measured by pulsed-wave Doppler, and early diastolic strain rate (SRe) was measured by speckle tracking of the left ventricle. E was indexed to SRe and the early myocardial relaxation velocity (e') to obtain the E/SRe and E/e', respectively. The endpoint was new-onset AF. During follow-up (median 5.6 years, IQR: 5.0-6.1 years), 23 (6%) of the 369 patients developed AF. In unadjusted analyses, both E/SRe and E/e' were significantly associated with AF [E/SRe: HR = 1.06; (1.03-1.10); p < 0.001, per 10 increase] and [E/e': HR = 1.11 (1.05-1.17); p < 0.001, per 1 increase] and had equal Harrell's C-statistic of 0.71. However, only E/SRe remained an independent predictor after multivariable adjustments for clinical and echocardiographic parameters [E/SRe: HR = 1.06 (1.00-1.11); p = 0.044, per 10 increase]. E/SRe was further significantly associated with AF in patients with E/e' < 14 HR = 1.09 (1.01-1.17); p = 0.030, per 10 increase), also after multivariable adjustments. E/SRe is an independent predictor of AF in STEMI patients, even in subjects with seemingly normal filling pressure.

Single-lead electrocardiogram Artificial Intelligence model with risk factors detects atrial fibrillation during sinus rhythm

AIMS

Guidelines recommend opportunistic screening for atrial fibrillation (AF), using a 30 s single-lead electrocardiogram (ECG) recorded by a wearable device. Since many patients have paroxysmal AF, identification of patients at high risk presenting with sinus rhythm (SR) may increase the yield of subsequent long-term cardiac monitoring. The aim is to evaluate an AI-algorithm trained on 10 s single-lead ECG with or without risk factors to predict AF.

METHODS AND RESULTS

This retrospective study used 13 479 ECGs from AF patients in SR around the time of diagnosis and 53 916 age- and sex-matched control ECGs, augmented with 17 risk factors extracted from electronic health records. AI models were trained and compared using 1- or 12-lead ECGs, with or without risk factors. Model bias was evaluated by age- and sex-stratification of results. Random forest models identified the most relevant risk factors. The single-lead model achieved an area under the curve of 0.74, which increased to 0.76 by adding six risk factors (95% confidence interval: 0.74-0.79). This model matched the performance of a 12-lead model. Results are stable for both sexes, over ages ranging from 40 to 90 years. Out of 17 clinical variables, 6 were sufficient for optimal accuracy of the model: hypertension, heart failure, valvular disease, history of myocardial infarction, age, and sex.

CONCLUSION

An AI model using a single-lead SR ECG and six risk factors can identify patients with concurrent AF with similar accuracy as a 12-lead ECG-AI model. An age- and sex-matched data set leads to an unbiased model with consistent predictions across age groups.

Evaluation of atrial fibrillation using wearable device signals and home blood pressure data in the Michigan Predictive Activity & Clinical Trajectories in Health (MIPACT) Study: A Subgroup Analysis (MIPACT-AFib)

Background

The rising adoption of wearable technology increases the potential to identify arrhythmias. However, specificity of these notifications is poorly defined and may cause anxiety and unnecessary resource utilization. Herein, we report results of a follow-up screening protocol for incident atrial fibrillation/flutter (AF) within a large observational digital health study.

Methods

The MIPACT Study enrolled 6,765 adult patients who were provided an Apple Watch and blood pressure (BP) monitors. From March to July 2019, participants were asked to contact the study team for any irregular heart rate (HR) notification. They were assessed using structured questionnaires and asked to provide 6 Apple Watch EKGs. Those with arrhythmias or non-diagnostic EKGs were sent 7-day monitors. The EHR was reviewed after 3 years to determine if participants developed arrhythmias.

Results

86 participants received notifications and met inclusion criteria. Mean age was 50.5 (SD 16.9) years, and 46 (53.3%) were female. Of 76 participants assessed by the study team, 32 (42.1%) reported anxiety surrounding notifications. Of 59 participants who sent at least 1 EKG, 52 (88.1%) were in sinus rhythm, 3 (5.1%) AF, 2 (3.4%) indeterminate, and 2 (3.4%) sinus bradycardia. Cardiac monitor demonstrated AF in 2 of 3 participants with AF on Apple Watch EKGs. 2 contacted their PCPs and were diagnosed with AF. In total, 5 cases of AF were diagnosed with 1 additional case identified during EHR review.

Conclusion

Wearable devices produce alarms that can frequently be anxiety provoking. Research is needed to determine the implications of these alarms and appropriate follow-up.

Diagnosis and Treatment of New-Onset Perioperative Atrial Fibrillation

This article reviews medical and surgical risk factors for developing atrial fibrillation (AF), the most common sustained dysrhythmia in the United States. Evidence for assessment and management of patients with AF, including AF newly identified in the preoperative clinic, immediately preoperatively, intraoperatively, and unstable AF, is presented. A stepwise approach to guide anesthetic decision-making in the assessment of newly identified preoperative AF is proposed. Anesthetic considerations, including the potential impacts of anesthetic and vasopressor selection, and current evidence related to rate control and rhythm control via pharmacologic or electrical cardioversion as well as anticoagulation strategies are discussed.

Improving Automatic Smartwatch Electrocardiogram Diagnosis of Atrial Fibrillation by Identifying Regularity within Irregularity

Smartwatches equipped with automatic atrial fibrillation (AF) detection through electrocardiogram (ECG) recording are increasingly prevalent. We have recently reported the limitations of the Apple Watch (AW) in correctly diagnosing AF. In this study, we aim to apply a data science approach to a large dataset of smartwatch ECGs in order to deliver an improved algorithm. We included 723 patients (579 patients for algorithm development and 144 patients for validation) who underwent ECG recording with an AW and a 12-lead ECG (21% had AF and 24% had no ECG abnormalities). Similar to the existing algorithm, we first screened for AF by detecting irregularities in ventricular intervals. However, as opposed to the existing algorithm, we included all ECGs (not applying quality or heart rate exclusion criteria) but we excluded ECGs in which we identified regular patterns within the irregular rhythms by screening for interval clusters. This "irregularly irregular" approach resulted in a significant improvement in accuracy compared to the existing AW algorithm (sensitivity of 90% versus 83%, specificity of 92% versus 79%, p < 0.01). Identifying regularity within irregular rhythms is an accurate yet inclusive method to detect AF using a smartwatch ECG.

Characterizing Real-World Implementation of Consumer Wearables for the Detection of Undiagnosed Atrial Fibrillation in Clinical Practice: Targeted Literature Review

BACKGROUND

Atrial fibrillation (AF), the most common cardiac arrhythmia, is often undiagnosed because of lack of awareness and frequent asymptomatic presentation. As AF is associated with increased risk of stroke, early detection is clinically relevant. Several consumer wearable devices (CWDs) have been cleared by the US Food and Drug Administration for irregular heart rhythm detection suggestive of AF. However, recommendations for the use of CWDs for AF detection in clinical practice, especially with regard to pathways for workflows and clinical decisions, remain lacking.

OBJECTIVE

We conducted a targeted literature review to identify articles on CWDs characterizing the current state of wearable technology for AF detection, identifying approaches to implementing CWDs into the clinical workflow, and characterizing provider and patient perspectives on CWDs for patients at risk of AF.

METHODS

PubMed, ClinicalTrials.gov, UpToDate Clinical Reference, and DynaMed were searched for articles in English published between January 2016 and July 2023. The searches used predefined Medical Subject Headings (MeSH) terms, keywords, and search strings. Articles of interest were specifically on CWDs; articles on ambulatory monitoring tools, tools available by prescription, or handheld devices were excluded. Search results were reviewed for relevancy and discussed among the authors for inclusion. A qualitative analysis was conducted and themes relevant to our study objectives were identified.

RESULTS

A total of 31 articles met inclusion criteria: 7 (23%) medical society reports or guidelines, 4 (13%) general reviews, 5 (16%) systematic reviews, 5 (16%) health care provider surveys, 7 (23%) consumer or patient surveys or interviews, and 3 (10%) analytical reports. Despite recognition of CWDs by medical societies, detailed guidelines regarding CWDs for AF detection were limited, as was the availability of clinical tools. A main theme was the lack of pragmatic studies assessing real-world implementation of CWDs for AF detection. Clinicians expressed concerns about data overload; potential for false positives; reimbursement issues; and the need for clinical tools such as care pathways and guidelines, preferably developed or endorsed by professional organizations. Patient-facing challenges included device costs and variability in digital literacy or technology acceptance.

CONCLUSIONS

This targeted literature review highlights the lack of a comprehensive body of literature guiding real-world implementation of CWDs for AF detection and provides insights for informing additional research and developing appropriate tools and resources for incorporating these devices into clinical practice. The results should also provide an impetus for the active involvement of medical societies and other health care stakeholders in developing appropriate tools and resources for guiding the real-world use of CWDs for AF detection. These resources should target clinicians, patients, and health care systems with the goal of facilitating clinician or patient engagement and using an evidence-based approach for establishing guidelines or frameworks for administrative workflows and patient care pathways.

Cardiovascular Manifestations of Human Monkeypox Virus: An Updated Review

Cardiovascular manifestations in human monkeypox virus (MPXV) infection has gained increasing recognition as significant complications with both social and clinical implications. Myocarditis, viral pericarditis, heart failure, and arrhythmias can occur, leading to adverse effects on individuals' health and quality of life. Understanding the detailed pathophysiology of these cardiovascular manifestations is essential for improved diagnosis and management. The social implications of these cardiovascular complications are multifaceted, ranging from public health concerns and the impact on individuals' quality of life to psychological distress and social stigma. Clinically, diagnosing, and managing these complications present challenges, requiring a multidisciplinary approach and specialized care. The burden on healthcare resources necessitates preparedness and resource allocation to effectively address these complications. We delve into the pathophysiological mechanisms involved, including viral-induced cardiac damage, immune response, and inflammatory processes. Additionally, we explore the types of cardiovascular manifestations and their clinical presentations. Addressing cardiovascular manifestations' social and clinical implications in MPXV infection requires a comprehensive approach involving healthcare professionals, public health authorities, and communities. By prioritizing research, enhancing diagnosis and treatment strategies, and promoting preventive measures, we can mitigate the impact of these complications, improve patient care, and protect public health.

Reaching the Frail Elderly for the Diagnosis and Management of Atrial Fibrillation-REAFEL

BACKGROUND

Frail elderly patients are exposed to suffering strokes if they do not receive timely anticoagulation to prevent stroke associated to atrial fibrillation (AF). Evaluation in the cardiological ambulatory can be cumbersome as it often requires repeated visits.

AIM

To develop and implement CardioShare, a shared-care model where primary care leads patient management, using a compact Holter monitor device with asynchronous remote support from cardiologists.

METHODS

CardioShare was developed in a feasibility phase, tested in a pragmatic cluster randomization trial (primary care clinics as clusters), and its implementation potential was evaluated with an escalation test. Mixed methods were used to evaluate the impact of this complex intervention, comprising quantitative observations, semi-structured interviews, and workshops.

RESULTS

Between February 2020 and December 2021, 314 patients (30% frail) were included, of whom 75% had AF diagnosed/not found within 13 days; 80% in both groups avoided referral to cardiologists. Patients felt safe and primary care clinicians satisfied. In an escalation test, 58 primary-care doctors evaluated 93 patients over three months, with remote support from four hospitals in the Capital Region of Denmark.

CONCLUSIONS

CardioShare was successfully implemented for AF evaluation in primary care.

Obesity-Related Atrial Fibrillation: Cardiac Manifestation of a Systemic Disease

Atrial fibrillation (AF) is the most common arrhythmia worldwide and is associated with increased morbidity and mortality. The mechanisms underlying AF are complex and multifactorial. Although it is well known that obesity is a strong risk factor for AF, the mechanisms underlying obesity-related AF are not completely understood. Current evidence proposes that in addition to overall hemodynamic changes due to increased body weight, excess adiposity raises systemic inflammation and oxidative stress, which lead to adverse atrial remodeling. This remodeling includes atrial fibrosis, atrial dilation, decreased electrical conduction between atrial myocytes, and altered ionic currents, making atrial tissue more vulnerable to both the initiation and maintenance of AF. However, much remains to be learned about the mechanistic links between obesity and AF. This knowledge will power the development of novel diagnostic tools and treatment options that will help combat the rise of the global AF burden among the obesity epidemic.

The causal effects of genetically determined human blood metabolites on the risk of atrial fibrillation

Background

Blood metabolites have been found related to atrial fibrillation (AF), but the causal role is still unclear. Mendel randomization (MR) can give information about the causality between blood metabolites and AF.

Methods

Two-sample MR analysis was used to evaluate the causality between 486 blood metabolites and AF. Firstly, the genome-wide association study (GWAS) data for AF (from Nielsen et al.) was analyzed and some metabolites were identified. Then another GWAS data for AF (from Roselli et al.) was repeatedly analyzed to verify the results. Inverse variance weighted method was mainly used to determine the causality, and MR-egger, Weighted Median, and MR-PRESSO models were used as supplements of MR. Cochran's Q test was used to assess heterogeneity. And MR-Egger intercept and MR-PRESSO global test were performed to measure pleiotropy.

Results

The study used Bonferroni's corrected P value (P < 1.03 × 10-4) as the significance threshold. After MR analysis and replication analysis, we found two overlapped metabolites. Among which tryptophan betaine was the most significant causal metabolite in both AF GWAS data (from Nielsen et al.) (odds ratio (OR) = 0.83, 95% confidence interval (CI) = 0.76-0.90, P = 9.37 × 10-6) and AF GWAS data (from Roselli et al.) (OR = 0.82, 95% CI = 0.76-0.88, P = 2.00 × 10-7), while uridine was nominally significant metabolites in both AF GWAS data (from Nielsen et al.) (OR = 0.58, 95% CI = 0.40-0.84, P = 0.004) and AF GWAS data (from Roselli et al.) (OR = 0.56, 95% CI = 0.35-0.88, P = 0.01). And the results of sensitivity analysis showed that none of them had obvious heterogeneity or pleiotropy.

Conclusion

The study identified several blood metabolites that were causally related to AF, which may provide new perspectives on the pathogenesis of AF.

The use of digital health in heart rhythm care

INTRODUCTION

Digital health is a broad term that includes telecommunication technologies to collect, share and manipulate health information to improve patient health and health care services. With the growing use of wearables, artificial intelligence, machine learning, and other novel technologies, digital health is particularly relevant to the field of cardiac arrhythmias, with roles pertinent to education, prevention, diagnosis, management, prognosis, and surveillance.

AREAS COVERED

This review summarizes information on the clinical use of digital health technology in arrhythmia care and discusses its opportunities and challenges.

EXPERT OPINION

Digital health has begun to play an essential role in arrhythmia care regarding diagnostics, long-term monitoring, patient education and shared decision making, management, medication adherence, and research. Despite remarkable advances, integrating digital health technologies into healthcare faces challenges, including patient usability, privacy, system interoperability, physician liability, analysis and incorporation of the huge amount of real-time information from wearables, and reimbursement. Successful implementation of digital health technologies requires clear objectives and deep changes to existing workflows and responsibilities.

High-Dose Oral Amiodarone for Cardioversion of Atrial Fibrillation: A Case Report

With the rising prevalence of atrial fibrillation (AF), it has become a global health problem with increasing complications and high medical costs. Here, we describe the case of a 52-year-old woman with chest discomfort and frequent palpitations for the last few months. A careful clinical and instrumental examination showed that the patient had AF. Sinus rhythm was restored by cardioversion using high-dose oral amiodarone therapy. Although this medication can be an alternative with several advantages over electrical cardioversion in the future, further studies are needed to establish its efficacy and safety profile.

Genome and atrial fibrillation

Atrial fibrillation (AF), the most common type of arrhythmia, can cause several adverse effects, such as stroke, heart failure, and cognitive dysfunction, also in addition to reducing quality of life and increasing mortality. Evidence suggests that AF is caused by a combination of genetic and clinical predispositions. In line with this, genetic studies on AF have progressed significantly through linkage studies, genome-wide association studies, use of polygenic risk scores, and studies on rare coding variations, gradually elucidating the relationship between genes and the pathogenesis and prognosis of AF. This article will review current trends in genetic analysis concerning AF.

Does early detection of atrial fibrillation reduce the risk of thromboembolic events? Rationale and design of the Heartline study

BACKGROUND

The impact of using direct-to-consumer wearable devices as a means to timely detect atrial fibrillation (AF) and to improve clinical outcomes is unknown.

METHODS

Heartline is a pragmatic, randomized, and decentralized application-based trial of US participants aged ≥65 years. Two randomized cohorts include adults with possession of an iPhone and without a history of AF and those with a diagnosis of AF taking a direct oral anticoagulant (DOAC) for ≥30 days. Participants within each cohort are randomized (3:1) to either a core digital engagement program (CDEP) via iPhone application (Heartline application) and an Apple Watch (Apple Watch Group) or CDEP alone (iPhone-only Group). The Apple Watch Group has the watch irregular rhythm notification (IRN) feature enabled and access to the ECG application on the Apple Watch. If an IRN notification is issued for suspected AF then the study application instructs participants in the Apple Watch Group to seek medical care. All participants were "watch-naïve" at time of enrollment and have an option to either buy or loan an Apple Watch as part of this study. The primary end point is time from randomization to clinical diagnosis of AF, with confirmation by health care claims. Key secondary endpoint are claims-based incidence of a 6-component composite cardiovascular/systemic embolism/mortality event, DOAC medication use and adherence, costs/health resource utilization, and frequency of hospitalizations for bleeding. All study assessments, including patient-reported outcomes, are conducted through the study application. The target study enrollment is approximately 28,000 participants in total; at time of manuscript submission, a total of 26,485 participants have been enrolled into the study.

CONCLUSION

The Heartline Study will assess if an Apple Watch with the IRN and ECG application, along with application-facilitated digital health engagement modules, improves time to AF diagnosis and cardiovascular outcomes in a real-world environment.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT04276441.

Cost-Effectiveness of Atrial Fibrillation Screening Strategies: A Systematic Review

Background

Atrial fibrillation (AF) is the most common cardiac arrhythmia. AF is associated with an increased risk of stroke. We aimed to review systematically the cost-effectiveness of screening strategies for patients with AF.

Methods

To find related research and articles, articles published in Iranian and international databases by using a combination of MeSH (Medical Subject Headings) terms and based on inclusion and exclusion criteria were searched and reviewed until Dec 2020. The main outcome measures of the final articles were incremental cost-effectiveness ratios (ICER) per gained or additional quality-adjusted life years (QALYs), additional case detected, and avoided stroke.

Results

Out of 3,360 studies found, finally, fifteen studies were included in the research. The lowest ICER numerical value was 78.39 for AF screening using ECG for 65-85 yr old Japanese women. The highest value of this index is equal to 70864.31 for performing ECG monitoring for more than 60 d for Canadians over 80 yr without AF history. In two studies, the results were expressed with the years of life gained (YLG measure. Of course, in one study, the results were not reported with this measure, and in one study, the results were reported with ICER.

Conclusion

Most of the studies acknowledged the cost-effectiveness of different AF screening strategies. However, studies that confirmed the cost-effectiveness of population-based screening were more than studies that confirmed the cost-effectiveness of other screening strategies.

The N-Glycosylation of Total Plasma Proteins and IgG in Atrial Fibrillation

Atrial fibrillation is a disease with a complex pathophysiology, whose occurrence and persistence are caused not only by aberrant electrical signaling in the heart, but by the development of a susceptible heart substrate. These changes, such as the accumulation of adipose tissue and interstitial fibrosis, are characterized by the presence of inflammation. N-glycans have shown great promise as biomarkers in different diseases, specifically those involving inflammatory changes. To assess the changes in the N-glycosylation of the plasma proteins and IgG in atrial fibrillation, we analyzed the N-glycosylation of 172 patients with atrial fibrillation, before and six months after a pulmonary vein isolation procedure, with 54 cardiovascularly healthy controls. An analysis was performed using ultra-high-performance liquid chromatography. We found one oligomannose N-glycan structure from the plasma N-glycome and six IgG N-glycans, mainly revolving around the presence of bisecting N-acetylglucosamine, that were significantly different between the case and control groups. In addition, four plasma N-glycans, mostly oligomannose structures and a derived trait that was related to them, were found to be different in the patients who experienced an atrial fibrillation recurrence during the six-month follow-up. IgG N-glycosylation was extensively associated with the CHA2DS2-VASc score, confirming its previously reported associations with the conditions that make up the score. This is the first study looking at the N-glycosylation patterns in atrial fibrillation and warrants further investigation into the prospect of glycans as biomarkers for atrial fibrillation.

Potential of electronic devices for detection of health problems in older adults at home: A systematic review and meta-analysis

OBJECTIVE

The aim of this review was to evaluate the overall diagnostic performance of e-devices for detection of health problems in older adults at home.

METHODS

A systematic review was conducted following the PRISMA-DTA guidelines.

RESULTS

31 studies were included with 24 studies included in meta-analysis. The included studies were divided into four categories according to the signals detected: physical activity (PA), vital signs (VS), electrocardiography (ECG) and other. The meta-analysis showed the pooled estimates of sensitivity and specificity were 0.94 and 0.98 respectively in the 'VS' group. The pooled sensitivity and specificity were 0.97 and 0.98 respectively in the 'ECG' group.

CONCLUSIONS

All kinds of e-devices perform well in diagnosing the common health problems. While ECG-based health problems detection system is more reliable than VS-based ones. For sole signal detection system has limitation in diagnosing specific health problems, more researches should focus on developing new systems combined of multiple signals.

A Smartwatch System for Continuous Monitoring of Atrial Fibrillation in Older Adults After Stroke or Transient Ischemic Attack: Application Design Study

BACKGROUND

The prevalence of atrial fibrillation (AF) increases with age and can lead to stroke. Therefore, older adults may benefit the most from AF screening. However, older adult populations tend to lag more than younger groups in the adoption of, and comfort with, the use of mobile health (mHealth) apps. Furthermore, although mobile apps that can detect AF are available to the public, most are designed for intermittent AF detection and for younger users. No app designed for long-term AF monitoring has released detailed system design specifications that can handle large data collections, especially in this age group.

OBJECTIVE

This study aimed to design an innovative smartwatch-based AF monitoring mHealth solution in collaboration with older adult participants and clinicians.

METHODS

The Pulsewatch system is designed to link smartwatches and smartphone apps, a website for data verification, and user data organization on a cloud server. The smartwatch in the Pulsewatch system is designed to continuously monitor the pulse rate with embedded AF detection algorithms, and the smartphone in the Pulsewatch system is designed to serve as the data-transferring hub to the cloud storage server.

RESULTS

We implemented the Pulsewatch system based on the functionality that patients and caregivers recommended. The user interfaces of the smartwatch and smartphone apps were specifically designed for older adults at risk for AF. We improved our Pulsewatch system based on feedback from focus groups consisting of patients with stroke and clinicians. The Pulsewatch system was used by the intervention group for up to 6 weeks in the 2 phases of our randomized clinical trial. At the conclusion of phase 1, 90 trial participants who had used the Pulsewatch app and smartwatch for 14 days completed a System Usability Scale to assess the usability of the Pulsewatch system; of 88 participants, 56 (64%) endorsed that the smartwatch app is "easy to use." For phases 1 and 2 of the study, we collected 9224.4 hours of smartwatch recordings from the participants. The longest recording streak in phase 2 was 21 days of consecutive recordings out of the 30 days of data collection.

CONCLUSIONS

This is one of the first studies to provide a detailed design for a smartphone-smartwatch dyad for ambulatory AF monitoring. In this paper, we report on the system's usability and opportunities to increase the acceptability of mHealth solutions among older patients with cognitive impairment.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03761394; https://www.clinicaltrials.gov/ct2/show/NCT03761394.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1016/j.cvdhj.2021.07.002.

Atrial fibrillation: Epigenetic aspects and role of sodium-glucose cotransporter 2 inhibitors

Atrial fibrillation (AF) is the most frequent arrhythmia and is associated with substantial morbidity and mortality. Pathophysiological aspects consist in the activation of pro-fibrotic signaling and Ca²⁺ handling abnormalities at atrial level. Structural and electrical remodeling creates a substrate for AF by triggering conduction abnormalities and cardiac arrhythmias. The care of AF patients focuses predominantly on anticoagulation, symptoms control and the management of risk factors and comorbidities. The goal of AF therapy points to restore sinus rhythm, re-establish atrioventricular synchrony and improve atrial contribution to the stroke volume. New layer of information to better comprehend AF pathophysiology, and identify targets for novel pharmacological interventions consists of the epigenetic phenomena including, among others, DNA methylation, histone modifications and noncoding RNAs. Moreover, the benefits of sodium-glucose cotransporter 2 inhibitors (SGLT2i) in diabetic and non-diabetic patients at cardiovascular risk as well as emerging evidence on the ability of SGLT2i to modify epigenetic signature in cardiovascular diseases provide a solid background to investigate a possible role of this drug class in the onset and progression of AF. In this review, following a summary of pathophysiology and management, epigenetic mechanisms in AF and the potential of sodium-glucose SGLT2i in AF patients are discussed.

Artificial intelligence-enabled mobile electrocardiograms for event prediction in paroxysmal atrial fibrillation

Background

Paroxysmal atrial fibrillation (AF) often eludes early diagnosis, resulting in significant morbidity and mortality. Artificial intelligence (AI) has been used to predict AF from sinus rhythm electrocardiograms (ECGs), but AF prediction using sinus rhythm mobile electrocardiograms (mECG) remains unexplored.

Objective

The purpose of this study was to investigate the utility of AI to predict AF events prospectively and retrospectively using sinus rhythm mECG data.

Methods

We trained a neural network to predict AF events from sinus rhythm mECGs obtained from users of the Alivecor KardiaMobile 6L device. We tested our model on sinus rhythm mECGs within ±0-2 days, ±3-7 days, and ±8-30 days from AF events to determine the optimal screening window. Finally, we tested our model on mECGs from before an AF event to determine whether AF can be predicted prospectively.

Results

We included 73,861 users with 267,614 mECGs (mean age 58.14 years; 35% women). Users with paroxysmal AF contributed 60.15% of mECGs. Model performance on the test set comprising control and study samples across all windows of interest showed an area under the curve (AUC) score of 0.760 (95% confidence interval [CI] 0.759-0.760), sensitivity of 0.703 (95% CI 0.700-0.705), specificity of 0.684 (95% CI 0.678-0.685), and accuracy of 69.4% (95% CI 0.692-0.700). Model performance was better on ±0-2 day samples (sensitivity 0.711; 95% CI 0.709-0.713) and worse on the ±8-30 day window (sensitivity 0.688; 95% CI 0.685-0.690), with performance on the ±3-7 day window falling in between (sensitivity 0.708; 95% CI 0.704-0.710).

Conclusion

Neural networks can predict AF using a widely scalable and cost-effective mobile technology prospectively and retrospectively.

Correlation between Serum Myosin Light Chain 4 Levels and Recurrence after Radiofrequency Ablation in Patients with Atrial Fibrillation

Atrial fibrillation (AF) is the most common arrhythmia that is harmful to human health. This study aims to explore the relationship between myosin light chain 4 (MYL4) and AF recurrence after radiofrequency ablation (RFA). Patients with AF (n = 85) were enrolled, and healthy subjects (n = 90) with normal sinus rhythm and no previous history of AF were selected as controls. The serum levels of MYL4, transforming growth factor (TGF) -β1, and procollagen type-I C-terminal propeptide (PICP) were determined. The correlation between MYL4 and atrial fibrosis remodeling indicators (TGF-β1/PICP) and left atrial diameter (LAD) was analyzed. The influence of MYL4 on AF recurrence after RFA was evaluated, and the independent correlation between them was assessed. Patients with AF and the controls showed no significant differences in age, gender, body mass index, systolic blood pressure, diastolic blood pressure, left ventricular ejection fraction, triglycerides, total cholesterol, high-density lipoprotein, low-density lipoprotein, white blood cell count, neutrophil/lymphocyte ratio, brain natriuretic peptide, and history of smoking, drinking, hypertension, and diabetes (P > 0.05), but with increased LAD in patients with AF (P < 0.01). Serum MYL4 level was reduced in patients with AF (0.6 ± 0.2) compared with that of controls (0.1 ± 0.6) (P < 0.01), and it was negatively correlated with TGF-β1, PICP, and LAD (r = -0.2389, P < 0.05; r = -0.5174, P < 0.01; r = -0.3191; P < 0.01). Low levels of MYL4 increased the risk of AF recurrence after RFA (χ² = 16.64; P < 0.0001). A low MYL4 level in patients with AF showed a poorer prognosis. Serum MYL4 level and AF type were independent risk factors affecting AF recurrence after RFA.

Relationship between nutritional status and length of hospital stay among patients with atrial fibrillation - a result of the nutritional status heart study

Background

Nutritional status is related to the prognosis and length of hospital stay (LOHS) of patients with atrial fibrillation (AF). This study aimed to assess how nutritional status affects LOHS for patients with AF.

Methods

We performed retrospective analysis of the medical records of 1,813 patients admitted urgently with a diagnosis of AF to the Institute of Heart Diseases of the University Clinical Hospital in Wroclaw, Poland.

Results

In total, 1,813 patients were included in the analysis. The average LOHS in the entire group was 3.53 ± 3.41 days. The mean BMI was 28.7 kg/m² (SD: 5.02). Patients who were hospitalized longer were statistically more likely to have a Nutritional Risk Score (NRS) ≥3 (p = 0.028). A higher percentage of longer hospitalized patients with LDL levels below 70 mg/dl (p < 0.001) and those with HDL ≥40 mg/dl (p < 0.001) were observed. Study participants with NRS ≥3 were an older group (M = 76.3 years), with longer mean LOHS (M = 4.44 days). The predictors of LOHS in the univariate model were age (OR = 1.04), LDL (OR = 0.99), HDL (OR = 0.98), TC (OR = 0.996), CRP (OR = 1, 02, p < 0.001), lymphocytes (OR = 0.97, p = 0.008) and in the multivariate model were age, LDL (mg/dl), HDL (mg/dl), Na, and K.

Conclusion

For nutritional status, factors indicating the risk of prolonged hospitalization in patients with AF are malnutrition, lower serum LDL, HDL, potassium, and sodium levels identified at the time of admission to the cardiology department. Assessment of nutritional status in patients with AF is important both in the context of evaluating obesity and malnutrition status, as both conditions can alter the prognosis of patients. Further studies are needed to determine the exact impact of the above on the risk of prolonged hospitalization.

Correlation Between Serum Albumin and D-Dimer Levels in 909 Patients with Non-Valvular Atrial Fibrillation: A Retrospective Study from a Single Center in China

BACKGROUND D-dimer level can reflect the hypercoagulable state of atrial fibrillation (AF) and predict thromboembolic events. However, no effective indicator associated with D-dimer of AF patients has been found to prevent thromboembolic events in AF. This retrospective study from a single center aimed to investigate the correlation between serum albumin and D-dimer levels in 909 patients with non-valvular AF (NVAF) and 653 subjects in sinus rhythm. MATERIAL AND METHODS A total of 909 NVAF patients and 653 sex- and age-matched sinus rhythm participants were used to compare serum albumin and D-dimer levels. Serum albumin was determined by colorimetry, and D-dimer level was determined by latex-enhanced photoimmunoassay. We analyzed the correlation of serum albumin and D-dimer with NVAF by correlation analysis, logistic regression analysis, and receiver operating characteristic (ROC) curve. RESULTS Albumin (P<0.001) and D-dimer (P<0.001) were significantly associated with NVAF. Among NVAF patients, D-dimer level was negatively correlated with albumin levels (P<0.001), and albumin level was an independent risk factor of abnormal D-dimer level (>0.5 ug/mL), which was also an effective predictor of abnormal D-dimer level (the area under the ROC curve was 0.77, P<0.001), and the optimal cutoff value was 36.95 g/L. CONCLUSIONS Serum albumin and D-dimer levels were significantly associated with NVAF. In NVAF patients, D-dimer level was inversely correlated with albumin levels, and albumin level was an independent risk factor and effective predictor of abnormal D-dimer level. Close examination and supplementation of serum albumin can prevent thromboembolic events, but further clinical research and confirmation are needed.

Neurovisceral interactions within the brain-heart axis as the basis of neurocardiology

The use of a systematic approach to the study of the etiology of a certain pathology makes it possible to improve the understanding of its pathogenesis, as well as to develop more effective diagnostic and therapeutic approaches, including improving the prediction of its risk. Within this review, we will consider such an area of interdisciplinary research as neurocardiology, which studies the brain-heart axis. Examples of cardiovascular diseases associated with organic and functional disorders of this axis will be considered, as well as the prospects for research in this area and their translational significance for clinical medicine.

Atrial Fibrillation, thromboembolic risk, and the potential role of the natriuretic peptides, a focus on BNP and NT-proBNP - A narrative review

Atrial fibrillation (AF) is one of the most commonly encountered arrythmia in clinical practice. AF itself can be driven by genetic predisposition, ectopic electrical activity, and abnormal atrial tissue substrates. Often there is no single etiological mechanism, but rather a combination of factors that feed back to remodel and worsen tissue substrate, "AF begets AF". The clinical consequences of AF can often include emboli, heart failure, and early mortality. The classical AF cardioembolic (CE) concept requires thrombus formation in the left atrial appendage, with subsequent embolization. The temporal dissociation between AF occurrence and CE events has thrown doubt on AF as the driver of this mechanism. Instead, there has been a resurgence of the "atrial cardiomyopathy" (ACM) concept. An ACM is proposed as a potential mechanism of embolic disease through promotion of prothrombotic mechanisms, with AF instead reflecting atrial disease severity. Regardless, AF has been implicated in 25% to 30% of cryptogenic strokes. Natriuretic peptide(NP)s have been shown to be elevated in AF, with higher levels of both NT-proBNP and BNP being predictive of incidental AF. NPs potentially reflect the atrial environment and could be used to identify an underlying ACM. Therefore, this narrative review examines this evidence and mechanisms that may underpin the role of NPs in identifying atrial dysfunction, with focus on both, BNP and NTproBNP. We explore their potential role in the prediction and screening for both, ACM and AF. Moreover, we compare both NPs directly to ascertain a superior biomarker.

Multimodal Approach for the Prediction of Atrial Fibrillation Detected After Stroke: SAFAS Study

Background

Intensive screening for atrial fibrillation (AF) has led to a better recognition of this cause in stroke patients. However, it is currently debated whether AF Detected After Stroke (AFDAS) has the same pathophysiology and embolic risk as prior-to-stroke AF. We thus aimed to systematically approach AFDAS using a multimodal approach combining clinical, imaging, biological and electrocardiographic markers.

Methods

Patients without previously known AF admitted to the Dijon University Hospital (France) stroke unit for acute ischemic stroke were prospectively enrolled. The primary endpoint was the presence of AFDAS at 6 months, diagnosed through admission ECG, continuous electrocardiographic monitoring, long-term external Holter during the hospital stay, or implantable cardiac monitor if clinically indicated after discharge.

Results

Of the 240 included patients, 77 (32%) developed AFDAS. Compared with sinus rhythm patients, those developing AFDAS were older, more often women and less often active smokers. AFDAS patients had higher blood levels of NT-proBNP, osteoprotegerin, galectin-3, GDF-15 and ST2, as well as increased left atrial indexed volume and lower left ventricular ejection fraction. After multivariable analysis, galectin-3 ≧ 9 ng/ml [OR 3.10; 95% CI (1.03–9.254), p = 0.042], NT-proBNP ≧ 290 pg/ml [OR 3.950; 95% CI (1.754–8.892, p = 0.001], OPG ≥ 887 pg/ml [OR 2.338; 95% CI (1.015–5.620), p = 0.046) and LAVI ≥ 33.5 ml/m2 [OR 2.982; 95% CI (1.342–6.625), p = 0.007] were independently associated with AFDAS.

Conclusion

A multimodal approach combining imaging, electrocardiography and original biological markers resulted in good predictive models for AFDAS. These results also suggest that AFDAS is probably related to an underlying atrial cardiopathy.

Clinical Trial Registration

[www.ClinicalTrials.gov], identifier [NCT03570060].

Performance of an electronic health record-based predictive model to identify patients with atrial fibrillation across countries

Background

Atrial fibrillation (AF) burden on patients and healthcare systems warrants innovative strategies for screening asymptomatic individuals.

Objective

We sought to externally validate a predictive model originally developed in a German population to detect unidentified incident AF utilising real-world primary healthcare databases from countries in Europe and Australia.

Methods

This retrospective cohort study used anonymized, longitudinal patient data from 5 country-level primary care databases, including Australia, Belgium, France, Germany, and the UK. The study eligibility included adult patients (≥45 years) with either an AF diagnosis (cases) or no diagnosis (controls) who had continuous enrolment in the respective database prior to the study period. Logistic regression was fitted to a binary response (yes/no) for AF diagnosis using pre-determined risk factors.

Results

AF patients were from Germany (n = 63,562), the UK (n = 42,652), France (n = 7,213), Australia (n = 2,753), and Belgium (n = 1,371). Cases were more likely to have hypertension or other cardiac conditions than controls in all validation datasets compared to the model development data. The area under the receiver operating characteristic (ROC) curve in the validation datasets ranged from 0.79 (Belgium) to 0.84 (Germany), comparable to the German study model, which had an area under the curve of 0.83. Most validation sets reported similar specificity at approximately 80% sensitivity, ranging from 67% (France) to 71% (United Kingdom). The positive predictive value (PPV) ranged from 2% (Belgium) to 16% (Germany), and the number needed to be screened was 50 in Belgium and 6 in Germany. The prevalence of AF varied widely between these datasets, which may be related to different coding practices. Low prevalence affected PPV, but not sensitivity, specificity, and ROC curves.

Conclusions

AF risk prediction algorithms offer targeted ways to identify patients using electronic health records, which could improve screening number and the cost-effectiveness of AF screening if implemented in clinical practice.

Investigation of the Evolution of Wavelet Higher-Order Dynamics in Atrial Fibrillation

Atrial fibrillation (AF) is the most common cardiac arrhythmia and is associated with significant morbidity and mortality. Owing to the advances in sensor technology and the emergence of wearable devices that enable daily self-monitoring, ECG signal processing methods for the automatic detection of AF are more pertinent than ever. In this paper, we investigate the use of wavelet higher-order statistics (WHOS) for feature extraction and differentiation between normal sinus rhythm and AF. The proposed approach captures the evolution of the WHOS dynamics and quantifies the changes in the time-varying characteristics of the frequency couplings caused by AF. Results obtained from the statistical analysis of a dataset of 5834 single-lead ECG recordings, reveal 46/50 statistically significant features and provide insight into the complexity of the evolution of the ECG non-linearities during AF.

Impact of dronedarone on patients with atrial fibrillation and diabetes: A sub-analysis of the ATHENA and EURIDIS/ADONIS studies

AIM

This post hoc analysis evaluated efficacy and safety of dronedarone in atrial fibrillation (AF) and atrial flutter (AFL) patients with/without diabetes.

METHODS

Patients were categorized according to baseline diabetes status. Time-to-event analyses were performed using Kaplan-Meier method. Hazard-ratios were assessed using Cox models.

RESULTS

945/4628 (dronedarone = 482; placebo = 463) patients in ATHENA and 215/1237 (dronedarone = 148; placebo = 67) patients in EURIDIS/ADONIS studies had diabetes. In ATHENA, there were higher rates of CV hospitalization/death in patients with diabetes (39.5%) than without diabetes (34.7%). Incidence of first CV hospitalization/death was lower in patients with diabetes treated with dronedarone (35.1%) than placebo (44.1%), and time to this event was longer in those treated with dronedarone than placebo (log-rank p = 0.005). Median AF/AFL recurrence time was longer in patients treated with dronedarone than placebo in patients with diabetes (ATHENA: 722 vs 527 days, log-rank p = 0.004; EURIDIS/ADONIS: 100 vs 23 days, log-rank p = 0.15) or without diabetes (ATHENA: 741 vs 492 days, log-rank p < 0.0001; EURIDIS/ADONIS: 120 vs 59 days, log-rank p = 0.0002). Occurrence of any treatment-related adverse events with dronedarone was similar for patients with/without diabetes and was comparable to placebo.

CONCLUSIONS

Dronedarone reduced incidence of CV hospitalization/death, AF/AFL recurrence and increased time to these events in AF/AFL patients with/without diabetes.

TRIAL REGISTRATION

Not applicable, as it was a post hoc analysis. This article is based on previously conducted studies (ATHENA: NCT00174785, EURIDIS: NCT00259428, and ADONIS: NCT00259376).

Reaching Frail Elderly Patients to Optimize Diagnosis and Management of Atrial Fibrillation (REAFEL): A Feasibility Study of a Cross-Sectoral Shared-Care Model

Introduction: Atrial fibrillation (AF) management in primary care often requires a referral to cardiology clinics, which can be strenuous for frail patients. We developed “cardio-share” (CS), a new cross-sector collaboration model, to ease this process. General practitioners (GPs) can use a compact Holter monitor (C3 from Cortrium) to receive remote advice from the cardiologist. Objective: To test the feasibility and acceptability of the CS model to manage suspected AF in frail elderly patients. Methods: We used a mixed methods design, including the preparation of qualitative semistructured interviews of GPs and nurses. Results: Between MAR-2019 and FEB-2020, 54 patients were consulted through the CS model, of whom 35 underwent C3 Holter monitoring. The time from referral to a final Holter report was shortened from a mean (SD) of 117 (45) days in usual care to 30 days (13) with the CS model. Furthermore, 90% of the patients did not need to attend visits at the cardiology clinic. The GPs and nurses highlighted the ease of using the C3 monitor. Their perception was that patients were confident in the GPs’ collaboration with cardiologists. Conclusions: The CS model using a C3 monitor for AF is both feasible and seems acceptable to GPs. The elapsed time from referral to the Holter report performed for the diagnosis was significantly reduced.

Prediction of Atrial Fibrillation Being Asymptomatic at First Onset by Cardiac Pacing

Asymptomatic or silent atrial fibrillation (AF) has long been a clinical problem due to the incidence of ischemic stroke. A method is needed to predict the development of silent AF before the occurrence of ischemic stroke. This study was focused on the symptoms of AF, especially palpitation, in pacemaker patients. We assessed the hypothesis that absence of palpitation during rapid ventricular pacing could be a predictor of future onset AF being asymptomatic.In this study, we assessed the presence of symptoms during RV pacing and AF symptoms on 145 pacemaker patients at the outpatient clinic by VVI pacing at 120 ppm. The relationship between symptoms during RV pacing and symptom during AF was assessed. The predictive value of absence of symptom during RV pacing on AF being asymptomatic was assessed.Of 145 patients, 74 had previous AF episode. Among the AF patients, absence of symptom during VVI pacing was associated with AF being asymptomatic.Of 145 patients, 71 had no previous AF events. There were 14 patients who had new-onset AF or atrial flutter (AFL) after the device implantation. Four of the 14 patients (28.6%) were symptomatic during first AF/AFL episode, and 10 (71.4%) were asymptomatic during first-onset AF. All ten patients who were asymptomatic during cardiac pacing test were asymptomatic during their initial episodes of AF as well.This study showed that absence of symptoms during rapid ventricular pacing was associated with first-onset AF being asymptomatic.

Artificial intelligence-electrocardiography to detect atrial fibrillation: trend of probability before and after the first episode

Aims

Artificial intelligence (AI) enabled electrocardiography (ECG) can detect latent atrial fibrillation (AF) in patients with sinus rhythm (SR). However, the change of AI-ECG probability before and after the first AF episode is not well characterized. We sought to characterize the temporal trend of AI-ECG AF probability around the first episode of AF.

Methods and results

We retrospectively studied adults who had at least one ECG in SR prior to an ECG that documented AF. An AI network calculated the AF probability from ECGs during SR (positive defined >8.7%, based on optimal sensitivity and specificity). The AI-ECG probability was reported prior to and after the first episode of AF and stratified by age and CHA₂DS₂-VASc score. Mixed effect models were used to assess the rate of change between time points. A total of 59 212 patients with 544 330 ECGs prior to AF and 413 486 ECGs after AF were included. The mean time between the first positive AI-ECG and first AF was 5.4 ± 5.7 years. The mean AI-ECG probability was 19.8% 2-5 years prior to AF, 23.6% 1-2 years prior to AF, 34.0% 0-3 months prior to AF, 40.9% 0-3 months after AF, 35.2% 1-2 years after AF, and 42.2% 2-5 years after AF (P < 0.001). The rate of increase prior to AF was higher for age >50 years CHA₂DS₂-VASc score ≥4.

Conclusion

The AI-ECG probability progressively increases with time prior to the first AF episode, transiently decreases 1-2 years following AF and continues to increase thereafter.

Additional value of left atrium remodeling assessed by three-dimensional echocardiography for the prediction of atrial fibrillation recurrence after cryoballoon ablation

Cryoballoon ablation (CBA) is a safe and efficient therapeutic option for atrial fibrillation (AF). However, AF recurrence occurs in 25% of the patients, leading to repeated ablations and complications. Previous reports have shown that left atrium (LA) assessed by M-Mode and two-dimensional echocardiography (2DE) predicts AF recurrence. Nevertheless, these methods imply geometrical assumptions of the LA remodeling, which is a three-dimensional process. We hypothesized that LA remodeling by three-dimensional echocardiography (3DE) has an additional value for AF recurrence prediction post-CBA. 172 consecutive patients (62.2 ± 12.2 years, 61% male) were prospectively recruited. Echocardiography was performed before CBA. Blanking period was defined as the first three months post-ablation. The primary endpoint was AF recurrence after the blanking period. 50 (29%) patients had AF recurrence. 3DE LA maximum volume index (LAVI) had the highest incremental predictive value for AF recurrence (HR 5.50, 95% CI 1.34 -22.45, p < 0.001). In patients with non-dilated LA diameter index and LAVI by 2DE, LAVI by 3DE was able to discriminate AF recurrence with a sensitivity of 90% and a specificity of 66%, for an optimal cut-off value of 30.4 ml/m2. LA remodeling by 3DE predicted AF recurrence, even in patients with non-dilated LA by M-Mode and 2DE, suggesting that 3DE might reflect better and earlier the asymmetric and variable nature of LA remodeling and it should be considered for systematic use to evaluate AF recurrence risk post-CBA.

Postoperative Atrial Fibrillation in Adults with Obstructive Sleep Apnea Undergoing Coronary Artery Bypass Grafting in the RICCADSA Cohort

Postoperative atrial fibrillation (POAF) occurs in 20−50% of patients with coronary artery disease (CAD) after coronary artery bypass grafting (CABG). Obstructive sleep apnea (OSA) is also common in adults with CAD, and may contribute to POAF as well to the reoccurrence of AF in patients at long-term. In the current secondary analysis of the Randomized Intervention with Continuous Positive Airway Pressure (CPAP) in Coronary Artery Disease and Obstructive Sleep Apnea (RICCADSA) trial (Trial Registry: ClinicalTrials.gov; No: NCT 00519597), we included 147 patients with CABG, who underwent a home sleep apnea testing, in average 73 ± 30 days after the surgical intervention. POAF was defined as a new-onset AF occurring within the 30 days following the CABG. POAF was observed among 48 (32.7%) patients, occurring within the first week among 45 of those cases. The distribution of the apnea-hypopnea-index (AHI) categories < 5.0 events/h (no-OSA); 5.0−14.9 events/h (mild OSA); 15.0−29.9 events/h (moderate OSA); and ≥30 events/h (severe OSA), was 4.2%, 14.6%, 35.4%, and 45.8%, in the POAF group, and 16.2%, 17.2%, 39.4%, and 27.3%, respectively, in the no-POAF group. In a multivariate logistic regression model, there was a significant risk increase for POAF across the AHI categories, with the highest odds ratio (OR) for severe OSA (OR 6.82, 95% confidence interval 1.31−35.50; p = 0.023) vs. no-OSA, independent of age, sex, and body-mass-index. In the entire cohort, 90% were on β-blockers according to the clinical routines, they all had sinus rhythm on the electrocardiogram at baseline before the study start, and 28 out of 40 patients with moderate to severe OSA (70%) were allocated to CPAP. During a median follow-up period of 67 months, two patients (none with POAF) were hospitalized due to AF. To conclude, severe OSA was significantly associated with POAF in patients with CAD undergoing CABG. However, none of those individuals had an AF-reoccurrence at long term, and whether CPAP should be considered as an add-on treatment to β-blockers in secondary prevention models for OSA patients presenting POAF after CABG requires further studies in larger cohorts.

Optimal opportunistic screening of atrial fibrillation using pulse palpation in cardiology outpatient clinics: Who and how

Background

Atrial fibrillation (AF) remain a prevalent undiagnosed condition frequently encountered in primary care.

Objective

We aimed to find the parameters that optimize the diagnostic accuracy of pulse palpation to detect AF. We also aimed to create a simple algorithm for selecting which individuals would benefit from pulse palpation and, if positive, receive an ECG to detect AF.

Methods

Nurses from four Cardiology outpatient clinics palpated 7,844 pulses according to a randomized list of arterial territories and durations of measure and immediately followed by a 12-lead ECG, which we used as the reference standard. We calculated the sensitivity and specificity of the palpation parameters. We also assessed whether diagnostic accuracy depended on the nurse’s experience or on a list of clinical factors of the patients. With this information, we estimated the positive predictive values and false omission rates according to very few clinical factors readily available in primary care (age, sex, and diagnosis of heart failure) and used them to create the algorithm.

Results

The parameters associated with the highest diagnostic accuracy were palpation of the radial artery and classifying as irregular those palpations in which the nurse was uncertain about pulse regularity or unable to palpate pulse (sensitivity = 79%; specificity = 86%). Specificity decreased with age. Neither the nurse’s experience nor any investigated clinical factor influenced diagnostic accuracy. We provide the algorithm to select the ≥40 years old individuals that would benefit from a pulse palpation screening: a) do nothing in <60 years old individuals without heart failure; b) do ECG in ≥70 years old individuals with heart failure; c) do radial pulse palpation in the remaining individuals and do ECG if the pulse is irregular or you are uncertain about its regularity or unable to palpate it.

Conclusions

Opportunistic screening for AF using optimal pulse palpation in candidate individuals according to a simple algorithm may have high effectiveness in detecting AF in primary care.

Ameliorative Impact of Liraglutide on Chronic Intermittent Hypoxia-Induced Atrial Remodeling

Atrial fibrillation (AF) is the most frequent form of clinical cardiac arrhythmias. Previous evidence proved that atrial anatomical remodeling (AAR) and atrial electrical remodeling (AER) are crucial for the progression and maintenance of AF. This study is aimed at investigating the impact of the glucagon-like peptide-1 (GLP-1) receptor agonist, Liraglutide (Lir), on atrial remodeling (AR) mouse model induced by chronic intermittent hypoxia (CIH). C57BL/6 mice were categorized randomly into the control, Lir, CIH, and CIH+Lir groups. CIH was performed in CIH and CIH+Lir groups for 12 weeks. Lir (0.3 mg/kg/day, s.c) was administered to the Lir and CIH+Lir groups for four weeks, beginning from the ninth week of CIH. Meanwhile, echocardiography and right atrial endocardial electrophysiology via jugular vein, as well as induction rate and duration of AF, were evaluated. Masson and Sirius red staining assays were utilized to assess the extent of fibrosis in the atrial tissue of the mice. Immunohistochemical staining, RT-qPCR, and Western blotting were performed to evaluate the marker levels of AAR and AER and the expression of genes and proteins of the miR-21/PTEN/PI3K/AKT signaling pathway, respectively. ELISA was also performed to evaluate the changes of serum inflammatory factor levels. The CIH group exhibited significant AR, increased atrial fibrosis, and a higher incidence rate of AF compared to the control group. Lir could significantly downregulate the protein expression level in the PI3K/p-AKT pathway and upregulated that of phosphatase and tensin homolog deleted on chromosome ten (PTEN). Moreover, Lir downregulated the expression of miR-21. However, the protein expressions of CACNA1C and KCNA5 in atrial tissue were not changed significantly. In addition, Lir significantly attenuated the levels of markers of inflammation (TNF-α and IL-6) in the serum. In the mouse model of CIH, Lir treatment could ameliorate AR by the miR-21/PTEN/PI3K/AKT signaling pathway and modulation of inflammatory responses.

Supermarket/Hypermarket Opportunistic Screening for Atrial Fibrillation (SHOPS-AF): A Mixed Methods Feasibility Study Protocol

Aims: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and a key risk factor for ischaemic stroke. Following AF detection, treatment with oral anticoagulation can significantly lower mortality and morbidity rates associated with this risk. The availability of several hand-held devices which can detect AF may enable trained health professionals to adopt AF screening approaches which do not interfere with people’s daily routines. This study aims to investigate the effectiveness of a hand-held device (the MyDiagnostick single-lead Electrocardiogram (ECG) sensor) in screening for AF when embedded into the handles of supermarket trolleys. Methods: A mixed methods two-phase approach will be taken. The quantitative first phase will involve the recruitment of 2000 participants from a convenience sample at four large supermarkets with pharmacies. Prospective participants will be asked to conduct their shopping using a trolley embedded with a MyDiagnostick sensor. If the device identifies a participant with AF, the in-store pharmacist will be dispatched to take a manual pulse measurement and a static control sensor reading and offer a cardiologist consultation referral. When the sensor does not detect AF, a researcher will confirm the reading with a manual pulse measurement. ECGs will be compiled, and the sensitivity, specificity and positive and negative predictive values will be determined. A qualitative second phase will consist of semi-structured interviews carried out with those pharmacists and store managers in-store during the running of the trial period. These will explore the perceptions of staff regarding the merits of embedding sensors in the handles of supermarket trolleys to detect AF. Conclusion: This feasibility study will inform a larger future definitive trial.

Analyzability of Photoplethysmographic Smartwatch Data by the Preventicus Heartbeats Algorithm During Everyday Life: Feasibility Study

BACKGROUND

Continuous heart rate monitoring via mobile health technologies based on photoplethysmography (PPG) has great potential for the early detection of sustained cardiac arrhythmias such as atrial fibrillation. However, PPG measurements are impaired by motion artifacts.

OBJECTIVE

The aim of this investigation was to evaluate the analyzability of smartwatch-derived PPG data during everyday life and to determine the relationship between the analyzability of the data and the activity level of the participant.

METHODS

A total of 41 (19 female and 22 male) adults in good cardiovascular health (aged 19-79 years) continuously wore a smartwatch equipped with a PPG sensor and a 3D accelerometer (Cardio Watch 287, Corsano Health BV) for a period of 24 hours that represented their individual daily routine. For each participant, smartwatch data were analyzed on a 1-minute basis by an algorithm designed for heart rhythm analysis (Preventicus Heartbeats, Preventicus GmbH). As outcomes, the percentage of analyzable data (PAD) and the mean acceleration (ACC) were calculated. To map changes of the ACC and PAD over the course of one day, the 24-hour period was divided into 8 subintervals comprising 3 hours each.

RESULTS

Univariate analysis of variance showed a large effect (η_p²> 0.6; P<.001) of time interval (phase) on the ACC and PAD. The PAD ranged between 34% and 100%, with an average of 71.5% for the whole day, which is equivalent to a period of 17.2 hours. Between midnight and 6 AM, the mean values were the highest for the PAD (>94%) and the lowest for the ACC (<6×10^-3 m/s²). Regardless of the time of the day, the correlation between the PAD and ACC was strong (r=-0.64). A linear regression analysis for the averaged data resulted in an almost perfect coefficient of determination (r²=0.99).

CONCLUSIONS

This study showed a large relationship between the activity level and the analyzability of smartwatch-derived PPG data. Given the high yield of analyzable data during the nighttime, continuous arrhythmia screening seems particularly effective during sleep phases.

Value of echocardiography in evaluating efficacy of radiofrequency catheter ablation in patients with atrial fibrillation

OBJECTIVE

To analyze the cardiac structure and function of patients with recurrent atrial fibrillation (AF) after radiofrequency catheter ablation (RFCA) with echocardiography and to predict the factors affecting recurrence.

METHODS

In this retrospective study, 87 patients who received RFCA for AF in the Weihai Municipal Hospital from June 2018 to December 2019 were enrolled. According to the recovery of postoperative sinus rhythm (SR), patients with recovered SR were assigned to the research group (Res group, n=60), while those with AF recurrence were included in the control group (Con group, n=27). The transthoracic echocardiography was adopted to measure the changes of left atrium-related parameters of patients before RFCA and at 6 months after surgery, and the transesophageal three-dimensional echocardiography was adopted for measuring the changes of left atrial appendage (LAA)-related parameters. In addition, multivariate logistic regression was performed to analyze the factors influencing postoperative recurrence of AF.

RESULTS

After 6-month follow up, SR was restored in 60 cases and AF recurred in 27 cases. After surgery, the left atrial anteroposterior diameter (LAAPD), left atrial left and right diameter (LALRD), left atrial up and down diameter (LAUDD), maximum volume of left atrium (LAVmax), minimum volume of left atrium (LAVmin), opening diameter of LAA (LAAOD), maximum volume of LAA (LAAVmax), and minimum volume of LAA (LAAV min) of the Res group decreased, and were lower than those of the Con group. In addition, the left atrial ejection fraction (LAEF), vessel function index and dilatation index of the Res group increased significantly postoperatively, and were higher than those of the Con group. The Res group also showed significantly higher LAA area change percentage [LAAAC (%)] and LAA emptying velocity (LAAEV) than the Con group. Moreover, age, history of hypertension, LAVmax and LAAAC (%) were identified to be the independent risk factors for postoperative recurrence of AF.

CONCLUSION

Patients with increased left atrial diameter and volume, large LAAOD, and small ejection fraction are more susceptible to AF recurrence, and LAAOD is a predictor of postoperative recurrence of AF.

Prevalence of asymptomatic atrial fibrillation among multimorbid elderly patients: diagnostic implications

Advancing age of the global population is one of the main reasons for the uprising trend in atrial fibrillation (AF) prevalence worldwide leading to a proper "AF epidemic". Strictly related to the increasing prevalence of AF in the elderly is the relevant burden of cardiac end extra-cardiac comorbidities that these patients show. Patients with AF are frequently asymptomatic (i.e., asymptomatic or silent AF) and thus the arrhythmia is generally underdiagnosed. Detainment of proper treatment in elderly and comorbid patients may potentially result in significant morbidity and mortality. Therefore, in recent years, several screening strategies (systematic vs opportunistic screening) for asymptomatic AF have been developed and early diagnosis of AF is an important treatment goal that can improve prognosis. This review will focus on the prevalence of asymptomatic AF in the elderly, frequently associated comorbidities, screening strategies, and implications for a correct AF diagnosis.

Lack of authentic atrial fibrillation in commonly used murine atrial fibrillation models

The mouse is a useful preclinical species for evaluating disease etiology due to the availability of a wide variety of genetically modified strains and the ability to perform disease-modifying manipulations. In order to establish an atrial filtration (AF) model in our laboratory, we profiled several commonly used murine AF models. We initially evaluated a pharmacological model of acute carbachol (CCh) treatment plus atrial burst pacing in C57BL/6 mice. In an effort to observe micro-reentrant circuits indicative of authentic AF, we employed optical mapping imaging in isolated mouse hearts. While CCh reduced atrial refractoriness and increased atrial tachyarrhythmia vulnerability, the left atrial (LA) excitation patterns were rather regular without reentrant circuits or wavelets. Therefore, the atrial tachyarrhythmia resembled high frequency atrial flutter, not typical AF per se. We next examined both a chronic angiotensin II (Ang II) infusion model and the surgical model of transverse aortic constriction (TAC), which have both been reported to induce atrial and ventricular structural changes that serve as a substrates for micro-reentrant AF. Although we observed some extent of atrial remodeling such as fibrosis or enlarged LA diameter, burst pacing-induced atrial tachyarrhythmia vulnerability did not differ from control mice in either model. This again suggested that an AF-like pathophysiology is difficult to demonstrate in the mouse. To continue searching for a valid murine AF model, we studied mice with a cardiac-specific deficiency (KO) in liver kinase B1 (Cardiac-LKB1), which has been reported to exhibit spontaneous AF. Indeed, the electrocardiograms (ECG) of conscious Cardiac-LKB1 KO mice exhibited no P waves and had irregular RR intervals, which are characteristics of AF. Histological evaluation of Cardiac-LKB1 KO mice revealed dilated and fibrotic atria, again consistent with AF. However, atrial electrograms and optical mapping revealed that electrical activity was limited to the sino-atrial node area with no electrical conduction into the atrial myocardium beyond. Thus, Cardiac-LKB1 KO mice have severe atrial myopathy or atrial standstill, but not AF. In summary, the atrial tachyarrhythmias we observed in the four murine models were distinct from typical human AF, which often exhibits micro- or macro-reentrant atrial circuits. Our results suggest that the four murine AF models we examined may not reflect human AF well, and raise a cautionary note for use of those murine models to study AF.

NICE atrial fibrillation guideline snubs wearable technology: a missed opportunity?

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and a growing public health epidemic. In the UK, over 1.3 million people have a diagnosis of AF and an estimated 400,000 remain undiagnosed. AF-related strokes account for a quarter of all strokes and, as AF episodes are often asymptomatic, are still often the first manifestation of AF. Early diagnosis and initiation of oral anticoagulation, where appropriate, may prevent some of these thromboembolic strokes. Public Health England is committed to decrease the incidence of AF-related strokes and has sponsored initiatives aimed at improving AF detection by promoting the uptake of wearable technologies. However, the National Institute for Health and Care Excellence (NICE) has not recommended wearable technology in their recent AF diagnosis and management guidelines (NG196). Diagnostic accuracy of single-lead electrocardiography (ECG) generated by the latest iteration of wearable devices is excellent and, in many cases, superior to general practitioner interpretation of the 12-lead ECG. High-quality ECG from wearable devices that unequivocally shows AF can expedite AF detection. Otherwise, there is a real risk of delaying AF diagnosis with the potential of devastating consequences for patients and their families.