Screening for atrial fibrillation: a European Heart Rhythm Association (EHRA) consensus document endorsed by the Heart Rhythm Society (HRS), Asia Pacific Heart Rhythm Society (APHRS), and Sociedad Latinoamericana de Estimulación Cardíaca y Electrofisiología (SOLAECE)

Smart watch applications in atrial fibrillation detection: Current state and future directions

INTRODUCTION

Atrial fibrillation (Afib) is a prevalent chronic arrhythmia associated with severe complications, including stroke, heart failure, and increased mortality. This review explores the use of smartwatches for Afib detection, addressing the limitations of current monitoring methods and emphasizing the potential of wearable technology in revolutionizing healthcare.

RESULTS/OBSERVATION

Current Afib detection methods, such as electrocardiography, have limitations in sensitivity and specificity. Smartwatches with advanced sensors offer continuous monitoring, improving the chances of detecting asymptomatic and paroxysmal Afib. The review meticulously examines major clinical trials studying Afib detection using smartwatches, including the landmark Apple Heart Study and ongoing trials such as the Heart Watch, Heartline, and Fitbit Heart Study. Detailed summaries of participant numbers, smartwatch devices used, and key findings are presented. It also comments on the cost-effectiveness and scalability of smartwatch-based screening, highlighting the potential to reduce healthcare costs and improve patient outcomes.

CONCLUSION/RELEVANCE

The integration of wearable technology into healthcare can lead to earlier diagnosis, improved patient engagement, and enhanced cardiac health monitoring. Despite ethical considerations and disparities, the potential benefits outweigh the challenges. This review calls for increased awareness, collaboration with insurance companies, and ongoing research efforts to optimize smartwatch accuracy and encourage widespread adoption of Afib detection. With insights from major trials, this review serves as a comprehensive reference for healthcare professionals and policymakers, guiding future strategies in the early diagnosis and management of atrial fibrillation.

Association of Diagonal Earlobe Crease with Risk of Atrial Fibrillation in Stable Patients with Coronary Artery Disease

Background: Diagonal earlobe crease (DELC) is a proposed visible predictor of coronary artery disease (CAD). However, studies on the association between atrial fibrillation (AF) and DELC are lacking. This study evaluated the association between DELC and the incidence of AF in patients with CAD. Methods: A total of 669 participants aged <65 years (mean, 53.8 ± 7.5 years) diagnosed with CAD and without AF were evaluated for the presence of DELC. The study outcome was the incidence of AF based on the presence of DELC. The study period was planned for 60 months with a minimum follow-up period of 12 months. Results: Herein, the incidence of DELC was 10.8%. During the follow-up period (44.6 ± 14.9 months), the incidences of AF development were 16.4% and 8.4% in DELC and non-DELC groups, respectively. Kaplan-Meier analysis revealed that the occurrence of AF was significantly higher in the DELC group than in the non-DELC group (log-rank test, p = 0.02). Compared with patients without DELC, patients with DELC had a high risk of AF development (adjusted hazard ratio = 1.88, 95% confidence interval = 1.01-3.53). Conclusions: DELC is associated with an increased risk of AF in patients with CAD. These findings may aid in the detection of AF in patients with CAD.

Effects of atrial fibrillation screening according to thyroid function: Post-hoc analysis of the randomized LOOP study

PURPOSE

Subclinical thyroid dysfunction is a marker for atrial fibrillation (AF) and stroke risk. This study explored the effects of AF screening according to thyroid-stimulating hormone (TSH) levels.

METHODS

An AF screening trial (the LOOP study) was analyzed post-hoc according to baseline TSH. The primary outcome was stroke or systemic embolism (SE). Secondary outcomes included major bleeding, all-cause death, and the combination of stroke, SE, and cardiovascular death.

RESULTS

TSH measurement was available in 6003 of 6004 trial participants, 1500 randomized to implantable loop recorder (ILR) screening for AF and anticoagulation upon detection vs. 4503 to usual care; mean age was 74.7±4.1 years and 2836 (47%) were women. AF detection was approximately triple for ILR vs usual care across TSH tertiles (adjusted p-interaction=0.44). In the first tertile, screening was associated with decreased risk of the primary outcome (hazard ratio 0.52 [0.30-0.90]; p=0.02) and stroke, SE, or cardiovascular death (hazard ratio 0.54 [0.34-0.84]; p=0.006) compared to usual care, while no effect was observed among participants with higher TSH (adjusted p-interaction 0.03 and 0.01, respectively). There was no effect on other outcomes. Analyses of continuous TSH or excluding those with abnormal TSH or thyroid medication showed similar results.

CONCLUSION

AF screening and subsequent treatment was associated with decreased stroke risk among participants with low TSH, though the yield of screening was similar across TSH levels. TSH may be useful as a marker to indicate benefit from AF screening vs. overdiagnosis and overtreatment. These findings should be considered exploratory and warrant further study.

TRIAL REGISTRATION

ClinicalTrials.gov, identifier: NCT0203645.

Novel Technologies in the Detection of Atrial Fibrillation: Review of Literature and Comparison of Different Novel Technologies for Screening of Atrial Fibrillation

Atrial fibrillation (AF) is globally the most common arrhythmia associated with significant morbidity and mortality. It impairs the quality of the patient's life, imposing a remarkable burden on public health, and the healthcare budget. The detection of AF is important in the decision to initiate anticoagulation therapy to prevent thromboembolic events. Nonetheless, AF detection is still a major clinical challenge as AF is often paroxysmal and asymptomatic. AF screening recommendations include opportunistic or systematic screening in patients ≥65 years of age or in those individuals with other characteristics pointing to an increased risk of stroke. The popularities of well-being and taking personal responsibility for one's own health are reflected in the continuous development and growth of mobile health technologies. These novel mobile health technologies could provide a cost-effective solution for AF screening and an additional opportunity to detect AF, particularly its paroxysmal and asymptomatic forms.

Innovative approaches to atrial fibrillation prediction: should polygenic scores and machine learning be implemented in clinical practice?

Atrial fibrillation (AF) prediction and screening are of important clinical interest because of the potential to prevent serious adverse events. Devices capable of detecting short episodes of arrhythmia are now widely available. Although it has recently been suggested that some high-risk patients with AF detected on implantable devices may benefit from anticoagulation, long-term management remains challenging in lower-risk patients and in those with AF detected on monitors or wearable devices as the development of clinically meaningful arrhythmia burden in this group remains unknown. Identification and prediction of clinically relevant AF is therefore of unprecedented importance to the cardiologic community. Family history and underlying genetic markers are important risk factors for AF. Recent studies suggest a good predictive ability of polygenic risk scores, with a possible additive value to clinical AF prediction scores. Artificial intelligence, enabled by the exponentially increasing computing power and digital data sets, has gained traction in the past decade and is of increasing interest in AF prediction using a single or multiple lead sinus rhythm electrocardiogram. Integrating these novel approaches could help predict AF substrate severity, thereby potentially improving the effectiveness of AF screening and personalizing the management of patients presenting with conditions such as embolic stroke of undetermined source or subclinical AF. This review presents current evidence surrounding deep learning and polygenic risk scores in the prediction of incident AF and provides a futuristic outlook on possible ways of implementing these modalities into clinical practice, while considering current limitations and required areas of improvement.

Role of the Electrocardiogram for Identifying the Development of Atrial Fibrillation

Atrial fibrillation (AF), a prevalent cardiac arrhythmia, is associated with increased morbidity and mortality worldwide. Stroke, the leading cause of serious disability in the United States, is among the important complications of this arrhythmia. Recent studies have demonstrated that certain clinical variables can be useful in the prediction of AF development in the future. The electrocardiogram (ECG) is a simple and cost-effective technology that is widely available in various healthcare settings. An emerging body of evidence has suggested that ECG tracings preceding the development of AF can be useful in predicting this arrhythmia in the future. Various variables on ECG especially different P wave parameters have been investigated in the prediction of new-onset AF and found to be useful. Several risk models were also introduced using these variables along with the patient's clinical data. However, current guidelines do not provide a clear consensus regarding implementing these prediction models in clinical practice for identifying patients at risk of AF. Also, the role of intensive screening via ECG or implantable devices based on this scoring system is unclear. The purpose of this review is to summarize AF and various related terminologies and explain the pathophysiology and electrocardiographic features of this tachyarrhythmia. We also discuss the predictive electrocardiographic features of AF, review some of the existing risk models and scoring system, and shed light on the role of monitoring device for screening purposes.

Association of atrial mechanical dispersion with atrial fibrillation recurrence following catheter ablation: results of the ASTRA-AF pilot study

AIMS

For patients with symptomatic drug-refractory atrial fibrillation (AF), catheter ablation to achieve rhythm control is an important therapeutic option. The atrial mechanical dispersion measured as standard deviation of the time to peak strain (SD-TPS) is associated with the risk of AF recurrence following catheter ablation.

METHODS

The study cohort prospectively enrolled n = 132 consecutive patients with paroxysmal (n = 88) or persistent AF (n = 44) presenting for de novo pulmonary vein isolation (PVI) and followed for 1 year. We related left atrial (LA) volume, LA ejection fraction, SD-TPS, and global longitudinal strain of the left ventricle and clinical variables (sex, age, and type of AF) to AF recurrence.

RESULTS

Kaplan-Meier curves showed higher AF recurrence rate with an increase of SD-TPS with the calculated cut-off of 38.6 ms. Uni- and multivariable Cox regression analysis could show that SD-TPS had the highest relevance regarding AF recurrence with a HR of 1.05 (95% CI, 1.01; 1.09, p = 0.01) and HR of 1.05 (95% CI, 1.01; 1.09, p = 0.02) per 10 ms increase. In the additional analyses for the model including the clinical variables age, sex, and type of AF with paroxysmal or persisting AF, SD-TPS did only show a trend and after adjusting for covariates, SD-TPS showed a HR of 1.04 (95% CI, 0.99; 1.09, p = 0.09) per 10 ms increase.

CONCLUSION

Atrial mechanical dispersion was associated with recurrent AF.

Enablers and Hindrances of Lifestyle Changes Among Patients With Atrial Fibrillation: A Qualitative Study

BACKGROUND

Atrial fibrillation (AF) seriously affects the health status and quality of life of affected patients. However, the lifestyle changes recommended by the guidelines for patients are not ideal. Hence, understanding the factors that promote and hinder healthy behavior changes in patients with AF is crucial for self-management.

OBJECTIVE

The aims of this study were to understand the factors enabling and hindering health behaviors in patients with AF and to provide a reference for promoting health management among these patients.

METHODS

Using the purposive sampling method, 22 patients with AF admitted to the Cardiac Center of Beijing Chaoyang Hospital, Capital Medical University, from March 2021 to June 2021 were selected for in-depth face-to-face interviews. The thematic analysis method was used to summarize and refine the themes.

RESULTS

The following 2 themes and 15 subthemes were eventually extracted by analyzing and summarizing the interview data. The 7 factors facilitating health behaviors in patients with AF were risk perception, outcome expectancy, behavioral intention, action plan, response plan, self-efficacy, and social support. There were 8 hindering factors: personal preferences and habits, specific customary culture, weak self-control, accessibility of exercise conditions, symptom-related distress, cognitive weakness, multiple medication use, and insufficient awareness of condition monitoring.

CONCLUSIONS

The factors affecting health behaviors in patients with AF are complex, and healthcare providers should reinforce the facilitators of health behaviors in these patients and provide them with targeted interventions against hindering factors. Results can be used to develop health behavior intervention programs for patients with AF.

Prediction of atrial fibrillation from at-home single-lead ECG signals without arrhythmias

Early identification of atrial fibrillation (AF) can reduce the risk of stroke, heart failure, and other serious cardiovascular outcomes. However, paroxysmal AF may not be detected even after a two-week continuous monitoring period. We developed a model to quantify the risk of near-term AF in a two-week period, based on AF-free ECG intervals of up to 24 h from 459,889 patch-based ambulatory single-lead ECG (modified lead II) recordings of up to 14 days. A deep learning model was used to integrate ECG morphology data with demographic and heart rhythm features toward AF prediction. Observing a 1-day AF-free ECG recording, the model with deep learning features produced the most accurate prediction of near-term AF with an area under the curve AUC = 0.80 (95% confidence interval, CI = 0.79-0.81), significantly improving discrimination compared to demographic metrics alone (AUC 0.67; CI = 0.66-0.68). Our model was able to predict incident AF over a two-week time frame with high discrimination, based on AF-free single-lead ECG recordings of various lengths. Application of the model may enable a digital strategy for improving diagnostic capture of AF by risk stratifying individuals with AF-negative ambulatory monitoring for prolonged or recurrent monitoring, potentially leading to more rapid initiation of treatment.

Sinus node dysfunction and stroke risk: a systematic review and meta-analysis

OBJECTIVES

The role of cardiac arrhythmia in ischaemic stroke is widely studied, but the size of the stroke risk in patients with sinus node dysfunction (SND) with and without atrial fibrillation (AF) is unclear. This systematic review and meta-analysis aimed to compare the risk of stroke and its associated factors in patients with SND with and without AF.

DESIGN

A systematic review and meta-analysis was conducted based on the Grading of Recommendations, Assessment, Development and Evaluation approach.

DATA SOURCES

PubMed, EMBASE and Cochrane Database were searched until December 2022.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Studies that investigate stroke in patients with SND diagnosed with or without AF/atrial flutter.

DATA EXTRACTION AND SYNTHESIS

Two independent authors screened studies for inclusion and extracted data. Literature quality assessment was performed using the Newcastle-Ottawa Scale and the Cochrane Collaboration Tool. The overall risk of stroke was estimated using the random-effects model. The generic inverse variance method was used to calculate the pooled estimates of stroke-associated factors. We performed a sensitivity analysis using a fixed-effects model.

RESULTS

Of the 929 records retrieved, 6 papers (106 163 patients) met the inclusion criteria. The average yearly stroke incidence in patients with SND was 1.542% (95% CI: 1.334% to 1.749%). The stroke incidence was similar between the isolated SND (1.587%; 95% CI: 1.510% to 1.664%) and non-isolated (SND+AF) (1.660%; 95% CI: 0.705% to 2.615%) groups. AF (HR, 95% CI: 1.53 (1.01 to 2.33)), stroke/transient ischaemia attack/other thrombotic events (HR, 95% CI: 2.54 (1.14 to 5.69)), hypertension (HR, 95% CI: 1.51 (1.11 to 2.07)) and heart failure (HR, 95% CI: 1.41 (1.01 to 1.97)) were associated with stroke in the SND population.

CONCLUSION

Our findings suggest that patients with SND carry a similar risk of stroke to those with combined SND and AF. Future studies are needed to investigate whether interventions targeting stroke prevention, such as anticoagulation therapy, can help to prevent stroke in patients with SND.

PROSPERO REGISTRATION NUMBER

CRD42023408436.

Stroke prevention and intracranial hemorrhage risk in atrial fibrillation management: A mini review

This mini-review examines the management of atrial fibrillation (AF) in patients at high risk of bleeding, with a focus on stroke prevention and intracranial hemorrhage risk. Anticoagulant therapy is commonly advised for AF patients, but it can elevate the risk of intracranial hemorrhage in certain individuals prone to bleeding. Two primary perspectives for managing high-risk patients are discussed: adhering to strict anticoagulation therapy or opting for alternative treatments like left atrial appendage closure (LAAC) or aspirin. The benefits and drawbacks of each approach are evaluated, emphasizing the importance of a personalized management plan based on patient risk profiles, comorbidities, and preferences. Ongoing research, including artificial intelligence, advances in LAAC devices, and combination therapies, is explored to enhance stroke prevention and minimize bleeding risk in AF management. A multidisciplinary approach and continuous investigation are vital to achieving better patient outcomes and overall care in this context.

EHRA expert consensus document on the management of arrhythmias in frailty syndrome, endorsed by the Heart Rhythm Society (HRS), Asia Pacific Heart Rhythm Society (APHRS), Latin America Heart Rhythm Society (LAHRS), and Cardiac Arrhythmia Society of Southern Africa (CASSA)

There is an increasing proportion of the general population surviving to old age with significant chronic disease, multi-morbidity, and disability. The prevalence of pre-frail state and frailty syndrome increases exponentially with advancing age and is associated with greater morbidity, disability, hospitalization, institutionalization, mortality, and health care resource use. Frailty represents a global problem, making early identification, evaluation, and treatment to prevent the cascade of events leading from functional decline to disability and death, one of the challenges of geriatric and general medicine. Cardiac arrhythmias are common in advancing age, chronic illness, and frailty and include a broad spectrum of rhythm and conduction abnormalities. However, no systematic studies or recommendations on the management of arrhythmias are available specifically for the elderly and frail population, and the uptake of many effective antiarrhythmic therapies in these patients remains the slowest. This European Heart Rhythm Association (EHRA) consensus document focuses on the biology of frailty, common comorbidities, and methods of assessing frailty, in respect to a specific issue of arrhythmias and conduction disease, provide evidence base advice on the management of arrhythmias in patients with frailty syndrome, and identifies knowledge gaps and directions for future research.

[Asymptomatic atrial fibrillation : Screening and therapy]

Atrial fibrillation (AF) is the most common cardiac arrhythmia affecting millions of people worldwide and poses a significant burden to the health care system. AF screening of the general population or of a specific higher-risk population could not only lead to earlier detection of AF but also to a prompt initiation of an adequate therapy to prevent complications such as stroke or death and consecutively to a potential reduction of health care costs, especially in asymptomatic AF patients. To conduct screening programs, accessible new technology devices such as "wearables", smartwatches, and implantable event recorders provide an innovative solution. However, as data regarding screening are inconclusive, routine AF screening of the population is currently not recommended by the European Society of Cardiology. Recently published studies have indicated that anticoagulation and early rhythm control of asymptomatic AF could avoid occurrence of clinical endpoints. This article reports on the scientific results of the current literature as well as gaps of evidence and discusses possible treatment options of asymptomatic AF.

Evaluation of Huawei smart wearables for detection of atrial fibrillation in patients following ischemic stroke: The Liverpool-Huawei stroke study

BACKGROUND

Atrial fibrillation (AF) often remains undetected following stroke. Documenting AF is critical to initiate oral anticoagulation, which has proven benefit in reducing recurrent stroke and mortality in patients with AF. The accuracy and acceptability of using smart wearables to detect AF in patients following stroke is unknown.

METHODS

The aims of the Liverpool-Huawei Stroke Study are to determine the effectiveness, cost-effectiveness and patient and staff acceptability of using Huawei smart wearables to detect AF following ischemic stroke. The study plans to recruit 1,000 adults aged ≥18 years following ischemic stroke from participating hospitals over 12 months. All participants will be asked to wear a Huawei smart band for 4 weeks postdischarge. If participants do not have access to a compatible smartphone required for the study, they will be provided with a smartphone for the 4-week AF monitoring period.

RESULTS

Participants with suspected AF detected by the smart wearables, without previous known AF, will be referred for further evaluation. To determine the effectiveness of the Huawei smart wearables to detect AF, the positive predictive value will be determined. Patient acceptability of using this technology will also be examined. Additional follow-up assessments will be conducted at 6 and 12 months, and clinical outcomes recorded in relation to prevalent and incident AF post-stroke. The study opened for recruitment on May 30, 2022, and is currently open at 4 participating hospitals; the first 106 participants have been recruited. One further hospital is preparing to open for recruitment.

CONCLUSIONS

This prospective study will examine the effectiveness and acceptability of the use of smart wearables in patients following ischemic stroke. This could have important implications for detection of AF and therefore, earlier prophylaxis for recurrent stroke. The study is registered on https://www.isrctn.com/ (Identifier ISRCTN30693819).

Higher coronary artery calcium score is associated with increased risk of atrial fibrillation recurrence after catheter ablation

BACKGROUND

Coronary artery calcium score (CACS) is associated with an increased risk of atrial fibrillation (AF) development, but scarce data are available regarding the impact on AF recurrence. This study aims to assess the impact of CACS on AF recurrence following catheter ablation.

METHODS

Retrospective study of patients with AF undergoing cardiac computed tomography (CCT) before ablation (2017-2019). Patients with coronary artery disease (CAD), significant valvular heart disease and previous catheter ablation were excluded. A cut-off of CACS ≥ 100 was used according to literature.

RESULTS

A total of 311 patients were included (median age 57 [48, 64] years, 65% men and 21% with persistent AF). More than half of the patients had a CACS > 0 (52%) and 18% a CACS ≥ 100. Patients with CACS ≥ 100 were older (64 [59, 69] vs 55 [46, 63] years, p ​< ​0.001), had more frequently hypertension (68% vs 42%, p ​< ​0.001) and diabetes mellitus (21% vs 10%, p ​= ​0.020). During a median follow-up of 34 months (12-57 months), 98 patients (32%) had AF recurrence. CACS ≥ 100 was associated with increased risk of AF recurrence (unadjusted Cox regression: hazard ratio [HR] 2.0; 95% confidence interval [CI], 1.3-3.1, p ​= ​0.002). After covariate adjustment, CACS ≥ 100 and persistent AF remained independent predictors of AF recurrence (HR, 1.7; 95% CI, 1.0-2.8, p ​= ​0.039 and HR, 2.0; 95% CI, 1.3-3.2, p ​= ​0.004, respectively).

CONCLUSION

An opportunistic evaluation of CACS could be an important tool to improve clinical care considering that CACS ≥ 100 was independently associated with a 69% increase in the risk of AF recurrence after first catheter ablation.

Prevalence of atrial fibrillation : The Swiss population-based CoLaus|PsyCoLaus study

BACKGROUND

Atrial fibrillation (AF) is the most common arrhythmia worldwide and is associated with increased morbi-mortality. The prevalence of AF in the Western world is increasing; however, reports on the prevalence of AF in the past decade are scarce, and whether the prevalence of AF increased during the last decade in Switzerland remains uncertain. Therefore, using data from a Swiss population-based sample, we aimed to assess the point prevalence of AF from 2014 to 2017 and to investigate determinants of AF.

METHODS

A cross-sectional analysis of 4616 Caucasian participants aged 45-86 years (55% women) from a population-based sample was designed to explore the point prevalence and determinants of cardiovascular risk factors in the population of Lausanne, Switzerland. AF was assessed using electrocardiography (ECG) between 2014 and 2017.

RESULTS

Overall, the point prevalence of AF was 0.9% (95% confidence interval [95% CI]: 0.7-1.2%) and the combined AF + atrial flutter (AFL) point prevalence was 1.1% (95% CI: 8.4-1.5%). The point prevalence of AF was higher among men (81% vs. 19% in women) and increased with age, reaching 3.1% in participants aged ≥ 80. In multivariable analysis, male gender (odds ratio and 95% CI: 4.98 [1.01-24.6]) and increasing age (2.86 [1.40-5.87] per decade) were associated with AF.

CONCLUSION

The point prevalence of AF and of AF + AFL, assessed between 2014 and 2017 in the city of Lausanne (Switzerland), was low but increased with age and in men.

Atrial fibrillation and stroke

INTRODUCTION

Stroke is one of the leading causes of mortality and morbidity globally. Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia. It is set to reach epidemic proportions. AF is associated with a five-fold increase in risk of stroke. Strokes caused by AF more often are fatal or result in severe disability. Even though the incidence of stroke has been significantly reduced by oral anticoagulation, AF is thought to account for a significant proportion of cryptogenic strokes where no etiology is identified.

AREAS COVERED

This article reviews the literature related to AF and stroke, pathophysiological insights, diagnosis of AF in stroke patients, and its management (Graphical Abstract).

EXPERT OPINION

The pathophysiology of thrombogenesis that links AF and stroke is not well understood and is an area of active research to identify new therapeutic targets to prevent AF and stroke. As the nature of AF and stroke is multifaceted, an integrated care approach to managing AF and stroke is increasingly essential.

Machine learning for atrial fibrillation risk prediction in patients with sleep apnea and coronary artery disease

Background

Patients with sleep apnea (SA) and coronary artery disease (CAD) are at higher risk of atrial fibrillation (AF) than the general population. Our objectives were: to evaluate the role of CAD and SA in determining AF risk through cluster and survival analysis, and to develop a risk model for predicting AF.

Methods

Electronic medical record (EMR) database from 22,302 individuals including 10,202 individuals with AF, CAD, and SA, and 12,100 individuals without these diseases were analyzed using K-means clustering technique; k-nearest neighbor (kNN) algorithm and survival analysis. Age, sex, and diseases developed for each individual during 9 years were used for cluster and survival analysis.

Results

The risk models for AF, CAD, and SA were identified with high accuracy and sensitivity (0.98). Cluster analysis showed that CAD and high blood pressure (HBP) are the most prevalent diseases in the AF group, HBP is the most prevalent disease in CAD; and HBP and CAD are the most prevalent diseases in the SA group. Survival analysis demonstrated that individuals with HBP, CAD, and SA had a 1.5-fold increased risk of developing AF [hazard ratio (HR): 1.49, 95% CI: 1.18-1.87, p = 0.0041; HR: 1.46, 95% CI: 1.09-1.96, p = 0.01; HR: 1.54, 95% CI: 1.22-1.94, p = 0.0039, respectively] and individuals with chronic kidney disease (CKD) developed AF approximately 50% earlier than patients without these comorbidities in a period of 7 years (HR: 3.36, 95% CI: 1.46-7.73, p = 0.0023). Comorbidities that contributed to develop AF earlier in females compared to males in the group of 50-64 years were HBP (HR: 3.75 95% CI: 1.08-13, p = 0.04) CAD and SA in the group of 60-75 years were (HR: 2.4 95% CI: 1.18-4.86, p = 0.02; HR: 2.51, 95% CI: 1.14-5.52, p = 0.02, respectively).

Conclusion

Machine learning based algorithms demonstrated that CAD, SA, HBP, and CKD are significant risk factors for developing AF in a Latin-American population.

Serial 7-Day Electrocardiogram Patch Screening for AF in High-Risk Older Women by the CHARGE-AF Score

BACKGROUND

Asymptomatic atrial fibrillation (AF) is associated with an increased risk of stroke. The yield of serial electrocardiographic (ECG) screening for AF is unknown.

OBJECTIVES

The aim of this study was to determine the frequency of AF detected by serial, 7-day ECG patch screenings in older women identified as having an elevated risk of AF according to the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology)-AF clinical prediction score.

METHODS

Postmenopausal women with a 5-year predicted risk of new-onset AF ≥5% according to CHARGE-AF were recruited from the ongoing WHISH (Women's Health Initiative Strong and Healthy) randomized trial of a physical activity intervention. Participants with AF at baseline by self-report or medical records review were excluded. Screening with 7-day ECG patch monitors was performed at baseline, 6 months, and 12 months from study enrollment.

RESULTS

On baseline monitoring, 2.5% of the cohort had AF detected, increasing to 3.7% by 6 months and 4.9% cumulatively by 12 months. Yield of patch screening was higher among participants with a higher (≥10%) CHARGE-AF score: 4.2% had AF detected at baseline, 5.9% at 6 months, and 7.2% at 12 months. Most participants with patch-identified AF never had a clinical diagnosis of AF (36 of 46 [78%]).

CONCLUSIONS

Older women with an elevated CHARGE-AF score had a high prevalence of AF on 7-day ECG patch screening. Serial screening over 12 months substantially increased the detection of AF. These data can be useful in helping identify high-risk participants for enrollment in future studies of the management of asymptomatic AF.(Women's Health Initiative Silent Atrial Fibrillation Recording Study [WHISH STAR]; NCT05366803.).

Feasibility of screening for atrial fibrillation in a domiciliary setting: opportunistic one-time screening at preventive home visits in municipalities

Current evidence base for atrial fibrillation (AF) screening is insufficient. An important finding in the STROKESTOP study was that non-participants had significantly worse outcomes. In a group of potentially non-participants feasibility of opportunistic screening in a domiciliary setting with municipality preventive home visits to citizens ≥75 years was investigated. Handheld ECG device was used by trained municipality caregivers followed by cardiologist assessment. Eighty-five percent consented to being screened, and seven of 477 screened were found with AF. Opportunistic screening in preventive home visits had a high participation rate and was feasible. Randomized trials are needed before making any firm conclusions.

Clinical applications of heart rhythm monitoring tools in symptomatic patients and for screening in high-risk groups

Recent technological advances have facilitated and diversified the options available for the diagnosis of cardiac arrhythmias. Ranging from simple resting or exercise electrocardiograms to more sophisticated and expensive smartphones and implantable cardiac monitors. These tests and devices may be used for varying periods of time depending on symptom frequency. The choice of the most appropriate heart rhythm test should be guided by clinical evaluation and optimized following accurate characterization of underlying symptoms, 'red flags', risk factors, and consideration of cost-effectiveness of the different tests. This review provides evidence-based guidance for assessing suspected arrhythmia in patients who present with symptoms or in the context of screening, such as atrial fibrillation or advanced conduction disturbances following transcatheter aortic valve implantation in high-risk groups. This is intended to help clinicians choose the most appropriate diagnostic tool to facilitate the management of patients with suspected arrhythmias.

Cluster randomised controlled trial of screening for atrial fibrillation in people aged 70 years and over to reduce stroke: protocol for the pilot study for the SAFER trial

INTRODUCTION

Atrial fibrillation (AF) is a common arrhythmia associated with 30% of strokes, as well as other cardiovascular disease, dementia and death. AF meets many criteria for screening, but there is limited evidence that AF screening reduces stroke. Consequently, no countries recommend national screening programmes for AF. The Screening for Atrial Fibrillation with ECG to Reduce stroke (SAFER) trial aims to determine whether screening for AF is effective at reducing risk of stroke. The aim of the pilot study is to assess feasibility of the main trial and inform implementation of screening and trial procedures.

METHODS AND ANALYSIS

SAFER is planned to be a pragmatic randomised controlled trial (RCT) of over 100 000 participants aged 70 years and over, not on long-term anticoagulation therapy at baseline, with an average follow-up of 5 years. Participants are asked to record four traces every day for 3 weeks on a hand-held single-lead ECG device. Cardiologists remotely confirm episodes of AF identified by the device algorithm, and general practitioners follow-up with anticoagulation as appropriate. The pilot study is a cluster RCT in 36 UK general practices, randomised 2:1 control to intervention, recruiting approximately 12 600 participants. Pilot study outcomes include AF detection rate, anticoagulation uptake and other parameters to incorporate into sample size calculations for the main trial. Questionnaires sent to a sample of participants will assess impact of screening on psychological health. Process evaluation and qualitative studies will underpin implementation of screening during the main trial. An economic evaluation using the pilot data will confirm whether it is plausible that screening might be cost-effective.

ETHICS AND DISSEMINATION

The London-Central Research Ethics Committee (19/LO/1597) and Confidentiality Advisory Group (19/CAG/0226) provided ethical approval. Dissemination will be via publications, patient-friendly summaries, reports and engagement with the UK National Screening Committee.

TRIAL REGISTRATION NUMBER

ISRCTN72104369.

Reimbursement practices for use of digital devices in atrial fibrillation and other arrhythmias: a European Heart Rhythm Association survey

AIMS

Since digital devices are increasingly used in cardiology for assessing cardiac rhythm and detecting arrhythmias, especially atrial fibrillation (AF), our aim was to evaluate the expectations and opinions of healthcare professionals in Europe on reimbursement policies for the use of digital devices (including wearables) in AF and other arrhythmias.

METHODS AND RESULTS

An anonymous survey was proposed through announcements on the European Heart Rhythm Association website, social media channels, and mail newsletter. Two hundred and seventeen healthcare professionals participated in the survey: 32.7%, reported regular use of digital devices, 45.2% reported that they sometimes use these tools, 18.6% that they do not use but would like to. Only a minority (3.5%) reported a lack of trust in digital devices. The survey highlighted a general propensity to provide medical consultation for suspected AF or other arrhythmias detected by a consumer-initiated use of digital devices, even if time constraints and reimbursement availability emerged as important elements. More than 85% of respondents agreed that reimbursement should be applied for clinical use of digital devices, also in different settings such as post-stroke, post-cardioversion, post-ablation, and in patients with palpitations or syncope. Finally, 73.6% of respondents confirmed a lack of reimbursement fees in their country for physicians' consultations (tracings interpretation) related to digital devices.

CONCLUSIONS

Digital devices, including wearables, are increasingly and widely used for assessing cardiac rhythm and detecting AF, but a definition of reimbursement policies for physicians' consultations is needed.

Wearable device use and technology preferences in cancer survivors with or at risk for atrial fibrillation

Background

Cancer survivors face increased risk of heart disease, including atrial fibrillation (AF). Certain types of technology, such as consumer wearable devices, can be useful to monitor for AF, but little is known about wearables and AF monitoring in cancer survivor populations.

Objective

The purpose of this study was to understand technology usage and preferences in cancer survivors with or at risk for AF, and to describe demographic factors associated with wearable device ownership in this population.

Methods

Eligible patients completed a remote survey assessment regarding use of commercial wearable devices. The survey contained questions designed to assess commercial wearable device use, electronic health communications, and perceptions regarding the participant's cardiac health.

Results

A total of 424 cancer survivors (mean age 74.2 years; 53.1% female; 98.8% white) were studied. Although most participants owned a smartphone (85.9%), only 31.8% owned a wearable device. Over half (53.5%) of cancer survivors were worried about their heart health. Overall, patients believed arrhythmias (79.7%) were the most important heart condition for a wearable to detect. Survivors reported being most willing to share blood pressure (95.6%) and heart rate (95.3%) data with their providers and were least willing to share information about their diet, weight, and physical activity using these devices.

Conclusion

Understanding factors such as device ownership, usage, and heart health concerns in cancer survivors can play an important role in improving cardiovascular monitoring and its accessibility. Long-term patient outcomes may be improved by incorporating wearable devices into routine care of cancer survivors.

Sensitivity and specificity of automated blood pressure devices to detect atrial fibrillation: A systematic review and meta-analysis of diagnostic accuracy

Background

Atrial fibrillation (AF) is a prevalent and preventable cause of stroke and mortality.

Aim

This systematic review and meta-analysis aimed to investigate the sensitivity and specificity of office and out-of-office automated blood pressure (BP) devices to detect AF.

Methods

Diagnostic studies, extracted from databases such as Ovid Medline and Embase, on AF detection by BP device(s), electrocardiography, and reported sensitivity and specificity, were included. Screening of abstracts and full texts, data extraction, and quality assessment were conducted independently by two investigators using Covidence software. The sensitivity and specificity of the BP devices were pooled using a random-effects model.

Results

Sixteen studies including 10,158 participants were included. Only a few studies were conducted in primary care (n = 3) or with a low risk of bias (n = 5). Office BP devices, which utilised different algorithms to detect AF, had a sensitivity and specificity of 96.2 and 94%, respectively. Specificity was reduced when only one positive result was considered among consecutive BP measurements. Only a few studies (n = 3) investigated out-of-office BP. Only one study (n = 100) suggested the use of ≥79 and ≥26% of positive readings on 24-h ambulatory BP measurements to detect AF and paroxysmal AF, respectively.

Conclusions

Office BP devices can be used clinically to screen for AF in high-risk populations. Clinical trials are needed to determine the effect of AF screening using office BP devices in reducing stroke risk and mortality. Further studies are also required to guide out-of-office use of BP devices for detecting paroxysmal AF or AF.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022319541, PROSPERO CRD42022319541.

Screening, Diagnosis and Management of Atrial Fibrillation in Cancer Patients: Current Evidence and Future Perspectives

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia in the general population, carrying a high morbimortality burden, and this also holds true in cancer patients. The association between AF and cancer goes even further, with some studies suggesting that AF can be a marker of occult cancer. There is, however, a remarkable paucity of data concerning specific challenges of AF management in cancer patients. AF prompt recognition and management in this special population can lessen the arrhythmia-related morbidity and have an important prognostic benefit. This review will focus on current AF diagnosis and management challenges in cancer patients, with special emphasis on AF screening strategies and devices, and anticoagulation therapy with non-vitamin K antagonist oral anti-coagulants (NOACs) for thromboembolic prevention in these patients. Some insights concerning future perspectives for AF prevention, diagnosis, and treatment in this special population will also be addressed.

Automated detection of atrial fibrillation based on vocal features analysis

INTRODUCTION

Early detection of atrial fibrillation (AF) is desirable but challenging due to the often-asymptomatic nature of AF. Known screening methods are limited and most of them depend of electrocardiography or other techniques with direct contact with the skin. Analysis of voice signals from natural speech has been reported for several applications in medicine. The study goal was to evaluate the usefulness of vocal features analysis for the detection of AF.

METHODS

This prospective study was performed in two medical centers. Patients with persistent AF admitted for cardioversion were enrolled. The patients pronounced the vowels "Ahh" and "Ohh" were recorded synchronously with an ECG tracing. An algorithm was developed to provide an "AF indicator" for detection of AF from the speech signal.

RESULTS

A total of 158 patients were recruited. The final analysis of "Ahh" and "Ohh" syllables was performed on 143 and 142 patients, respectively. The mean age was 71.4 ± 9.3 and 43% of patients were females. The developed AF indicator was reliable. Its numerical value decreased significantly in sinus rhythm (SR) after the cardioversion ("Ahh": from 13.98 ± 3.10 to 7.49 ± 1.58; "Ohh": from 11.39 ± 2.99 to 2.99 ± 1.61). The values at SR were significantly more homogenous compared to AF as indicated by a lower standard deviation. The area under the receiver operating characteristic curve was >0.98 and >0.89 ("Ahh" and "Ohh," respectively, p < .001). The AF indicator sensitivity is 95% with 82% specificity.

CONCLUSION

This study is the first report to demonstrate feasibility and reliability of the identification of AF episodes using voice analysis with acceptable accuracy, within the identified limitations of our study methods. The developed AF indicator has higher accuracy using the "Ahh" syllable versus "Ohh."

Prevalence and risk of atrial fibrillation in China: A national cross-sectional epidemiological study

BACKGROUND

Atrial fibrillation (AF) is the most common persistent cardiac arrhythmia. This study aimed to estimate its prevalence and explore associated factors in adults aged 18 years or older in China.

METHODS

Study data were derived from a national sample from July 2020 to September 2021. Participants were recruited using a multistage stratified sampling method from twenty-two provinces, autonomous regions, and municipalities in China. AF was determined based on a history of diagnosed AF or electrocardiogram results.

FINDINGS

A total of 114,039 respondents were included in the final analysis with a mean age of 55 years (standard deviation 17), 52·1% of whom were women. The crude prevalence of AF was 2·3% (95% confidence interval [CI] 1·7-2·8) and increased with age. The age-standardized AF prevalence was 1·6% (95% CI 1·6-1·7%) overall, and 1·7% (1·6-1·8%), 1·4% (1·3-1·5%), 1·6% (95% CI 1·5-1·7%), and 1·7% (1·6-1·9%) in men, women, urban areas, and rural areas, respectively. The prevalence was higher in the central regions (2·5%, 2·3-2·7%) than in the western regions (1·5%, 1·0-2·0%) and eastern regions (1·1%, 1·0-1·2%) in the overall population, either in the gender or residency subgroups. The associated factors for AF included age (per 10 years; odds ratio 1·41 [95% CI 1·38-1·46]; p < 0·001), men (1·34 [1·24-1·45]; p < 0·001), hypertension (1·22 [1·12-1·33]; p < 0·001), coronary heart disease (1·44 [1·28-1·62]; p < 0·001), chronic heart failure (3·70 [3·22-4·26]; p < 0·001), valvular heart disease (2·13 [1·72-2·63]; p < 0·001), and transient ischaemic attack/stroke (1·22 [1·04-1·43]; p = 0·013).

INTERPRETATION

The prevalence of AF was 1.6% in the Chinese adult population and increased with age, with significant geographic variation. Older age, male sex, and cardiovascular disease were potent factors associated with AF. It is crucial to increase the awareness of AF and disseminate standardized treatment in clinical settings to reduce the disease burden.

FUNDING

This research was supported the Nature Science Foundation of Hubei province (No: 2017CFB204).

Direct-to-consumer detection of atrial fibrillation in a smartwatch electrocardiogram: Medical overuse, medicalisation and the experience of consumers

The Apple Watch Electrocardiogram (ECG) is a digital feature that detects signs of atrial fibrillation (AFib), a heart arrhythmia that can lead to stroke. Unlike AFib detection offered in a clinical setting to patients or those at higher risk, the Apple Watch ECG is a direct-to-consumer (DTC) product marketed to the healthy as a self-performed medical test. The feature is incorporated in the design as one of many applications in a multifunctional smartwatch. The Apple Watch ECG signals the movement of consumer wearables into the domain of medical devices, and the highly contested practice of AFib screening. This article examines how this technology produces new avenues for medical overuse among people who are unlikely to gain clinical benefit, and who as active consumers become medicalised via taking part in disease-specific monitoring. Interviews with Apple Watch ECG consumers suggest their strongly trust in the Apple brand is amplified by the promissory quality of screening and technical innovation. What would otherwise be a costly clinical procedure is condensed into an accessible function in a wearable device. Consequently, AFib screening loses its clinical purpose, and is instead refashioned into a component of healthy lifestyle behaviour. Repeat self-screening becomes 'bundled' with similar health monitoring practices routinised in consumer wearables. Active uptake supports a market for the product and adds to the reputation of the Apple brand such that consumers become complicit in legitimising a medical practice that has limited clinical justification.

Mobile health technology in atrial fibrillation

INTRODUCTION

Mobile health (mHealth) solutions in atrial fibrillation (AF) are becoming widespread, thanks to everyday life devices such as smartphones. Their use is validated both in monitoring and in screening scenarios. In the published literature, the diagnostic accuracy of mHealth solutions wide differs, and their current clinical use is not well established in principal guidelines.

AREAS COVERED

mHealth solutions have progressively built an AF-detection chain to guide patients from the device's alert signal to the health care practitioners' (HCPs) attention. This review aims to critically evaluate the latest evidence regarding mHealth devices and the future possible patient's uses in everyday life.

EXPERT OPINION

The patients are the first to be informed of the rhythm anomaly, leading to the urgency of increasing the patients' AF self-management. Furthermore, HCPs need to update themselves about mHealth devices use in clinical practice. Nevertheless, these are promising instruments in specific populations, such as post-stroke patients, to promote an early arrhythmia diagnosis in the post-ablation/cardioversion period, allowing checks on the efficacy of the treatment or intervention.

An accurate and efficient method to train classifiers for atrial fibrillation detection in ECGs: Learning by asking better questions

BACKGROUND

An increasing number of wearables are capable of measuring electrocardiograms (ECGs), which may help in early detection of atrial fibrillation (AF). Therefore, many studies focus on automated detection of AF in ECGs. A major obstacle is the required amount of manually labelled data. This study aimed to provide an efficient and reliable method to train a classifier for AF detection using large datasets of real-life ECGs.

METHOD

Human-controlled semi-supervised learning was applied, consisting of two phases: the pre-training phase and the semi-automated training phase. During pre-training, an initial classifier was trained, which was used to predict the classes of new ECG segments in the semi-automated training phase. Based on the degree of certainty, segments were added to the training dataset automatically or after human validation. Thereafter, the classifier was retrained and this procedure was repeated. To test the model performance, a real-life telemetry dataset containing 3,846,564 30-s ECG segments of hospitalized patients (n = 476) and the CinC Challenge 2017 database were used.

RESULTS

After pre-training, the average F1-score on a hidden testing dataset was 89.0%. Furthermore, after the pre-training phase 68.0% of all segments in the hidden test set could be classified with an estimated probability of successful classification of 99%, providing an F1-score of 97.9% for these segments. During the semi-automated training phase, this F1-score showed little variation (97.3%-97.9% in the hidden test set), whilst the number of segments which could be automatically classified increased from 68.0% to 75.8% due to the enhanced training dataset. At the same time, the overall F1-score increased from 89.0% to 91.4%.

CONCLUSIONS

Human-validated semi-supervised learning makes training a classifier more time efficient without compromising on accuracy, hence this method might be valuable in the automated detection of AF in real-life ECGs.

Atrial fibrillation prevalence and predictors in patients with diabetes: a cross-sectional screening study

Prevalence of atrial fibrillation (AF) and diabetes is increasing worldwide. Diabetes is a risk factor for AF and both increase stroke risk. Previous AF screening studies have recruited highrisk patient groups, but not with diabetes as the target group. This study aims to determine whether people with diabetes have a higher prevalence of AF than the general population and investigate whether determinants, such as diabetes duration or diabetes control, add to AF risk. In a cross-sectional screening study, patients with diabetes were recruited via their GP surgeries or a diabetes centre. A 30-second single-lead electrocardiogram (ECG) was recorded using the Kardia^® device, along with physiological measurements and details relating to risk factor variables. There were 300 participants recruited and 16 patients identified with AF (5.3% prevalence). This demonstrated a significantly greater likelihood of AF than the background population (p=0.043). People with diabetes and AF were significantly older than those who only had diabetes. More people with type 2 diabetes had AF than people with type 1. Prediction of AF diagnosis by age, sex, diabetes type, diabetes duration and level of control revealed only age as a significant predictor. In conclusion, these findings add to existing data around the association of these chronic conditions, supporting AF screening in this high-risk group, particularly in those of older age. This can contribute to appropriate management of both conditions in combination, not least with regards to stroke prevention.

Budget impact analysis of a machine learning algorithm to predict high risk of atrial fibrillation among primary care patients

AIMS

We investigated whether the use of an atrial fibrillation (AF) risk prediction algorithm could improve AF detection compared with opportunistic screening in primary care and assessed the associated budget impact.

METHODS AND RESULTS

Eligible patients were registered with a general practice in UK, aged 65 years or older in 2018/19, and had complete data for weight, height, body mass index, and systolic and diastolic blood pressure recorded within 1 year. Three screening scenarios were assessed: (i) opportunistic screening and diagnosis (standard care); (ii) standard care replaced by the use of the algorithm; and (iii) combined use of standard care and the algorithm. The analysis considered a 3-year time horizon, and the budget impact for the National Health Service (NHS) costs alone or with personal social services (PSS) costs. Scenario 1 would identify 79 410 new AF cases (detection gap reduced by 22%). Scenario 2 would identify 70 916 (gap reduced by 19%) and Scenario 3 would identify 99 267 new cases (gap reduction 27%). These rates translate into 2639 strokes being prevented in Scenario 1, 2357 in Scenario 2, and 3299 in Scenario 3. The 3-year NHS budget impact of Scenario 1 would be £45.3 million, £3.6 million (difference ‒92.0%) with Scenario 2, and £46.3 million (difference 2.2%) in Scenario 3, but for NHS plus PSS would be ‒£48.8 million, ‒£80.4 million (64.8%), and ‒£71.3 million (46.1%), respectively.

CONCLUSION

Implementation of an AF risk prediction algorithm alongside standard opportunistic screening could close the AF detection gap and prevent strokes while substantially reducing NHS and PSS combined care costs.

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.

Targeted vs. full population screening costs for incident atrial fibrillation and AF-related stroke for a healthy population aged 65 years in the United Kingdom

AIMS

Atrial Fibrillation (AF) is the most common sustained heart arrhythmia and a major preventable cause of stroke. Stroke accounts for a large amount of health and social care funding and over the coming years is likely to place an increasing cost burden on the wider UK health care system. We therefore need to understand how an opportunistic AF screening programme would impact on healthcare costs of AF (and AF-related stroke) for the NHS.

METHODS AND RESULTS

Using UK population forecasts and prior published data we initially calculated the number of people to be screened, newly-diagnosed and treated for Atrial Fibrillation (AF), and the associated costs of such a programme for all 65 year olds and for just a 'high risk' group. The reduction in the number of stroke cases recorded and the associated cost savings were subsequently calculated, for 2020 and the projected estimates over the following decade. The number of newly diagnosed AF patients at 65 years old for the two groups (all 65 year olds and for just a 'high risk' group) would be in 6754 and 797 in 2020, rising to 9200 and 1086 in 2030, respectively. In 2020 the cost of the screening programme for the two options would be £14.3m and £1.7m. If AF is medicated and monitored then there would be a subsequent reduction in the number of stroke cases in 2020 by 4323 or 510 depending on the group screened, with associated savings of £394.2m and £46.5m,  respectively. Focussing on 2030 and should opportunistic screenings for AF be introduced at age 65, with subsequent treatment, it is predicted to reduce the number of stroke cases over the decade by 5888 if all 65 year olds are screened and 695 if just the high risk group are screened. If the number of strokes can be reduced by treating these screened AF patients, we would substantially reduce the health and social care costs of stroke by £654.6m and £77.3m,  respectively.

CONCLUSION

The number of newly diagnosed AF patients at age 65 will rise over the decade between 2020 and 2030. Screening and treatment of AF will substantially reduce the health and social care costs of AF-related stroke in the NHS.

Atrial fibrillation (AF) pilot screening programme in primary care in Ireland: an implementation study protocol

INTRODUCTION

Atrial fibrillation (AF) is a major risk factor for stroke. There is a fivefold increase in stroke risk in the presence of AF. The irregular beating of the heart enables blood stasis which allows clots to form. These can migrate to the brain causing a stroke. AF is common and its incidence increases with age. AF is often asymptomatic and early detection enables effective preventive treatment reducing stroke risk by up to two-thirds.Stroke contributes significantly to morbidity and mortality globally. In Ireland, it is the leading cause of acquired disability and second leading cause of death. The cost associated with stroke is significant. Stroke risk increases with age and is a public health priority.Internationally, there is consensus among experts that AF screening is valuable. In Ireland, the National Cardiovascular Policy recommended establishing a screening programme. However, there are many ways to screen for AF including pulse palpation, mobile ECG devices, 12-lead ECG and personal health monitoring devices.This study aims to investigate the acceptability, feasibility and impact of AF screening in primary care using a handheld mobile ECG device.

METHODS AND ANALYSIS

General practitioners (GPs) and practice nurses in the South of Ireland will opportunistically screen patients aged ≥65 years for AF at routine consultation using a handheld one-lead ECG device, KardiaMobile. This study will screen up to 4000 patients. Blood pressure and smoking status will be checked concurrently. A mixed-method evaluation will be undertaken including a partial economic evaluation. Anonymised data will be collected from participating practices and qualitative interviews will be conducted with GP, nurse and patient participants.

ETHICS AND DISSEMINATION

Ethical approval has been granted by the Clinical Research Ethics Committee in University College Cork. Dissemination will involve publication in peer-reviewed journals and presentation at national and international conferences.

Patient-Led Mass Screening for Atrial Fibrillation in the Older Population Using Handheld Electrocardiographic Devices Integrated With a Clinician-Coordinated Remote Central Monitoring System: Protocol for a Randomized Controlled Trial and Process Evaluation

Background

Atrial fibrillation (AF) is common in older people and increases the risk of stroke. The feasibility and effectiveness of the implementation of a patient-led AF screening program for older people are unknown.

Objective

This study aims to examine the feasibility and effectiveness of an AF screening program comprising patient-led monitoring of single-lead electrocardiograms (ECGs) with clinician-coordinated central monitoring to diagnose AF among community-dwelling people aged ≥75 years in Australia.

Methods

This is a nationwide randomized controlled implementation trial conducted via the internet and remotely among 200 community-dwelling adults aged ≥75 years with no known AF. Randomization will be performed in a 1:1 allocation ratio for the intervention versus control. Intervention group participants will be enrolled in the monitoring program at randomization. They will receive a handheld single-lead ECG device and training on the self-recording of ECGs on weekdays and submit their ECGs via their smartphones. The control group participants will receive usual care from their general practitioners for the initial 6 months and then commence the 6-month monitoring program. The ECGs will be reviewed centrally by trained personnel. Participants and their general practitioners will be notified of AF and other clinically significant ECG abnormalities.

Results

This study will establish the feasibility and effectiveness of implementing the intervention in this patient population. The primary clinical outcome is the AF detection rate, and the primary feasibility outcome is the patient satisfaction score. Other outcomes include appropriate use of anticoagulant therapy, participant recruitment rate, program engagement (eg, frequency of ECG transmission), agreement in ECG interpretation between the device automatic algorithm and clinicians, the proportion of participants who complete the trial and number of dropouts, and the impact of frailty on feasibility and outcomes. We will conduct a qualitative evaluation to examine the barriers to and acceptability and enablers of implementation. Ethics approval was obtained from the human research ethics committee at the University of Sydney (project number 2020/680). The results will be disseminated via conventional scientific forums, including peer-reviewed publications and presentations at national and international conferences.

Conclusions

By incorporating an integrated health care approach involving patient empowerment, centralized clinician-coordinated ECG monitoring, and facilitation of primary care and specialist services, it is possible to diagnose and treat AF early to reduce stroke risk. This study will provide new information on how to implement AF screening using digital health technology practicably and feasibly for older and frail populations residing in the community.

Trial Registration

Australian New Zealand Clinical Trials Registry ACTRN12621000184875; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=380877

International Registered Report Identifier (IRRID)

DERR1-10.2196/34778

2021 Asia Pacific Heart Rhythm Society (APHRS) practice guidance on atrial fibrillation screening

In this paper, the Asia Pacific Heart Rhythm Society (APHRS) sought to provide practice guidance on AF screening based on recent evidence, with specific considerations relevant to the Asia-Pacific region. A key recommendation is opportunistic screening for people aged ≥65 years (all countries), with systematic screening to be considered for people aged ≥75 years or who have additional risk factors (all countries).

Atrial fibrillation: a geriatric perspective on the 2020 ESC guidelines

BACKGROUND

The Task Force for the diagnosis and management of atrial fibrillation (AF) of the European Society of Cardiology (ESC) published in 2020 the updated Guidelines for the Diagnosis and Management of Atrial Fibrillation with the contribution of the European Heart Rhythm Association (EHRA) of the ESC and the European Association for Cardiothoracic Surgery (EACTS).

METHODS AND RESULTS

In this narrative viewpoint, we approach AF from the perspective of aging medicine and try to provide the readers with information usually neglected in clinical routine, mainly due to the fact that while the large majority of AF patients in real life are older, frail and cognitively impaired, these are mostly excluded from clinical trials, and physicians' attitudes often prevail over standardized algorithms.

CONCLUSIONS

On the basis of existing evidence, (1) opportunistic AF screening by pulse palpation or ECG rhythm strip is cost-effective, and (2) whereas advanced chronological age by itself is not a contraindication to AF treatment, a Comprehensive Geriatric Assessment (CGA) including frailty, cognitive impairment, falls and bleeding risk may assist in clinical decision making to provide the best individualized treatment.

Remote Screening for Atrial Fibrillation by a Federal Cardiac Monitoring System in Primary Care Patients in Russia: Results from the Prospective Interventional Multicenter FECAS-AFS Study

Background:

Objective:

Methods:

Results:

Conclusion:

Mobile health technologies in the diagnosis and management of atrial fibrillation

PURPOSE OF REVIEW

Atrial fibrillation is the most common sustained rhythm abnormality and is associated with stroke, heart failure, cognitive decline, and premature death. Digital health technologies using consumer-grade mobile technologies (i.e. mHealth) capable of recording heart rate and rhythm can now reliably detect atrial fibrillation using single lead or multilead ECG or photoplethysmography (PPG). This review will discuss how these developments are being used to detect and manage atrial fibrillation.

RECENT FINDINGS

Studies have established the accuracy of mHealth devices for atrial fibrillation detection. The feasibility of using mHealth technology to screen for atrial fibrillation has also been established, though the utility of screening is controversial. In addition to screening, key aspects of atrial fibrillation management can also be performed remotely and effectively using mHealth, though with some important limitations.

SUMMARY

mHealth technologies have proven disruptive in the diagnosis and management of atrial fibrillation. Healthcare providers can leverage these advances to better care for their atrial fibrillation patients whenever necessary.