Screening for Atrial Fibrillation in Older Adults at Primary Care Visits: VITAL-AF Randomized Controlled Trial

Clinical outcomes of atrial fibrillation screening: a meta-analysis of randomized controlled trials

BACKGROUND

Several randomized controlled trials (RCTs) have investigated the benefits of atrial fibrillation (AF) screening. However, since none have shown a significant reduction in stroke rates, the impact of screening on clinical outcomes remains uncertain.

MATERIALS AND METHODS

We conducted a systematic review and meta-analysis of RCTs reporting clinical outcomes of systematic AF screening in participants without known AF. Pooled risk ratios (RRs) were computed for all-cause stroke or systemic embolism, major bleeding, and all-cause mortality, comparing screening with no screening.

RESULTS

Seven RCTs encompassing 76 458 participants were identified. One trial utilized implantable loop recorders for rhythm monitoring, while the others employed non-invasive screening methods. Pooled results indicated that AF screening was associated with a significant reduction in all-cause stroke or systemic embolism (RR 0.932, 95% CI 0.873-0.996, I2 = 0%, p = 0.037), but had no effect on major bleeding (RR 0.996, 95% CI 0.935-1.060, I2 = 0%, p = 0.876) or all-cause mortality (RR 0.987, 95% CI 0.945-1.031, I2 = 0%, p = 0.550). We estimated a number needed to screen of 148 to prevent one stroke or systemic embolism over a 10-year period in a population of 75-year-olds. When only non-invasive screening methods were considered, the reduction in strokes was not statistically significant (RR 0.942, 95% CI 0.880-1.008, I2 = 0%, p = 0.083).

CONCLUSIONS

Systematic AF screening is associated with a modest yet statistically significant 7% relative reduction in stroke and systemic embolism, with no observed impact on major bleeding or all-cause mortality.

Smartphone-Based Applications for Atrial Fibrillation Detection: A Systematic Review and Meta-Analysis of Diagnostic Test Accuracy

Background: Atrial fibrillation (AF) burden is strongly associated with an increased risk of stroke, which, in most cases, can be prevented through earlier detection of AF and the timely initiation of anticoagulation therapy. Smartphone devices can provide a simple, non-invasive, cost-effective early AF detection solution. Methods: PubMed, Embase, and Scopus databases were searched for studies comparing smartphone-based photoplethysmography (PPG) with standard electrocardiogram for AF detection. A bivariate random-effects model with a 95% confidence interval (CI) was applied to generate the summary receiver operating characteristic (SROC) curve. Results: Fourteen studies were included, comprising 5,090 patients with an AF prevalence of 31.6%. The pooled sensitivity and specificity were 0.96 (95% CI, 0.93-0.97) and 0.97 (95% CI, 0.95-0.98). The area under the SROC curve was 0.98 (95% CI, 0.94-0.99). The diagnostic odds ratio was 960 (95% CI, 439-2,104), with significant heterogeneity (I2 = 51%). The projected positive and negative predictive values were 66.5% and 99.7%, respectively, in the elderly population aged >65 years and 39.2% and 99.9% in the general population. Conclusion: Smartphone-based PPG demonstrated relatively high sensitivity and specificity and appears capable of ruling out AF. Patients aged >65 are more likely to benefit from AF screening.

Assessing heart rate fragmentation to predict atrial fibrillation in the general population aged 65: the PROOF-AF study

Aims

Screening the general population aged 65 for atrial fibrillation (AF) has been proposed as a preventive measure against potential complications. Metrics derived from heart rate variability (HRV) that depict heart rate fragmentation (HRF) have been suggested to reflect autonomic nervous system dysfunction. The aim of the study was to assess the predictive capacity of HRV markers, including HRF, for AF occurrence over an 18-year follow-up and to develop a predictive score for AF onset among the general population aged 65 at the study's inception.

Methods and results

The PROOF prospective cohort consisted of 1011 subjects aged 65 with no history of AF nor history of cardiovascular disease. A 24 h Holter-electrocardiogram was performed at baseline and HRV, from which HRV indices using temporal, frequency, and non-linear methods, and the percentage of inflection points (PIPs) were calculated. The PROOF cohort demonstrated a cumulative incidence of AF of 13.0% during a median follow-up of 17.8 years. Male gender, hypertension, decreased heart rate and α1, and increased premature atrial complex burden, PNN50, and PIP were independent predictors of AF occurrence. Subsequently, the PROOF-AF risk score was developed, ranging from 0 to 7, providing interesting predictive capacity [area under the curve (AUC) = 70.1%, negative predictive value = 92.0%, and accuracy = 72.0%]. The high-risk group (PROOF-AF score from 5 to 7) and the intermediate-risk group (PROOF-AF score from 2 to 4) exhibited a 16.8- and 5.4-fold higher risk, respectively, of developing AF.

Conclusion

Heart rate fragmentation parameters, included in the PROOF-AF score, may be used to identify healthy individuals aged 65 who are at high risk of developing AF and assist population screening.

Identifying a Heterogeneous Effect of Atrial Fibrillation Screening in Older Adults: A Secondary Analysis of the VITAL-AF Trial

Background

One-time atrial fibrillation (AF) screening trials have produced mixed results; we sought a subset for whom screening is effective.

Methods

We conducted a secondary analysis of VITAL-AF, a randomized trial of one-time, brief, single-lead ECG screening during primary care visits. We tested two approaches to identify a subgroup where screening is effective. First, we developed an effect-based model using a T-learner. Specifically, we separately predicted the likelihood of AF diagnosis under screening and usual care conditions; the difference in probabilities was the predicted screening effectiveness. Second, we used a validated AF risk model to test for heterogeneous screening effectiveness.

Results

In the effect-based analysis, in the highest quartile of predicted screening effectiveness, AF diagnosis rates were higher in the screening group (4.00 vs. 2.88 per 100 person-years, rate difference 1.12, 95% CI 0.11 to 2.13). In the risk-based analysis, in the highest quartile of baseline AF risk, AF diagnosis rates were also higher in the screening group (5.55 vs. 4.23 per 100 person-years, rate difference 1.32, 95% CI 0.14 to 2.50). Predicted screening effectiveness and predicted baseline AF risk were weakly correlated (Spearman correlation coefficient 0.23). Patients with low primary care use, using rate control medications, females, and Black patients were overrepresented in the high-effectiveness group even when they were not at high risk of developing AF.

Conclusions

In a secondary analysis of VITAL-AF, we identified subgroups where one-time screening was associated with increased AF diagnoses using both effect-based and risk-based approaches. In this study, predicted AF risk was only a partial proxy for predicted screening effectiveness. Even when individuals are not in the high-risk subset, features like low primary care use and rate control medication use can identify individuals for whom AF screening has a large impact. Future AF screening efforts should focus on screening both "high-risk" and "high-effectiveness" individuals.

What is Known

Because trials testing office-based screening for atrial fibrillation have produced mixed results, some have suggested we focus screening efforts on high-risk individuals.Newer methods allow us to test for screening heterogeneity using risk-based analyses and separately effect-based analyses, which disentangle screening effects from baseline disease risk.

What the Study Adds

Both the risk-based analysis and the effect-based analysis identified "high-risk" and "high-effectiveness" subgroups, respectively, where one-time AF screening was effective."High-risk" and "high-effectiveness" groups only partially overlap; even when individuals are not in the high-risk subset, features like low primary care use and rate control medication use an identify individuals for whom AF screening has a large impact.Future AF screening efforts should focus on screening both "high-risk" and "high-effectiveness" people.

Risk-based screening for the evaluation of atrial fibrillation in general practice (R-BEAT): a randomized cross-over trial

BACKGROUND

The optimal approach to the diagnosis of atrial fibrillation in primary care is unclear.

AIM

To determine if external loop recorder (ELR) screening improves atrial fibrillation detection in community-dwelling adults with a CHA2DS2-VASc score of greater than two.

DESIGN

Randomized cross-over clinical trial.

METHODS

Community-dwelling adults ≥55 years with a CHA2DS2-VASc score of greater than two, who were deemed suitable for atrial fibrillation screening and oral anticoagulation by their general practitioner were randomly assigned to immediate or delayed ELR monitoring. The intervention period was ELR cardiac monitoring for 1 week and the usual care period was healthcare professional pulse screening and completion of electrocardiogram (ECG) or cardiac rhythm strip if pulse was identified as irregular.

RESULTS

Of the 488 participants randomized, 244 were assigned to the immediate monitoring period (intervention) and 244 were assigned to the delayed monitoring period. Mean (SD) age was 75.0 (7.0) years and 333 participants were women (68%). Atrial fibrillation was detected in 32 of 488 participants (6.6%) in the intervention period versus five of 488 (1%) in the usual care period (absolute difference, 5.53% (3.2-7.9%), P < 0.001; number needed to screen 15 (11-23)). Twelve cases (37.5%) of ELR-detected atrial fibrillation were greater than 24 h in duration. Oral anticoagulation was initiated in all participants (n = 32).

CONCLUSIONS

Among older community-dwelling adults with a CHA2DS2-VASc score of greater than two, screening with ELR for one week was associated with a 5.5% incremental detection of new atrial fibrillation over usual care.

TRIAL REGISTRATION

ClinicalTrials.gov Register: NCT03911986.

2025 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2025 AHA Statistical Update is the product of a full year's worth of effort in 2024 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. This year's edition includes a continued focus on health equity across several key domains and enhanced global data that reflect improved methods and incorporation of ≈3000 new data sources since last year's Statistical Update.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

A machine learning-based model for predicting paroxysmal and persistent atrial fibrillation based on EHR

BACKGROUND

There is no effective way to accurately predict paroxysmal and persistent atrial fibrillation (AF) subtypes unless electrocardiogram (ECG) observation is obtained. We aim to develop a predictive model using a machine learning algorithm for identification of paroxysmal and persistent AF, and investigate the influencing factors.

METHODS

We collected demographic data, medication use, serological indicators, and baseline cardiac ultrasound data of all included subjects, totaling 50 variables. The diagnosis of AF subtypes is confirmed by ECG observation for at least more than 7 days. Variable selection was performed by spearman correlation analysis, recursive feature elimination, and least absolute shrinkage and selection operator regression. We built a prediction model for AF using three machine learning methods. Finally, the significance of each variable was analyzed by Shapley additive explanations method.

RESULTS

After screening, we found the optimal variable set consisting of 10 variables. The model we built achieved good predictive performance (AUC = 0.870, 95%CI 0.858 to 0.882), and had specificity of 0.851 (95%CI 0.844 to 0.858) and sensitivity of 0.716 (95%CI 0.676 to 0.755). Good predictive performance was stably achieved in different age subgroups and different gender subgroups. LA and NT-proBNP were the two most important variables for predicting paroxysmal and persistent AF in all models, except for the female subgroup aged less than 60 years.

CONCLUSIONS

Our model makes it possible to predict paroxysmal and persistent AF based on baseline data at admission. Early and individualized intervention strategies based on our model may help to improve clinical outcomes in AF patients.

Consumer-grade wearable devices in arrhythmia diagnostics for clinicians: where we are and where we are going

Atrial arrhythmias, including atrial fibrillation (AF), are a major contributor to cardiovascular morbidity and mortality. Early detection and effective management are critical to mitigating adverse outcomes such as stroke, heart failure, and overall mortality. Wearable devices have emerged as promising tools for monitoring, detecting, and managing atrial arrhythmias near-continuously. This comprehensive analysis explores these wearable technologies' current role and capabilities for clinicians' daily practice. Despite challenges related to data accuracy, privacy, patient compliance, and integration with healthcare systems, ongoing advancements hold significant promise for the future. Continued research and development are essential to fully realize the potential of wearables in improving clinical outcomes for patients with atrial arrhythmias.

Wear Your Heart on Your Sleeve: Smart Textile ECG Wearables for Comfort, Integration, Signal Quality and Continuous Monitoring in Paroxysmal Atrial Fibrillation

Atrial fibrillation (AF), a prevalent cardiac arrhythmia and a major contributor to stroke risk, is anticipated to increase in incidence with the aging global population. For effective AF management, particularly for paroxysmal AF (PAF), long-term and accurate monitoring is essential. However, traditional monitoring methods, including Holter ECGs and implantable cardiac monitors (ICMs), present limitations in comfort, compliance and extended monitoring capabilities. Recent advancements in wearable technology have introduced smart textile-based ECG devices, which incorporate electrochemical sensors into fabrics, enabling non-invasive, continuous monitoring while enhancing user comfort. This review evaluates textile-based ECG devices by comparing their performance-assessed through AF detection rates, signal-to-noise ratio (SNR) and total analysis time-against conventional Holter monitoring and the 12-lead ECG. Furthermore, this review examines user acceptability factors, including patient-reported comfort, usability during resting and physical activities and skin-related adverse effects. The findings aim to provide insights for future device development and facilitate their integration into clinical practice.

Screening and diagnosis of atrial fibrillation using wearable devices

In recent years, the development and use of various devices for the screening of atrial fibrillation (AF) have significantly increased. Such devices include 12-lead electrocardiogram (ECG), photoplethysmography systems, and single-lead ECG and ECG patches. This review outlines several studies that have focused on the feasibility and efficacy of such devices for AF screening, and summarizes the risks and benefits involved in the initiation of anticoagulant therapy after early detection of AF. We also describe several ongoing trials on unresolved issues associated with AF screening. Overall, this review provides a comprehensive summary of the current state of AF screening and its implications for patient care.

Atrial Fibrillation Burden on a 14-Day ECG Monitor: Findings From the GUARD-AF Trial Screening Arm

BACKGROUND

The "burden" of atrial fibrillation (AF) detected by screening likely influences stroke risk, but the distribution of burden is not well described.

OBJECTIVES

This study aims to determine the frequency of AF and the distribution of AF burden found when screening individuals ≥70 years of age with a 14-day electrocardiograph monitor.

METHODS

This is a cohort study of the screening arm of a randomized AF screening trial among those ≥70 years of age without a prior AF diagnosis (between 2019 and 2021). Screening was performed with a 14-day continuous electrocardiogram patch monitor.

RESULTS

Analyzable patches were returned by 5,684 (95%) of screening arm participants; the median age was 75 years (Q1-Q3: 72-78 years), 57% were female, and the median CHA2DS2-VASc score was 3 (Q1-Q3: 2-4). AF was detected in 252 participants (4.4%); 29 (0.5%) patients had continuous AF and 223 (3.9%) had paroxysmal AF. Among those with paroxysmal AF, the average indices of AF burden were of low magnitude with right-skewed distributions. The median percent time in AF was 0.46% (Q1-Q3: 0.02%-2.48%), or 75 (Q1-Q3: 3-454) minutes, and the median longest episode was 38 (Q1-Q3: 2-245) minutes. The upper quartile threshold of 2.48% time in AF corresponded to 7.6 hours. Age >80 years was associated with screen-detected AF in our multivariable model (OR: 1.46; 95% CI: 1.06-2.02).

CONCLUSIONS

Most AF detected in these older patients was very low burden. However, one-quarter of those with AF had multiple hours of AF, raising concern about stroke risk. These findings have implications for targeting populations for AF screening trials and for responding to heart rhythm alerts from mobile devices (GUARD-AF [A Study to Determine if Identification of Undiagnosed Atrial Fibrillation in People at least 70 Years of Age Reduces the Risk of Stroke]; NCT04126486).

A randomized controlled implementation study integrating patient self-screening with a remote central monitoring system to screen community dwellers aged 75 years and older for atrial fibrillation

AIMS

Diagnosis of atrial fibrillation (AF) provides opportunities to reduce stroke risk. This study aimed to compare AF diagnosis rates, participant satisfaction, and feasibility of an electrocardiogram (ECG) self-screening virtual care system with usual care.

METHODS AND RESULTS

This randomized controlled implementation study involving community-dwelling people aged ≥75 years was conducted from May 2021 to June 2023. Participants were given a handheld single-lead ECG device and trained to self-record ECGs once daily on weekdays for 12 months. The control group received usual care with their general practitioners in the first 6 months and participated in the subsequent 6 months. Atrial fibrillation diagnosis and participant satisfaction were assessed at 6 months. Two hundred participants (mean age 79.0 ± 3.4 years; 54.0% female; 72.5% urban) were enrolled. Atrial fibrillation was diagnosed in 10/97 (10.3%) intervention participants and 2/100 (2.0%) in the control group (odds ratio 5.6, 95% confidence interval 1.4-37.3, P = 0.03). In the intervention, 80% of AF cases were diagnosed within 3 months. 91/93 (97.9%) intervention participants and 55/93 (59.1%) control-waitlisted participants (P < 0.001) were satisfied with AF screening. Of the expected 20 days per month, the overall monthly median number of days participants self-recorded ECGs was 20 (interquartile range 17-22). Participants were confident using the device (93%), reported it was easy to use (98%), and found screening efficient (96%).

CONCLUSION

Patient-led AF self-screening using single-lead ECG devices with a remote central monitoring system was feasible, acceptable, and effective in diagnosing AF among older people. This screening model could be adapted for implementation, interfacing with integrated care models within existing health systems.

REGISTRATION

Australian New Zealand Clinical Trials Registry identifier: ACTRN12621000184875.

Effect of implantable loop recorder-based continuous rhythm monitoring on incident atrial fibrillation and stroke: An updated systematic review and meta-analysis of randomized controlled trials

BACKGROUND

In patients with a history of stroke or those at high risk for developing stroke, a continuous rhythm monitoring strategy using an implantable loop recorder (ILR) is often performed to screen for atrial fibrillation (AF).

OBJECTIVES

The purpose of this study was to perform a systematic review (MEDLINE and EMBASE) including randomized controlled trials comparing ILR-based continuous rhythm monitoring vs usual care in patients with a history of stroke or patients at high risk for developing stroke.

METHODS

A meta-analysis was performed, and aggregate risk ratio (RR) and risk difference (RD) with 95% confidence interval (CI) were calculated.

RESULTS

Four randomized controlled trials with 7237 patients (ILR 2114, non-ILR 5123) were included. ILR vs non-ILR was associated with increased detection of incident AF (RR 3.88; 95% CI 2.23-6.75; P <.00001; number needed to treat [NNT] = 7.7; I2 = 61%), increased appropriate initiation of anticoagulation (RR 2.29; 95% CI 2.07-2.55; P <.00001; NNT = 6.7; I2 = 0), and a 25% lower risk of developing stroke (RR 0.75; 95% CI 0.59-0.95]; P = .02; NNT = 100; I2 = 0%). In patients with history of stroke there was no difference in the risk of developing incident stroke (RR 0.83; 95% CI 0.61-1.14]; P = .25; I2 = 0%).

CONCLUSION

Our meta-analysis showed that screening for AF with ILR is associated with increased detection of AF and increased initiation of appropriate anticoagulation therapy in patients with a history of stroke or those with risk factors for stroke. The benefit of stroke risk reduction with ILR remains unclear, and future studies focused on the inclusion of patients without a history of stroke are needed to elucidate this uncertainty.

[Digital devices for heart rhythm monitoring in atrial fibrillation patients scheduled for elective electrical cardioversion]

INTRODUCTION AND OBJECTIVES

Management in recent-onset atrial fibrillation (AF) is to achieve sinus rhythm (SR) by cardioversion (CV). However, frequently SR is spontaneously restored, making scheduled admission unnecessary and causing misutilization of healthcare resources. Emerging medical technology allows accurate heart rhythm monitoring. This study evaluated this technology in these patients, preventing unnecessary admission and providing an earlier management.

METHODS

A multicenter study was designed including patients with AF scheduled for elective electrical CV. Patients submitted ECG recordings to a central CoreLab daily, twice a day and whenever they present symptoms, until CV (spontaneous or scheduled) and a week afterwards. Whenever a spontaneous conversion to SR was detected, investigators were contacted to confirm SR and abort admission. Patients' satisfaction was evaluated using a test for perceived utility, convenience, and accessibility.

RESULTS

74 patients were enrolled (age 62±10 years). Twenty-two patients (30%) showed spontaneous conversion to SR. A total of 22 admissions and 16 transesophageal echocardiograms were prevented. Among 52 patients admitted for CV, 45 (88%) were discharged in SR. During follow-up after conversion to SR (spontaneous or electrical), recurrences of AF occurred in 24 patients (34%). At the end of the follow-up 51 patients (69%) remained in SR. The CoreLab received 93% of the expected ECG transmissions. Patient's overall satisfaction score was 9.1 over 10.

CONCLUSION

Digital devices for heart rhythm monitoring can optimize the management of AF patients scheduled for elective CV, preventing unnecessary admissions and providing a more rational use of healthcare resources.

Effect of Screening for Undiagnosed Atrial Fibrillation on Stroke Prevention

BACKGROUND

Atrial fibrillation (AF) often remains undiagnosed, and it independently raises the risk of ischemic stroke, which is largely reversible by oral anticoagulation. Although randomized trials using longer term screening approaches increase identification of AF, no studies have established that AF screening lowers stroke rates.

OBJECTIVES

To address this knowledge gap, the GUARD-AF (Reducing Stroke by Screening for Undiagnosed Atrial Fibrillation in Elderly Individuals) trial screened participants in primary care practices using a 14-day continuous electrocardiographic monitor to determine whether screening for AF coupled with physician/patient decision-making to use oral anticoagulation reduces stroke and provides a net clinical benefit compared with usual care.

METHODS

GUARD-AF was a prospective, parallel-group, randomized controlled trial designed to test whether screening for AF in people aged ≥70 years using a 14-day single-lead continuous electrocardiographic patch monitor could identify patients with undiagnosed AF and reduce stroke. Participants were randomized 1:1 to screening or usual care. The primary efficacy and safety outcomes were hospitalization due to all-cause stroke and bleeding, respectively. Analyses used the intention-to-treat population.

RESULTS

Enrollment began on December 17, 2019, and involved 149 primary care sites across the United States. The COVID-19 pandemic led to premature termination of enrollment, with 11,905 participants in the intention-to-treat population. Median follow-up was 15.3 months (Q1-Q3: 13.8-17.6 months). Median age was 75 years (Q1-Q3: 72-79 years), and 56.6% were female. The risk of stroke in the screening group was 0.7% vs 0.6% in the usual care group (HR: 1.10; 95% CI: 0.69-1.75). The risk of bleeding was 1.0% in the screening group vs 1.1% in the usual care group (HR: 0.87; 95% CI: 0.60-1.26). Diagnosis of AF was 5% in the screening group and 3.3% in the usual care group, and initiation of oral anticoagulation after randomization was 4.2% and 2.8%, respectively.

CONCLUSIONS

In this trial, there was no evidence that screening for AF using a 14-day continuous electrocardiographic monitor in people ≥70 years of age seen in primary care practice reduces stroke hospitalizations. Event rates were low, however, and the trial did not enroll the planned sample size.(Reducing Stroke by Screening for Undiagnosed Atrial Fibrillation in Elderly Individuals [GUARD-AF]; NCT04126486).

[Cardiovascular preventive recommendations. PAPPS 2024 thematic updates]

The recommendations of the semFYC's Program for Preventive Activities and Health Promotion (PAPPS) for the prevention of vascular diseases (VD) are presented. New in this edition are new sections such as obesity, chronic kidney disease and metabolic hepatic steatosis, as well as a 'Don't Do' section in the different pathologies treated. The sections have been updated: epidemiological review, where the current morbidity and mortality of CVD in Spain and its evolution as well as the main risk factors are described; vascular risk (VR) and recommendations for the calculation of CV risk; main risk factors such as arterial hypertension, dyslipidemia and diabetes mellitus, describing the method for their diagnosis, therapeutic objectives and recommendations for lifestyle measures and pharmacological treatment; indications for antiplatelet therapy, and recommendations for screening of atrial fibrillation, and recommendations for management of chronic conditions. The quality of testing and the strength of the recommendation are included in the main recommendations.

A Program to Optimize the Detection of Paroxysmal Atrial Fibrillation: The RITMO Study

BACKGROUND

Atrial fibrillation (AF) is the most common sustained arrythmia, but still underdiagnosed especially among asymptomatic patients.

OBJECTIVES

To evaluate a simple strategy to optimize the identification of AF.

METHODS

Asymptomatic patients aged 65 years or older, with hypertension or heart failure (HF), were included. Data were inserted into the REDCap software platform. Patients were assessed for the risk for AF using the Stroke Risk Analysis (SRA) mathematical algorithm, which was applied on a one-hour electrocardiogram (ECG). All patients at high risk for AF were instructed to follow a home ECG protocol for seven days using a portable Kardia 6 (OMRON, AliveCor®). The Kolmogorov-test was used to test the normality of quantitative variables; those with normal distribution were expressed as mean and standard deviation. A p<0.05 was set as statistically significant.

RESULTS

A total of 423 patients were assessed; 15 were excluded due to absence of SRA, yielding a sample of 408 patients. In 13 (3.2%), AF was identified, 120 (29.4%) were considered at high risk and 275 (67.4%) without increased risk for AF. Of the 120 high-risk patients, 111 successfully completed the seven-day protocol with Kardia; at least one episode of AF was identified in 43 patients.

CONCLUSION

The strategy adopted in the RITMO study was shown to be effective in identifying AF in asymptomatic elderly patients with hypertension or HF, with an incidence of 13.7% (56/408).

Management of atrial fibrillation in older adults

Most people with atrial fibrillation are older adults, in whom atrial fibrillation co-occurs with other chronic conditions, polypharmacy, and geriatric syndromes such as frailty. Yet most randomized controlled trials and expert guidelines use an age agnostic approach. Given the heterogeneity of aging, these data may not be universally applicable across the spectrum of older adults. This review synthesizes the available evidence and applies rigorous principles of aging science. After contextualizing the burden of comorbidities and geriatric syndromes in people with atrial fibrillation, it applies an aging focused approach to the pillars of atrial fibrillation management, describing screening for atrial fibrillation, lifestyle interventions, symptoms and complications, rate and rhythm control, coexisting heart failure, anticoagulation therapy, and left atrial appendage occlusion devices. Throughout, a framework is suggested that prioritizes patients' goals and applies existing evidence to all older adults, whether atrial fibrillation is their sole condition, one among many, or a bystander at the end of life.

Electrocardiogram (EKG) knowledge and interpretation proficiency among healthcare professionals in Pakistan: a prospective cross-sectional study

Background

Electrocardiogram (EKG) is a commonly used diagnostic tool for the evaluation of the electrical activity of the heart. The purpose of this study was to assess the knowledge and interpretation proficiency of EKG among healthcare professionals (HCPs) in Pakistan.

Methods

This prospective cross-sectional study was conducted among HCPs working in different healthcare settings. A structured questionnaire was used to assess the participants' theoretical knowledge and ability to interpret EKG findings. The data were analyzed using descriptive statistics and χ2 tests. The study indicates that EKG knowledge and interpretation proficiency among HCPs in Pakistan is unsatisfactory. The inadequacy of training periods of EKG training sessions and insufficient participation of HCPs in offered training opportunities put forward the need for the formation and introduction of better structured and efficient EKG training programmes.

Results

A total of 511 HCPs participated in the study, 28% of whom reportedly had received formal training for EKG interpretation. About 80% of the participants correctly identified theoretical questions pertaining to EKG, while 58% of the participants were able to accurately interpret EKG findings, and most HCPs (69.9%) read fewer than ten EKGs per week.

Conclusion

This study demonstrates a lack of expertise and a poor understanding of EKG in HCPs of Pakistan. The low level of EKG knowledge and interpretation proficiency among HCPs may lead to diagnostic errors and poor patient outcomes. Therefore, efforts should be made to improve EKG education and training among HCPs in Pakistan.

Automated interpretations of single-lead electrocardiograms predict incident atrial fibrillation: The VITAL-AF trial

BACKGROUND

Single-lead electrocardiograms (1L ECGs) are increasingly used for atrial fibrillation (AF) detection. Automated 1L ECG interpretation may have prognostic value for future AF in cases in which screening does not result in a short-term AF diagnosis.

OBJECTIVE

We sought to investigate the association between automated 1L ECG interpretation and incident AF.

METHODS

VITAL-AF was a randomized controlled trial investigating the effectiveness of screening for AF by 1L ECGs. For this study, participants were divided into 4 groups based on automated classification of 1L ECGs. Patients with prevalent AF were excluded. Associations between groups and incident AF were assessed by Cox proportional hazards models adjusted for risk factors. The start of follow-up was defined as 60 days after the latest 1L ECG (as some individuals had numerous screening 1L ECGs).

RESULTS

The study sample included never screened (n = 16,306), normal (n = 10,914), other (n = 2675), and possible AF (n = 561). Possible AF had the highest AF incidence (5.91 per 100 person-years; 95% confidence interval [CI], 4.24-8.23). Possible AF was associated with greater hazard of incident AF compared with normal (adjusted hazard ratio, 2.48; 95% CI, 1.66-3.71). Other was associated with greater hazard of incident AF compared with normal (1.41; 95% CI, 1.04-1.90).

CONCLUSION

In patients undergoing AF screening with 1L ECGs without prevalent AF or AF within 60 days of screening, presumptive positive and indeterminate 1L ECG interpretations were associated with future AF. Abnormal 1L ECG recordings may identify individuals at higher risk for future AF.

Integrating Clinical, Genetic, and Electrocardiogram-Based Artificial Intelligence to Estimate Risk of Incident Atrial Fibrillation

Background

AF risk estimation is feasible using clinical factors, inherited predisposition, and artificial intelligence (AI)-enabled electrocardiogram (ECG) analysis.

Objective

To test whether integrating these distinct risk signals improves AF risk estimation.

Methods

In the UK Biobank prospective cohort study, we estimated AF risk using three models derived from external populations: the well-validated Cohorts for Aging in Heart and Aging Research in Genomic Epidemiology AF (CHARGE-AF) clinical score, a 1,113,667-variant AF polygenic risk score (PRS), and a published AI-enabled ECG-based AF risk model (ECG-AI). We estimated discrimination of 5-year incident AF using time-dependent area under the receiver operating characteristic (AUROC) and average precision (AP).

Results

Among 49,293 individuals (mean age 65±8 years, 52% women), 825 (2.4%) developed AF within 5 years. Using single models, discrimination of 5-year incident AF was higher using ECG-AI (AUROC 0.705 [95%CI 0.686-0.724]; AP 0.085 [0.071-0.11]) and CHARGE-AF (AUROC 0.785 [0.769-0.801]; AP 0.053 [0.048-0.061]) versus the PRS (AUROC 0.618, [0.598-0.639]; AP 0.038 [0.028-0.045]). The inclusion of all components ("Predict-AF3") was the best performing model (AUROC 0.817 [0.802-0.832]; AP 0.11 [0.091-0.15], p<0.01 vs CHARGE-AF+ECG-AI), followed by the two component model of CHARGE-AF+ECG-AI (AUROC 0.802 [0.786-0.818]; AP 0.098 [0.081-0.13]). Using Predict-AF3, individuals at high AF risk (i.e., 5-year predicted AF risk >2.5%) had a 5-year cumulative incidence of AF of 5.83% (5.33-6.32). At the same threshold, the 5-year cumulative incidence of AF was progressively higher according to the number of models predicting high risk (zero: 0.67% [0.51-0.84], one: 1.48% [1.28-1.69], two: 4.48% [3.99-4.98]; three: 11.06% [9.48-12.61]), and Predict-AF3 achieved favorable net reclassification improvement compared to both CHARGE-AF+ECG-AI (0.039 [0.015-0.066]) and CHARGE-AF+PRS (0.033 [0.0082-0.059]).

Conclusions

Integration of clinical, genetic, and AI-derived risk signals improves discrimination of 5-year AF risk over individual components. Models such as Predict-AF3 have substantial potential to improve prioritization of individuals for AF screening and preventive interventions.

Trends in atrial fibrillation-related mortality in Europe, 2008-2019

AIMS

Update data regarding the atrial fibrillation (AF)-related mortality trend in Europe remain scant. We assess the age- and sex-specific trends in AF-related mortality in the European states between the years 2008 and 2019.

METHODS AND RESULTS

Data on cause-specific deaths and population numbers by sex for European countries were retrieved through the publicly available World Health Organization mortality dataset for the years 2008-2019. Atrial fibrillation-related deaths were ascertained when the International Classification of Diseases, 10th Revision code I48 was listed as the underlying cause of death in the medical death certificate. To calculate annual trends, we assessed the average annual % change (AAPC) with relative 95% confidence intervals (CIs) using Joinpoint regression. During the study period, 773 750 AF-related deaths (202 552 males and 571 198 females) occurred in Europe. The age-adjusted mortality rate (AAMR) linearly increased from 12.3 (95% CI: 11.2-12.9) per 100 000 population in 2008 to 15.3 (95% CI: 14.7-15.7) per 100 000 population in 2019 [AAPC: +2.0% (95% CI: 1.6-3.5), P < 0.001] with a more pronounced increase among men [AAPC: +2.7% (95% CI: 1.9-3.5), P < 0.001] compared with women [AAPC: +1.7% (95% CI: 1.1-2.3), P < 0.001] (P for parallelism 0.01). Higher AAMR increases were observed in some Eastern European countries such as Latvia, Lithuania, and Poland, while the lower increases were mainly clustered in Central Europe.

CONCLUSION

Over the last decade, the age-adjusted AF-related mortality has increased in Europe, especially among males. Disparities still exist between Western and Eastern European countries.

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.

Controversies in Diagnosis and Management of Atrial Fibrillation

Early detection of atrial fibrillation (AF) plays an important role in decreasing adverse cardiovascular outcomes. It is estimated, however, that one-third of those with AF are asymptomatic and may experience the adverse effects of the arrhythmia prior to being detected clinically. In the past, AF was diagnosed on 12-lead electrocardiogram or medically prescribed external monitors. The development of device-monitoring technologies capable of recording AF or AF-surrogates such as atrial high-rate episodes on cardiovascular implantable electronic devices or photoplethysmography/electrocardiogram on consumer-grade wearable devices, has resulted in increased recognition of device-detected, subclinical, AF. Recent studies reveal information about the stroke risk associated with these subclinical events and the response to anticoagulation and raise important questions about the use of both medical and direct-to-consumer AF detection devices for screening purposes. In addition to screening and detection of AF, emerging studies are also being conducted on different strategies for maintenance of sinus rhythm and stroke prevention including catheter ablation and left atrial appendage occlusion. This review aims to highlight recent developments and future studies in these areas.

Screening for atrial fibrillation: the role of CHA2DS2-VASc and atrial fibrillation burden

Individuals with subclinical atrial fibrillation (AF) face an increased risk of thromboembolic events, which may potentially be mitigated through AF screening and subsequent anticoagulation. However, data from randomized clinical trials (RCTs) indicate a lower stroke risk in subclinical AF compared with the clinical phenotype. This-along with the inherent bleeding risk related to anticoagulation-seems to render the net clinical benefit of AF screening less evident. Further, current guidelines recommend consideration of CHA2DS2-VASc score and AF episode duration to guide screening and treatment. These recommendations, in general, lack support and seem questionable in view of the limited RCT data. More evidence is warranted to provide insights into the potential benefits of screening and treatment of screen-detected AF in specific population subgroups and AF phenotypes.

Cardiogeriatrics: the current state of the art

It is estimated that by 2050, 17% of the world's population will be greater than 85 years old, which, combined with cardiovascular disease (CVD) being the leading cause of death and disability, sets an unprecedented burden on our health and care systems. This perfect storm will be accompanied by a rise in the prevalence of CVD due to increased survival of patients with pre-existing CVD and the incidence of CVD that is associated with the process of ageing. In this review, we will focus on the diagnosis and management of common CVD conditions in old age, namely: heart failure (HF), coronary artery disease (CAD), atrial fibrillation (AF) and valvular heart disease (VHD). Despite limited evidence, clinical guidelines are increasingly considering the complexity of management of these conditions in the older person, which often coexist, for example, AF and HF or CAD and VHD. Furthermore, they, in turn, need specific consideration in the context of comorbidities, polypharmacy, frailty and impaired cognition found in this age group. Hence, the emerging role of the geriatric cardiologist is therefore vital in performing comprehensive geriatric assessment, attending multidisciplinary team meetings and ultimately considering the patient and the sum of their diseases in their totality. There have been recent advances in CVD management but how we apply these to deliver integrated care to the elderly population is key. This review article aims to bring together emerging studies and guidelines on assessment and management of CVD in the elderly, summarising latest definitions, diagnostics, therapeutics and future challenges.

Atrial High-Rate Episodes in Elderly Patients: The Anticoagulation Therapy Dilemma

Atrial fibrillation (AF) has been associated with higher morbidity and mortality rates, especially in older patients. Subclinical atrial fibrillation (SCAF) is defined as the presence of atrial high-rate episodes (AHREs) > 190 bpm for 10 consecutive beats > 6 min and <24 h, as detected by cardiac implanted electronic devices (CIEDs). The selection of eligible patients for anticoagulation therapy among elderly individuals with AHREs detected through CIEDs remains a contentious issue. The meta-analysis of ARTESiA and NOAH-AFNET 6 clinical trials revealed that taking Edoxaban or Apixaban as oral anticoagulation therapy can reduce the risk of stroke by approximately 32% while increasing the risk of major bleeding by approximately 62%. However, it is still unclear which are, among patients with SCAF, those who can take the highest net clinical benefit from anticoagulant therapy. The present review summarizes the current evidence on this intriguing issue and suggests strategies to try to better stratify the risk of stroke and systemic embolism in patients with AHREs. We propose incorporating some parameters including chronic kidney disease (CKD), obesity, enlarged left atrial volume, the efficacy in blood pressure management, and frailty into the traditional CHA2DS2-VASc score. Future trials will be needed to verify the clinical usefulness of the proposed prognostic score mainly in the view of a personalized therapeutic approach in patients with SCAF.

Randomised controlled trial of population screening for atrial fibrillation in people aged 70 years and over to reduce stroke: protocol for the SAFER trial

INTRODUCTION

There is a lack of evidence that the benefits of screening for atrial fibrillation (AF) outweigh the harms. Following the completion of the Screening for Atrial Fibrillation with ECG to Reduce stroke (SAFER) pilot trial, the aim of the main SAFER trial is to establish whether population screening for AF reduces incidence of stroke risk.

METHODS AND ANALYSIS

Approximately 82 000 people aged 70 years and over and not on oral anticoagulation are being recruited from general practices in England. Patients on the palliative care register or residents in a nursing home are excluded. Eligible people are identified using electronic patient records from general practices and sent an invitation and consent form to participate by post. Consenting participants are randomised at a ratio of 2:1 (control:intervention) with clustering by household. Those randomised to the intervention arm are sent an information leaflet inviting them to participate in screening, which involves use of a handheld single-lead ECG four times a day for 3 weeks. ECG traces identified by an algorithm as possible AF are reviewed by cardiologists. Participants with AF are seen by a general practitioner for consideration of anticoagulation. The primary outcome is stroke. Major secondary outcomes are: death, major bleeding and cardiovascular events. Follow-up will be via electronic health records for an average of 4 years. The primary analysis will be by intention-to-treat using time-to-event modelling. Results from this trial will be combined with follow-up data from the cluster-randomised pilot trial by fixed-effects meta-analysis.

ETHICS AND DISSEMINATION

The London-Central National Health Service Research Ethics Committee (19/LO/1597) provided ethical approval. Dissemination will include public-friendly summaries, reports and engagement with the UK National Screening Committee.

TRIAL REGISTRATION NUMBER

ISRCTN72104369.

Electrocardiogram prediction of atrial fibrillation risk after stroke: A protocol for systematic review and meta-analysis

BACKGROUND

Atrial fibrillation (AF) is one of the most common clinical arrhythmias. This study aims to predict the risk of post-stroke AF through electrocardiographic changes in sinus rhythm.

METHODS

We searched the MEDLINE (PubMed) and EMBASE databases to identify relevant research articles published until August 2023. Prioritized items from systematic reviews and meta-analyses were screened, and data related to AF detection rate were extracted. A meta-analysis using a random-effects model was conducted for data synthesis and analysis.

RESULTS

A total of 32 studies involving electrocardiograms (ECG) were included, with a total analysis population of 330,284 individuals. Among them, 16,662 individuals (ECG abnormal group) developed AF, while 313,622 individuals (ECG normal group) did not. ECG patterns included terminal P-wave terminal force V1, interatrial block (IAB), advanced interatrial block, abnormal P-wave axis, pulse rate prolongation, and atrial premature complexes. Overall, 15,762 patients experienced AF during the study period (4.77%). In the ECG abnormal group, the proportion was 14.21% (2367/16,662), while in the control group (ECG normal group), the proportion was 4.27% (13,395/313,622). The pooled risk ratio for developing AF was 2.45 (95% confidence interval [CI]: 2.02-2.98, P < .001), with heterogeneity (I2) of 95%. The risk ratio values of alAB, P-wave terminal force V1, interatrial block, abnormal P-wave axis, pulse rate prolongation and atrial premature complexes were 4.12 (95% CI, 2.99-5.66), 1.47 (95% CI, 1.19-1.82), 2.54 (95% CI, 1.83-3.52), 1.70 (95% CI, 0.98-2.97), 2.65 (95% CI, 1.88-3.72), 3.79 (95% CI, 2.12-6.76), respectively.

CONCLUSION

There is a significant correlation between ECG patterns and the occurrence of AF. The alAB exhibited the highest level of predictability for the occurrence of AF. These indicators support their use as screening tools to identify high-risk individuals who may benefit from further examinations or empirical anticoagulation therapy following stroke.

Longer and better lives for patients with atrial fibrillation: the 9th AFNET/EHRA consensus conference

AIMS

Recent trial data demonstrate beneficial effects of active rhythm management in patients with atrial fibrillation (AF) and support the concept that a low arrhythmia burden is associated with a low risk of AF-related complications. The aim of this document is to summarize the key outcomes of the 9th AFNET/EHRA Consensus Conference of the Atrial Fibrillation NETwork (AFNET) and the European Heart Rhythm Association (EHRA).

METHODS AND RESULTS

Eighty-three international experts met in Münster for 2 days in September 2023. Key findings are as follows: (i) Active rhythm management should be part of the default initial treatment for all suitable patients with AF. (ii) Patients with device-detected AF have a low burden of AF and a low risk of stroke. Anticoagulation prevents some strokes and also increases major but non-lethal bleeding. (iii) More research is needed to improve stroke risk prediction in patients with AF, especially in those with a low AF burden. Biomolecules, genetics, and imaging can support this. (iv) The presence of AF should trigger systematic workup and comprehensive treatment of concomitant cardiovascular conditions. (v) Machine learning algorithms have been used to improve detection or likely development of AF. Cooperation between clinicians and data scientists is needed to leverage the potential of data science applications for patients with AF.

CONCLUSIONS

Patients with AF and a low arrhythmia burden have a lower risk of stroke and other cardiovascular events than those with a high arrhythmia burden. Combining active rhythm control, anticoagulation, rate control, and therapy of concomitant cardiovascular conditions can improve the lives of patients with AF.

Anticoagulation with edoxaban in patients with long atrial high-rate episodes ≥24 h

BACKGROUND AND AIMS

Patients with long atrial high-rate episodes (AHREs) ≥24 h and stroke risk factors are often treated with anticoagulation for stroke prevention. Anticoagulation has never been compared with no anticoagulation in these patients.

METHODS

This secondary pre-specified analysis of the Non-vitamin K antagonist Oral anticoagulants in patients with Atrial High-rate episodes (NOAH-AFNET 6) trial examined interactions between AHRE duration at baseline and anticoagulation with edoxaban compared with placebo in patients with AHRE and stroke risk factors. The primary efficacy outcome was a composite of stroke, systemic embolism, or cardiovascular death. The safety outcome was a composite of major bleeding and death. Key secondary outcomes were components of these outcomes and electrocardiogram (ECG)-diagnosed atrial fibrillation.

RESULTS

Median follow-up of 2389 patients with core lab-verified AHRE was 1.8 years. AHRE ≥24 h were present at baseline in 259/2389 patients (11%, 78 ± 7 years old, 28% women, CHA2DS2-VASc 4). Clinical characteristics were not different from patients with shorter AHRE. The primary outcome occurred in 9/132 patients with AHRE ≥24 h (4.3%/patient-year, 2 strokes) treated with anticoagulation and in 14/127 patients treated with placebo (6.9%/patient-year, 2 strokes). Atrial high-rate episode duration did not interact with the efficacy (P-interaction = .65) or safety (P-interaction = .98) of anticoagulation. Analyses including AHRE as a continuous parameter confirmed this. Patients with AHRE ≥24 h developed more ECG-diagnosed atrial fibrillation (17.0%/patient-year) than patients with shorter AHRE (8.2%/patient-year; P < .001).

CONCLUSIONS

This hypothesis-generating analysis does not find an interaction between AHRE duration and anticoagulation therapy in patients with device-detected AHRE and stroke risk factors. Further research is needed to identify patients with long AHRE at high stroke risk.

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.

The feasibility of population screening for paroxysmal atrial fibrillation using hand-held electrocardiogram devices

AIMS

There are few data on the feasibility of population screening for paroxysmal atrial fibrillation (AF) using hand-held electrocardiogram (ECG) devices outside a specialist setting or in people over the age of 75. We investigated the feasibility of screening when conducted without face-to-face contact ('remote') or via in-person appointments in primary care and explored impact of age on screening outcomes.

METHODS AND RESULTS

People aged ≥65 years from 13 general practices in England participated in screening during 2019-20. This involved attending a practice nurse appointment (10 practices) or receiving an ECG device by post (three practices). Participants were asked to use a hand-held ECG for 1-4 weeks. Screening outcomes included uptake, quality of ECGs, AF detection rates, and uptake of anticoagulation if AF was detected. Screening was carried out by 2141 (87.5%) of people invited to practice nurse-led screening and by 288 (90.0%) invited to remote screening. At least 56 interpretable ECGs were provided by 98.0% of participants who participated for 3 weeks, with no significant differences by setting or age, except people aged 85 or over (91.1%). Overall, 2.6% (64/2429) screened participants had AF, with detection rising with age (9.2% in people aged 85 or over). A total of 53/64 (82.8%) people with AF commenced anticoagulation. Uptake of anticoagulation did not vary by age.

CONCLUSION

Population screening for paroxysmal AF is feasible in general practice and without face-to-face contact for all ages over 64 years, including people aged 85 and over.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Promises and Perils of Consumer Mobile Technologies in Cardiovascular Care: JACC Scientific Statement

Direct-to-consumer (D2C) wearables are becoming increasingly popular in cardiovascular health management because of their affordability and capability to capture diverse health data. Wearables may enable continuous health care provider-patient partnerships and reduce the volume of episodic clinic-based care (thereby reducing health care costs). However, challenges arise from the unregulated use of these devices, including questionable data reliability, potential misinterpretation of information, unintended psychological impacts, and an influx of clinically nonactionable data that may overburden the health care system. Further, these technologies could exacerbate, rather than mitigate, health disparities. Experience with wearables in atrial fibrillation underscores these challenges. The prevalent use of D2C wearables necessitates a collaborative approach among stakeholders to ensure effective integration into cardiovascular care. Wearables are heralding innovative disease screening, diagnosis, and management paradigms, expanding therapeutic avenues, and anchoring personalized medicine.

New-onset atrial fibrillation and chronic coronary syndrome in the CLARIFY registry

BACKGROUND AND AIMS

Data on new-onset atrial fibrillation (NOAF) in patients with chronic coronary syndromes (CCS) are scarce. This study aims to describe the incidence, predictors, and impact on cardiovascular (CV) outcomes of NOAF in CCS patients.

METHODS

Data from the international (45 countries) CLARIFY registry (prospeCtive observational LongitudinAl RegIstry oF patients with stable coronary arterY disease) were used. Among 29 001 CCS outpatients without previously reported AF at baseline, patients with at least one episode of AF/flutter diagnosed during 5-year follow-up were compared with patients in sinus rhythm throughout the study.

RESULTS

The incidence rate of NOAF was 1.12 [95% confidence interval (CI) 1.06-1.18] per 100 patient-years (cumulative incidence at 5 years: 5.0%). Independent predictors of NOAF were increasing age, increasing body mass index, low estimated glomerular filtration rate, Caucasian ethnicity, alcohol intake, and low left ventricular ejection fraction, while high triglycerides were associated with lower incidence. New-onset atrial fibrillation was associated with a substantial increase in the risk of adverse outcomes, with adjusted hazard ratios of 2.01 (95% CI 1.61-2.52) for the composite of CV death, non-fatal myocardial infarction, or non-fatal stroke, 2.61 (95% CI 2.04-3.34) for CV death, 1.64 (95% CI 1.07-2.50) for non-fatal myocardial infarction, 2.27 (95% CI 1.85-2.78) for all-cause death, 8.44 (95% CI 7.05-10.10) for hospitalization for heart failure, and 4.46 (95% CI 2.85-6.99) for major bleeding.

CONCLUSIONS

Among CCS patients, NOAF is common and is strongly associated with worse outcomes. Whether more intensive preventive measures and more systematic screening for AF would improve prognosis in this population deserves further investigation.

Deep Learning of Electrocardiograms in Sinus Rhythm From US Veterans to Predict Atrial Fibrillation

Importance

Early detection of atrial fibrillation (AF) may help prevent adverse cardiovascular events such as stroke. Deep learning applied to electrocardiograms (ECGs) has been successfully used for early identification of several cardiovascular diseases.

Objective

To determine whether deep learning models applied to outpatient ECGs in sinus rhythm can predict AF in a large and diverse patient population.

Design, Setting, and Participants

This prognostic study was performed on ECGs acquired from January 1, 1987, to December 31, 2022, at 6 US Veterans Affairs (VA) hospital networks and 1 large non-VA academic medical center. Participants included all outpatients with 12-lead ECGs in sinus rhythm.

Main Outcomes and Measures

A convolutional neural network using 12-lead ECGs from 2 US VA hospital networks was trained to predict the presence of AF within 31 days of sinus rhythm ECGs. The model was tested on ECGs held out from training at the 2 VA networks as well as 4 additional VA networks and 1 large non-VA academic medical center.

Results

A total of 907 858 ECGs from patients across 6 VA sites were included in the analysis. These patients had a mean (SD) age of 62.4 (13.5) years, 6.4% were female, and 93.6% were male, with a mean (SD) CHA2DS2-VASc (congestive heart failure, hypertension, age, diabetes mellitus, prior stroke or transient ischemic attack or thromboembolism, vascular disease, age, sex category) score of 1.9 (1.6). A total of 0.2% were American Indian or Alaska Native, 2.7% were Asian, 10.7% were Black, 4.6% were Latinx, 0.7% were Native Hawaiian or Other Pacific Islander, 62.4% were White, 0.4% were of other race or ethnicity (which is not broken down into subcategories in the VA data set), and 18.4% were of unknown race or ethnicity. At the non-VA academic medical center (72 483 ECGs), the mean (SD) age was 59.5 (15.4) years and 52.5% were female, with a mean (SD) CHA2DS2-VASc score of 1.6 (1.4). A total of 0.1% were American Indian or Alaska Native, 7.9% were Asian, 9.4% were Black, 2.9% were Latinx, 0.03% were Native Hawaiian or Other Pacific Islander, 74.8% were White, 0.1% were of other race or ethnicity, and 4.7% were of unknown race or ethnicity. A deep learning model predicted the presence of AF within 31 days of a sinus rhythm ECG on held-out test ECGs at VA sites with an area under the receiver operating characteristic curve (AUROC) of 0.86 (95% CI, 0.85-0.86), accuracy of 0.78 (95% CI, 0.77-0.78), and F1 score of 0.30 (95% CI, 0.30-0.31). At the non-VA site, AUROC was 0.93 (95% CI, 0.93-0.94); accuracy, 0.87 (95% CI, 0.86-0.88); and F1 score, 0.46 (95% CI, 0.44-0.48). The model was well calibrated, with a Brier score of 0.02 across all sites. Among individuals deemed high risk by deep learning, the number needed to screen to detect a positive case of AF was 2.47 individuals for a testing sensitivity of 25% and 11.48 for 75%. Model performance was similar in patients who were Black, female, or younger than 65 years or who had CHA2DS2-VASc scores of 2 or greater.

Conclusions and Relevance

Deep learning of outpatient sinus rhythm ECGs predicted AF within 31 days in populations with diverse demographics and comorbidities. Similar models could be used in future AF screening efforts to reduce adverse complications associated with this disease.

Smartphone-based atrial fibrillation screening in the general population: feasibility and impact on medical treatment

Aims

The aim of this study is to determine the feasibility, detection rate, and therapeutic implications of large-scale smartphone-based screening for atrial fibrillation (AF).

Methods and results

Subjects from the general population in Belgium were recruited through a media campaign to perform AF screening during 8 consecutive days with a smartphone application. The application analyses photoplethysmography traces with artificial intelligence and offline validation of suspected signals to detect AF. The impact of AF screening on medical therapy was measured through questionnaires. Atrial fibrillation was detected in the screened population (n = 60.629) in 791 subjects (1.3%). From this group, 55% responded to the questionnaire. Clinical AF [AF confirmed on a surface electrocardiogram (ECG)] was newly diagnosed in 60 individuals and triggered the initiation of anti-thrombotic therapy in 45%, adjustment of rate or rhythm controlling strategies in 62%, and risk factor management in 17%. In subjects diagnosed with known AF before screening, a positive screening result led to these therapy adjustments in 9%, 39%, and 11%, respectively. In all subjects with clinical AF and an indication for oral anti-coagulation (OAC), OAC uptake increased from 56% to 74% with AF screening. Subjects with clinical AF were older with more co-morbidities compared with subclinical AF (no surface ECG confirmation of AF) (P < 0.001). In subjects with subclinical AF (n = 202), therapy adjustments were performed in only 7%.

Conclusion

Smartphone-based AF screening is feasible at large scale. Screening increased OAC uptake and impacted therapy of both new and previously diagnosed clinical AF but failed to impact risk factor management in subjects with subclinical AF.

Accuracy and variability of cardiologist interpretation of single lead electrocardiograms for atrial fibrillation: The VITAL-AF trial

BACKGROUND

Screening for atrial fibrillation (AF) using consumer-based devices capable of producing a single lead electrocardiogram (1L ECG) is increasing. There are limited data on the accuracy of physician interpretation of these tracings. The goal of this study is to assess the sensitivity, specificity, confidence, and variability of cardiologist interpretation of point-of-care 1L ECGs.

METHODS

Fifteen cardiologists reviewed point-of-care handheld 1L ECGs collected from patients aged 65 years or older enrolled in the VITAL-AF clinical trial [NCT035115057] who underwent cardiac rhythm assessments with a 1L ECG using an AliveCor KardiaMobile device. Random sampling of 1L ECGs for cardiologist review was stratified by the AliveCor algorithm interpretation. A 12L ECG performed on the same day for clinical purposes was used as the gold standard. Cardiologists each reviewed a common sample of 200 1L ECG tracings and completed a survey associated with each tracing. Cardiologists were blinded to both the AliveCor algorithm and same day 12L ECG interpretation. For each tracing, study cardiologists were asked to assess the rhythm (sinus rhythm, AF, unclassifiable), report their assessment of the quality of the tracing, and rate their confidence in rhythm interpretation. The outcomes included the sensitivity, specificity, variability, and confidence in physician interpretation. Variables associated with each measure were identified using multivariable regression.

RESULTS

The average sensitivity for AF was 77.4% (range 50%-90.6%, standard deviation [SD]=11.4%) and the average specificity was 73.0% (range 41.3%-94.6%, SD = 15.4%). The mean variability was 30.8% (range 0%-76.2%, SD = 23.2%). The average reviewer confidence of 1L ECG rhythm assessment was 3.6 out of 5 (range 2.5-4.2, SD = 0.6). Patient and tracing factors associated with sensitivity, specificity, variability, and confidence were identified and included age, body mass index, and presence of artifact.

CONCLUSION

Cardiologist interpretation of point-of-care handheld 1L ECGs has modest diagnostic sensitivity and specificity with substantial variability for AF classification despite high confidence. Variability in cardiologist interpretation of 1L ECGs highlights the importance of confirmatory testing for diagnosing AF.

Performance of Single-Lead Handheld Electrocardiograms for Atrial Fibrillation Screening in Primary Care: The VITAL-AF Trial

Background

Handheld single-lead electrocardiographic (1L ECG) devices are increasingly used for atrial fibrillation (AF) screening, but their real-world performance is not well understood.

Objectives

The purpose of this study was to quantify the diagnostic test characteristics of 1L ECG automated interpretations for prospective AF screening.

Methods

We calculated the diagnostic test characteristics of the AliveCor KardiaMobile 1L ECG (AliveCor, US) algorithm using unblinded cardiologist overread as the gold standard using single 30s tracings administered by medical assistants among individuals aged ≥65 years participating in the VITAL-AF trial (NCT03515057) of population-based AF screening embedded within routine primary care.

Results

A total of 14,230 individuals (mean age 74 ± 7 years, 60% women, 82% White) had 31,376 tracings reviewed by 13 cardiologists. A total of 24,906 (79.6%) tracings had an AliveCor interpretation of normal, 5,046 (16.1%) were unclassified, 797 (2.5%) were possible AF, and 573 (1.8%) were no analysis. Cardiologists read 808 (2.6%) tracings as AF. AliveCor possible AF had a PPV of 51.7% (95% CI: 47.8%-55.6%). AliveCor normal had an NPV of 99.8% (95% CI: 99.7%-99.8%). The AliveCor algorithm had an overall sensitivity of 51.0% (95% CI: 47.1%-54.9%) and a specificity of 98.7% (95% CI: 98.6%-98.9%). AliveCor tracings interpreted as unclassified (PPV 5.9%, 95% CI: 5.1%-6.7%) and no analysis (PPV 6.5%, 95% CI: 4.6%-8.9%) had low predictive values for AF and were increasingly prevalent at older ages (13.7% for age 65-69 years to 28.1% for age ≥85 years, P < 0.01).

Conclusions

In an older primary care population undergoing AF screening with handheld 1L ECGs, automated algorithm interpretations were sufficiently accurate to exclude the presence of AF but not to establish an AF diagnosis.

Effect of clinic-based single-lead electrocardiogram rhythm assessment on oral anticoagulation prescriptions in patients with previously diagnosed atrial fibrillation

Background

Despite benefits of oral anticoagulation (OAC), many individuals with diagnosed atrial fibrillation (AF) do not receive OAC.

Objective

The purpose of this study was to assess whether cardiac rhythm assessment for AF impacted use of OAC in patients with previously diagnosed AF.

Methods

VITAL-AF was a cluster randomized controlled trial conducted in 16 primary care practices assessing the efficacy of AF rhythm assessment with single-lead electrocardiogram in routine care. Patients 65 years and older were offered rhythm assessment at visits. In this secondary analysis, we evaluated rhythm assessment uptake and compared initiation and discontinuation of OAC in patients with previously diagnosed AF from intervention and control arms over 1 year.

Results

The study included 4593 patients with previously diagnosed AF (2250 intervention; 2343 control). In the intervention arm, 2022 (89.9%) completed rhythm assessment (median 2 visits with rhythm assessment) and 40.1% had ≥1 "Possible AF" result. Initiation of OAC was similar in the intervention (17.7%) and control (19.1%) arms but was influenced by the rhythm assessment result: higher with a "Possible AF" (26.1%; adjusted odds ratio [aOR] 1.62; 95% confidence interval [CI] 1.04-2.51), and lower with a "Normal" result (9.9%; aOR 0.45; 95% CI 0.29-0.71) compared to control. OAC discontinuation was similar in the intervention (6.3%) and control (7.2%) arms, with lower discontinuation with a "Possible AF" result (3.8%; aOR 0.51; 95% CI 0.32-0.81).

Conclusions

Including patients with previously diagnosed AF in a point-of-care rhythm assessment strategy did not increase overall OAC use compared to the control arm. However, the rhythm assessment result influenced both initiation and discontinuation of OAC.

The influence of atrial high-rate episodes on stroke and cardiovascular death: an update

Atrial high-rate episodes (AHRE) are atrial tachyarrhythmias detected by continuous rhythm monitoring by pacemakers, defibrillators, or implantable cardiac monitors. Atrial high-rate episodes occur in 10-30% of elderly patients without atrial fibrillation. However, it remains unclear whether the presence of these arrhythmias has therapeutic consequences. The presence of AHRE increases the risk of stroke compared with patients without AHRE. Oral anticoagulation would have the potential to reduce the risk of stroke in patients with AHRE but is also associated with a rate of major bleeding of ∼2%/year. The stroke rate in patients with AHRE appears to be lower than the stroke rate in patients with atrial fibrillation. Wearables like smart-watches will increase the absolute number of patients in whom atrial arrhythmias are detected. It remains unclear whether anticoagulation is effective and, equally important, safe in patients with AHRE. Two randomized clinical trials, NOAH-AFNET6 and ARTESiA, are expected to report soon. They will provide much-needed information on the efficacy and safety of oral anticoagulation in patients with AHRE.

Screening for undiagnosed atrial fibrillation using a single-lead electrocardiogram at primary care visits: patient uptake and practitioner perspectives from the VITAL-AF trial

BACKGROUND

Screening for atrial fibrillation (AF) is appealing because AF is common, when undiagnosed may increase stroke risk, and stroke is preventable with anticoagulants. This study assessed patient and primary care practitioner (PCP) acceptability of screening for AF using a 30-s single-lead electrocardiogram (SL-ECG) during outpatient visits.

METHODS

Secondary analyses of a cluster randomized trial. All patients ≥ 65 years old without prevalent AF seen during a 1-year period and their PCPs. Screening using a SL-ECG was performed by medical assistants during check-in at 8 intervention sites among verbally consenting patients. PCPs were notified of "possible AF" results; management was left to their discretion. Control practices continued with usual care. Following the trial, PCPs were surveyed about AF screening. Outcomes included screening uptake and results, and PCP preferences for screening.

RESULTS

Fifteen thousand three hundred ninety three patients were seen in intervention practices (mean age 73.9 years old, 59.7% female). Screening occurred at 78% of 38,502 individual encounters, and 91% of patients completed ≥ 1 screening. The positive predictive value of a "Possible AF" result (4.7% of SL-ECG tracings) at an encounter prior to a new AF diagnosis was 9.5%. Same-day 12-lead ECGs were slightly more frequent among intervention (7.0%) than control (6.2%) encounters (p = 0.07). Among the 208 PCPs completing a survey (73.6%; 78.9% intervention, 67.7% control), most favored screening for AF (87.2% vs. 83.6%, respectively), though SL-ECG screening was favored by intervention PCPs (86%) while control PCPs favored pulse palpation (65%). Both groups were less certain if AF screening should be done outside of office visits with patch monitors (47% unsure) or consumer devices (54% unsure).

CONCLUSIONS

Though the benefits and harms of screening for AF remain uncertain, most older patients underwent screening and PCPs were able to manage SL-ECG results, supporting the feasibility of routine primary care screening. PCPs exposed to a SL-ECG device preferred it over pulse palpation. PCPs were largely uncertain about AF screening done outside of practice visits.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03515057. Registered May 3, 2018.

Incident atrial fibrillation and adverse clinical outcomes during extended follow-up of participants recruited to the remote heart rhythm sampling using the AliveCor heart monitor to screen for atrial fibrillation: the REHEARSE-AF study

Aims

Atrial fibrillation (AF) is an important risk factor for stroke, which is commonly asymptomatic, particularly in older patients, and often undetected until cardiovascular events occur. Development of novel technology has helped to improve detection of AF. However, the longer-term benefit of systematic electrocardiogram (ECG) screening on cardiovascular outcomes is unclear.

Methods and results

In the original REHEARSE-AF study, patients were randomized to twice-weekly portable electrocardiogram (iECG) assessment or routine care. After discontinuing the trial portable iECG assessment, electronic health record data sources provided longer-term follow-up analysis. Cox regression was used to provide unadjusted and adjusted hazard ratios (HR) [95% confidence intervals (CI)] for clinical diagnosis, events, and anticoagulant prescriptions during the follow-up period. Over the median 4.2-year follow-up, although a greater number of patients were diagnosed with AF in the original iECG group (43 vs. 31), this was not significant (HR 1.37, 95% CI 0.86-2.19). No differences were seen in the number of strokes/systemic embolisms or deaths between the two groups (HR 0.92, 95% CI 0.54-1.54; HR 1.07, 95% CI 0.66-1.73). Findings were similar when restricted to those with CHADS-VASc ≥ 4.

Conclusion

A 1-year period of home-based, twice-weekly screening for AF increased diagnoses of AF for the screening period but did not lead to increased diagnoses of AF or a reduction in cardiovascular-related events or all-cause death over a median of 4.2 years, even in those at highest risk of AF. These results suggest that benefits of regular ECG screening over a 1-year period are not maintained after cessation of the screening protocol.

Evaluation of atrial anatomical remodeling in atrial fibrillation with machine-learned morphological features

PURPOSE

To elucidate the role of atrial anatomical remodeling in atrial fibrillation (AF), we proposed an automatic method to extract and analyze morphological characteristics in left atrium (LA), left atrial appendage (LAA) and pulmonary veins (PVs) and constructed classifiers to evaluate the importance of identified features.

METHODS

The LA, LAA and PVs were segmented from contrast computed tomography images using either a commercial software or a self-adaptive algorithm proposed by us. From these segments, geometric and fractal features were calculated automatically. To reduce the model complexity, a feature selection procedure is adopted, with the important features identified via univariable analysis and ensemble feature selection. The effectiveness of this approach is well illustrated by the high accuracy of our models.

RESULTS

Morphological features, such as LAA ostium dimensions and LA volume and surface area, statistically distinguished ([Formula: see text]) AF patients or AF with LAA filling defects (AF(def+)) patients among all patients. On the test set, the best model to predict AF among all patients had an area under the receiver operating characteristic curve (AUC) of 0.91 (95% CI, 0.8-1) and the best model to predict AF(def+) among all patients had an AUC of 0.92 (95% CI, 0.81-1).

CONCLUSION

This study automatically extracted and analyzed atrial morphology in AF and identified atrial anatomical remodeling that statistically distinguished AF or AF(def+). The importance of identified atrial morphological features in characterizing AF or AF(def+) was validated by corresponding classifiers. This work provides a good foundation for a complete computer-assisted diagnostic workflow of predicting the occurrence of AF or AF(def+).