Effectiveness of screening for atrial fibrillation and its determinants. A meta-analysis

Assessing the impact of atrial fibrillation self-care interventions: A systematic review

This systematic review evaluates the efficacy of self-care interventions for atrial fibrillation (AF), focusing on strategies for maintenance, monitoring, and management applied individually or in combination. Adhering to the 2020 PRISMA guidelines, the search strategy spanned literature from 2005 to 2023, utilizing keywords and subject headings for "atrial fibrillation" and "self-care" combined with the Boolean operator AND. The databases searched included Medline, Embase, and CINAHL. The initial search, conducted on February 17, 2021, and updated on May 16, 2023, identified 5160 articles, from which 2864 unique titles and abstracts were screened. After abstract screening, 163 articles were reviewed in full text, resulting in 27 articles being selected for data extraction; these studies comprised both observational and randomized controlled trial designs. A key finding in our analysis reveals that self-care interventions, whether singular, dual, or integrated across all three components, resulted in significant improvements across patient-reported, clinical, and healthcare utilization outcomes compared to usual care. Educational interventions, often supported by in-person sessions or telephone follow-ups, emerged as a crucial element of effective AF self-care. Additionally, the integration of mobile and web-based technologies alongside personalized education showed promise in enhancing outcomes, although their full potential remains underexplored. This review highlights the importance of incorporating comprehensive, theory-informed self-care interventions into routine clinical practice and underscores the need for ongoing innovation and the implementation of evidence-based strategies. The integration of education and technology in AF self-care aligns with the recommendations of leading health organizations, advocating for patient-centered, technology-enhanced approaches to meet the evolving needs of the AF population.

Supermarket/hypermarket opportunistic screening for atrial fibrillation (SHOPS-AF) using sensors embedded in the handles of supermarket trolleys: A feasibility study

BACKGROUND

Atrial fibrillation (AF) increases the risk of death, stroke, heart failure, cognitive decline, and healthcare costs but is often asymptomatic and undiagnosed. There is currently no national screening program for AF. The advent of validated hand-held devices allows AF to be detected in non-healthcare settings, enabling screening to be undertaken within the community.

METHOD AND RESULTS

In this novel observational study, we embedded a MyDiagnostick single lead ECG sensor into the handles of shopping trolleys in four supermarkets in the Northwest of England: 2155 participants were recruited. Of these, 231 participants either activated the sensor or had an irregular pulse, suggesting AF. Some participants agreed to use the sensor but refused to provide their contact details, or consent to pulse assessment. In addition, some data were missing, resulting in 203 participants being included in the final analyses. Fifty-nine participants (mean age 73.6 years, 43% female) were confirmed or suspected of having AF; 20 were known to have AF and 39 were previously undiagnosed. There was no evidence of AF in 115 participants and the remaining 46 recordings were non-diagnostic, mainly due to artefact. Men and older participants were significantly more likely to have newly diagnosed AF. Due to the number of non-diagnostic ECGs (n = 46), we completed three levels of analyses, excluding all non-diagnostic ECGs, assuming all non-diagnostic ECGs were masking AF, and assuming all non-diagnostic ECGs were not AF. Based on the results of the three analyses, the sensor's sensitivity (95% CI) ranged from 0.70 to 0.93; specificity from 0.15 to 0.97; positive predictive values (PPV) and negative predictive values (NPV) ranged from 0.24 to 0.56 and 0.55 to 1.00, respectively. These values should be interpreted with caution, as the ideal reference standard on 1934 participants was imperfect.

CONCLUSION

The study demonstrates that the public will engage with AF screening undertaken as part of their daily routines using hand-held devices. Sensors can play a key role in identifying asymptomatic patients in this way, but the technology must be further developed to reduce the quantity of non-diagnostic ECGs.

Adherence to a handheld device-based atrial fibrillation screening protocol is associated with clinical outcomes

OBJECTIVE

To evaluate adherence and adherence consistency to the handheld ECG device-based screening protocol and their association with adverse cerebral and cardiovascular outcomes in two systematic atrial fibrillation (AF) screening programmes.

METHODS

In 2012 (Systematic ECG Screening for Atrial Fibrillation Among 75-Year Old Subjects in the Region of Stockholm and Halland, Sweden (STROKESTOP) study) and 2016 (Stepwise mass screening for atrial fibrillation using N-terminal pro b-type natriuretic peptide (STROKESTOP II) study), half of all 75- and 76-year-old inhabitants of up to two Swedish regions were invited to participate in a systematic AF screening programme. Participants were instructed to perform 30-second measurements twice daily in STROKESTOP and four times daily in STROKESTOP II for 2 weeks. Adherence was defined as the number of measurements performed divided by the number of measurements asked, whereas adherence consistency was defined as the number of days with complete registrations.

RESULTS

In total, 6436 participants (55.7% female) from STROKESTOP and 3712 (59.8% female) from STROKESTOP II were included. Median adherence and adherence consistency were 100 (92-100)% and 12 (11-13) days in STROKESTOP and 90 (75-98)% and 8 (3-11) days in STROKESTOP II. Female sex and lower education were factors associated with both optimal adherence and adherence consistency in both studies. In STROKESTOP, low adherence and adherence consistency were associated with higher risk of adverse cerebral and cardiovascular outcomes (HR for composite primary endpoint 1.30 (1.11 to 1.51), p=0.001), including stroke (HR 1.68 (1.22 to 2.32), p=0.001) and dementia (1.67 (1.27 to 2.19), p<0.001).

CONCLUSIONS

Adherence to twice daily handheld ECG measurements in STROKESTOP was higher than to four times daily measurements in STROKESTOP II. Female sex and lower educational attainment were associated with ≥100% adherence and adherence consistency. Low adherence and adherence consistency were associated with a higher risk of adverse outcomes.

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.

Prevalence of Obstructive Sleep Apnea Among Atrial Fibrillation Patients: A Cross-Sectional Study from Jordan

Background

Obstructive Sleep Apnea (OSA) is a common respiratory disorder that causes intermittent upper airway collapse during sleep and can lead to various acute cardiovascular complications. Atrial Fibrillation (AF) is the most common sustained cardiac arrhythmia and is associated with an increased risk of cardiovascular hospitalization and all-cause mortality. Our study aimed to investigate the prevalence of individuals with AF and those considered at high risk for OSA.

Methods

A cross-sectional study was conducted with a population comprising patients who had visited KAUH cardiology clinics between 2017-2019; subjects were categorized into AF patients and general cardiology patients. Patients were surveyed for OSA using the Berlin Questionnaire to assess the degree of OSA symptoms and to classify patients into high- or low-risk groups based on their responses.

Results

Of the 656 patients, 545 met our inclusion criteria, of whom 192 were diagnosed with AF. Comparable demographic characteristics were observed between the AF and non-AF groups, barring higher rates of obesity (p=0.001) and smoking (p=0.042) in the AF group. The prevalence of high-risk OSA was significantly higher in AF patients (68.2%) compared to non-AF patients (29.4%), with an adjusted odds ratio of 2.473 times (95% CI: 1.434 -4.266, p=0.001) greater for AF. The age, gender, and BMI categories did not differ significantly between the two groups. Binary logistic regression revealed significant associations between OSA and risk factors such as asthma (OR=4.408, 95% CI: 2.634-7.376, p=0.001).

Conclusion

These results serve to display a statistically significant increase in high-risk OSA in existing AF patients, irrespective of the presence of conventional OSA risk factors; this could imply a more immediate and direct relationship between both diseases and calls to include routine screening for OSA in patients diagnosed, newly or otherwise, with AF.

Recommended assessment and management of sleep disordered breathing in patients with atrial fibrillation, hypertension and heart failure: Taiwan Society of Cardiology/Taiwan Society of sleep Medicine/Taiwan Society of pulmonary and Critical Care Medicine joint consensus statement

Sleep disordered breathing (SDB) is highly prevalent and may be linked to cardiovascular disease in a bidirectional manner. The Taiwan Society of Cardiology, Taiwan Society of Sleep Medicine and Taiwan Society of Pulmonary and Critical Care Medicine established a task force of experts to evaluate the evidence regarding the assessment and management of SDB in patients with atrial fibrillation (AF), hypertension and heart failure with reduced ejection fraction (HFrEF). The GRADE process was used to assess the evidence associated with 15 formulated questions. The task force developed recommendations and determined strength (Strong, Weak) and direction (For, Against) based on the quality of evidence, balance of benefits and harms, patient values and preferences, and resource use. The resulting 11 recommendations are intended to guide clinicians in determining which the specific patient-care strategy should be utilized by clinicians based on the needs of individual patients.

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

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

Build a bridge between ECG and EEG signals for atrial fibrillation diagnosis using AI methods

Atrial fibrillation (AF) is a very common type of cardiac arrhythmia. The main characteristic of AF is an abnormally rapid and disordered atrial rhythm causing an atrial dysfunction, which can be visualized on an electrocardiograph (ECG) and distinguished by irregular fluctuations. Despite continuous and considerable efforts to analyze the pathophysiology of AF, it is challenging to determine the underlying pathogenesis of the disease in individual patients. This study aims to build a bridge between ECG and electroencephalogram (EEG) signals to probe the strong influence between human brain activity and AF by AI methods. We first found that the one-second data fragment shows the most excellent performance in our time window configuration. Secondly, in our proposed measurement, most cortical potentials were partly associated with AF. Thirdly, we found that only a few channels of data were sufficient for analysis. Finally, our experiment shows δ wave has the best performance compared to other wave bands. By AI methods, the paper contributes to concluding that δ wave band of EEG is the most associated brain wave type with AF. By EEG signals from typical regions, the central region, parietal and Occipital might be the most associated encephalic regions with AF. The clinical trial registration number for our study is ChiCTR2300068625.

Early Diagnosis of Atrial Fibrillation and Stroke Incidence in Primary Care: Translating Measurements into Actions-A Retrospective Cohort Study

(1) Background: AF-related strokes will triple by 2060, are associated with an increased risk of cognitive decline, and alone or in combination, will be one of the main health and economic burdens on the European population. The main goal of this paper is to describe the incidence of new AF associated with stroke, cognitive decline and mortality among people at high risk for AF. (2) Methods: Multicenter, observational, retrospective, community-based studies were conducted from 1 January 2015 to 31 December 2021. The setting was primary care centers. A total of 40,297 people aged ≥65 years without previous AF or stroke were stratified by AFrisk at 5 years. The main measurements were the overall incidence density/1000 person-years (CI95%) of AF and stroke, prevalence of cognitive decline, and Kaplan-Meier curve. (3) Results: In total, 46.4% women, 77.65 ± 8.46 years old on average showed anAF incidence of 9.9/10³/year (CI95% 9.5-10.3), associated with a four-fold higher risk of stroke (CI95% 3.4-4.7), cognitive impairment(OR 1.34 (CI95% 1.1-1.5)), and all-cause mortality (OR 1.14 (CI95% 1.0-1.2)), but there was no significant difference in ischemic heart disease, chronic kidney disease, or peripheral arteriopathy. Unknown AF was diagnosed in 9.4% and of these patients, 21.1% were diagnosed with new stroke. (4) Conclusions: The patients at high AF risk (Q4th) already had an increased cardiovascular risk before they were diagnosed with AF.

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.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, 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, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association 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 COVID-19 (coronavirus disease 2019) publications, 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.

Screening for atrial fibrillation in the elderly: A network meta-analysis of randomized trials

BACKGROUND

Randomized controlled trials (RCTs) investigating the optimal screening strategy for atrial fibrillation (AF) have yielded conflicting results.

OBJECTIVE

To examine the comparative efficacy of different AF screening strategies in older adults.

METHODS

We searched MEDLINE, EMBASE and Cochrane without language restrictions through January 2022, for RCTs evaluating the outcomes of non-invasive AF screening approaches among adults ≥65 years. We conducted a pairwise meta-analysis comparing any AF screening approach versus no screening, and a network meta-analysis comparing systematic screening versus opportunistic screening versus no screening. The primary outcome was new AF detection.

RESULTS

The final analysis included 9 RCTs with 85,209 patients. The weighted median follow-up was 12 months. The mean age was 73.4 years and men represented 45.6%. On pairwise meta-analysis, any AF screening (either systematic or opportunistic) was associated with higher AF detection (1.8% vs. 1.3%; risk ratio [RR] 2.10; 95% confidence interval [CI] 1.20-3.65) and initiation of oral anticoagulation (RR 3.26; 95%CI 1.15-9.23), compared with no screening. There was no significant difference between any AF screening versus no screening in all-cause mortality (RR 0.97; 95%CI 0.93-1.01) or acute cerebrovascular accident (CVA) (RR 0.92; 95%CI 0.84-1.01). On network meta-analysis, only systematic screening was associated with higher AF detection (RR 2.73; 95% CI 1.62-4.59) and initiation of oral anticoagulation (RR 5.67; 95% CI 2.68-11.99), but not with the opportunistic screening, compared with no screening.

CONCLUSION

Systematic AF screening using non-invasive tools was associated with higher rate of new AF detection and initiation of OAC, but opportunistic screening was not associated with higher detection rates. There were no significant differences between the various AF screening approaches with respect to rates of all-cause mortality or CVA events. However, these analyses are likely underpowered and future RCTs are needed to examine the impact of systematic AF screening on mortality and CVA outcomes.

PRIMARY FUNDING SOURCE

None.

[Cardiovascular preventive recommendations. PAPPS 2022 thematic updates. Working groups of the PAPPS]

The recommendations of the semFYC's Program for Preventive Activities and Health Promotion (PAPPS) for the prevention of cardiovascular diseases (CVD) are presented. The following sections are included: epidemiological review, where the current morbidity and mortality of CVD in Spain and its evolution as well as the main risk factors are described; cardiovascular (CV) risk 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.

Is machine learning the future for atrial fibrillation screening?

Atrial fibrillation (AF) is the most common arrhythmia and causes significant morbidity and mortality. Early identification of AF may lead to early treatment of AF and may thus prevent AF-related strokes and complications. However, there is no current formal, cost-effective strategy for population screening for AF. In this review, we give a brief overview of targeted screening for AF, AF risk score models used for screening and describe the different screening tools. We then go on to extensively discuss the potential applications of machine learning in AF screening.

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

Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, 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, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.

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 programme for early diagnosis of atrial fibrillation: a multi-centre study in primary care

BACKGROUND

Atrial fibrillation (AF) is a morbid disease whose complications can be prevented if prompt and correctly treated.

OBJECTIVE

To assess the usefulness of an early AF diagnosis programme in at-risk individuals in primary care centres.

METHODS

In an open-label, multi-centre, controlled interventional study, individuals with one or more risk factors for AF but without known AF were enrolled. They were allocated to intervention and control groups in a 1:2 ratio. Participants in the intervention group had three clinical and educational visits (0, 6 and 12 months). In intervention subgroup A, an electrocardiogram (ECG) was performed at each visit and in subgroup B, only if arrhythmia was detected on auscultation. After 2 years, the medical records of all participants were reviewed. Participants diagnosed with AF were followed for two additional years.

RESULTS

Of the total 2231 participants enrolled, 1503 (67.36%) were allocated to the control group and 728 (32.63%) to the intervention groups (355 in subgroup A, 373 subgroup B). The groups showed similar clinical characteristics. New-onset AF was diagnosed in 38 patients. Early detection in subgroup B was similar to subgroup A and superior to control group (3.2% versus 1.2%, hazard ratio 3.149, 95% confidence interval 1.503-6.597, P = 0.002). AF patients in subgroups A and B had similar long-term complications and a tendency for fewer complications than AF patients in the control group.

CONCLUSIONS

An intervention programme consisting of health education, systematic auscultation and opportunistic ECG by a primary care provider is a useful method for the early diagnosis of AF.

Accuracy of Detecting Atrial Fibrillation: A Systematic Review and Meta-Analysis of Wrist-Worn Wearable Technology

Atrial fibrillation (AF) is the most commonly diagnosed arrhythmia, and ECG remains the gold standard for diagnosing AF. Wrist-worn technologies are appealing for their ability to passively process near-continuous pulse signals. The clinical application of wearable devices is controversial. Our systematic review and meta-analysis qualitatively and quantitatively analyze available literature on wrist-worn wearable devices (Apple Watch, Samsung, and KardiaBand) and their sensitivity and specificity in detecting AF compared to conventional methods. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed, yielding nine studies (n = 1,581). Observational studies assessing the sensitivity and specificity of wrist-worn wearables in detecting AF in patients with and without a history of AF were included and analyzed using a fixed-effect model with an inverse-variance method. In patients with a history of AF, the overall sensitivity between device groups did not significantly differ (96.83%; P = 0.207). Specificity significantly differed between Apple, Samsung, and KardiaBand (99.61%, 81.13%, and 97.98%, respectively; P<0.001). The effect size for this analysis was highest in the Samsung device group. Two studies (n = 796) differentiated cohorts to assess device sensitivity in patients with known AF and device specificity in patients with normal sinus rhythm (NSR) (sensitivity: 96.02%; confidence intervals (CI) 93.85%-97.59% and specificity: 98.82%; CI:97.46%-99.57%). Wrist-worn wearable devices demonstrate promising results in detecting AF in patients with paroxysmal AF. However, more rigorous prospective data is needed to understand the limitations of these devices in regard to varying specificities which may lead to unintended downstream medical testing and costs.

Efficient on-site confirmatory testing for atrial fibrillation with derived 12-lead ECG in a wireless body area network

Smartphones that can support and assist the screening of various cardiovascular diseases are gaining popularity in recent years. The timely detection, diagnosis, and treatment of atrial fibrillation (AF) are critical, especially for those who are at risk of stroke. AF detection via screening with wearable devices should always be confirmed by a standard 12-lead electrocardiogram (ECG). However, the inability to perform on-site AF confirmatory testing results in increased patient anxiety, followed by unnecessary diagnostic procedures and treatments. Also, the delay in confirmation procedure may conclude the condition as non-AF while it was indeed present at the time of screening. To overcome these challenges, we propose an efficient on-site confirmatory testing for AF with 12-lead ECG derived from the reduced lead set (RLS) in a wireless body area network (WBAN) environment. The reduction in the number of leads enhances the comfort level of patients as well as minimizes the hurdles associated with continuous telemonitoring applications such as data transmission, storage, and bandwidth of the overall system. The proposed method is characterized by segment-wise regression and a lead selection algorithm, facilitating improved P-wave reconstruction. Further, an efficient AF detection algorithm is proposed by incorporating a novel three-level P-wave evidence score with an RR irregularity evidence score. The proposed on-site AF confirmation test reduces false positives and false negatives by 88% and 53% respectively, compared to single lead screening. In addition, the proposed lead derivation method improves accuracy, F 1 -score, and Matthews correlation coefficient (MCC) for the on-site AF detection compared to existing related methods.

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.

Early atrial fibrillation detection and the transition to comprehensive management

Current atrial fibrillation (AF) guidelines recommend screening for AF in individuals above 65 years or with other characteristics suggestive of increased stroke risk. Several mobile health (mHealth) approaches are available to identify AF. Although most wearables or ECG machines include algorithms to detect AF, an ECG confirmation of AF is necessary to establish a suspected diagnosis of AF. Early detection of AF is important to allow early initiation of AF management, and early rhythm control therapy lowered risk of adverse cardiovascular outcomes among patients with early AF aged >75 or with a CHA2DS2-VASc score ≥2 and cardiovascular conditions in the EAST-AFNET 4 study. Strategies for early AF detection should be always linked to a comprehensive work-up infrastructure organized within an integrated care pathway to allow early initiation and guidance of AF treatment in newly detected AF patients. In this review article, we summarize strategies and mHealth approaches for early AF detection and the transition to early AF management including AF symptoms evaluation and assessment of AF progression as well as AF risk factors.

Screening for Atrial Fibrillation in the Older Population: A Randomized Clinical Trial

Importance

Atrial fibrillation (AF) is a major cause of preventable strokes. Screening asymptomatic individuals for AF may increase anticoagulant use for stroke prevention.

Objective

To evaluate 2 home-based AF screening interventions.

Design, Setting, and Participants

This multicenter randomized clinical trial recruited individuals from primary care practices aged 75 years or older with hypertension and without known AF. From April 5, 2015, to March 26, 2019, 856 participants were enrolled from 48 practices.

Interventions

The control group received standard care (routine clinical follow-up plus a pulse check and heart auscultation at baseline and 6 months). The screening group received a 2-week continuous electrocardiographic (cECG) patch monitor to wear at baseline and at 3 months, in addition to standard care. The screening group also received automated home blood pressure (BP) machines with oscillometric AF screening capability to use twice-daily during the cECG monitoring periods.

Main Outcomes and Measures

With intention-to-screen analysis, the primary outcome was AF detected by cECG monitoring or clinically within 6 months. Secondary outcomes included anticoagulant use, device adherence, and AF detection by BP monitors.

Results

Of the 856 participants, 487 were women (56.9%); mean (SD) age was 80.0 (4.0) years. Median cECG wear time was 27.4 of 28 days (interquartile range [IQR], 18.4-28.0 days). In the primary analysis, AF was detected in 23 of 434 participants (5.3%) in the screening group vs 2 of 422 (0.5%) in the control group (relative risk, 11.2; 95% CI, 2.7-47.1; P = .001; absolute difference, 4.8%; 95% CI, 2.6%-7.0%; P < .001; number needed to screen, 21). Of those with cECG-detected AF, median total time spent in AF was 6.3 hours (IQR, 4.2-14.0 hours; range 1.3 hours-28 days), and median duration of the longest AF episode was 5.7 hours (IQR, 2.9-12.9 hours). Anticoagulation was initiated in 15 of 20 patients (75.0%) with cECG-detected AF. By 6 months, anticoagulant therapy had been prescribed for 18 of 434 participants (4.1%) in the screening group vs 4 of 422 (0.9%) in the control group (relative risk, 4.4; 95% CI, 1.5-12.8; P = .007; absolute difference, 3.2%; 95% CI, 1.1%-5.3%; P = .003). Twice-daily AF screening using the home BP monitor had a sensitivity of 35.0% (95% CI, 15.4%-59.2%), specificity of 81.0% (95% CI, 76.7%-84.8%), positive predictive value of 8.9% (95% CI, 4.9%-15.5%), and negative predictive value of 95.9% (95% CI, 94.5%-97.0%). Adverse skin reactions requiring premature discontinuation of cECG monitoring occurred in 5 of 434 participants (1.2%).

Conclusions and Relevance

In this randomized clinical trial, among older community-dwelling individuals with hypertension, AF screening with a wearable cECG monitor was well tolerated, increased AF detection 10-fold, and prompted initiation of anticoagulant therapy in most cases. Compared with continuous ECG, intermittent oscillometric screening with a BP monitor was an inferior strategy for detecting paroxysmal AF. Large trials with hard clinical outcomes are now needed to evaluate the potential benefits and harms of AF screening.

Trial Registration

ClinicalTrials.gov Identifier: NCT02392754.

Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, 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, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2021 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease.

RESULTS

Each of the 27 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, policy makers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Clinical Factors Associated with Atrial Fibrillation Detection on Single-Time Point Screening Using a Hand-Held Single-Lead ECG Device

Our aim was to assess the prevalence of unknown atrial fibrillation (AF) among adults during single-time point rhythm screening performed during meetings or social recreational activities organized by patient groups or volunteers. A total of 2814 subjects (median age 68 years) underwent AF screening by a handheld single-lead ECG device (MyDiagnostick). Overall, 56 subjects (2.0%) were diagnosed with AF, as a result of 12-lead ECG following a positive/suspected recording. Screening identified AF in 2.9% of the subjects ≥ 65 years. None of the 265 subjects aged below 50 years was found positive at AF screening. Risk stratification for unknown AF based on a CHA₂DS₂VASc > 0 in males and >1 in females (or CHA₂DS₂VA > 0) had a high sensitivity (98.2%) and a high negative predictive value (99.8%) for AF detection. A slightly lower sensitivity (96.4%) was achieved by using age ≥ 65 years as a risk stratifier. Conversely, raising the threshold at ≥75 years showed a low sensitivity. Within the subset of subjects aged ≥ 65 a CHA₂DS₂VASc > 1 in males and >2 in females, or a CHA₂DS₂VA > 1 had a high sensitivity (94.4%) and negative predictive value (99.3%), while age ≥ 75 was associated with a marked drop in sensitivity for AF detection.

Opportunistic atrial fibrillation screening and detection in "self-service health check-up stations": a brief overview of current technology potential and possibilities

Up to a fifth of patients who suffer a stroke had undiagnosed atrial fibrillation (AF). About 30% of AF patients are asymptomatic and remain undiagnosed, so there are no obvious (to the patient) forewarnings. Opportunistic screening for AF applied to the above clinical situation can save lives, since the strokes that occur as a result of AF are often large, severely debilitating or fatal. Today, anyone can buy a good, FDA-approved mobile electrocardiogram (ECG) device/smartwatch for AF detection on Amazon for €100-400, but not very many asymptomatic AF patients, particularly older patients, will do so on their own. In this article, we introduce the concept and potential benefits of opportunistic AF screening and detection in a community setting using the latest generation of affordable digital ECG capture and interpretation solutions integrated into easy-to-use "self-service health check-up stations" installed in public spaces, such as supermarkets and pharmacies. A comprehensive trial of the proposed self-service health check-up stations for AF screening is needed to produce more evidence to convince decision makers to fully buy into the idea of a nation-wide screening programme using these kiosks.

The Cost-Effectiveness of One-Time Opportunistic Screening for Atrial Fibrillation in Different Age Cohorts of Inhabitants in Denmark Aged 65 Years and Above. A Markov Modelled Analysis

AIM

The objective was to evaluate the cost-effectiveness of one-time opportunistic screening for AF in general practice in citizens aged ≥65 years in Denmark compared to a no-screening alternative following current Danish practice.

METHODS AND RESULTS

A decision tree and a Markov model were designed to simulate costs and quality-adjusted life years (QALYs) in a hypothetical cohort of citizens aged ≥65 years equivalent to the Danish population (1 M citizens) over the course of 19 years, using a healthcare and societal perspective. Share of detected AF patients following opportunistic screening was retrieved from a recent Danish screening study, whereas the risk stroke and bleedings in AF patients were based on population data from national registries and their associated costs was obtained from published national registry studies.The present study showed that one-time opportunistic screening for AF was more costly, but also more effective compared to a no-screening alternative. The analysis predicts that one-time opportunistic screening of all Danes aged ≥65 years potentially can identify an additional 10,300 AF patients and prevent 856 strokes in the period considered. The incremental cost of such a screening program is €56.4 M, with a total gain of 6,000 QALYs, resulting in an incremental cost-effectiveness ratio of €9,400 per QALY gained.

CONCLUSION

Opportunistic screening in general practice in citizens aged ≥65 years in Denmark is cost-effective compared to a willingness-to-pay threshold of €22,000. The study and its findings support a potential implementation of opportunistic screening for AF at the general practitioner level in Denmark.

Results, barriers and enablers in atrial fibrillation case finding: barriers in opportunistic atrial fibrillation case finding-a cross-sectional study

BACKGROUND

Atrial fibrillation (AF) is often asymptomatic, and screening is not routinely undertaken.

OBJECTIVE

Evaluate the feasibility and effectiveness of a population-based case finding program and to identify the enablers of and/or barriers to its implementation.

METHODS

We conducted a cross-sectional study of a health care case finding program for AF from 1 January 2016, to 31 December 2017, that included 48 336 people ≥60 years of age in the region of Terresde l'Ebre (Catalonia, Spain). We analysed the effect on the prevalence of AF and, stratified by age, on the incidence of new diagnoses of AF. We assessed the sociodemographic and clinical variables related to the realization of a case finding.

RESULTS

A total of 32 090 (62.4%) people were screened for AF. We observed a significant increase in the AF prevalence after 2 years of program intervention (5.9-7.7%; P < 0.001). The detection of new AF cases was significantly higher in the case finding group across the whole of the age range, and 765 (2.6%) new AF cases were diagnosed using case finding. The factors that were significantly associated with an underuse of case finding were: age <70 years, urban residence, institutionalized status, Pfeiffer score ≥2, Charlson score >3 and number of visits <7/year.

CONCLUSIONS

A health care program of case finding is feasible and is associated with a significant increase in the prevalence and incidence of AF. The results depend on factors such as the ease of access to health care, age, place of residence and comorbidities.

Detecting undiagnosed atrial fibrillation in UK primary care: Validation of a machine learning prediction algorithm in a retrospective cohort study

AIMS

To evaluate the ability of a machine learning algorithm to identify patients at high risk of atrial fibrillation in primary care.

METHODS

A retrospective cohort study was undertaken using the DISCOVER registry to validate an algorithm developed using a Clinical Practice Research Datalink (CPRD) dataset. The validation dataset included primary care patients in London, England aged ≥30 years from 1 January 2006 to 31 December 2013, without a diagnosis of atrial fibrillation in the prior 5 years. Algorithm performance metrics were sensitivity, specificity, positive predictive value, negative predictive value (NPV) and number needed to screen (NNS). Subgroup analysis of patients aged ≥65 years was also performed.

RESULTS

Of 2,542,732 patients in DISCOVER, the algorithm identified 604,135 patients suitable for risk assessment. Of these, 3.0% (17,880 patients) had a diagnosis of atrial fibrillation recorded before study end. The area under the curve of the receiver operating characteristic was 0.87, compared with 0.83 in algorithm development. The NNS was nine patients, matching the CPRD cohort. In patients aged ≥30 years, the algorithm correctly identified 99.1% of patients who did not have atrial fibrillation (NPV) and 75.0% of true atrial fibrillation cases (sensitivity). Among patients aged ≥65 years (n = 117,965), the NPV was 96.7% with 91.8% sensitivity.

CONCLUSIONS

This atrial fibrillation risk prediction algorithm, based on machine learning methods, identified patients at highest risk of atrial fibrillation. It performed comparably in a large, real-world population-based cohort and the developmental registry cohort. If implemented in primary care, the algorithm could be an effective tool for narrowing the population who would benefit from atrial fibrillation screening in the United Kingdom.

Global epidemiology of atrial fibrillation: An increasing epidemic and public health challenge

Background

Atrial fibrillation is the most frequent cardiac arrhythmia. It has been estimated that 6–12 million people worldwide will suffer this condition in the US by 2050 and 17.9 million people in Europe by 2060. Atrial fibrillation is a major risk factor for ischemic stroke and provokes important economic burden along with significant morbidity and mortality.

Aim

We provide here comprehensive and updated statistics on worldwide epidemiology of atrial fibrillation.

Methods

An electronic search was conducted for atrial fibrillation. The epidemiologic information was retrieved from the Global Health Data Exchange database, which is regarded as one of the most comprehensive worldwide catalogs of surveys, censuses, vital statistics, and other health-related data.

Results

A total of 3.046 million new cases of atrial fibrillation worldwide were registered in the database during 2017. The estimated incidence rate for 2017 (403/millions inhabitants) was 31% higher than the corresponding incidence in 1997. The worldwide prevalence of atrial fibrillation is 37,574 million cases (0.51% of worldwide population), increased also by 33% during the last 20 years. The highest burden is seen in countries with high socio-demographic index, though the largest recent increased occurred in middle socio-demographic index countries. Future projections suggest that absolute atrial fibrillation burden may increase by >60% in 2050.

Conclusions

Our analyses suggest that atrial fibrillation incidence and prevalence have increased over the last 20 years and will continue to increase over the next 30 years, especially in countries with middle socio-demographic index, becoming one of the largest epidemics and public health challenges.

Smartwatch for the Detection of Atrial Fibrillation

Atrial fibrillation (AF) is the most common arrhythmia and poses a substantial economic burden due to associated thromboembolic complications. Screening for AF may theoretically be effective, but there is no consensus regarding the optimal screening method because the available tools are either invasive or not cost-effective. Recently, smartwatch industry has received a surge of interest for this purpose by introducing technologies such as photoplethysmography, artificial intelligence, and actual electrodes taking an electrocardiogram to measure and analyze heart rate and rhythm with relatively acceptable accuracy. Combined with other features such as ease of use and connectivity, smartwatches can potentially be used for large-scale AF screening and might eventually replace the current gold standards. In this review, we discuss the feasibility of this approach and summarize the current evidence on AF detection with smartwatches.