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

Biomarkers for predicting atrial fibrillation: An explorative sub-analysis of the randomised SCREEN-AF trial

BACKGROUND

Atrial fibrillation (AF) is a common treatable risk factor for stroke. Screening for paroxysmal AF in general practice is difficult, but biomarkers might help improve screening strategies.

OBJECTIVES

We investigated six blood biomarkers for predicting paroxysmal AF in general practice.

METHODS

This was a pre-specified sub-study of the SCREEN-AF RCT done in Germany. Between 12/2017-03/2019, we enrolled ambulatory individuals aged 75 years or older with a history of hypertension but without known AF. Participants in the intervention group received active AF screening with a wearable patch, continuous ECG monitoring for 2x2 weeks and usual care in the control group. The primary endpoint was ECG-confirmed AF within six months after randomisation. High-sensitive Troponin I (hsTnI), brain natriuretic peptide (BNP), N-terminal pro-B-type natriuretic peptide (NT-pro BNP), N-terminal pro atrial natriuretic peptide (NT-ANP), mid-regional pro atrial natriuretic peptide (MR-pro ANP) and C-reactive protein (CRP) plasma levels were investigated at randomisation for predicting AF within six months after randomisation.

RESULTS

Blood samples were available for 291 of 301 (96.7%) participants, including 8 with AF (3%). Five biomarkers showed higher median results in AF-patients: BNP 78 vs. 41 ng/L (p = 0.012), NT-pro BNP 273 vs. 186 ng/L (p = 0.029), NT-proANP 4.4 vs. 3.5 nmol/L (p = 0.027), MR-pro ANP 164 vs. 125 pmol/L (p = 0.016) and hsTnI 7.4 vs. 3.9 ng/L (p = 0.012). CRP levels were not different between groups (2.8 vs 1.9 mg/L, p = 0.1706).

CONCLUSION

Natriuretic peptide levels and hsTnI are higher in patients with AF than without and may help select patients for AF screening, but larger trials are needed.

Atrial Fibrillation Screening During Routine Automated Office, Home, and Ambulatory Blood Pressure Measurement: A Diagnostic Test Accuracy Systematic Review and Meta-Analysis

BACKGROUND

Atrial fibrillation (AF) is often asymptomatic and undiagnosed. As AF and hypertension often coexist, opportunistic AF detection during routine automated blood pressure (BP) measurement appears to be an attractive screening method.

METHODS

A systematic literature search was conducted to identify studies assessing the diagnostic test accuracy of office, home, or 24-hour ambulatory BP measuring devices with AF detection algorithms versus reference electrocardiography. Analyses were performed per participant (AF status based on several BP readings; most office/home devices) or per reading (AF status based on individual readings; all ambulatory devices). A meta-analysis stratified by device type (office/home/ambulatory) was conducted to calculate pooled measures of diagnostic accuracy. Sensitivity/meta-regression analyses were also performed.

RESULTS

Among 3096 records initially retrieved, 23 diagnostic test accuracy studies were included. Data derived from 11 093 individuals (weighted age 69 years, males 56%, hypertensives 79%, diabetics 24%, and AF prevalence 17%) indicated a pooled sensitivity 0.97 (95% CI, 0.92-0.99), specificity 0.93 (95% CI, 0.90-0.95), and accuracy 0.93 (95% CI, 0.89-0.95), with generally consistent results using office, home, or ambulatory BP devices (slightly lower specificity with the latter). The positive and negative predictive values were 0.70 (95% CI, 0.60-0.80) and 0.99 (95% CI, 0.98-1.00), respectively. Sensitivity analyses indicated lower specificity in studies implementing reading versus participant analyses. Most studies presented a low risk of bias and minor applicability concerns.

CONCLUSIONS

There is considerable and consistent evidence suggesting high diagnostic accuracy of AF detection algorithms implemented in automated BP monitors during routine BP measurements in and out of the office. AF diagnosis requires verification (electrocardiography) before treatment is administered.

Risk calculator for incident atrial fibrillation across a range of prediction horizons

BACKGROUND

The increasing burden of atrial fibrillation (AF) emphasizes the need to identify high-risk individuals for enrolment in clinical trials of AF screening and primary prevention. We aimed to develop prediction models to identify individuals at high-risk of AF across prediction horizons from 6-months to 10-years.

METHODS

We used secondary-care linked primary care electronic health record data from individuals aged ≥30 years without known AF in the UK Clinical Practice Research Datalink-GOLD dataset between January 2, 1998 and November 30, 2018; randomly divided into derivation (80%) and validation (20%) datasets. Models were derived using logistic regression from known AF risk factors for incident AF in prediction periods of 6 months, 1-year, 2-years, 5-years, and 10-years. Performance was evaluated using in the validation dataset with bootstrap validation with 200 samples, and compared against the CHA2DS2-VASc and C2HEST scores.

RESULTS

Of 2,081,139 individuals in the cohort (1,664,911 in the development dataset, 416,228 in the validation dataset), the mean age was 49.9 (SD 15.4), 50.7% were women, and 86.7% were white. New cases of AF were 7,386 (0.4%) within 6 months, 15,349 (0.7%) in 1 year, 38,487 (1.8%) in 5 years, and 79,997 (3.8%) by 10 years. Valvular heart disease and heart failure were the strongest predictors, and association of hypertension with AF increased at longer prediction horizons. The optimal risk models incorporated age, sex, ethnicity, and 8 comorbidities. The models demonstrated good-to-excellent discrimination and strong calibration across prediction horizons (AUROC, 95%CI, calibration slope: 6-months, 0.803, 0.789-0.821, 0.952; 1-year, 0.807, 0.794-0.819, 0.962; 2-years, 0.815, 0.807-0.823, 0.973; 5-years, 0.807, 0.803-0.812, 1.000; 10-years 0.780, 0.777-0.784, 1.010), and superior to the CHA2DS2-VASc and C2HEST scores. The models are available as a web-based FIND-AF calculator.

CONCLUSIONS

The FIND-AF models demonstrate high discrimination and calibration across short- and long-term prediction horizons in 2 million individuals. Their utility to inform trial enrolment and clinical decisions for AF screening and primary prevention requires further study.

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.

Assessment and Management of Atrial Fibrillation in Older Adults with Frailty

Atrial fibrillation (AF) is a major driver of morbidity and mortality among older adults with frailty. Moreover, frailty is highly prevalent in older adults with AF. Understanding and addressing the needs of frail older adults with AF is imperative to guide clinicians caring for older adults. In this review, we summarize current evidence to support the assessment and management of older adults with AF and frailty, incorporating numerous recent landmark trials and studies in the context of the 2023 US AF guideline.

Deep learning evaluation of echocardiograms to identify occult atrial fibrillation

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

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.

Wearable 12-Lead ECG Acquisition Using a Novel Deep Learning Approach from Frank or EASI Leads with Clinical Validation

The 12-lead electrocardiogram (ECG) is crucial in assessing patient decisions. However, portable ECG devices capable of acquiring a complete 12-lead ECG are scarce. For the first time, a deep learning-based method is proposed to reconstruct the 12-lead ECG from Frank leads (VX, VY, and VZ) or EASI leads (VES, VAS, and VAI). The innovative ECG reconstruction network called M2Eformer is composed of a 2D-ECGblock and a ProbDecoder module. The 2D-ECGblock module adaptively segments EASI leads into multi-periods based on frequency energy, transforming the 1D time series into a 2D tensor representing within-cycle and between-cycle variations. The ProbDecoder module aims to extract Probsparse self-attention and achieve one-step output for the target leads. Experimental results from comparing recorded and reconstructed 12-lead ECG using Frank leads indicate that M2Eformer outperforms traditional ECG reconstruction methods on a public database. In this study, a self-constructed database (10 healthy individuals + 15 patients) was utilized for the clinical diagnostic validation of ECG reconstructed from EASI leads. Subsequently, both the ECG reconstructed using EASI and the recorded 12-lead ECG were subjected to a double-blind diagnostic experiment conducted by three cardiologists. The overall diagnostic consensus among three cardiology experts, reaching a rate of 96%, indicates the significant utility of EASI-reconstructed 12-lead ECG in facilitating the diagnosis of cardiac conditions.

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.

Effectiveness of single-lead ECG devices for detecting atrial fibrillation: An overview of systematic reviews

BACKGROUND

Individuals with atrial fibrillation (AF) are at an increased risk for stroke. Early detection of undiagnosed AF by screening is recommended. Single-lead electrocardiogram (ECG) is the most widely used technology in AF detection. Several systematic reviews on the diagnostic accuracy of single-lead ECG devices for AF detection have been performed but have yielded inconclusive results.

AIMS

The aim of this study was to synthesize the available evidence on the effectiveness of single-lead ECG devices in detecting AF.

METHODS

An overview of systematic reviews was conducted. Five English databases (Cochrane Database of Systematic Reviews, PubMed, Embase, Ovid, and Web of Science) and two Chinese databases (Wanfang and CNKI) were searched from inception to July 31, 2021. Systematic reviews that examined the accuracy of tools based on single-lead ECG technology for detecting AF were included. A narrative data synthesis was performed.

RESULTS

Eight systematic reviews were finally included. Systematic reviews with meta-analysis showed that single-lead ECG-based devices had good sensitivity and specificity (both ≥90%) in detecting AF. According to subgroup analysis, the sensitivities of tools used in populations with a history of AF were all >90%. However, among handheld and thoracic placed single-lead ECG devices, large variations in diagnostic performance were observed.

LINKING EVIDENCE TO ACTION

Single-lead ECG devices can potentially be used for AF detection. Due to the heterogeneity in the study population and tools, future studies are warranted to explore the suitable circumstances in which each tool could be applied for AF screening in an effective and cost-effective manner.

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.

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

Background

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

Methods

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

Results

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

Conclusion

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

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

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

Risk of atrial fibrillation and association with other diseases: protocol of the derivation and international external validation of a prediction model using nationwide population-based electronic health records

INTRODUCTION

Atrial fibrillation (AF) is a major public health issue and there is rationale for the early diagnosis of AF before the first complication occurs. Previous AF screening research is limited by low yields of new cases and strokes prevented in the screened populations. For AF screening to be clinically and cost-effective, the efficiency of identification of newly diagnosed AF needs to be improved and the intervention offered may have to extend beyond oral anticoagulation for stroke prophylaxis. Previous prediction models for incident AF have been limited by their data sources and methodologies.

METHODS AND ANALYSIS

We will investigate the application of random forest and multivariable logistic regression to predict incident AF within a 6-month prediction horizon, that is, a time-window consistent with conducting investigation for AF. The Clinical Practice Research Datalink (CPRD)-GOLD dataset will be used for derivation, and the Clalit Health Services (CHS) dataset will be used for international external geographical validation. Analyses will include metrics of prediction performance and clinical utility. We will create Kaplan-Meier plots for individuals identified as higher and lower predicted risk of AF and derive the cumulative incidence rate for non-AF cardio-renal-metabolic diseases and death over the longer term to establish how predicted AF risk is associated with a range of new non-AF disease states.

ETHICS AND DISSEMINATION

Permission for CPRD-GOLD was obtained from CPRD (ref no: 19_076). The CPRD ethical approval committee approved the study. CHS Helsinki committee approval 21-0169 and data usage committee approval 901. The results will be submitted as a research paper for publication to a peer-reviewed journal and presented at peer-reviewed conferences.

TRIAL REGISTRATION NUMBER

A systematic review to guide the overall project was registered on PROSPERO (registration number CRD42021245093). The study was registered on ClinicalTrials.gov (NCT05837364).

Prevalence of high-risk aortic arch atherosclerosis features on computed tomography angiography in embolic stroke of undetermined source

INTRODUCTION

Embolic stroke of undetermined source (ESUS) comprises a heterogenous group. There is a need to further identify etiologies within this group to guide management strategies. We examined the prevalence of aortic arch atherosclerosis (AAA) on CT angiography (CTA) in patients with embolic stroke of undetermined source (ESUS) to characterize high-risk plaque features.

METHODS

All patients from two prospective multicenter acute ischemic stroke studies (INTERRSeCT and PRove-IT) were included if the CTA adequately imaged the proximal aortic arch and the stroke etiology was recorded. Three readers blinded to stroke etiology analyzed the following AAA plaque features on baseline CTA at the time of stroke: 1) thickness in millimetres (mm); 2) morphology (none, smooth, ulcerated, or protruding); 3) location within the aortic arch (proximal, transverse, or distal); and 4) calcification (none, single small, multiple small, single large, or diffuse extensive).

RESULTS

We included 1063 patients, of which 293 (27.6%) had ESUS (mean age 67.5 years; 46.4% men; median NIHSS 12; 80.6% large vessel occlusion). Mean AAA thickness was significantly larger in ESUS patients (3.8 mm) compared to non-ESUS patients (3.0 mm; p<0.0001) and to a subgroup of patients with large artery atherosclerosis (2.9 mm; p=0.003). ESUS patients had a significantly higher proportion of ulcerated or protruding plaques (17.4% vs 10.3%; risk ratio 1.7, 95% C.I. 1.2-2.4, p=0.002). The location of AAA in the ESUS group was the ascending aorta in 37.9%, transverse arch in 42.3%, and descending aorta in 84.6%. Although AAA was mostly located in the distal aortic arch, ulcerated or protruding plaques were least common in the distal arch (p=0.002). There was no difference between ESUS and non-ESUS patients in plaque location (p=0.23) or calcification grade (p=0.092).

CONCLUSION

ESUS patients in our study had thicker AAA and a higher prevalence of ulcerated or protruding plaques located more proximally within the aortic arch. High-risk plaque features may suggest a causal role of AAA in the ESUS population with visible intracranial occlusions.

Mobile Health and Preventive Medicine

Wearable devices providing health-related data (mobile health [mHealth]) have grown in numbers and types of data available over the past 2 decades. Applications in prevention with some of the longest track records are activity trackers to promote fitness (primary prevention), mobile electrocardiogram devices to detect arrhythmias (secondary prevention), and continuous glucose monitoring to improve glycemic control in type 2 diabetes (tertiary prevention). Continued integration of multiple diverse data streams and improved interfaces with individuals (such as artificial intelligence-driven health coaches), and health care teams (as in the hospital-at-home concept), promise to optimize use of mHealth to improve clinical and public health outcomes.

Left Atrial Strain and Incident Atrial Fibrillation in Older Adults

Atrial fibrillation (AF) is frequent in older adults and associated with left atrial (LA) dysfunction. LA strain (LAε) and LA strain rate (LASR) may detect subclinical LA disease. We investigated whether reduced LAε and LASR predict new-onset AF in older adults without history of AF or stroke. LAε and LASR were assessed by speckle-tracking echocardiography in 824 participants from the community-based Cardiovascular Abnormalities and Brain Lesions study. Positive longitudinal LAε and LASR during ventricular systole, LASR during early ventricular diastole, and LASR during LA contraction were measured. Cause-specific hazards regression model evaluated the association of LAε and LASR with incident AF, adjusting for pertinent covariates. The mean age was 71.1 ± 9.2 years (313 men, 511 women). During a mean follow-up of 10.9 years, new-onset AF occurred in 105 participants (12.7%). Lower LAε and LASR at baseline were observed in patients with new-onset AF (all p <0.01). In multivariable analysis, positive longitudinal LAε (adjusted hazard ratio [HR] per SD decrease 2.05, confidence interval [CI] 1.24 to 3.36) and LASR during LA contraction (HR per SD increase 2.24, CI 1.37 to 3.65) remained associated with new-onset AF, independently of LA volumes and left ventricular function. Along with positive longitudinal LAε, reduced LASR during ventricular systole predicted AF in participants with LA volume below the median value (HR 2.54, CI 1.10 to 6.09), whereas reduced LASR during LA contraction predicted AF in participants with larger LA (HR 2.35, CI 1.31 to 4.23). In conclusion, reduced positive longitudinal LAε and LASR predict new-onset AF in older adults regardless of LA size and may improve AF risk stratification.

Cost-Effectiveness of AF Screening With 2-Week Patch Monitors: The mSToPS Study

BACKGROUND

The mSToPS study (mHealth Screening to Prevent Strokes) reported screening older Americans at risk for atrial fibrillation (AF) and stroke using 2-week patch monitors was associated with increased rates of AF diagnosis and anticoagulant prescription within 1 year and improved clinical outcomes at 3 years relative to matched controls. Cost-effectiveness of this AF screening approach has not been explored.

METHODS

We conducted a US-based health economic analysis of AF screening using patient-level data from mSToPS. Clinical outcomes, resource use, and costs were obtained through 3 years using claims data. Individual costs, survival, and quality-adjusted life years (QALYs) were projected over a lifetime horizon using regression modeling, US life tables, and external data where needed. Adjustment between groups was performed using propensity score bin bootstrapping.

RESULTS

Screening participants (mean age, 74 years, 41% female, median CHA2DS2-VASC score 3) wore on average 1.7 two-week monitors at a mean cost of $614/person. Over 3 years, outpatient visits were more frequent for monitored than unmonitored individuals (difference 190 per 100 patient-years [95% CI, 82-298]), but emergency department visits (-8.3 [95% CI, -12.6 to -4.1]) and hospitalizations (-15.2 [CI, -22 to -8.6]) were less frequent. Total adjusted 3-year costs were slightly higher (mean difference, $1551 [95% CI, -$1047 to $4038]) in the monitoring group. In patient-level projections, the monitoring group had slightly greater quality-adjusted survival (8.81 versus 8.71 QALYs, difference, 0.09 [95% CI, -0.05 to 0.24]) and slightly higher lifetime costs, resulting in an incremental cost-effectiveness ratio of $36 100/QALY gained. With bootstrap resampling, the incremental cost-effectiveness ratio for monitoring was <$50 000/QALY in 64% of study replicates, and <$150 000/QALY in 91%.

CONCLUSIONS

Using lifetime projections derived from the mSToPS study, we found that AF screening using 2-week patch monitors in older Americans was associated with high economic value. Confirmation of these uncertain findings in a randomized trial is warranted.

REGISTRATION

URL: https://www.clinicaltrials.gov; Unique identifier: NCT02506244.

Non-invasive mid-term electrocardiogram patch monitoring is effective in detecting atrial fibrillation

BACKGROUND

Atrial fibrillation (AF) is a cause of serious morbidity such as stroke. Early detection and treatment of AF is important. Current guidelines recommend screening via opportunistic pulse taking or 12‑lead electrocardiogram. Mid-term ECG patch monitors increases the sensitivity of AF detection.

METHODS

The Singapore Atrial Fibrillation Study is a prospective multi-centre study aiming to study the incidence of AF in patients with no prior AF and a CHA2DS2-VASc score of at least 1, with the use of a mid-term continuous ECG monitoring device (Spyder ECG). Consecutive patients from both inpatient and outpatient settings were recruited from 3 major hospitals from May 2016 to December 2019.

RESULTS

Three hundred and fifty-five patients were monitored. 6 patients (1.7%) were diagnosed with AF. There were no significant differences in total duration of monitoring between the AF and non-AF group (6.39 ± 3.19 vs 5.42 ± 2.46 days, p = 0.340). Patients with newly detected AF were more likely to have palpitations (50.0% vs 11.8%, p = 0.027). Half of the patients (n = 3, 50.0%) were diagnosed on the first day of monitoring and the rest were diagnosed after 24 h. On univariate analysis, only hyperlipidemia was associated with reduced odds of being diagnosed with AF (OR HR 0.08 CI 0.01-0.74, p = 0.025). In a group of 128 patients who underwent coronary artery bypass grafting and had post-operative ECG monitoring, 9 patients (7.0%) were diagnosed with post-operative AF.

CONCLUSIONS

The use of non-invasive mid-term patch-based ECG monitoring is an effective modality for AF screening.

Atrial Fibrillation Recurrence in Patients With Transient New-Onset Atrial Fibrillation Detected During Hospitalization for Noncardiac Surgery or Medical Illness : A Matched Cohort Study

BACKGROUND

Atrial fibrillation (AF) is often detected for the first time in patients who are hospitalized for another reason. Long-term risks for AF recurrence in these patients are unclear.

OBJECTIVE

To estimate risk for AF recurrence in patients with new-onset AF during a hospitalization for noncardiac surgery or medical illness compared with a matched population without AF.

DESIGN

Matched cohort study. (ClinicalTrials.gov: NCT03221777).

SETTING

Three academic hospitals in Hamilton, Ontario, Canada.

PARTICIPANTS

The study enrolled patients hospitalized for noncardiac surgery or medical illness who had transient new-onset AF. For each participant, an age- and sex-matched control participant with no history of AF from the same hospital ward was recruited. All participants left the hospital in sinus rhythm.

MEASUREMENTS

14-day electrocardiographic (ECG) monitor at 1 and 6 months and telephone assessment at 1, 6, and 12 months. The primary outcome was AF lasting at least 30 seconds on the monitor or captured by ECG 12-lead during routine care at 12 months.

RESULTS

Among 139 participants with transient new-onset AF (70 patients with medical illness and 69 surgical patients) and 139 matched control participants, the mean age was 71 years (SD, 10), the mean CHA2DS2-VASc score was 3.0 (SD, 1.5), and 59% were male. The median duration of AF during the index hospitalization was 15.8 hours (IQR, 6.4 to 49.6 hours). After 1 year, recurrent AF was detected in 33.1% (95% CI, 25.3% to 40.9%) of participants in the transient new-onset AF group and 5.0% (CI, 1.4% to 8.7%) of matched control participants; after adjustment for the number of ECG monitors worn and for baseline clinical differences, the adjusted relative risk was 6.6 (CI, 3.2 to 13.7). After exclusion of participants who had electrical or pharmacologic cardioversion during the index hospitalization (n = 40) and their matched control participants and limiting to AF events detected by the patch ECG monitor, recurrent AF was detected in 32.3% (CI, 23.1% to 41.5%) of participants with transient new-onset AF and 3.0% (CI, 0% to 6.4%) of matched control participants.

LIMITATIONS

Generalizability is limited, and the study was underpowered to evaluate subgroups and clinical predictors.

CONCLUSION

Among patients who have transient new-onset AF during a hospitalization for noncardiac surgery or medical illness, approximately 1 in 3 will have recurrent AF within 1 year.

PRIMARY FUNDING SOURCE

Peer-reviewed grants.

Comparison of the 11-Day Adhesive ECG Patch Monitor and 24-h Holter Tests to Assess the Response to Antiarrhythmic Drug Therapy in Paroxysmal Atrial Fibrillation

Accurate assessment of the response to the antiarrhythmic drug (AAD) in atrial fibrillation (AF) is crucial to achieve adequate rhythm control. We evaluated the effectiveness of extended cardiac monitoring using an adhesive ECG patch in the detection of drug-refractory paroxysmal AF. Patients diagnosed with paroxysmal AF and receiving AAD therapy were enrolled. The subjects simultaneously underwent 11-day adhesive ECG patch monitoring and a 24-h Holter test. The primary study outcome was a detection rate of drug-refractory AF or atrial tachycardia (AT) lasting ≥30 s. A total of 59 patients were enrolled and completed the study examinations. AF or AT was detected in 28 (47.5%) patients by an 11-day ECG patch monitor and in 8 (13.6%) patients by a 24-h Holter test (p < 0.001). The 11-day ECG patch monitor identified an additional 20 patients (33.8%) with drug-refractory AF not detected by the 24-h Holter, and as a result, the treatment plan was changed in 11 patients (10 catheter ablations, one medication change). In conclusion, extended cardiac rhythm monitoring using an adhesive ECG patch in patients with paroxysmal AF under AAD therapy led to over a threefold higher detection of drug-refractory AF episodes, compared to the 24-h Holter test.

Future Innovations in Novel Detection for Atrial Fibrillation (FIND-AF): pilot study of an electronic health record machine learning algorithm-guided intervention to identify undiagnosed atrial fibrillation

INTRODUCTION

Atrial fibrillation (AF) is associated with a fivefold increased risk of stroke. Oral anticoagulation reduces the risk of stroke, but AF is elusive. A machine learning algorithm (Future Innovations in Novel Detection of Atrial Fibrillation (FIND-AF)) developed to predict incident AF within 6 months using data in primary care electronic health records (EHRs) could be used to guide AF screening. The objectives of the FIND-AF pilot study are to determine yields of AF during ECG monitoring across AF risk estimates and establish rates of recruitment and protocol adherence in a remote AF screening pathway.

METHODS AND ANALYSIS

The FIND-AF Pilot is an interventional, non-randomised, single-arm, open-label study that will recruit 1955 participants aged 30 years or older, without a history of AF and eligible for oral anticoagulation, identified as higher risk and lower risk by the FIND-AF risk score from their primary care EHRs, to a period of remote ECG monitoring with a Zenicor-ECG device. The primary outcome is AF diagnosis during ECG monitoring, and secondary outcomes include recruitment rates, withdrawal rates, adherence to ECG monitoring and prescription of oral anticoagulation to participants diagnosed with AF during ECG monitoring.

ETHICS AND DISSEMINATION

The study has ethical approval (the North West-Greater Manchester South Research Ethics Committee reference 23/NW/0180). Findings will be announced at relevant conferences and published in peer-reviewed journals in line with the Funder's open access policy.

TRIAL REGISTRATION NUMBER

NCT05898165.

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.

Fully digital self-screening for atrial fibrillation with patch electrocardiogram

AIMS

Atrial fibrillation (AF) is the most common arrhythmia worldwide. The AF is associated with severe mortality, morbidity, and healthcare costs, and guidelines recommend screening people at risk. However, screening methods and organization still need to be clarified. The current study aimed to assess the feasibility of a fully digital self-screening procedure and to assess the prevalence of undetected AF using a continuous patch electrocardiogram (ECG) monitoring system.

METHODS AND RESULTS

Individuals ≥65 years old with at least one additional risk factor for stroke from the general population of Norway were invited to a fully digital continuous self-screening for AF using a patch ECG device (ECG247 Smart Heart Sensor). Participants self-reported clinical characteristics and usability online, and all participants received digital feedback of their results. A total of 2118 individuals with a mean CHA2DS2-VASc risk score of 2.6 (0.9) were enrolled in the study [74% women; mean age 70.1 years (4.2)]. Of these, 1849 (87.3%) participants completed the ECG self-screening test, while 215 (10.2%) did not try to start the test and 54 (2.5%) failed to start the test. The system usability score was 84.5. The mean ECG monitoring time was 153 h (87). Atrial fibrillation was detected in 41 (2.2%) individuals.

CONCLUSION

This fully digitalized self-screening procedure for AF demonstrated excellent feasibility. The number needed to screen was 45 to detect one unrecognized case of AF in subjects at risk for stroke. Randomized studies with long-term follow-up are needed to assess whether self-screening for AF can reduce the incidence of AF-related complications.

CLINICAL TRIALS

NCT04700865.

Predictors of participation in atrial fibrillation screening among community residents in China

BACKGROUND

Atrial fibrillation (AF) is associated with increased stroke risk, but many cases of AF remain undiagnosed. Screening is suggested for early detection of AF. However, nonparticipation in screening is frequently reported, and the underlying causes of why patients choose to participate or not are poorly understood.

OBJECTIVES

To explore factors associated with participation in AF screening in a high-risk population in China.

METHODS

A cross-sectional study was conducted among community residents who were at risk for AF in Guangzhou, China, from February to September 2022. Data on AF knowledge, attitude, subjective norms, perceived behavioral control, and willingness to participate in AF screening were collected. Sociodemographic and clinical data were also collected. Multiple linear stepwise regression analysis was performed to explore predictors for participation in AF screening.

RESULTS

In total, 420 participants were included, with a mean age of 74.4 (±7.43) years old. The results showed that 77.4% of participants reported that they were likely to participate in AF screening. The results of multiple linear regression showed that perceived behavioral control (β =0.591, 95% CI: 0.071, 0.094), attitude (β =0.085, 95% CI: 0.001, 0.025), and having an AF diagnosis (β =0.098, 95% CI: 0.068, 0.494) were positively associated with willingness to participate in AF screening.

CONCLUSIONS

Chinese patients are more likely to participate in AF screening when they perceive great control over their behavior, hold a positive attitude, and have an AF diagnosis. The findings provide clues for future interventions aimed at improving the AF screening participation rate.

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.

Identification and validation of key genes associated with atrial fibrillation in the elderly

Background

Atrial fibrillation (AF) is the most common cardiac arrhythmia and significantly increases the risk of stroke and heart failure (HF), contributing to a higher mortality rate. Increasing age is a major risk factor for AF; however, the mechanisms of how aging contributes to the occurrence and progression of AF remain unclear. This study conducted weighted gene co-expression network analysis (WGCNA) to identify key modules and hub genes and determine their potential associations with aging-related AF.

Materials and methods

WGCNA was performed using the AF dataset GSE2240 obtained from the Gene Expression Omnibus, which contained data from atrial myocardium in cardiac patients with permanent AF or sinus rhythm (SR). Hub genes were identified in clinical samples. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were also performed.

Results

Green and pink were the most critical modules associated with AF, from which nine hub genes, PTGDS, COLQ, ASTN2, VASH1, RCAN1, AMIGO2, RBP1, MFAP4, and ALDH1A1, were hypothesized to play key roles in the AF pathophysiology in elderly and seven of them have high diagnostic value. Functional enrichment analysis demonstrated that the green module was associated with the calcium, cyclic adenosine monophosphate (cAMP), and peroxisome proliferator-activated receptors (PPAR) signaling pathways, and the pink module may be associated with the transforming growth factor beta (TGF-β) signaling pathway in myocardial fibrosis.

Conclusion

We identified nine genes that may play crucial roles in the pathophysiological mechanism of aging-related AF, among which six genes were associated with AF for the first time. This study provided novel insights into the impact of aging on the occurrence and progression of AF, and identified biomarkers and potential therapeutic targets for AF.

Antithrombotic therapy and bleeding risk in the era of aggressive lipid-lowering: current evidence, clinical implications, and future perspectives

ABSTRACT

The clinical efficacy of proprotein convertase subtilisin/kexin type 9 inhibitors (PCSK9i) in reducing major cardiovascular adverse events related to atherosclerotic cardiovascular disease (ASCVD) has been well established in recent large randomized outcome trials. Although the cardiovascular and all-cause mortality benefit of PCSK9i remains inconclusive, current cholesterol management guidelines have been modified toward more aggressive goals for lowering low-density lipoprotein cholesterol (LDL-C). Consequently, the emerging concept of "the lower the better" has become the paradigm of ASCVD prevention. However, there is evidence from observational studies of a U-shaped association between baseline LDL-C levels and all-cause mortality in population-based cohorts. Among East Asian populations, low LDL-C was associated with an increased risk for hemorrhagic stroke in patients not on antithrombotic therapy. Accumulating evidence showed that low LDL-C was associated with an enhanced bleeding risk in patients on dual antiplatelet therapy following percutaneous coronary intervention. Additionally, low LDL-C was associated with a higher risk for incident atrial fibrillation and thereby, a possible increase in the risk for intracranial hemorrhage after initiation of anticoagulation therapy. The mechanism of low-LDL-C-related bleeding risk has not been fully elucidated. This review summarizes recent evidence of low-LDL-C-related bleeding risk in patients on antithrombotic therapy and discusses potential measures for reducing this risk, underscoring the importance of carefully weighing the pros and cons of aggressive LDL-C lowering in patients on antithrombotic therapy.

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.

The DZHK research platform: maximisation of scientific value by enabling access to health data and biological samples collected in cardiovascular clinical studies

The German Centre for Cardiovascular Research (DZHK) is one of the German Centres for Health Research and aims to conduct early and guideline-relevant studies to develop new therapies and diagnostics that impact the lives of people with cardiovascular disease. Therefore, DZHK members designed a collaboratively organised and integrated research platform connecting all sites and partners. The overarching objectives of the research platform are the standardisation of prospective data and biological sample collections among all studies and the development of a sustainable centrally standardised storage in compliance with general legal regulations and the FAIR principles. The main elements of the DZHK infrastructure are web-based and central units for data management, LIMS, IDMS, and transfer office, embedded in a framework consisting of the DZHK Use and Access Policy, and the Ethics and Data Protection Concept. This framework is characterised by a modular design allowing a high standardisation across all studies. For studies that require even tighter criteria additional quality levels are defined. In addition, the Public Open Data strategy is an important focus of DZHK. The DZHK operates as one legal entity holding all rights of data and biological sample usage, according to the DZHK Use and Access Policy. All DZHK studies collect a basic set of data and biosamples, accompanied by specific clinical and imaging data and biobanking. The DZHK infrastructure was constructed by scientists with the focus on the needs of scientists conducting clinical studies. Through this, the DZHK enables the interdisciplinary and multiple use of data and biological samples by scientists inside and outside the DZHK. So far, 27 DZHK studies recruited well over 11,200 participants suffering from major cardiovascular disorders such as myocardial infarction or heart failure. Currently, data and samples of five DZHK studies of the DZHK Heart Bank can be applied for.

Wearable Devices in Cardiovascular Medicine

Wearable devices, such as smartwatches and activity trackers, are commonly used by patients in their everyday lives to manage their health and well-being. These devices collect and analyze long-term continuous data on measures of behavioral or physiologic function, which may provide clinicians with a more comprehensive view of a patients' health compared with the traditional sporadic measures captured by office visits and hospitalizations. Wearable devices have a wide range of potential clinical applications ranging from arrhythmia screening of high-risk individuals to remote management of chronic conditions such as heart failure or peripheral artery disease. As the use of wearable devices continues to grow, we must adopt a multifaceted approach with collaboration among all key stakeholders to effectively and safely integrate these technologies into routine clinical practice. In this Review, we summarize the features of wearable devices and associated machine learning techniques. We describe key research studies that illustrate the role of wearable devices in the screening and management of cardiovascular conditions and identify directions for future research. Last, we highlight the challenges that are currently hindering the widespread use of wearable devices in cardiovascular medicine and provide short- and long-term solutions to promote increased use of wearable devices in clinical care.

Protocol for a Systematic Review and Individual Participant Data Meta-Analysis of Randomized Trials of Screening for Atrial Fibrillation to Prevent Stroke

INTRODUCTION

 Atrial fibrillation (AF) is a common cause of stroke. Timely diagnosis of AF and treatment with oral anticoagulation (OAC) can prevent up to two-thirds of AF-related strokes. Ambulatory electrocardiographic (ECG) monitoring can identify undiagnosed AF in at-risk individuals, but the impact of population-based ECG screening on stroke is uncertain, as ongoing and published randomized controlled trials (RCTs) have generally been underpowered for stroke.

METHODS AND ANALYSIS

 The AF-SCREEN Collaboration, with support from AFFECT-EU, have begun a systematic review and individual participant data meta-analysis of RCTs evaluating ECG screening for AF. The primary outcome is stroke. Secondary outcomes include AF detection, OAC prescription, hospitalization, mortality, and bleeding.After developing a common data dictionary, anonymized data will be collated from individual trials into a central database. We will assess risk of bias using the Cochrane Collaboration tool, and overall quality of evidence with the Grading of Recommendations Assessment, Development and Evaluation approach.We will pool data using random effects models. Prespecified subgroup and multilevel meta-regression analyses will explore heterogeneity. We will perform prespecified trial sequential meta-analyses of published trials to determine when the optimal information size has been reached, and account for unpublished trials using the SAMURAI approach.

IMPACT AND DISSEMINATION

 Individual participant data meta-analysis will generate adequate power to assess the risks and benefits of AF screening. Meta-regression will permit exploration of the specific patient, screening methodology, and health system factors that influence outcomes.

TRIAL REGISTRATION NUMBER

 PROSPERO CRD42022310308.

Contemporary prevalence estimates of undiagnosed and diagnosed atrial fibrillation in the United States

BACKGROUND

Atrial fibrillation (AF) prevalence estimates vary and have been based on cohorts with clinically established or diagnosed disease. Undiagnosed AF prevalence estimates are less certain as they are based on nongeneralizable convenience samples.

HYPOTHESIS

Because AF is often asymptomatic, it my remain undiagnosed until the development of complications such as stroke or heart failure. Consequently, the observed prevalence of diagnosed AF from the literature may underestimate total disease burden. We therefore sought to estimate the total prevalence of both diagnosed and undiagnosed AF.

METHODS

We performed a retrospective cohort study from 2012 to 2017 using data from five US medical claims data sets. Undiagnosed AF prevalence was estimated based on the observed incidence of ischemic stroke, systemic embolism (SE), and AF incidence after a stroke/SE. The diagnosed AF cohort included AF patients between Q1 2014 and Q3 2015. The undiagnosed AF cohort were patients with assumed undiagnosed AF in the year before a stroke/SE and who were newly diagnosed with AF in the 3-month poststroke/SE. Stroke/SE incidence was calculated among all AF patients and the ratio of number of undiagnosed AF patients to stroke rate was created. Age- and sex-adjusted estimates were stratified by period of assumed undiagnosed AF before poststroke/SE AF diagnosis (1 or 2 years).

RESULTS

The estimated US prevalence of AF (diagnosed and undiagnosed) in Q3 2015 was 5 628 000 cases, of which 591 000 cases (11%) were undiagnosed. The assumed 2-year undiagnosed AF prevalence was 23% (1 531 000) of the total prevalent patients with AF (6 568 000). Undiagnosed (vs. diagnosed) AF patients were older and had higher CHA2DS2-VASc scores. Of undiagnosed AF, 93% had CHA2DS2-VASc ≥2 and met OAC criteria.

CONCLUSIONS

These contemporary estimates demonstrate the high prevalence of undiagnosed AF in the United States. Undiagnosed AF patients are composed of primarily elderly individuals who if diagnosed, would meet criteria for stroke prevention therapy.

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.

Prevalence and Prognostic Significance of Bradyarrhythmias in Patients Screened for Atrial Fibrillation vs Usual Care: Post Hoc Analysis of the LOOP Randomized Clinical Trial

Importance

There is increasing interest in heart rhythm monitoring and technologies to detect subclinical atrial fibrillation (AF), which may lead to incidental diagnosis of bradyarrhythmias.

Objective

To assess bradyarrhythmia prevalence and prognostic significance in persons screened for AF using implantable loop recorder (ILR) compared with unscreened persons.

Design, Setting, and Participants

This was a post hoc analysis of the Implantable Loop Recorder Detection of Atrial Fibrillation to Prevent Stroke (LOOP) randomized clinical trial, which took place in 4 sites in Denmark. Participants were 70 years or older without known AF but diagnosed with at least 1 of the following: hypertension, diabetes, heart failure, or prior stroke. Participants were recruited by letter invitation between January 31, 2014, and May 17, 2016. The median (IQR) follow-up period was 65 (59-70) months. Analysis took place between February and June 2022.

Interventions

ILR screening for AF with treatment of any bradyarrhythmia left to the discretion of the treating physician (ILR group) vs usual care (control group).

Main Outcomes and Measures

Adjudicated bradyarrhythmia episodes, pacemaker implantation, syncope, and sudden cardiovascular death.

Results

A total of 6004 participants were randomized (mean [SD] age, 75 [4.1] years; 2837 [47.3%] female; 5444 [90.7%] with hypertension; 1224 [20.4%] with prior syncope), 4503 to control and 1501 to ILR. Bradyarrhythmia was diagnosed in 172 participants (3.8%) in the control group vs 312 participants (20.8%) in the ILR group (hazard ratio [HR], 6.21 [95% CI, 5.15-7.48]; P < .001), and these were asymptomatic in 41 participants (23.8%) vs 249 participants (79.8%), respectively. The most common bradyarrhythmia was sinus node dysfunction followed by high-grade atrioventricular block. Risk factors for bradyarrhythmia included higher age, male sex, and prior syncope. A pacemaker was implanted in 132 participants (2.9%) vs 67 (4.5%) (HR, 1.53 [95% CI, 1.14-2.06]; P < .001), syncope occurred in 120 (2.7%) vs 33 (2.2%) (HR, 0.83 [95% CI, 0.56-1.22]; P = .34), and sudden cardiovascular death occurred in 49 (1.1%) vs 18 (1.2%) (HR, 1.11 [95% CI, 0.64-1.90]; P = .71) in the control and ILR groups, respectively. Bradyarrhythmias were associated with subsequent syncope, cardiovascular death, and all-cause death, with no interaction between bradyarrhythmia and randomization group.

Conclusions and Relevance

More than 1 in 5 persons older than 70 years with cardiovascular risk factors can be diagnosed with bradyarrhythmias when long-term continous monitoring for AF is applied. In this study, ILR screening led to a 6-fold increase in bradyarrhythmia diagnoses and a significant increase in pacemaker implantations compared with usual care but no change in the risk of syncope or sudden death.

An ECG-based machine learning model for predicting new-onset atrial fibrillation is superior to age and clinical features in identifying patients at high stroke risk

BACKGROUND

Several large trials have employed age or clinical features to select patients for atrial fibrillation (AF) screening to reduce strokes. We hypothesized that a machine learning (ML) model trained to predict AF risk from 12‑lead electrocardiogram (ECG) would be more efficient than criteria based on clinical variables in indicating a population for AF screening to potentially prevent AF-related stroke.

METHODS

We retrospectively included all patients with clinical encounters in Geisinger without a prior history of AF. Incidence of AF within 1 year and AF-related strokes within 3 years of the encounter were identified. AF-related stroke was defined as a stroke where AF was diagnosed at the time of stroke or within a year after the stroke. The efficiency of five methods was evaluated for selecting a cohort for AF screening. The methods were selected from four clinical trials (mSToPS, GUARD-AF, SCREEN-AF and STROKESTOP) and the ECG-based ML model. We simulated patient selection for the five methods between the years 2011 and 2014 and evaluated outcomes for 1 year intervals between 2012 and 2015, resulting in a total of twenty 1-year periods. Patients were considered eligible if they met the criteria before the start of the given 1-year period or within that period. The primary outcomes were numbers needed to screen (NNS) for AF and AF-associated stroke.

RESULTS

The clinical trial models indicated large proportions of the population with a prior ECG for AF screening (up to 31%), coinciding with NNS ranging from 14 to 18 for AF and 249-359 for AF-associated stroke. At comparable sensitivity, the ECG ML model indicated a modest number of patients for screening (14%) and had the highest efficiency in NNS for AF (7.3; up to 60% reduction) and AF-associated stroke (223; up to 38% reduction).

CONCLUSIONS

An ECG-based ML risk prediction model is more efficient than contemporary AF-screening criteria based on age alone or age and clinical features at indicating a population for AF screening to potentially prevent AF-related strokes.

General practitioners' perceptions on opportunistic single-time point screening for atrial fibrillation: A European quantitative survey

Background

There is no clear guidance on how to implement opportunistic atrial fibrillation (AF) screening in daily clinical practice.

Objectives

This study evaluated the perception of general practitioners (GPs) about value and practicalities of implementing screening for AF, focusing on opportunistic single-time point screening with a single-lead electrocardiogram (ECG) device.

Methods

A descriptive cross-sectional study was conducted with a survey developed to assess overall perception concerning AF screening, feasibility of opportunistic single-lead ECG screening and implementation requirements and barriers.

Results

A total of 659 responses were collected (36.1% Eastern, 33.4% Western, 12.1% Southern, 10.0% Northern Europe, 8.3% United Kingdom & Ireland). The perceived need for standardized AF screening was rated as 82.7 on a scale from 0 to 100. The vast majority (88.0%) indicated no AF screening program is established in their region. Three out of four GPs (72.1%, lowest in Eastern and Southern Europe) were equipped with a 12-lead ECG, while a single-lead ECG was less common (10.8%, highest in United Kingdom & Ireland). Three in five GPs (59.3%) feel confident ruling out AF on a single-lead ECG strip. Assistance through more education (28.7%) and a tele-healthcare service offering advice on ambiguous tracings (25.2%) would be helpful. Preferred strategies to overcome barriers like insufficient (qualified) staff, included integrating AF screening with other healthcare programs (24.9%) and algorithms to identify patients most suitable for AF screening (24.3%).

Conclusion

GPs perceive a strong need for a standardized AF screening approach. Additional resources may be required to have it widely adopted into clinical practice.

Screen-Detected Atrial Fibrillation and "Micro-Atrial Fibrillation" and Risk of Cardiovascular Events after Myocardial Infarction in Elderly Patients

BACKGROUND

Incident atrial fibrillation (AF) occurs in 5-10% of patients after acute myocardial infarction (AMI) and is associated with adverse outcomes. Guidelines now recommend screening for AF in all elderly patients. However, the relevance of screen-detected AF and short episodes of irregular supraventricular ectopic beats ("micro-AF") after AMI is unknown.

OBJECTIVES

The objective of the study was to investigate the value of 2-week intermittent ECG screening to detect incident AF and "micro-AF" in elderly patients 12 months after an AMI and its association with risk of cardiovascular events.

METHODS

This was an investigator-initiated, multicenter sub-study of the OMega-3 fatty acids in Elderly patients with Myocardial Infarction (OMEMI) trial, in Norway. Women and men aged 70-82 years, with a recent AMI, were recruited during 2012-2018. All participants had a 12-lead ECG performed at 3, 12, and 24 months. Patients without AF 1 year after the index AMI underwent 2 weeks of intermittent 30-s "thumb ECG" screening. Incident AF and "micro-AF" (episodes of ≥3 consecutive irregular supraventricular ectopic beats) were registered, and the association with risk of major cardiovascular events (MACEs; nonfatal AMI, stroke, coronary revascularization, hospitalization for heart failure, or all-cause death) was analyzed with logistic regression.

RESULTS

Among 1014 patients (198 [28.7%] women), 255 (25.1%) had known AF or AF identified at baseline. New-onset AF was detected clinically or at study visits in 39 (3.8%) patients. By screening participants without AF (n = 567), unknown AF was identified in 4 (0.7%) and "micro-AF" in 27 (4.8%) patients. Among 43 patients with incident AF, 21 (48.8%) experienced a MACE, which was significantly higher than those without AF (n = 114, 15.9%; p < 0.001), driven by a higher risk of AMI or revascularization. Nine (33.3%) patients with "micro-AF" and 75 (13.9%) without "micro-AF" experienced a MACE (p = 0.002), explained mostly by a higher risk of heart failure hospitalization (p < 0.001). Using patients without AF and "micro-AF" as reference, "micro-AF" was associated with an intermediate risk of MACE (OR 2.8; 95% CI 1.2-6.4) and new-onset AF with a high risk of MACE (OR 5.3; 95% CI 2.8-10.0).

CONCLUSIONS

Two-week intermittent ECG screening identified few cases of new-onset AF but a substantial number of patients with "micro-AF." "Micro-AF" was associated with an increased risk of major cardiovascular events, albeit with an intermediate risk compared to those with new-onset AF.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Personalized approach using wearable technology for early detection of atrial fibrillation in high-risk primary care patients (PATCH-AF): Study protocol for a cluster randomized controlled trial

BACKGROUND

Atrial fibrillation (AF) is a common cardiac arrhythmia with a lifetime risk of one in 4. Unfortunately, AF often remains undetected, particularly when it is paroxysmal, for which single time-point evaluation is less effective. Recently, unobtrusive cardiac arrhythmia monitoring devices have become available, providing the opportunity to conduct prolonged electrocardiographic (ECG) monitoring in a patient-friendly manner. We hypothesize that applying these devices in at risk patients may improve AF detection, particularly when used during repeated episodes. We therefore aim to evaluate the diagnostic yield of yearly screening for atrial fibrillation when using a wearable device for continuous ECG monitoring for 7 days in primary care patients ≥ 65 years deemed at high-risk of AF (CHA₂DS₂VASc score ≥3 for men or ≥4 for women) compared with usual care over a study period of 3 years.

METHODS

Primary care based, cluster-randomized controlled trial with 10 general practices randomized to the intervention group and 10 general practices randomized to control group. In each group, we aim to enroll 930 patients, ≥65 years and a CHA₂DS₂VASc score ≥3 for men or ≥ 4 for women. The intervention consists of continuous ECG monitoring for 7 days at start of the study (t = 0), after one (t = 1) and 2 years (t = 2). The control practices will follow usual diagnostic care procedures.

RESULTS

Results are expected in 2025.

CONCLUSIONS

This study differs from previous randomized controlled trials, as it involves longitudinal screening of a risk-stratified population. In case of a beneficial diagnostic yield, the PATCH-AF study will add to the evidence for AF screening.

TRIAL REGISTRATION

The PATCH-AF study is registered at The Netherlands Trial Register (NTR number NL9656).

Prolonged cardiac monitoring for stroke prevention: A systematic review and meta-analysis of randomized-controlled clinical trials

Introduction:

Prolonged cardiac monitoring (PCM) substantially improves the detection of subclinical atrial fibrillation (AF) among patients with history of ischemic stroke (IS), leading to prompt initiation of anticoagulants. However, whether PCM may lead to IS prevention remains equivocal.

Patients and methods:

In this systematic review and meta-analysis, randomized-controlled clinical trials (RCTs) reporting IS rates among patients with known cardiovascular risk factors, including but not limited to history of IS, who received PCM for more than 7 days versus more conservative cardiac rhythm monitoring methods were pooled.

Results:

Seven RCTs were included comprising a total of 9048 patients with at least one known cardiovascular risk factor that underwent cardiac rhythm monitoring. PCM was associated with reduction of IS occurrence compared to conventional monitoring (Risk Ratio: 0.76; 95% CI: 0.59–0.96; I2 = 0%). This association was also significant in the subgroup of RCTs investigating implantable cardiac monitoring (Risk Ratio: 0.75; 95% CI: 0.58–0.97; I2 = 0%). However, when RCTs assessing PCM in both primary and secondary prevention settings were excluded or when RCTs investigating PCM with a duration of 7 days or less were included, the association between PCM and reduction of IS did not retain its statistical significance. Regarding the secondary outcomes, PCM was related to higher likelihood for AF detection and anticoagulant initiation. No association was documented between PCM and IS/transient ischemic attack occurrence, all-cause mortality, intracranial hemorrhage, or major bleeding.

Conclusion:

PCM may represent an effective stroke prevention strategy in selected patients. Additional RCTs are warranted to validate the robustness of the reported associations.

Detection of Atrial Fibrillation in a Large Population Using Wearable Devices: The Fitbit Heart Study

BACKGROUND

Morbidity from undiagnosed atrial fibrillation (AF) may be preventable with early detection. Many consumer wearables contain optical photoplethysmography (PPG) sensors to measure pulse rate. PPG-based software algorithms that detect irregular heart rhythms may identify undiagnosed AF in large populations using wearables, but minimizing false-positive detections is essential.

METHODS

We performed a prospective remote clinical trial to examine a novel PPG-based algorithm for detecting undiagnosed AF from a range of wrist-worn devices. Adults aged ≥22 years in the United States without AF, using compatible wearable Fitbit devices and Android or iOS smartphones, were included. PPG data were analyzed using a novel algorithm that examines overlapping 5-minute pulse windows (tachograms). Eligible participants with an irregular heart rhythm detection (IHRD), defined as 11 consecutive irregular tachograms, were invited to schedule a telehealth visit and were mailed a 1-week ambulatory ECG patch monitor. The primary outcome was the positive predictive value of the first IHRD during ECG patch monitoring for concurrent AF.

RESULTS

A total of 455 699 participants enrolled (median age 47 years, 71% female, 73% White) between May 6 and October 1, 2020. IHRDs occurred for 4728 (1%) participants, and 2070 (4%) participants aged ≥65 years during a median of 122 (interquartile range, 110-134) days at risk for an IHRD. Among 1057 participants with an IHRD notification and subsequent analyzable ECG patch monitor, AF was present in 340 (32.2%). Of the 225 participants with another IHRD during ECG patch monitoring, 221 had concurrent AF on the ECG and 4 did not, resulting in an IHRD positive predictive value of 98.2% (95% CI, 95.5%-99.5%). For participants aged ≥65 years, the IHRD positive predictive value was 97.0% (95% CI, 91.4%-99.4%).

CONCLUSIONS

A novel PPG software algorithm for wearable Fitbit devices exhibited a high positive predictive value for concurrent AF and identified participants likely to have AF on subsequent ECG patch monitoring. Wearable devices may facilitate identifying individuals with undiagnosed AF.

REGISTRATION

URL: https://www.

CLINICALTRIALS

gov; Unique identifier: NCT04380415.

Stroke Prevention in Atrial Fibrillation

PURPOSE OF REVIEW

Atrial fibrillation is associated with a significant increase in stroke and systemic embolism. This review explores the areas of stroke prevention.

RECENT FINDINGS

In the last decade, NOAC has overtaken warfarin as the anticoagulant of choice for stroke prevention in AF. For patients unable to take anticoagulation, LAA closure has proven to be a valid option. The use of digital devices has led to widespread consumer-directed AF screening. It remains to be determined if all device detect AF pose the same amount of risk as recent studies have shown that short and infrequent episodes of AF may not benefit from anticoagulation. Stroke prevention is paramount in the management of AF. In this review we describe the risk factors contributing to stroke, recent advances in antithrombotic therapies, and the increasing role of digital health in guiding AF detection and stroke prevention.