Emerging Technologies for Identifying Atrial Fibrillation

Episode-level and clinical characterization of asymptomatic atrial fibrillation events

INTRODUCTION

Not all patients experience debilitating symptoms during Atrial Fibrillation (AF), some are asymptomatic. The reasons for this inter- and intrasubject variability is unknown.

PURPOSE

The study objective was NOAH characterize episode-level and clinical characteristics associated with symptomatic versus asymptomatic episodes of AF in patients with an implantable cardiac monitor (ICM).

METHODS

Patients with an AF episode detected on an ICM between 2007 and 2021 with overlapping clinical data from aggregated Electronic Health Records in the Optum® deidentified data set were included. Symptomatic episodes were labeled in real-time by the patient. Heart rate (HR) at onset, mean HR, AF Evidence Score (a measure of beat-to-beat irregularity), episode duration and Activity Index were evaluated for association with symptom status using multivariable regression modeling.

RESULTS

11 267 patients had AF episodes with clinical data available. The 1776 (15.8%) patients who reported symptomatic AF episodes were younger (67 ± 12 years vs. 71 ± 11 years old, p < .001) and had fewer cardiovascular co-morbidities than patients with asymptomatic AF exclusively. Symptomatic episodes were longer (5.5 [2.4, 14.4] h vs. 3.7 [1.7, 11] h, p < .001), had higher mean HR (103 ± 22 bpm vs. 88 ± 22 bpm, p < .001) and higher AF evidence scores (98 ± 27 vs. 82 ± 24, p < .001). These features were independently associated with symptomatic episodes on multivariable regression analysis and per-subject analysis in patients who had both symptomatic and asymptomatic episodes.

DISCUSSION

Episode-level characteristics differed between symptomatic AF episodes versus asymptomatic episodes in patients with ICMs. Symptomatic patients also had less comorbidities. These parameters may be useful in understanding variable symptomatic manifestation and remote stratification of AF episodes.

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.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Incidence of atrial fibrillation in patients with renal infarction: A retrospective cohort analysis of the Korean national health insurance registry

BACKGROUND

Regarding the pathophysiology of renal infarction (RI), cardioembolic causes could have large proportion. However, there are notable variations in prevalence of atrial fibrillation (AF) among patients with RI across different studies, ranging from 17 to 65%. The primary objective of this study is to analyze the incidence of AF in patients with RI.

METHODS

This nationwide retrospective cohort study enrolled 5200 patients with RI from the Korean National Institute of Health Services database spanning the years 2013 to 2019. The study accessed the AF incidence rate within 12 months in patients without a prior history of AF. Events occurring within 3 months of RI diagnosis were excluded to mitigate cases diagnosed during the initial screening or those with AF diagnoses that were potentially overlooked in the past.

RESULTS

AF occurred in 19.1% of patients with RI over the entire period (median: 2.5 years, interquartile range 1.04-4.25 years). The majority of AF cases (16.1%) occured within the first year, resulting in an overall incidence rate of 7.0 per 100 person-years. Patients with newly developed AF were, on average, older than those who did not develop AF (64.1 vs. 57.3 years, P < 0.001). The independent predictors of AF were identified as age, male sex, higher body mass index, current smoking, ischemic heart disease, and heart failure.

CONCLUSIONS

Physicians should consider the implementation of active rhythm monitoring for patients with RI to identify potential occurrence of subclinical AF, even if not initially diagnosed during the initial screening after RI diagnosis.

H. Lip G, Thomas GN, J. Moore D, Nirantharakumar K, Kumarendran B, Subaschandran K, Kanesamoorthy S, Uruthirakumar P, Guruparan M. Diagnostic accuracy of digital technologies compared with 12-lead ECG in the diagnosis of atrial fibrillation in adults: A protocol for a systematic review

BACKGROUND

Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia in the world. AF increases the risk of stroke 5-fold, though the risk can be reduced with appropriate treatment. Therefore, early diagnosis is imperative but remains a global challenge. In low-and middle-income countries (LMICs), a lack of diagnostic equipment and under-resourced healthcare systems generate further barriers. The rapid development of digital technologies that are capable of diagnosing AF remotely and cost-effectively could prove beneficial for LMICs. However, evidence is lacking on what digital technologies exist and how they compare in regards to diagnostic accuracy. We aim to systematically review the diagnostic accuracy of all digital technologies capable of AF diagnosis.

METHODS

MEDLINE, Embase and Web of Science will be searched for eligible studies. Free text terms will be combined with corresponding index terms where available and searches will not be limited by language nor time of publication. Cohort or cross-sectional studies comprising adult (≥18 years) participants will be included. Only studies that use a 12-lead ECG as the reference test (comparator) and report outcomes of sensitivity, specificity, the diagnostic odds ratio (DOR) or the positive and negative predictive value (PPV and NPV) will be included (or if they provide sufficient data to calculate these outcomes). Two reviewers will independently assess articles for inclusion, extract data using a piloted tool and assess risk of bias using the QUADAS-2 tool. The feasibility of a meta-analysis will be determined by assessing heterogeneity across the studies, grouped by index device, diagnostic threshold and setting. If a meta-analysis is feasible for any index device, pooled sensitivity and specificity will be calculated using a random effect model and presented in forest plots.

DISCUSSION

The findings of our review will provide a comprehensive synthesis of the diagnostic accuracy of available digital technologies capable for diagnosing AF. Thus, this review will aid in the identification of which devices could be further trialed and implemented, particularly in a LMIC setting, to improve the early diagnosis of AF.

TRIAL REGISTRATION

Systematic review registration: PROSPERO registration number is CRD42021290542. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021290542.

Atrial fibrillation and the risk of early-onset dementia and cognitive decline: An updated review

The relationship between atrial fibrillation (AF) and dementia has been well described; however, recent data suggest that AF confers a greater risk for the development of early-onset dementia irrespective of clinical stroke. Numerous mechanisms have been hypothesized to explain cognitive decline in the setting of AF, including silent cerebral ischemia, cerebral hypoperfusion, and cerebral microvascular disease. Despite the emergence of data supporting the increased risk of early-onset dementia in patients with AF, the underlying mechanism remains unclear. Furthermore, the mechanism may be influenced by survival bias, genetic susceptibility, or early dysfunction of brain adaptation. Investigation into why this relationship exists could change how prevention and treatment are evaluated.

Accuracy, Usability, and Adherence of Smartwatches for Atrial Fibrillation Detection in Older Adults After Stroke: Randomized Controlled Trial

BACKGROUND

Atrial fibrillation (AF) is a common cause of stroke, and timely diagnosis is critical for secondary prevention. Little is known about smartwatches for AF detection among stroke survivors. We aimed to examine accuracy, usability, and adherence to a smartwatch-based AF monitoring system designed by older stroke survivors and their caregivers.

OBJECTIVE

This study aims to examine the feasibility of smartwatches for AF detection in older stroke survivors.

METHODS

Pulsewatch is a randomized controlled trial (RCT) in which stroke survivors received either a smartwatch-smartphone dyad for AF detection (Pulsewatch system) plus an electrocardiogram patch or the patch alone for 14 days to assess the accuracy and usability of the system (phase 1). Participants were subsequently rerandomized to potentially 30 additional days of system use to examine adherence to watch wear (phase 2). Participants were aged 50 years or older, had survived an ischemic stroke, and had no major contraindications to oral anticoagulants. The accuracy for AF detection was determined by comparing it to cardiologist-overread electrocardiogram patch, and the usability was assessed with the System Usability Scale (SUS). Adherence was operationalized as daily watch wear time over the 30-day monitoring period.

RESULTS

A total of 120 participants were enrolled (mean age 65 years; 50/120, 41% female; 106/120, 88% White). The Pulsewatch system demonstrated 92.9% (95% CI 85.3%-97.4%) accuracy for AF detection. Mean usability score was 65 out of 100, and on average, participants wore the watch for 21.2 (SD 8.3) of the 30 days.

CONCLUSIONS

Our findings demonstrate that a smartwatch system designed by and for stroke survivors is a viable option for long-term arrhythmia detection among older adults at risk for AF, though it may benefit from strategies to enhance adherence to watch wear.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03761394; https://clinicaltrials.gov/study/NCT03761394.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1016/j.cvdhj.2021.07.002.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Design and Implementation of an Atrial Fibrillation Detection Algorithm on the ARM Cortex-M4 Microcontroller

At present, a medium-level microcontroller is capable of performing edge computing and can handle the computation of neural network kernel functions. This makes it possible to implement a complete end-to-end solution incorporating signal acquisition, digital signal processing, and machine learning for the classification of cardiac arrhythmias on a small wearable device. In this work, we describe the design and implementation of several classifiers for atrial fibrillation detection on a general-purpose ARM Cortex-M4 microcontroller. We used the CMSIS-DSP library, which supports Naïve Bayes and Support Vector Machine classifiers, with different kernel functions. We also developed Python scripts to automatically transfer the Python model (trained in Scikit-learn) to the C environment. To train and evaluate the models, we used part of the data from the PhysioNet/Computing in Cardiology Challenge 2020 and performed simple classification of atrial fibrillation based on heart-rate irregularity. The performance of the classifiers was tested on a general-purpose ARM Cortex-M4 microcontroller (STM32WB55RG). Our study reveals that among the tested classifiers, the SVM classifier with RBF kernel function achieves the highest accuracy of 96.9%, sensitivity of 98.4%, and specificity of 95.8%. The execution time of this classifier was 720 μs per recording. We also discuss the advantages of moving computing tasks to edge devices, including increased power efficiency of the system, improved patient data privacy and security, and reduced overall system operation costs. In addition, we highlight a problem with false-positive detection and unclear significance of device-detected atrial fibrillation.

Anxiety, patient activation, and quality of life among stroke survivors prescribed smartwatches for atrial fibrillation monitoring

Background

The detection of atrial fibrillation (AF) in stroke survivors is critical to decreasing the risk of recurrent stroke. Smartwatches have emerged as a convenient and accurate means of AF diagnosis; however, the impact on critical patient-reported outcomes, including anxiety, engagement, and quality of life, remains ill defined.

Objectives

To examine the association between smartwatch prescription for AF detection and the patient-reported outcomes of anxiety, patient activation, and self-reported health.

Methods

We used data from the Pulsewatch trial, a 2-phase randomized controlled trial that included participants aged 50 years or older with a history of ischemic stroke. Participants were randomized to use either a proprietary smartphone-smartwatch app for 30 days of AF monitoring or no cardiac rhythm monitoring. Validated surveys were deployed before and after the 30-day study period to assess anxiety, patient activation, and self-rated physical and mental health. Logistic regression and generalized estimation equations were used to examine the association between smartwatch prescription for AF monitoring and changes in the patient-reported outcomes.

Results

A total of 110 participants (mean age 64 years, 41% female, 91% non-Hispanic White) were studied. Seventy percent of intervention participants were novice smartwatch users, as opposed to 84% of controls, and there was no significant difference in baseline rates of anxiety, activation, or self-rated health between the 2 groups. The incidence of new AF among smartwatch users was 6%. Participants who were prescribed smartwatches did not have a statistically significant change in anxiety, activation, or self-reported health as compared to those who were not prescribed smartwatches. The results held even after removing participants who received an AF alert on the watch.

Conclusion

The prescription of smartwatches to stroke survivors for AF monitoring does not adversely affect key patient-reported outcomes. Further research is needed to better inform the successful deployment of smartwatches in clinical practice.

Electrocardiogram Devices for Home Use: Technological and Clinical Scoping Review

BACKGROUND

Electrocardiograms (ECGs) are used by physicians to record, monitor, and diagnose the electrical activity of the heart. Recent technological advances have allowed ECG devices to move out of the clinic and into the home environment. There is a great variety of mobile ECG devices with the capabilities to be used in home environments.

OBJECTIVE

This scoping review aimed to provide a comprehensive overview of the current landscape of mobile ECG devices, including the technology used, intended clinical use, and available clinical evidence.

METHODS

We conducted a scoping review to identify studies concerning mobile ECG devices in the electronic database PubMed. Secondarily, an internet search was performed to identify other ECG devices available in the market. We summarized the devices' technical information and usability characteristics based on manufacturer data such as datasheets and user manuals. For each device, we searched for clinical evidence on the capabilities to record heart disorders by performing individual searches in PubMed and ClinicalTrials.gov, as well as the Food and Drug Administration (FDA) 510(k) Premarket Notification and De Novo databases.

RESULTS

From the PubMed database and internet search, we identified 58 ECG devices with available manufacturer information. Technical characteristics such as shape, number of electrodes, and signal processing influence the capabilities of the devices to record cardiac disorders. Of the 58 devices, only 26 (45%) had clinical evidence available regarding their ability to detect heart disorders such as rhythm disorders, more specifically atrial fibrillation.

CONCLUSIONS

ECG devices available in the market are mainly intended to be used for the detection of arrhythmias. No devices are intended to be used for the detection of other cardiac disorders. Technical and design characteristics influence the intended use of the devices and use environments. For mobile ECG devices to be intended to detect other cardiac disorders, challenges regarding signal processing and sensor characteristics should be solved to increase their detection capabilities. Devices recently released include the use of other sensors on ECG devices to increase their detection capabilities.

Atrial Fibrillation

Evidence for diagnosis and treatment of atrial fibrillation (AF) has expanded substantially since 2017, when In the Clinic last considered this subject. Direct oral anticoagulants have become the predominant therapy for thromboembolic disease, and antidotes for these drugs are now available. Device-based left atrial appendage occlusion is frequently used in patients who cannot tolerate systemic anticoagulation, and growing evidence suggests that early rhythm control improves outcomes. Catheter ablation is now frequently performed to prevent recurrent AF. Managing risk factors for AF, such as hypertension, diabetes, and obesity, remains paramount in prevention of this condition.

Telemedicine in Adult Congenital Heart Disease: Usefulness of Digital Health Technology in the Assistance of Critical Patients

The number of adults with congenital heart disease (ACHD) has progressively increased in recent years to surpass that of children. This population growth has produced a new demand for health care. Moreover, the 2019 coronavirus pandemic has caused significant changes and has underlined the need for an overhaul of healthcare delivery. As a result, telemedicine has emerged as a new strategy to support a patient-based model of specialist care. In this review, we would like to highlight the background knowledge and offer an integrated care strategy for the longitudinal assistance of ACHD patients. In particular, the emphasis is on recognizing these patients as a special population with special requirements in order to deliver effective digital healthcare.

Current status of real-world big data research in the cardiovascular field in Japan

Real-world data (RWD) are observational data obtained by collecting, structuring, and accumulating patient information among the medical big data. RWD are derived from a variety of patient medical care and health information outside of conventional research data, and include electronic health records, claims data, registry data of disease, drug and device, health check-up data, and more recently, patient information data from wearable devices. They are currently being utilized in various forms for optimal medical care and real-world evidence (RWE) is constructed through a process of hypothesis generation and verification based on the RWD research. Together with classic clinical research and pragmatic trials, RWE shapes the learning healthcare system and contributes to the improvement of medical care. In the cardiovascular medical care of the current super-aged society, the need for a variety of RWE and the research is increasing, since the guidelines established over time and the medical care based on it cannot necessarily be the best in accordance with the current medical situation. In this review, we focus on the RWD and RWE studies in the cardiovascular medical field and outlines their current status in Japan. Furthermore, we discuss the potential for extending the studies and issues related to the use of medical big data and RWD.

Contemporary Considerations in the Evolution of Wearable Technology for Arrhythmia Detection

Arrhythmias are an increasingly common cause of hospital admissions worldwide. Late detection of arrhythmias is associated with a significantly increased risk of cardiovascular complications. Early identification and management of life-threatening arrhythmias is paramount to reduce mortality. Wearable technologies are now widespread among the general population, providing a continuous output of healthcare data. However, this data are not routinely integrated into clinical practice. Here, we begin by outlining the current landscape in wearable technology for aiding arrhythmia detection; we then consider the clinical impact of wearable technology for both clinicians and patients; we further highlight the latest and emerging trials in wearable technology for arrhythmia detection and finally postulate the wider implications of the expansion of such cardiac devices.

Implantable loop recorders in patients with atrial fibrillation

INTRODUCTION

Implantable loop recorders (ILRs) provide practitioners with high-quality electrocardiographic data over an extended monitoring period. These data can guide the diagnosis and management of patients with atrial fibrillation (AF).

AREAS COVERED

This review summarizes the available evidence and consensus statements supporting the use of ILRs in the detection of AF, as well as monitoring of patients with known AF. Future directions for research are also discussed.

EXPERT OPINION

ILRs are the gold standard for detecting AF, providing superior diagnostic yield compared to other modes of ambulatory electrocardiography monitoring. Both experimental evidence and consensus statements support the use of ILRs in clinical settings where the diagnosis of AF may significantly change management, or where a high degree of sensitivity is needed. ILRs may also be used to monitor patients following AF ablation. More evidence is needed to better inform how ILR-detected AF should change management.

Consumer-Led Screening for Atrial Fibrillation: Frontier Review of the AF-SCREEN International Collaboration

The technological evolution and widespread availability of wearables and handheld ECG devices capable of screening for atrial fibrillation (AF), and their promotion directly to consumers, has focused attention of health care professionals and patient organizations on consumer-led AF screening. In this Frontiers review, members of the AF-SCREEN International Collaboration provide a critical appraisal of this rapidly evolving field to increase awareness of the complexities and uncertainties surrounding consumer-led AF screening. Although there are numerous commercially available devices directly marketed to consumers for AF monitoring and identification of unrecognized AF, health care professional-led randomized controlled studies using multiple ECG recordings or continuous ECG monitoring to detect AF have failed to demonstrate a significant reduction in stroke. Although it remains uncertain if consumer-led AF screening reduces stroke, it could increase early diagnosis of AF and facilitate an integrated approach, including appropriate anticoagulation, rate or rhythm management, and risk factor modification to reduce complications. Companies marketing AF screening devices should report the accuracy and performance of their products in high- and low-risk populations and avoid claims about clinical outcomes unless improvement is demonstrated in randomized clinical trials. Generally, the diagnostic yield of AF screening increases with the number, duration, and temporal dispersion of screening sessions, but the prognostic importance may be less than for AF detected by single-time point screening, which is largely permanent, persistent, or high-burden paroxysmal AF. Consumer-initiated ECG recordings suggesting possible AF always require confirmation by a health care professional experienced in ECG reading, whereas suspicion of AF on the basis of photoplethysmography must be confirmed with an ECG. Consumer-led AF screening is unlikely to be cost-effective for stroke prevention in the predominantly young, early adopters of this technology. Studies in older people at higher stroke risk are required to demonstrate both effectiveness and cost-effectiveness. The direct interaction between companies and consumers creates new regulatory gaps in relation to data privacy and the registration of consumer apps and devices. Although several barriers for optimal use of consumer-led screening exist, results of large, ongoing trials, powered to detect clinical outcomes, are required before health care professionals should support widespread adoption of consumer-led AF screening.

Opportunities and challenges in heart rhythm research: Rationale and development of an electrophysiology collaboratory

There are many challenges in the current landscape of electrophysiology (EP) clinical and translational research, including increasing costs and complexity, competing demands, regulatory requirements, and challenges with study implementation. This review seeks to broadly discuss the state of EP research, including challenges and opportunities. Included here are results from a Heart Rhythm Society (HRS) Research Committee member survey detailing HRS members' perspectives regarding both barriers to clinical and translational research and opportunities to address these challenges. We also provide stakeholder perspectives on barriers and opportunities for future EP research, including input from representatives of the U.S. Food and Drug Administration, industry, and research funding institutions that participated in a Research Collaboratory Summit convened by HRS. This review further summarizes the experiences of the heart failure and heart valve communities and how they have approached similar challenges in their own fields. We then explore potential solutions, including various models of research ecosystems designed to identify research challenges and to coordinate ways to address them in a collaborative fashion in order to optimize innovation, increase efficiency of evidence generation, and advance the development of new therapeutic products. The objectives of the proposed collaborative cardiac EP research community are to encourage and support scientific discourse, research efficiency, and evidence generation by exploring collaborative and equitable solutions in which stakeholders within the EP community can interact to address knowledge gaps, innovate, and advance new therapies.

Smartphone and wearable detected atrial arrhythmias in Older Adults: Results of a fully digital European Case finding study

Aims

Simplified detection of atrial arrhythmias via consumer-electronics would enable earlier therapy in at-risk populations. Whether this is feasible and effective in older populations is not known.

Methods and results

The fully remote, investigator-initiated Smartphone and wearable detected atrial arrhythmia in Older Adults Case finding study (Smart in OAC-AFNET 9) digitally enrolled participants ≥65 years without known atrial fibrillation, not receiving oral anticoagulation in Germany, Poland, and Spain for 8 weeks. Participants were invited by media communications and direct contacts. Study procedures adhered to European data protection. Consenting participants received a wristband with a photoplethysmography sensor to be coupled to their smartphone. The primary outcome was the detection of atrial arrhythmias lasting 6 min or longer in the first 4 weeks of monitoring. Eight hundred and eighty-two older persons (age 71 ± 5 years, range 65-90, 500 (57%) women, 414 (47%) hypertension, and 97 (11%) diabetes) recorded signals. Most participants (72%) responded to adverts or word of mouth, leaflets (11%) or general practitioners (9%). Participation was completely remote in 469/882 persons (53%). During the first 4 weeks, participants transmitted PPG signals for 533/696 h (77% of the maximum possible time). Atrial arrhythmias were detected in 44 participants (5%) within 28 days, and in 53 (6%) within 8 weeks. Detection was highest in the first monitoring week [incidence rates: 1st week: 3.4% (95% confidence interval 2.4-4.9); 2nd-4th week: 0.55% (0.33-0.93)].

Conclusion

Remote, digitally supported consumer-electronics-based screening is feasible in older European adults and identifies atrial arrhythmias in 5% of participants within 4 weeks of monitoring (NCT04579159).

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

AIMS

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

METHODS AND RESULTS

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

CONCLUSIONS

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

Early diagnosis and better rhythm management to improve outcomes in patients with atrial fibrillation: the 8th AFNET/EHRA consensus conference

Despite marked progress in the management of atrial fibrillation (AF), detecting AF remains difficult and AF-related complications cause unacceptable morbidity and mortality even on optimal current therapy. This document summarizes the key outcomes of the 8th AFNET/EHRA Consensus Conference of the Atrial Fibrillation NETwork (AFNET) and the European Heart Rhythm Association (EHRA). Eighty-three international experts met in Hamburg for 2 days in October 2021. Results of the interdisciplinary, hybrid discussions in breakout groups and the plenary based on recently published and unpublished observations are summarized in this consensus paper to support improved care for patients with AF by guiding prevention, individualized management, and research strategies. The main outcomes are (i) new evidence supports a simple, scalable, and pragmatic population-based AF screening pathway; (ii) rhythm management is evolving from therapy aimed at improving symptoms to an integrated domain in the prevention of AF-related outcomes, especially in patients with recently diagnosed AF; (iii) improved characterization of atrial cardiomyopathy may help to identify patients in need for therapy; (iv) standardized assessment of cognitive function in patients with AF could lead to improvement in patient outcomes; and (v) artificial intelligence (AI) can support all of the above aims, but requires advanced interdisciplinary knowledge and collaboration as well as a better medico-legal framework. Implementation of new evidence-based approaches to AF screening and rhythm management can improve outcomes in patients with AF. Additional benefits are possible with further efforts to identify and target atrial cardiomyopathy and cognitive impairment, which can be facilitated by AI.

Continuous mHealth Patch Monitoring for the Algorithm-Based Detection of Atrial Fibrillation: Feasibility and Diagnostic Accuracy Study

Background

The detection of atrial fibrillation (AF) is a major clinical challenge as AF is often paroxysmal and asymptomatic. Novel mobile health (mHealth) technologies could provide a cost-effective and reliable solution for AF screening. However, many of these techniques have not been clinically validated.

Objective

The purpose of this study is to evaluate the feasibility and reliability of artificial intelligence (AI) arrhythmia analysis for AF detection with an mHealth patch device designed for personal well-being.

Methods

Patients (N=178) with an AF (n=79, 44%) or sinus rhythm (n=99, 56%) were recruited from the emergency care department. A single-lead, 24-hour, electrocardiogram-based heart rate variability (HRV) measurement was recorded with the mHealth patch device and analyzed with a novel AI arrhythmia analysis software. Simultaneously registered 3-lead electrocardiograms (Holter) served as the gold standard for the final rhythm diagnostics.

Results

Of the HRV data produced by the single-lead mHealth patch, 81.5% (3099/3802 hours) were interpretable, and the subject-based median for interpretable HRV data was 99% (25th percentile=77% and 75th percentile=100%). The AI arrhythmia detection algorithm detected AF correctly in all patients in the AF group and suggested the presence of AF in 5 patients in the control group, resulting in a subject-based AF detection accuracy of 97.2%, a sensitivity of 100%, and a specificity of 94.9%. The time-based AF detection accuracy, sensitivity, and specificity of the AI arrhythmia detection algorithm were 98.7%, 99.6%, and 98.0%, respectively.

Conclusions

The 24-hour HRV monitoring by the mHealth patch device enabled accurate automatic AF detection. Thus, the wearable mHealth patch device with AI arrhythmia analysis is a novel method for AF screening.

Trial Registration

ClinicalTrials.gov NCT03507335; https://clinicaltrials.gov/ct2/show/NCT03507335

The Increasing Role of Rhythm Control in Patients With Atrial Fibrillation: JACC State-of-the-Art Review

The considerable mortality and morbidity associated with atrial fibrillation (AF) pose a substantial burden on patients and health care services. Although the management of AF historically focused on decreasing AF recurrence, it evolved over time in favor of rate control. Recently, more emphasis has been placed on reducing adverse cardiovascular outcomes using rhythm control, generally by using safe and effective rhythm-control therapies (typically antiarrhythmic drugs and/or AF ablation). Evidence increasingly supports early rhythm control in patients with AF that has not become long-standing, but current clinical practice and guidelines do not yet fully reflect this change. Early rhythm control may effectively reduce irreversible atrial remodeling and prevent AF-related deaths, heart failure, and strokes in high-risk patients. It has the potential to halt progression and potentially save patients from years of symptomatic AF; therefore, it should be offered more widely.

Current Advancement in Diagnosing Atrial Fibrillation by Utilizing Wearable Devices and Artificial Intelligence: A Review Study

Atrial fibrillation (AF) is a common arrhythmia affecting 8–10% of the population older than 80 years old. The importance of early diagnosis of atrial fibrillation has been broadly recognized since arrhythmias significantly increase the risk of stroke, heart failure and tachycardia-induced cardiomyopathy with reduced cardiac function. However, the prevalence of atrial fibrillation is often underestimated due to the high frequency of clinically silent atrial fibrillation as well as paroxysmal atrial fibrillation, both of which are hard to catch by routine physical examination or 12-lead electrocardiogram (ECG). The development of wearable devices has provided a reliable way for healthcare providers to uncover undiagnosed atrial fibrillation in the population, especially those most at risk. Furthermore, with the advancement of artificial intelligence and machine learning, the technology is now able to utilize the database in assisting detection of arrhythmias from the data collected by the devices. In this review study, we compare the different wearable devices available on the market and review the current advancement in artificial intelligence in diagnosing atrial fibrillation. We believe that with the aid of the progressive development of technologies, the diagnosis of atrial fibrillation shall be made more effectively and accurately in the near future.

Understanding Healthcare Professionals' Perspectives on Point-of-Care Testing

Point-of-care testing (POCT) is an emerging technology that provides crucial assistance in delivering healthcare. The COVID-19 pandemic led to the accelerated importance of POCT technology due to its in-home accessibility. While POCT use and implementation has increased, little research has been published about how healthcare professionals perceive these technologies. The objective of our study was to examine the current perspectives of healthcare professionals towards POCT. We surveyed healthcare professionals to quantify perceptions of POCT usage, adoption, benefits, and concerns between October 2020 and November 2020. Questions regarding POCT perception were assessed on a 5-point Likert Scale. We received a total of 287 survey responses. Of the respondents, 53.7% were male, 66.6% were white, and 30.7% have been in practice for over 20 years. We found that the most supported benefit was POCTs ability to improve patient management (92%) and that the most supported concern was that POCTs lead to over-testing (30%). This study provides a better understanding of healthcare workers' perspectives on POCT. To improve patient outcomes through the usage of POCT, greater research is needed to assess the needs and concerns of industry and healthcare stakeholders.

COVID-19: a gray swan's impact on the adoption of novel medical technologies

The COVID-19 pandemic offers a unique context and opportunity to investigate changes in healthcare professional perceptions towards the adoption of novel medical technologies, such as point-of-care technologies (POCTs). POCTs are a nascent technology that has experienced rapid growth as a result of COVID-19 due to their ability to increase healthcare accessibility via near-patient delivery, including at-home. We surveyed healthcare professionals before and during COVID-19 to explore whether the pandemic altered their perceptions about the usefulness of POCTs. Our network analysis method provided a structure for understanding this changing phenomenon. We uncovered that POCTs are not only useful for diagnosing COVID-19, but healthcare professionals also perceive them as increasingly important for diagnosing other diseases, such as cardiovascular, endocrine, respiratory, and metabolic diseases. Healthcare professionals also viewed POCTs as facilitating the humanization of epidemiology by improving disease management/monitoring and strengthening the clinician-patient relationship. As the accuracy and integration of these technologies into mainstream healthcare delivery improves, hurdles to their adoption dissipate, thereby encouraging healthcare professionals to rely upon them more frequently to diagnose, manage, and monitor diseases. The technological advances made in POCTs during COVID-19, combined with shifting positive perceptions of their utility by healthcare professionals, may better prepare us for the next pandemic.

Point-of-care testing, your cardiologist, and affairs of the heart

Background

Point-of-care testing (POCT) has applications across medical specialties and holds promise to improve patient care. While cardiovascular medicine has been attractive for POCT applications in recent years, little is known about how cardiovascular health professionals perceive them.

Objective

The objective of our study was to examine differences in perceptions and attitudes towards POCTs between cardiovascular health professionals compared to other healthcare professionals.

Methods

We surveyed healthcare professionals to assess perceptions of POCT usage and their benefits and concerns between October 2019 and March 2020. Questions regarding POCT perceptions were assessed on a 5-point Likert scale.

Results

We received a total of 148 survey responses; of the responders, 52% were male, 59% were physicians, and 50% worked in a hospital setting. We found that cardiology professionals were less likely, compared to other specialties, to view POCTs as improving patient management or reducing errors. These cardiology professionals were not constrained by resources or a lack of investment opportunities to implement these technologies.

Conclusion

This study provides a better understanding of perceptions about POCTs among healthcare specialists. To improve patient outcomes through the adoption and usage of POCTs, greater collaboration is advised among key industry and healthcare stakeholders.

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.

Prevention and Treatment of Atrial Fibrillation via Risk Factor Modification

Atrial fibrillation (AF) is the most common clinically significant arrhythmia, and it increases stroke risk. A preventive approach to AF is needed because virtually all treatments such as cardioversion, antiarrhythmic drugs, ablation, and anticoagulation are associated with high cost and carry significant risk. A systematic review was performed to identify effective lifestyle-based strategies for reducing primary and secondary AF. A PubMed search was performed using articles up to March 1, 2021. Search terms included atrial fibrillation, atrial flutter, exercise, diet, metabolic syndrome, type 2 diabetes mellitus, obesity, hypertension, stress, tobacco smoking, alcohol, Mediterranean diet, sodium, and omega-3 fatty acids. Additional articles were identified from the bibliographies of retrieved articles. The control of hypertension, ideally with a renin-angiotensin-aldosterone system inhibitor, is effective for preventing primary AF and recurrence. Obstructive sleep apnea is a common cause of AF, and treating it effectively reduces AF episodes. Alcohol increases the risk of AF in a dose-dependent manner, and abstinence reduces risk of recurrence. Sedentary behavior and chronic high-intensity endurance exercise are both risk factors for AF; however, moderate physical activity is associated with lower risk of AF. Recently, sodium-glucose cotransporter-2 inhibitors and glucagon-like peptide-1 agonists have been associated with reduced risk of AF. Among overweight/obese patients, weight loss of ≥10% is associated with reduced AF risk. Lifestyle changes and risk factor modification are highly effective for preventing AF.

Using smartwatches to observe changes in activity during recovery from critical illness following COVID-19: a 1 year multi-centre observational study. (Preprint)

Background

As a sequela of the COVID-19 pandemic, a large cohort of critical illness survivors have had to recover in the context of ongoing societal restrictions.

Objective

We aimed to use smartwatches (Fitbit Charge 3; Fitbit LLC) to assess changes in the step counts and heart rates of critical care survivors following hospital admission with COVID-19, use these devices within a remote multidisciplinary team (MDT) setting to support patient recovery, and report on our experiences with this.

Methods

We conducted a prospective, multicenter observational trial in 8 UK critical care units. A total of 50 participants with moderate or severe lung injury resulting from confirmed COVID-19 were recruited at discharge from critical care and given a smartwatch (Fitbit Charge 3) between April and June 2020. The data collected included step counts and daily resting heart rates. A subgroup of the overall cohort at one site—the MDT site (n=19)—had their smartwatch data used to inform a regular MDT meeting. A patient feedback questionnaire and direct feedback from the MDT were used to report our experience. Participants who did not upload smartwatch data were excluded from analysis.

Results

Of the 50 participants recruited, 35 (70%) used and uploaded data from their smartwatch during the 1-year period. At the MDT site, 74% (14/19) of smartwatch users uploaded smartwatch data, whereas 68% (21/31) of smartwatch users at the control sites uploaded smartwatch data. For the overall cohort, we recorded an increase in mean step count from 4359 (SD 3488) steps per day in the first month following discharge to 7914 (SD 4146) steps per day at 1 year (P=.003). The mean resting heart rate decreased from 79 (SD 7) beats per minute in the first month to 69 (SD 4) beats per minute at 1 year following discharge (P<.001). The MDT subgroup’s mean step count increased more than that of the control group (176% increase vs 42% increase, respectively; +5474 steps vs +2181 steps, respectively; P=.04) over 1 year. Further, 71% (10/14) of smartwatch users at the MDT site and 48% (10/21) of those at the control sites strongly agreed that their Fitbit motivated them to recover, and 86% (12/14) and 48% (10/21), respectively, strongly agreed that they aimed to increase their activity levels over time.

Conclusions

This is the first study to use smartwatch data to report on the 1-year recovery of patients who survived a COVID-19 critical illness. This is also the first study to report on smartwatch use within a post–critical care MDT. Future work could explore the role of smartwatches as part of a randomized controlled trial to assess clinical and economic effectiveness.

International Registered Report Identifier (IRRID)

RR2-10.12968/ijtr.2020.0102

Day-to-day measurement of physical activity and risk of atrial fibrillation

Aims 

The aim of this study was to investigate the association between within-individual changes in physical activity and onset of atrial fibrillation (AF).

Methods and results 

A total of 1410 participants from the general population (46.2% women, mean age 74.7 ± 4.1 years) with risk factors but with no prior AF diagnosis underwent continuous monitoring for AF episodes along with daily accelerometric assessment of physical activity using an implantable loop recorder during ≈3.5 years. The combined duration of monitoring was ≈1.6 million days, where 10 851 AF episodes lasting ≥60 min were detected in 361 participants (25.6%) with a median of 5 episodes (2, 25) each. The median daily physical activity was 112 (66, 168) min/day. A dynamic parameter describing within-individual changes in daily physical activity, i.e. average daily activity in the last week compared to the previous 100 days, was computed and used to model the onset of AF. A 1-h decrease in average daily physical activity was associated with AF onset the next day [odds ratio 1.24 (1.18–1.31)]. This effect was modified by overall level of activity (P < 0.001 for interaction), and the signal was strongest in the tertile of participants with lowest activity overall [low: 1.62 (1.41–1.86), mid: 1.27 (1.16–1.39), and high: 1.10 (1.01–1.19)].

Conclusions 

Within-individual changes in physical activity are associated with the onset of AF episodes as detected by continuous monitoring in a high-risk population. For each person, a 1-h decrease in daily physical activity during the last week increased the odds of AF onset the next day by ≈25%, while the strongest association was seen in the group with the lowest activity overall.

Clinical Trial Registration

ClinicalTrials.gov, identifier: NCT02036450.

Comparing Outcomes in Asymptomatic and Symptomatic Atrial Fibrillation: A Systematic Review and Meta-Analysis of 81,462 Patients

BACKGROUND

In atrial fibrillation (AF) patients, the presence of symptoms can guide the decision between rate or rhythm control therapy, but it is still unclear if AF-related outcomes are determined by symptomatic status of their clinical presentation.

METHODS

We performed a systematic review and metanalysis following the PRISMA recommendations on available studies that compared asymptomatic to symptomatic AF reporting data on all-cause mortality, cardiovascular death, and thromboembolic events (TEs). We included studies with a total number of patients enrolled equal to or greater than 200, with a minimum follow-up period of six months.

RESULTS

From the initial 5476 results retrieved after duplicates' removal, a total of 10 studies were selected. Overall, 81,462 patients were included, of which 21,007 (26%) were asymptomatic, while 60,455 (74%) were symptomatic. No differences were found between symptomatic and asymptomatic patients regarding the risks of all-cause death (odds ratio (OR) 1.03, 95% confidence interval (CI) 0.81-1.32), and cardiovascular death (OR 0.87, 95% CI 0.54-1.39). No differences between symptomatic and asymptomatic groups were evident for stroke (OR 1.22, 95% CI 0.77-1.93) and stroke/TE (OR 1.06, 95% CI 0.86-1.31) risks.

CONCLUSIONS

Mortality and stroke/TE events in AF patients were unrelated to symptomatic status of their clinical presentation. Adoption of management strategies in AF patients should not be based on symptomatic clinical status.

Use of Smartphones and Wearables for Arrhythmia Monitoring

Smartphones and other wearable electronic devices increasingly are used for ambulatory cardiac rhythm assessment. These consumer technologies have been evaluated in several studies for diagnosis and management of atrial fibrillation. Diverse mobile health applications, including management of other arrhythmias and medical conditions, are expanding alongside advances in technology. Electronic devices owned by millions of consumers have the potential to alter health care delivery as well as research design and implementation. This review provides an up-to-date discussion of the available mobile health technologies, specific applications and limitations for arrhythmia evaluation, their impact on health care systems, and key areas for future investigation.

New Technologies for Detection and Management of Atrial Fibrillation

Atrial fibrillation (AF) is a common and prevalent form of arrhythmia. It is associated with various morbidities with stroke being the major hazard. Since AF is often reported to be asymptomatic, many individuals remain unaware of their condition and may not receive the requisite treatment. Hence, screening for AF has gained substantial attention recently. Growing advancement in technology has paved way for numerous approaches for AF screening using medical-prescribed devices as well as consumer electronic devices. However, there still lies scope for large-scale randomized trials which would explore additional aspects associated with AF. This review very concisely summarizes AF, screening, present technology, current literature and clinical studies associated with it.

Atrial Fibrillation and Heart Failure with Preserved Ejection Fraction: Two Chronic Troublemakers

In this article, the definition; mechanisms; diagnostic strategies, including scoring systems; treatments; prognosis; and future perspectives in heart failure with preserved ejection fraction with atrial fibrillation, which are common comorbid conditions, are reviewed thoroughly.

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.

Screening for Atrial Fibrillation in American Indian Adults in a Tribal Primary Care Clinic

Background American Indian adults have a higher risk of atrial fibrillation (AF) compared with other racial groups. We implemented opportunistic screening to detect silent AF in American Indian adults attending a tribal health system using a mobile, single-lead ECG device. Methods and Results American Indian patients aged ≥50 years followed in a tribal primary care clinic with no history of AF underwent a 30-second ECG. A cardiologist overread all tracings to confirm the diagnosis of AF. After AF was confirmed, patients were referred to their primary care physician for initiation of anticoagulation. Patients seen over the same time period, who were not undergoing screening, served as controls. A total of 1019 patients received AF screening (mean age, 61.5±8.9 years, 62% women). Age and sex distribution of those screened was similar to the overall clinic population. New AF was diagnosed in 15 of 1019 (1.5%) patients screened versus 4 of 1267 (0.3%) patients who were not screened (mean difference, 1.2%; 95% CI, 0.3%-2.2%, P=0.002). Eight of 15 with new screen-detected AF were aged <65 years. Those with screen-detected AF were slightly older and had a higher CHA₂DS₂-VASc score than those without AF. Fourteen of 15 patients diagnosed with new AF had a CHA₂DS₂-VASc score ≥1 and initiated anticoagulation. Conclusions Opportunistic, mobile single-lead ECG screening for AF is feasible in tribal clinics, and detects more AF than usual care, leading to appropriate initiation of anticoagulation. AF develops at a younger age in American Indian adults who would likely benefit from earlier AF screening. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT03740477.

Explainable artificial intelligence to detect atrial fibrillation using electrocardiogram

INTRODUCTION

Early detection and intervention of atrial fibrillation (AF) is a cornerstone for effective treatment and prevention of mortality. Diverse deep learning models (DLMs) have been developed, but they could not be applied in clinical practice owing to their lack of interpretability. We developed an explainable DLM to detect AF using ECG and validated its performance using diverse formats of ECG.

METHODS

We conducted a retrospective study. The Sejong ECG dataset comprising 128,399 ECGs was used to develop and internally validated the explainable DLM. DLM was developed with two feature modules, which could describe the reason for DLM decisions. DLM was external validated using data from 21,837, 10,605, and 8528 ECGs from PTB-XL, Chapman, and PhysioNet non-restricted datasets, respectively. The predictor variables were digitally stored ECGs, and the endpoints were AFs.

RESULTS

During internal and external validation of the DLM, the area under the receiver operating characteristic curves (AUCs) of the DLM using a 12‑lead ECG in detecting AF were 0.997-0.999. The AUCs of the DLM with VAE using a 6‑lead and single‑lead ECG were 0.990-0.999. The AUCs of explainability about features such as rhythm irregularity and absence of P-wave were 0.961-0.993 and 0.983-0.993, respectively.

CONCLUSIONS

Our DLM successfully detected AF using diverse ECGs and described the reason for this decision. The results indicated that an explainable artificial intelligence methodology could be adopted to the DLM using ECG and enhance the transparency of the DLM for its application in clinical practice.