Yield of atrial fibrillation detection with Textile Wearable Holter from the acute phase of stroke: Pilot study of Crypto-AF registry

Atrial Imaging and Cardiac Rhythm in Cryptogenic Embolic Stroke: The ARIES Study

BACKGROUND

Unknown cardioembolic sources are frequent causes of cryptogenic stroke. We analyzed the risk of atrial fibrillation (AF) or high burden of ectopic atrial activity (HBEA) in patients with cryptogenic stroke, assessing atrial function and 1-year outcomes.

METHODS AND RESULTS

The ARIES (Atrial Imaging and Cardiac Rhythm in Cryptogenic Embolic Stroke) study is an observational study including patients with cryptogenic stroke. We analyzed the frequency of AF and HBEA (>3000 atrial ectopic beats/day or >2 bursts or atrial tachycardia between 3 beats and ≤30 seconds) in two 30-day Holter-ECGs, comparing advanced echocardiography signs of left atrial (LA) dysfunction according to rhythm: AF, HBEA, and normal sinus rhythm. We also evaluated 1-year stroke recurrence and mortality. The study included 109 patients; 35 (32.1%) patients had AF, 27 (24.8%) HBEA, and 47 (43.1%) normal sinus rhythm. Compared with those with normal sinus rhythm, patients with AF presented higher 2-dimensional and 3-dimensional LA indexed volumes (38.8±11.2 versus 27.3±11.8 mL/m2, and 50.6±17.2 versus 34.0±15.4 mL/m2, respectively, P<0.001), lower 3-dimensional LA ejection fraction (50±14.6 versus 62.7±11.8, P=0.001), LA reservoir strain (22.0±8.6 versus 30.4±10.5, P<0.001), and LA contraction strain (10.5±8.18 versus 17.1±7.5, P<0.001), remaining significant in multivariate analysis. Patients with HBEA showed higher LA indexed volumes and lower LA reservoir strain than patients with normal sinus rhythm only in univariate analysis. There were no differences in ischemic recurrence or mortality among the groups.

CONCLUSIONS

Patients with cryptogenic stroke showed a high incidence of AF and HBEA. AF is strongly related to LA volume, LA function, and LA reservoir and contraction strain, whereas HBEA showed milder structural changes. Advanced LA echocardiography could help patient selection for long-term ECG monitoring in suspected cardiac sources.

Use of wearable technology in cardiac monitoring after cryptogenic stroke or embolic stroke of undetermined source: a systematic review

INTRODUCTION

Prolonged cardiac monitoring after cryptogenic stroke or embolic stroke of undetermined source (ESUS) is necessary to identify atrial fibrillation (AF) that requires anticoagulation. Wearable devices may improve AF detection compared to conventional management. We aimed to review the evidence for the use of wearable devices in post-cryptogenic stroke and post-ESUS monitoring.

METHODS

We performed a systematic search of PubMed, EMBASE, Scopus and clinicaltrials.gov on 21 July 2022, identifying all studies that investigated the use of wearable devices in patients with cryptogenic stroke or ESUS. The outcomes of AF detection were analysed. Literature reports on electrocardiogram (ECG)-based (external wearable, handheld, patch, mobile cardiac telemetry [MCT], smartwatch) and photoplethysmography (PPG)-based (smartwatch, smartphone) devices were summarised.

RESULTS

A total of 27 relevant studies were included (two randomised controlled trials, seven prospective trials, 10 cohort studies, six case series and two case reports). Only four studies compared wearable technology to Holter monitoring or implantable loop recorder, and these studies showed no significant differences on meta-analysis (odds ratio 2.35, 95% confidence interval [CI] 0.74-7.48, I 2 = 70%). External wearable devices detected AF in 20.7% (95% CI 14.9-27.2, I 2 = 76%) of patients and MCT detected new AF in 9.6% (95% CI 7.4%-11.9%, I 2 = 56%) of patients. Other devices investigated included patch sensors, handheld ECG recorders and PPG-based smartphone apps, which demonstrated feasibility in the post-cryptogenic stroke and post-ESUS setting.

CONCLUSION

Wearable devices that are ECG or PPG based are effective for paroxysmal AF detection after cryptogenic stroke and ESUS, but further studies are needed to establish how they compare with Holter monitors and implantable loop recorder.

Tachyarrhythmias in congenital heart disease

The prevalence of congenital heart disease (CHD) in adult patients has risen with advances in diagnostic and surgical techniques. Surgical modifications and hemodynamic changes increase the susceptibility to arrhythmias, impacting morbidity and mortality rates, with arrhythmias being the leading cause of hospitalizations and sudden deaths. Patients with CHD commonly experience both supraventricular and ventricular arrhythmias, with each CHD type associated with different arrhythmia patterns. Macroreentrant atrial tachycardias, particularly cavotricuspid isthmus-dependent flutter, are frequently reported. Ventricular arrhythmias, including monomorphic ventricular tachycardia, are prevalent, especially in patients with surgical scars. Pharmacological therapy involves antiarrhythmic and anticoagulant drugs, though data are limited with potential adverse effects. Catheter ablation is preferred, demanding meticulous procedural planning due to anatomical complexity and vascular access challenges. Combining imaging techniques with electroanatomic navigation enhances outcomes. However, risk stratification for sudden death remains challenging due to anatomical variability. This article practically reviews the most common tachyarrhythmias, treatment options, and clinical management strategies for these patients.

Artificial intelligence cloud platform improves arrhythmia detection from insertable cardiac monitors to 25 cardiac rhythm patterns through multi-label classification

BACKGROUND

Electrocardiogram (ECG) is the gold standard for the diagnosis of cardiac arrhythmias and other heart diseases. Insertable cardiac monitors (ICMs) have been developed to continuously monitor cardiac activity over long periods of time and to detect 4 cardiac patterns (atrial tachyarrhythmias, ventricular tachycardia, bradycardia, and pause). However, interpretation of ECG or ICM subcutaneous ECG (sECG) is time-consuming for clinicians. Artificial intelligence (AI) classifies ECG and sECG with high accuracy in short times.

OBJECTIVE

To demonstrate whether an AI algorithm can expand ICM arrhythmia recognition from 4 to many cardiac patterns.

METHODS

We performed an exploratory retrospective study with sECG raw data coming from 20 patients wearing a Confirm Rx™ (Abbott, Sylmar, USA) ICM. The sECG data were recorded in standard conditions and then analyzed by AI (Willem™, IDOVEN, Madrid, Spain) and cardiologists, in parallel.

RESULTS

In nineteen patients, ICMs recorded 2261 sECGs in an average follow-up of 23 months. Within these 2261 sECG episodes, AI identified 7882 events and classified them according to 25 different cardiac rhythm patterns with a pondered global accuracy of 88%. Global positive predictive value, sensitivity, and F1-score were 86.77%, 83.89%, and 85.52% respectively. AI was especially sensitive for bradycardias, pauses, rS complexes, premature atrial contractions, and inverted T waves, reducing the median time spent to classify each sECG compared to cardiologists.

CONCLUSION

AI can process sECG raw data coming from ICMs without previous training, extending the performance of these devices and saving cardiologists' time in reviewing cardiac rhythm patterns detection.

Wearable technology and the cardiovascular system: the future of patient assessment

The past decade has seen a dramatic rise in consumer technologies able to monitor a variety of cardiovascular parameters. Such devices initially recorded markers of exercise, but now include physiological and health-care focused measurements. The public are keen to adopt these devices in the belief that they are useful to identify and monitor cardiovascular disease. Clinicians are therefore often presented with health app data accompanied by a diverse range of concerns and queries. Herein, we assess whether these devices are accurate, their outputs validated, and whether they are suitable for professionals to make management decisions. We review underpinning methods and technologies and explore the evidence supporting the use of these devices as diagnostic and monitoring tools in hypertension, arrhythmia, heart failure, coronary artery disease, pulmonary hypertension, and valvular heart disease. Used correctly, they might improve health care and support research.

Arrhythmic syncope: From diagnosis to management

Syncope is a concerning symptom that affects a large proportion of patients. It can be related to a heterogeneous group of pathologies ranging from trivial causes to diseases with a high risk of sudden death. However, benign causes are the most frequent, and identifying high-risk patients with potentially severe etiologies is crucial to establish an accurate diagnosis, initiate effective therapy, and alter the prognosis. The term cardiac syncope refers to those episodes where the cause of the cerebral hypoperfusion is directly related to a cardiac disorder, while arrhythmic syncope is cardiac syncope specifically due to rhythm disorders. Indeed, arrhythmias are the most common cause of cardiac syncope. Both bradyarrhythmia and tachyarrhythmia can cause a sudden decrease in cardiac output and produce syncope. In this review, we summarized the main guidelines in the management of patients with syncope of presumed arrhythmic origin. Therefore, we presented a thorough approach to syncope work-up through different tests depending on the clinical characteristics of the patients, risk stratification, and the management of syncope in different scenarios such as structural heart disease and channelopathies.

Intensive 90-day textile wearable Holter monitoring: an alternative to detect paroxysmal atrial fibrillation in selected patients with cryptogenic stroke

We aimed to demonstrate the feasibility of 90-day cardiac monitoring with an external Holter device and to find a target population able to benefit from such a technique. Cryptogenic stroke patients were continuously monitored for 90 days with a textile wearable Holter (TWH). Compliance and quality of the monitoring were assessed by the number of hours of ECG stored per month. Mean predictors of pAF, including age, gender, stroke severity, and atrial size (LAVI), were evaluated. One-year follow-up assessed pAF detection outside per protocol monitoring. Out of 224 patients included in 5 stroke centers, 163 patients (72.76%) fulfilled the criteria for the protocol. Median monitoring time was similar among the three months. Per protocol pAF detection reached 35.37% at 90 days. The age (OR 1.095; 95% CI 1.03-1.14) and the LAVI (OR 1.055; 95% CI 1.01-1.09) independently predicted pAF. The cut-off point of 70 years (AUC 0.68) (95% CI 0.60-0.76) predicted pAF with a sensitivity of 75.8% and specificity of 50.5%. The LAVI cut-off point of 28.5 (AUC 0.67) (95% CI 0.56-0.77) had a sensitivity of 63.6% and a specificity of 61.8% to detect pAF. The combination of both markers enhanced the validity of pAF detection sensitivity to 89.6%, with a specificity of 27.59%. These patients had increased risk of pAF during the 90-day monitoring HR 3.23 (χ² 7.15) and beyond 90 days (χ² 5.37). Intensive 90-days TWH monitoring detected a high percentage of pAF. However, a significant number of patients did not complete the monitoring. Patients older than 70 years and with enlarged left atria benefitted more from the protocol.

A meta-analysis of extended ECG monitoring in detection of atrial fibrillation in patients with cryptogenic stroke

Objective

The aim of this systematic review is to evaluate the various modalities available for extended ECG monitoring in the detection of atrial fibrillation (AF) following a cryptogenic stroke.

Methods

MEDLINE (Ovid), EMBASE (Ovid), Cochrane Central Register of Controlled Trials (CENTRAL) were searched from January 2011 to November 2021. All randomised controlled trials and prospective cohort studies including the use of extended ECG monitoring >24 hours with a minimum duration of AF of 30 s in patients with either cryptogenic strokes or transient ischaemic attacks were included. A random-effects model was used to pool effect estimates of AF detection rates from different ECG modalities.

Results

3924 studies were identified, of which 47 were included reporting on a pooled population of 6448 patients with cryptogenic stroke. The pooled AF rate for implantable loop recorders (ILRs) increased from 4.9% (3.0%–7.9%) at 1 month to 38.4% (20.4%–60.2%) at 36 months. Mobile cardiac outpatient telemetry (MCOT) had a significantly higher pooled AF detection rate of 12.8% (8.9%–17.9%) versus 4.9% (3.0%–7.9%) for ILR at 1 month (p<0.0001). Predictors for AF detection include duration of monitoring (p<0.0001) and age (p<0.0001) for ILRs, but only age for MCOTs (p<0.020).

Conclusion

MCOT has a higher rate of detection at 1 month and is less invasive. Beyond 1 month, compliance becomes a significant limitation for MCOT. MCOT may be a reasonable alternative AF screening tool for patients with cryptogenic stroke if ILR is not available.

PROSPERO registration number

CRD42022297782.

ESC Working Group on e-Cardiology Position Paper: accuracy and reliability of electrocardiogram monitoring in the detection of atrial fibrillation in cryptogenic stroke patients : In collaboration with the Council on Stroke, the European Heart Rhythm Association, and the Digital Health Committee

The role of subclinical atrial fibrillation as a cause of cryptogenic stroke is unambiguously established. Long-term electrocardiogram (ECG) monitoring remains the sole method for determining its presence following a negative initial workup. This position paper of the European Society of Cardiology Working Group on e-Cardiology first presents the definition, epidemiology, and clinical impact of cryptogenic ischaemic stroke, as well as its aetiopathogenic association with occult atrial fibrillation. Then, classification methods for ischaemic stroke will be discussed, along with their value in providing meaningful guidance for further diagnostic efforts, given disappointing findings of studies based on the embolic stroke of unknown significance construct. Patient selection criteria for long-term ECG monitoring, crucial for determining pre-test probability of subclinical atrial fibrillation, will also be discussed. Subsequently, the two major classes of long-term ECG monitoring tools (non-invasive and invasive) will be presented, with a discussion of each method's pitfalls and related algorithms to improve diagnostic yield and accuracy. Although novel mobile health (mHealth) devices, including smartphones and smartwatches, have dramatically increased atrial fibrillation detection post ischaemic stroke, the latest evidence appears to favour implantable cardiac monitors as the modality of choice; however, the answer to whether they should constitute the initial diagnostic choice for all cryptogenic stroke patients remains elusive. Finally, institutional and organizational issues, such as reimbursement, responsibility for patient management, data ownership, and handling will be briefly touched upon, despite the fact that guidance remains scarce and widespread clinical application and experience are the most likely sources for definite answers.

Detection of hidden atrial fibrillation in primary care using a long-term band-based ECG registration system: The DESCUUBRE-FA study

OBJECTIVE

To assess whether the use of a band-based electrocardiographic (ECG) monitoring system improves the diagnostic accuracy of traditional diagnostic methods for the detection of atrial fibrillation (AF).

METHODS

Multicenter and observational study of primary care patients at risk of AF. To be included, patients had to be aged ≥70 years, with no known AF, and have at least 1 major criterion (obesity, hyperthyroidism, heart failure) or 2 minor criteria (hypertension, diabetes, female sex, ischemic stroke, transient ischemic attack or systemic embolism, COPD, dyslipidemia, ischemic heart disease, peripheral artery disease). All patients were monitored using the Nuubo™ system for a single 2-week period.

RESULTS

A total of 600 patients were included (median age 77 years; 70% women; 84.3% hypertension, 27.2% diabetes, 9.2% prior stroke). The global rate of diagnosis of new AF in the overall population was 2.83%. All patients with AF were anticoagulated. In numerical terms, patients with AF (vs no AF) had a higher number of supraventricular extrasystoles and episodes of supraventricular tachycardia, as well as longer P wave duration; however, these differences did not reach statistical significance. Overall, participants were very satisfied with the device, and no relevant limitations in daily activities were observed during the 2-week study period.

CONCLUSIONS

In an elderly population at risk of AF, a band-based ECG monitoring approach applied for only 2 weeks detected approximately 3% of new cases of AF, leading to a change in antithrombotic therapy. Most participants considered the device easy to use and comfortable.

Proteins and pathways in atrial fibrillation and atrial cardiomyopathy underlying cryptogenic stroke

Background

Atrial fibrillation (AF) is one of the most prevalent causes of cryptogenic stroke. Also, apart from AF itself, structural and remodelling changes in the atria might be an underlying cause of cryptogenic stroke. We aimed to discover circulating proteins and reveal pathways altered in AF and atrial cardiomyopathy, measured by left atrial volume index (LAVI) and peak atrial longitudinal strain (PALS), in patients with cryptogenic stroke.

Methods

An aptamer array (including 1310 proteins) was measured in the blood of 20 cryptogenic stroke patients monitored during 28 days with a Holter device as a case-control study of the Crypto-AF cohort. Protein levels were compared between patients with (n = 10) and without AF (n = 10) after stroke, and the best candidates were tested in 111 patients from the same cohort (44 patients with AF and 67 without AF). In addition, in the first 20 patients, proteins were explored according to PALS and LAVI values.

Results

Forty-six proteins were differentially expressed in AF cases. Of those, four proteins were tested in a larger sample size. Only DPP7, presenting lower levels in AF patients, was further validated. Fifty-seven proteins correlated with LAVI, and 270 correlated with PALS. NT-proBNP was common in all the discovery analyses performed. Interestingly, many proteins and pathways were altered in patients with low PALS.

Conclusions

Multiple proteins and pathways related to AF and atrial cardiomyopathy have been revealed. The role of DPP7 as a biomarker for stroke aetiology should be further explored. Moreover, the present study may be considered hypothesis-generating.

Remote Cardiac Rhythm Monitoring in the Era of Smart Wearables: Present Assets and Future Perspectives

Remote monitoring and control of heart function are of primary importance for patient evaluation and management, especially in the modern era of precision medicine and personalized approach. Breaking technological developments have brought to the frontline a variety of smart wearable devices, such as smartwatches, chest patches/straps, or sensors integrated into clothing and footwear, which allow continuous and real-time recording of heart rate, facilitating the detection of cardiac arrhythmias. However, there is great diversity and significant differences in the type and quality of the information they provide, thus impairing their integration into daily clinical practice and the relevant familiarization of practicing physicians. This review will summarize the different types and dominant functions of cardiac smart wearables available in the market. Furthermore, we report the devices certified by official American and/or European authorities and the respective sources of evidence. Finally, we comment pertinent limitations and caveats as well as the potential answers that flow from the latest technological achievements and future perspectives.

Telemedicine in Cardiology: Modern Technologies to Improve Cardiovascular Patients’ Outcomes—A Narrative Review

The registration of physical signals has long been an important part of cardiological diagnostics. Current technology makes it possible to send large amounts of data to remote locations. Solutions that enable diagnosis and treatment without direct contact with patients are of enormous value, especially during the COVID-19 outbreak, as the elderly require special protection. The most important examples of telemonitoring in cardiology include the use of implanted devices such as pacemakers and defibrillators, as well as wearable sensors and data processing units. The arrythmia detection and monitoring patients with heart failure are the best studied in the clinical setting, although in many instances we still lack clear evidence of benefits of remote approaches vs. standard care. Monitoring for ischemia is less well studied. It is clear however that the economic and organizational gains of telemonitoring for healthcare systems are substantial. Both patients and healthcare professionals have expressed an enormous demand for the further development of such technologies. In addition to these subjects, in this paper we also describe the safety concerns associated with transmitting and storing potentially sensitive personal data.

Wearable technology to inform the prediction and diagnosis of cardiorespiratory events: a scoping review

BACKGROUND

The need for health systems that allow for continuous monitoring and early adverse event detection in individuals outside of the acute care setting has been highlighted by the global rise in chronic cardiorespiratory diseases and the recent COVID-19 pandemic. Currently, it is unclear what type of evidence exists concerning the use of physiological data collected from commercially available wrist and textile wearables to assist in clinical decision making. The aim of this review was therefore to systematically map and summarize the scientific literature surrounding the use of these wearables in clinical decision making as well as identify knowledge gaps to inform further research.

METHODOLOGY

Six electronic bibliographic databases were systematically searched (Ovid MEDLINE, EMBASE, CINAHL, PubMed, Scopus, and SportsDiscus). Publications from database inception to May 6, 2020 were reviewed for inclusion. Non-indexed literature relevant to this review was also searched systematically. Results were then collated, summarized and reported.

RESULTS

A total of 107 citations were retrieved and assessed for eligibility with 31 citations included in the final analysis. A review of the 31 papers revealed three major study designs which included (1) observational studies (n = 19), (2) case control series and reports (n = 8), and (3) reviews (n = 2). All papers examined the use of wearable monitoring devices for clinical decisions in the cardiovascular domain, with cardiac arrhythmias being the most studied. When compared to electrocardiogram (ECG) the performance of the wearables in facilitating clinical decisions varied depending upon the type of wearable, user's activity levels and setting in which they were employed. Observational studies collecting data in the inpatient and outpatient settings were equally represented. Eight case control series and reports were identified which reported on the use of wrist wearables in patients presenting to an emergency department or clinic to aid in the clinical diagnosis of a cardiovascular event. Two narrative reviews were identified which examined the impact of wearable devices in monitoring cardiovascular disease as well as potential challenges they may pose in the future.

CONCLUSIONS

To date, studies employing wearables to facilitate clinical decisions have largely focused upon the cardiovascular domain. Despite the ability of some wearables to collect physiological data accurately, there remains a need for a specialist physician to retrospectively review the raw data to make a definitive diagnosis. Analysis of the results has also highlighted gaps in the literature such as the absence of studies employing wearables to facilitate clinical decisions in the respiratory domain. The disproportionate study of wearables in atrial fibrillation detection in comparison to other cardiac arrhythmias and conditions, as well as the lack of diversity in the sample populations used prevents the generalizability of results.

Cardiac monitoring for patients with palpitations

Palpitations are one of the most common reasons for medical consultation. They tend to worry patients and can affect their quality of life. They are often a symptom associated with cardiac rhythm disorders, although there are other etiologies. For diagnosis, it is essential to be able to reliably correlate the symptoms with an electrocardiographic record allowing the identification or ruling out of a possible rhythm disorder. However, reaching a diagnosis is not always simple, given that they tend to be transitory symptoms and the patient is frequently asymptomatic at the time of assessment. In recent years, electrocardiographic monitoring systems have incorporated many technical improvements that solve several of the 24-h Holter monitor limitations. The objective of this review is to provide an update on the different monitoring methods currently available, remarking their indications and limitations, to help healthcare professionals to appropriately select and use them in the work-up of patients with palpitations.

Embolic Stroke of Undetermined Source: Approaches in Risk Stratification for Cardioembolism

Ischemic stroke is a leading cause of morbidity and mortality worldwide. Embolic stroke of undetermined source has been recently proposed to categorize nonlacunar ischemic strokes without confirmed etiology after adequate investigation with a likely embolic stroke mechanism. A strategy of empirical anticoagulation for embolic stroke of undetermined source patients is attractive but may only be beneficial in a select subset of patients. Strategies which would help identify the subset of embolic stroke of undetermined source patients most likely to have cardioembolic origin of stroke, and hence benefit from anticoagulation, are needed. This article will review current evidence which may be useful in the development of a risk stratification approach based on arrhythmia monitoring, cardiac imaging, and clinical risk stratification. This approach may be beneficial in clinical practice in improving patient outcomes and reducing stroke recurrence in this population; however, further work is required with active trials underway.

Monocyte-to-Lymphocyte Ratio in Clot Analysis as a Marker of Cardioembolic Stroke Etiology

The aim of the study was to find markers of high-risk cardioembolic etiology (HRCE) in patients with cryptogenic strokes (CS) through the analysis of intracranial clot by flow cytometry (FC). A prospective single-center study was designed including patients with large vessel occlusion strokes. The percentage of granulocytes, monocytes, lymphocytes, and monocyte-to-lymphocyte ratio (MLr) were analyzed in clots extracted after endovascular treatment (EVT) and in peripheral blood. Large arterial atherosclerosis (LAA) strokes and high-risk cardioembolic (HRCE) strokes were matched by demographics and acute reperfusion treatment data to obtain FC predictors for HRCE. Multilevel decision tree with boosting random forest classifiers was performed with each feature importance for HRCE diagnosis among CS. We tested the validity of the best FC predictor in a cohort of CS that underwent extensive diagnostic workup. Among 211 patients, 178 cases underwent per-protocol workup. The percentage of monocytes (OR 1.06, 95% CI 1.01-1.11) and MLr (OR 1.83, 95% CI 1.12-2.98) independently predicted HRCE diagnosis when LAA clots (n = 28) were matched with HRCE clots (n = 28). Among CS (n = 82), MLr was the feature with the highest weighted importance in the multilevel decision tree as a predictor for HRCE. MLr cutoff point of 1.59 yield sensitivity of 91.23%, specificity of 44%, positive predictive value of 78.79%, and negative predictive value of 68.75 for HRCE diagnosis among CS. MLr ≥ 1.6 in clot analysis predicted HRCE diagnosis (OR, 6.63, 95% CI 1.85-23.71) in a multivariate model adjusted for age. Clot analysis by FC revealed high levels of monocyte-to-lymphocyte ratio as an independent marker of cardioembolic etiology in cryptogenic strokes.

Digital health solutions in the screening of subclinical atrial fibrillation

Atrial fibrillation (AF) will become one of the biggest challenges in cardiovascular medicine in the near future. Attempting an improvement in future patient care calls explicitly for the screening of subclinical AF. Digital health solutions implementing communication technologies for the collection and analysis of digitally assessable data will most likely serve this need. Several new rapidly developing methods were introduced in the past decade. Although the vast majority still require scientific validation, the body of evidence is growing and several randomized controlled trials are planned. This review aims to give an overview of current technologies with a specific focus on mobile health (mHealth) and appraise their value with regard to the available scientific data.

Cardiac biometric variables and arrhythmic events during COVID-19 pandemic lockdown in patients with an implantable cardiac monitor for syncope work-up

Aim

To assess the changes induced by the COVID-19 lockdown on cardiac biometric variables recorded using an implantable cardiac monitor (ICM) in a patient population monitored for syncope work-up, as well to assess whether there has been an effect on arrhythmic events among the patients.

Methods

Longitudinal cohort study. We included 245 adult patients monitored with an ICM indicated for the investigation of syncope. The records from days 1 to 12 March 2020 (prior to the institution of lockdown by the state government) with days 16 to 28 March 2020 were compared.

Results

Daily physical exercise reduced markedly after the imposition of lockdown (132 [55-233] minutes vs. 78 [21-154] minutes). The mean daytime HR prior to lockdown was 77 [69-85] bpm, whereas during lockdown it was 74 [66-81] bpm. During the lockdown period, a drop in the variability in heart rate (114 [94-136] ms vs. 111 [92-133] ms) was observed. Although the incidence of AF was similar over both periods, the daily AF burden was significantly higher post-lockdown (405 [391-425] minutes vs. 423 [423-537] minutes). No differences in the number of other arrhythmias were found.

Conclusions

The establishment of mandatory lockdown has led to a marked drop in daily physical activity in this population which probably explains changes observed in other cardiac biometric variables. Although, in the short term, we have not documented an increased risk of arrhythmia, we cannot rule out an effect in the medium to long term or in other populations of at-risk patients.

2021 ISHNE/HRS/EHRA/APHRS collaborative statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals: From the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society

This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society describes the current status of mobile health ("mHealth") technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mHealth. The promises of predictive analytics but also operational challenges in embedding mHealth into routine clinical care are explored.

2021 ISHNE/ HRS/ EHRA/ APHRS collaborative statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals: From the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society

This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/ Heart Rhythm Society/ European Heart Rhythm Association/ Asia Pacific Heart Rhythm Society describes the current status of mobile health ("mHealth") technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mHealth. The promises of predictive analytics but also operational challenges in embedding mHealth into routine clinical care are explored.

2021 ISHNE / HRS / EHRA / APHRS Collaborative Statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals: From the International Society for Holter and Noninvasive Electrocardiology / Heart Rhythm Society / European Heart Rhythm Association / Asia Pacific Heart Rhythm Society

This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology / Heart Rhythm Society / European Heart Rhythm Association / Asia Pacific Heart Rhythm Society describes the current status of mobile health ("mHealth") technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mHealth. The promises of predictive analytics but also operational challenges in embedding mHealth into routine clinical care are explored.

[Cardiac biometric variables and arrhythmic events during COVID-19 pandemic lockdown in patients with an implantable cardiac monitor for syncope work-up]

AIM

To assess the changes induced by the COVID-19 lockdown on cardiac biometric variables recorded using an implantable cardiac monitor (ICM) in a patient population monitored for syncope work-up, as well to assess whether there has been an effect on arrhythmic events among the patients.

METHODS

Longitudinal cohort study. We included 245 adult patients monitored with an ICM indicated for the investigation of syncope. The records from days 1 to 12 March 2020 (prior to the institution of lockdown by the state government) with days 16 to 28 March 2020 were compared.

RESULTS

Daily physical exercise reduced markedly after the imposition of lockdown (132 [55-233] minutes vs. 78 [21-154] minutes). The mean daytime HR prior to lockdown was 77 [69-85] bpm, whereas during lockdown it was 74 [66-81] bpm. During the lockdown period, a drop in the variability in heart rate (114 [94-136] ms vs. 111 [92-133] ms) was observed. Although the incidence of AF was similar over both periods, the daily AF burden was significantly higher post-lockdown (405 [391-425] minutes vs. 423 [423-537] minutes). No differences in the number of other arrhythmias were found.

CONCLUSIONS

The establishment of mandatory lockdown has led to a marked drop in daily physical activity in this population which probably explains changes observed in other cardiac biometric variables. Although, in the short term, we have not documented an increased risk of arrhythmia, we cannot rule out an effect in the medium to long term or in other populations of at-risk patients.

2021 ISHNE/HRS/EHRA/APHRS Collaborative Statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals: From the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society

This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society describes the current status of mobile health ("mHealth") technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mHealth. The promises of predictive analytics but also operational challenges in embedding mHealth into routine clinical care are explored.

2021 ISHNE/HRS/EHRA/APHRS Expert Collaborative Statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals: From the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia-Pacific Heart Rhythm Society

This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia-Pacific Heart Rhythm Society describes the current status of mobile health technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mobile health. The promises of predictive analytics but also operational challenges in embedding mobile health into routine clinical care are explored.

B-type natriuretic peptide over N-terminal pro-brain natriuretic peptide to predict incident atrial fibrillation after cryptogenic stroke

BACKGROUND AND PURPOSE

B-type natriuretic peptide (BNP) and N-terminal pro-brain natriuretic peptide (NT-proBNP) are well-known surrogates of atrial fibrillation (AF) detection but studies usually present data on either BNP or NT-proBNP. The aim was to determine and directly compare the validity of the two biomarkers as a tool to predict AF and guide prolonged cardiac monitoring in cryptogenic stroke patients.

METHODS

Non-lacunar acute ischaemic stroke (<72 h) patients over 55 years of age with cryptogenic stroke after standard evaluation were included in the Crypto-AF study and blood was collected. BNP and NT-proBNP levels were determined by automated immunoassays. AF was assessed by 28 days' monitoring. Highest (optimizing specificity) and lowest (optimizing sensitivity) quartiles were used as biomarker cut-offs to build predictive models adjusted by sex and age. The integrated discrimination improvement index (IDI) and DeLong test were used to compare the performance of the two biomarkers.

RESULTS

From 320 patients evaluated, 218 were included in the analysis. AF was detected in 50 patients (22.9%). NT-proBNP (P < 0.001) and BNP (P < 0.001) levels were higher in subjects with AF and their levels correlated (r = 0.495, P < 0.001). BNP showed an increased area under the curve (0.720 vs. 0.669; P = 0.0218) and a better predictive capacity (IDI = 3.63%, 95% confidence interval 1.36%-5.91%) compared to NT-proBNP. BNP performed better than NT-proBNP in a specific model (IDI = 3.7%, 95% confidence interval 0.87%-6.5%), whilst both biomarkers performed similarly in the case of a sensitive model.

CONCLUSIONS

Both BNP and NT-proBNP were increased in cryptogenic stroke patients with AF detection. Interestingly, BNP outperforms NT-proBNP, especially in terms of specificity.

Predicting Atrial Fibrillation with High Risk of Embolization with Atrial Strain and NT-proBNP

The aim of the study was to determine markers of atrial dysfunction in patients with cryptogenic stroke to predict episodes of paroxysmal atrial fibrillation with high risk of embolization (HpAF). We classified patients included in the Crypto-AF study, Cryptogenic Stroke registry, to detect paroxysmal atrial fibrillation (pAF) with wearable Holter, according to the longest episode of pAF in three groups: without pAF detection, episodes of pAF shorter than 5 h, and episodes of pAF longer than 5 h (HpAF). Atrial dysfunction surrogates were evaluated: EKG pattern, Holter record and echocardiography parameters (left atria volume (LAVI), and peak atrial longitudinal and contraction strain (PALS and PACS). The level of N-terminal pro b-type natriuretic peptide (NT-proBNP) was determined. All patients were followed for 2 years to detect pAF and stroke recurrence. From 308 patients, 253 patients with high quality Holter analysis were selected. The distribution was No pAF 78.6% (n = 199), pAF < 5 h 7.9% (n = 20), and HpAF > 5 h 13.4% (n = 34). Age of the patients and combination of PALS and NT-proBNP independently predicted HpAF OR 1.07 (1.00; 1.15) and OR 3.05 (1.08; 8.60) respectively. The validity of PALS and NT-proBNP to detect patients at risk of HpAF was higher than the validity of age (AUC 0.82, sensitivity 78.95%, specificity 63%). Patients with PALS < 25% and NT-proBNP > 283 pg/ml had more detection of pAF during follow-up 35% vs. 5.1% OR 2.33 (1.05-5.13) (p < 0.001). Multimodal assessment of atrial dysfunction with PALS and NT-proBNP improved the prediction of pAF episodes with high embolic risk in patients with cryptogenic stroke.

Screening of Embolic Sources by Point-of-Care Ultrasound in the Acute Phase of Ischemic Stroke

Our objective was to evaluate hand-held echocardiography as point of care ultrasound scanning (POCUS) to detect sources of embolism in the acute phase of stroke. Prospective, unicentric observational cohort study of non-lacunar ischemic stroke patients evaluated by V Scan device. The main sources of embolism (MSEs) were classified into embolic valvulopathies and severe ventricular dysfunction. We looked for atrial fibrillation (AF) predictors in strokes of undetermined etiology. MSEs were detected in 19.23% (25/130). Large vessel occlusion (LVO) (odds ratio [OR]: 4.24, 95% confidence interval [CI]: 1.01-17.85) and chronic heart failure (OR: 13.25, 95% CI: 3.54-49.50) were independent predictors of MSEs. LVO (OR: 6.54, 95% CI: 1.62-26.27) and left atrial area >20 cm² (OR: 7.01, 95% CI: 1.75-28.09) independently predicted AF. Patients with LVO and chronic heart disease may benefit from hand-held echocardiography as part of POCUS in the acute phase of ischemic stroke. Left atrial area measured was an independent predictor of AF in strokes of undetermined etiology.

A Deep Learning Approach for Featureless Robust Quality Assessment of Intermittent Atrial Fibrillation Recordings from Portable and Wearable Devices

Atrial fibrillation (AF) is the most common heart rhythm disturbance in clinical practice. It often starts with asymptomatic and very short episodes, which are extremely difficult to detect without long-term monitoring of the patient’s electrocardiogram (ECG). Although recent portable and wearable devices may become very useful in this context, they often record ECG signals strongly corrupted with noise and artifacts. This impairs automatized ulterior analyses that could only be conducted reliably through a previous stage of automatic identification of high-quality ECG intervals. So far, a variety of techniques for ECG quality assessment have been proposed, but poor performances have been reported on recordings from patients with AF. This work introduces a novel deep learning-based algorithm to robustly identify high-quality ECG segments within the challenging environment of single-lead recordings alternating sinus rhythm, AF episodes and other rhythms. The method is based on the high learning capability of a convolutional neural network, which has been trained with 2-D images obtained when turning ECG signals into wavelet scalograms. For its validation, almost 100,000 ECG segments from three different databases have been analyzed during 500 learning-testing iterations, thus involving more than 320,000 ECGs analyzed in total. The obtained results have revealed a discriminant ability to detect high-quality and discard low-quality ECG excerpts of about 93%, only misclassifying around 5% of clean AF segments as noisy ones. In addition, the method has also been able to deal with raw ECG recordings, without requiring signal preprocessing or feature extraction as previous stages. Consequently, it is particularly suitable for portable and wearable devices embedding, facilitating early detection of AF as well as other automatized diagnostic facilities by reliably providing high-quality ECG excerpts to further processing stages.

Detecting Atrial Fibrillation in Patients With an Embolic Stroke of Undetermined Source (from the DAF-ESUS registry)

Atrial fibrillation (AF) causes a substantial proportion of embolic strokes of undeterminded source (ESUS). Effective detection of subclinical AF (SCAF) has important therapeutic implications. We conducted a prospective study to determine the prevalence of SCAF in patients with ESUS through of a 21-day Holter monitoring. In an early-monitoring group, Holter was initiated immediately after hospital discharge. The results were compared with a previous cohort of patients in whom the Holter was initiated at least 1 week after hospital discharge (late-monitoring group). We included 100 patients (50 each group; 69 ± 13 years, 56% male). Mean time from ESUS to Holter was 1.2 ± 1 day in the early-monitoring group and 30 ± 15 days in the late-monitoring group. SCAF was detected in 22% of patients in the early-monitoring and 6% in the late-monitoring group (p <0.05). Patients with SCAF were older (77 ± 9 vs 67 ± 11 years, p <0.05), with a higher rate of left atrial enlargement (50% vs 20%, p<0.05), renal impairment (28% vs 5%; p<0.01), and a slower mean heart rate (55 ± 6 vs 70 ± 6 beats/min; p<0.001). On multivariate analysis, the presence of persistent bradycardia (≤60 beats/min) in the 21-day Holter was a powerful and significant risk factor for SCAF. In conclusion, the sooner 21-day Holter electrocardiogram monitoring is initiated after ESUS, the more likely SCAF can be detected. Sinus bradycardia is a powerful predictor of SCAF in patients with ESUS.

Wearable devices for remote vital signs monitoring in the outpatient setting: an overview of the field

Early detection of physiological deterioration has been shown to improve patient outcomes. Due to recent improvements in technology, comprehensive outpatient vital signs monitoring is now possible. This is the first review to collate information on all wearable devices on the market for outpatient physiological monitoring.

A scoping review was undertaken. The monitors reviewed were limited to those that can function in the outpatient setting with minimal restrictions on the patient’s normal lifestyle, while measuring any or all of the vital signs: heart rate, ECG, oxygen saturation, respiration rate, blood pressure and temperature.

A total of 270 papers were included in the review. Thirty wearable monitors were examined: 6 patches, 3 clothing-based monitors, 4 chest straps, 2 upper arm bands and 15 wristbands. The monitoring of vital signs in the outpatient setting is a developing field with differing levels of evidence for each monitor. The most common clinical application was heart rate monitoring. Blood pressure and oxygen saturation measurements were the least common applications. There is a need for clinical validation studies in the outpatient setting to prove the potential of many of the monitors identified.

Research in this area is in its infancy. Future research should look at aggregating the results of validity and reliability and patient outcome studies for each monitor and between different devices. This would provide a more holistic overview of the potential for the clinical use of each device.

N-Terminal Pro B-Type Natriuretic Peptide's Usefulness for Paroxysmal Atrial Fibrillation Detection Among Populations Carrying Cardiovascular Risk Factors

Background: Atrial fibrillation (AF) systematic screening studies have not shown a clear usefulness in stroke prevention, as AF might present as paroxysmal and asymptomatic. This study aims to determine the usefulness of some blood-biomarkers to identify paroxysmal atrial fibrillation in the context of a screening programme. Methods: A total of 100 subjects aged 65-75 years with hypertension and diabetes were randomly selected. AF was assessed by conventional electrocardiogram (ECG) and 4 weeks monitoring with a wearable Holter device (Nuubo™). N-terminal pro B-type natriuretic peptide (NT-proBNP), apolipoprotein CIII (ApoC-III), von Willebrand factor (vWF), ADAMTS13, urokinase plasminogen activator surface receptor (uPAR), and urokinase plasminogen activator (uPA) were determined in serum/plasma samples and the levels were compared depending on AF presence and mode of detection. Results: The AF prevalence in the studied population was found to be 20%. In seven subjects, AF was only detected after 1 month of Holter monitoring (hAF group). NT-proBNP levels were higher in subjects with AF compared with subjects with no AF (p < 0.0001), even when only taking into account the hAF group (p = 0.031). No significant differences were found in the other biomarkers. The NT-proBNP >95 pg/ml cut-off showed high sensitivity and specificity to detect AF (95%, 66.2%) or hAF (85.72%, 66.2%) and was found to be an independent predictor of AF and hAF in a logistic regression analysis. NT-proBNP correlated with AF burden (r = 0.597, p = 0.024). Conclusion: NT-proBNP was elevated in AF cases not identified by ECG; thus, it may be used as a screening biomarker in asymptomatic high-risk populations, with a promising cut-off point of 95 pg/ml that requires further validation.

Cardioembolic Ischemic Stroke Gene Expression Fingerprint in Blood: a Systematic Review and Verification Analysis

An accurate etiological classification is key to optimize secondary prevention after ischemic stroke, but the cause remains undetermined in one third of patients. Several studies pointed out the usefulness of circulating gene expression markers to discriminate cardioembolic (CE) strokes, mainly due to atrial fibrillation (AF), while only exploring them in small cohorts. A systematic review of studies analyzing high-throughput gene expression in blood samples to discriminate CE strokes was performed. Significantly dysregulated genes were considered as candidates, and a selection of them was validated by RT-qPCR in 100 patients with defined CE or atherothrombotic (LAA) stroke etiology. Longitudinal performance was evaluated in 12 patients at three time points. Their usefulness as biomarkers for AF was tested in 120 cryptogenic strokes and 100 individuals at high-risk for stroke. Three published studies plus three unpublished datasets were considered for candidate selection. Sixty-seven genes were found dysregulated in CE strokes. CREM, PELI1, and ZAK were verified to be up-regulated in CE vs LAA (p = 0.010, p = 0.003, p < 0.001, respectively), without changes in their expression within the first 24 h after stroke onset. The combined up-regulation of these three biomarkers increased the probability of suffering from CE stroke by 23-fold. In cryptogenic strokes with subsequent AF detection, PELI1 and CREM showed overexpression (p = 0.017, p = 0.059, respectively), whereas in high-risk asymptomatic populations, all three genes showed potential to detect AF (p = 0.007, p = 0.007, p = 0.015). The proved discriminatory capacity of these gene expression markers to detect cardioembolism even in cryptogenic strokes and asymptomatic high-risk populations might bring up their use as biomarkers.

Assessment of signal quality measured with a smart 12-lead ECG acquisition T-shirt

BACKGROUND

Ambulatory ECG monitoring is typically achieved using portable devices with limited number of surface leads, autonomy, and length of recording. Smart garments with multiple conductive textile electrodes provide great promise to perform continuous and comfortable ECG monitoring.

METHODS

We evaluated the ECG signal quality measured on healthy subjects with a smart 12-lead ECG acquisition T-shirt or a 12-lead Holter recording. ECG signals were recorded during 3 min with both techniques in three resting positions (supine, seated, standing) and while walking. Three readers independently assessed ECG patterns and evaluated the denoising of the isoelectric line, the distinction of p waves, R peaks and RR intervals, and the possible appreciation of cardiac rhythm in at least 3 leads.

RESULTS

Thirty healthy subjects (70% males, 29.5 ± 7.8 years) were enrolled in the study. For all three resting conditions, cardiac rhythm was appreciated in 100% of recordings with distinction of p waves, R peaks, and isoelectric line in >97% of recordings. Appreciation of cardiac rhythm was lower in the walking conditions with both techniques (53.3% vs. 46.7%, Holter vs. smart T-shirt, p = .60) mainly due to difficulties to distinguish p waves. These results were consistent across both genders. All ECG parameters (heart rate, PR, QRS and QTC intervals) were comparable between both techniques. No skin irritation was seen with the textile electrodes.

CONCLUSIONS

A smart T-shirt with 13 textiles electrodes allows short-duration 12-lead ECG acquisition with quality levels comparable to Holter recordings. The novel device should now be evaluated for long-term non-invasive ECG monitoring.

External continuous ECG versus loop recording for atrial fibrillation detection in patients who had a stroke

BACKGROUND

Detection of atrial fibrillation (AF) in patients who had ischaemic stroke and transient ischaemic attack (IS/TIA) is recommended. We aimed to compare external loop recording (ELR) against simultaneous continuous ECG recording for AF detection in patients who had acute IS/TIA and determine sensitivity, specificity and positive predictive value of AF detection using ELR. We hypothesised ELR to detect 15% fewer patients with AF than continuous ECG recording.

METHODS

In this prospective cohort study, we included 1412 patients who had acute IS/TIA without prior AF. Monitoring was 48 hours. Primary outcome was AF >30 s. Cardiologist verified AF in continuous ECG was gold standard.

RESULTS

In continuous ECG, 38 (2.7%) patients had AF. ELR automatically categorised 219/1412 patients (15.5%) with AF, including 32/38 (85%) patients with AF in continuous ECG. After cardiologist adjudication of ELR recordings, AF was diagnosed in 57/219 patients, of which 32 (56%) had AF in continuous ECG. For adjudicated AF detection by ELR, sensitivity was 84%, 95% CI (69% to 94%), specificity was 98%, 95% CI (97% to 99%) and positive predictive value was 56%, 95% CI (42% to 69%).

CONCLUSION

Automatic AF detection with ELR results in an AF diagnosis in more than five patients without AF for each patient with AF as verified in continuous ECG. For adjudicated AF detection by ELR, sensitivity was confirmed to 84% and specificity 98%. Automatic ELR as investigated in this study may be considered to rule out AF, but it is not suitable as a single monitoring device for AF screening in patients early after stroke.

TRIAL REGISTRATION NUMBER

NCT02155907.

A randomized trial evaluating the accuracy of AF detection by four external ambulatory ECG monitors compared to permanent pacemaker AF detection

PURPOSE

Several external cardiac monitors (ECMs) have recently been developed. These have never been compared to 'gold standard' monitoring with concurrently implanted DDDRP pacemakers. The accuracy of AF detection of Zio XT Monitor (ZM), NUUBO Vest (NV) and Carnation Ambulatory Monitor (CAM) compared with Novacor 'R' Test 4 (RT) in patients (pts) with DDDRP PPM advanced Holters as the comparator, was evaluated.

METHODS

Twenty-one pts. with AF and a DDDRP PPM, each acting as their own control subject, wore every ECM for 2 weeks in randomized order. PPM downloads were performed at application and removal. Device ECGs were compared for AF burden and individual AF episodes with PPM Holters. Pt acceptability, wear time, costs and time expenditure were evaluated.

RESULTS

RT AF burden was less accurate than the ZM, NV or CAM (p < 0.05). Probability of inaccurate AF diagnosis was higher for RT than ZM or CAM OR 12.31 and 5.85, respectively (p = 0.025 and p = 0.042). ZM wear time was longer than the RT: 307 h vs. 224 h; p = 0.02. Acceptability was greater for CAM than RT (1.86 ± 2.63 compared with 0.57 ± 1.17 for CAM; p = 0.024). All ECMs were more expensive than RT (p < 0.00001).

CONCLUSIONS

All new ECMs were more expensive than the RT system; however, the ZM, NV and CAM are all more accurate than current standard practice RT device in AF burden assessment. The RT is more likely to give inaccurate diagnoses than ZM or CAM. This may have clinical implications.