Performance of a New Leadless Implantable Cardiac Monitor in Detecting and Quantifying Atrial Fibrillation Results of the XPECT Trial

No Detectable Differences in microRNA Plasma Levels between Diabetic Hypertensive Patients with and without Incident Subclinical Atrial Fibrillation

Background: Long-term rhythm monitoring (LTRM) can detect undiagnosed atrial fibrillation (AF) in patients at risk of AF and stroke. Circulating microRNAs (miRNAs), which have been shown to play a role in atrial electrical and structural remodelling, could help to select patients who would benefit most from LTRM. The aim of this study was to investigate whether patients with diabetes mellitus (DM) and hypertension and screen-detected subclinical AF (SCAF) using an insertable cardiac monitor (ICM) have significantly different plasma baseline levels of five selected miRNAs playing a role in the modulation of atrial electrical and structural remodelling (miR-21-5p, miR-29b-3p, miR-150-5p, miR-328-3p, and miR-432-5p) compared to those without SCAF. Methods: This study was performed at the outpatient clinic of a secondary academic teaching hospital between December 2013 and November 2015. Eligible patients were ≥65 years of age with DM and hypertension but without known heart diseases. All patients received an ICM. On the day of ICM implantation, blood samples for the measurement of plasma levels of the five miRNAs were drawn. In this post hoc analysis, we investigated their expression by reverse transcription-quantitative polymerase chain reaction. MiRNA plasma levels in patients with and without newly detected SCAF were compared. Results: We included 82 consecutive patients (median age of 71.3 years (IQR 67.4-75.1)), who were followed for a median of 588 days (IQR: 453-712 days). Seventeen patients (20.7%) had ICM-detected SCAF. Plasma levels of miR-328-3p, miR-29b-3p, miR-21-5p, miR-432-5p, and miR-150-5p were slightly but not significantly different in patients with incident SCAF compared with patients without. Conclusions: In patients with hypertension and DM, newly detected SCAF was not significantly associated with changes in expression levels of miR-21-5p, miR-29b-3p, miR-150-5p, miR-328-3p, and miR-432-5p.

2024 European Heart Rhythm Association/Heart Rhythm Society/Asia Pacific Heart Rhythm Society/Latin American Heart Rhythm Society expert consensus statement on catheter and surgical ablation of atrial fibrillation

In the last three decades, ablation of atrial fibrillation (AF) has become an evidence-based safe and efficacious treatment for managing the most common cardiac arrhythmia. In 2007, the first joint expert consensus document was issued, guiding healthcare professionals involved in catheter or surgical AF ablation. Mounting research evidence and technological advances have resulted in a rapidly changing landscape in the field of catheter and surgical AF ablation, thus stressing the need for regularly updated versions of this partnership which were issued in 2012 and 2017. Seven years after the last consensus, an updated document was considered necessary to define a contemporary framework for selection and management of patients considered for or undergoing catheter or surgical AF ablation. This consensus is a joint effort from collaborating cardiac electrophysiology societies, namely the European Heart Rhythm Association, the Heart Rhythm Society (HRS), the Asia Pacific HRS, and the Latin American HRS.

Impact of Atrial Fibrillation Burden on Health Care Costs and Utilization

BACKGROUND

Integrating patient-specific cardiac implantable electronic device (CIED)-detected atrial fibrillation (AF) burden with measures of health care cost and utilization allows for an accurate assessment of the AF-related impact on health care use.

OBJECTIVES

The goal of this study was to assess the incremental cost of device-recognized AF vs no AF; compare relative costs of paroxysmal atrial fibrillation (pAF), persistent atrial fibrillation (PeAF), and permanent atrial fibrillation (PermAF) AF; and evaluate rates and sources of health care utilization between cohorts.

METHODS

Using the de-identified Optum Clinformatics U.S. claims database (2015-2020) linked with the Medtronic CareLink database, CIED patients were identified who transmitted data ≥6 months postimplantation. Annualized per-patient costs in follow-up were analyzed from insurance claims and adjusted to 2020 U.S. dollars. Costs and rates of health care utilization were compared between patients with no AF and those with device-recognized pAF, PeAF, and PermAF. Analyses were adjusted for geographical region, insurance type, CHA2DS2-VASc score, and implantation year.

RESULTS

Of 21,391 patients (mean age 72.9 ± 10.9 years; 56.3% male) analyzed, 7,798 (36.5%) had device-recognized AF. The incremental annualized increased cost in those with AF was $12,789 ± $161,749 per patient, driven by increased rates of health care encounters, adverse clinical events associated with AF, and AF-specific interventions. Among those with AF, PeAF was associated with the highest cost, driven by increased rates of inpatient and outpatient hospitalization encounters, heart failure hospitalizations, and AF-specific interventions.

CONCLUSIONS

Presence of device-recognized AF was associated with increased health care cost. Among those with AF, patients with PeAF had the highest health care costs. Mechanisms for cost differentials include both disease-specific consequences and physician-directed interventions.

2024 European Heart Rhythm Association/Heart Rhythm Society/Asia Pacific Heart Rhythm Society/Latin American Heart Rhythm Society expert consensus statement on catheter and surgical ablation of atrial fibrillation

In the last three decades, ablation of atrial fibrillation (AF) has become an evidence-based safe and efficacious treatment for managing the most common cardiac arrhythmia. In 2007, the first joint expert consensus document was issued, guiding healthcare professionals involved in catheter or surgical AF ablation. Mounting research evidence and technological advances have resulted in a rapidly changing landscape in the field of catheter and surgical AF ablation, thus stressing the need for regularly updated versions of this partnership which were issued in 2012 and 2017. Seven years after the last consensus, an updated document was considered necessary to define a contemporary framework for selection and management of patients considered for or undergoing catheter or surgical AF ablation. This consensus is a joint effort from collaborating cardiac electrophysiology societies, namely the European Heart Rhythm Association, the Heart Rhythm Society, the Asia Pacific Heart Rhythm Society, and the Latin American Heart Rhythm Society .

An Artificial Intelligence Analysis of Electrocardiograms for the Clinical Diagnosis of Cardiovascular Diseases: A Narrative Review

Artificial intelligence (AI) applied to cardiovascular disease (CVD) is enjoying great success in the field of scientific research. Electrocardiograms (ECGs) are the cornerstone form of examination in cardiology and are the most widely used diagnostic tool because they are widely available, inexpensive, and fast. Applications of AI to ECGs, especially deep learning (DL) methods using convolutional neural networks (CNNs), have been developed in many fields of cardiology in recent years. Deep learning methods provide valuable support for rapid ECG interpretation, demonstrating a diagnostic capability overlapping with specialists in the diagnosis of CVD by a classical analysis of macroscopic changes in the ECG trace. Through photoplethysmography, wearable devices can obtain single-derivative ECGs for the recognition of AI-diagnosed arrhythmias. In addition, CNNs have been developed that recognize no macroscopic electrocardiographic changes and can predict, from a 12-lead ECG, atrial fibrillation, even from sinus rhythm; left and right ventricular function; hypertrophic cardiomyopathy; acute coronary syndromes; or aortic stenosis. The fields of application are many, but numerous are the limitations, mainly associated with the reliability of the acquired data, an inability to verify black box processes, and medico-legal and ethical problems. The challenge of modern medicine is to recognize the limitations of AI and overcome them.

Biodegradable, Biocompatible, and Implantable Multifunctional Sensing Platform for Cardiac Monitoring

Cardiac monitoring after heart surgeries is crucial for health maintenance and detecting postoperative complications early. However, current methods like rigid implants have limitations, as they require performing second complex surgeries for removal, increasing infection and inflammation risks, thus prompting research for improved sensing monitoring technologies. Herein, we introduce a nanosensor platform that is biodegradable, biocompatible, and integrated with multifunctions, suitable for use as implants for cardiac monitoring. The device has two electrochemical biosensors for sensing lactic acid and pH as well as a pressure sensor and a chemiresistor array for detecting volatile organic compounds. Its biocompatibility with myocytes has been tested in vitro, and its biodegradability and sensing function have been proven with ex vivo experiments using a three-dimensional (3D)-printed heart model and 3D-printed cardiac tissue patches. Moreover, an artificial intelligence-based predictive model was designed to fuse sensor data for more precise health assessment, making it a suitable candidate for clinical use. This sensing platform promises impactful applications in the realm of cardiac patient care, laying the foundation for advanced life-saving developments.

Implantable cardiac monitors: artificial intelligence and signal processing reduce remote ECG review workload and preserve arrhythmia detection sensitivity

Introduction

Implantable cardiac monitors (ICMs) provide long-term arrhythmia monitoring, but high rates of false detections increase the review burden. The new "SmartECG" algorithm filters false detections. Using large real-world data sets, we aimed to quantify the reduction in workload and any loss in sensitivity from this new algorithm.

Methods

Patients with a BioMonitor IIIm and any device indication were included from three clinical projects. All subcutaneous ECGs (sECGs) transmitted via remote monitoring were classified by the algorithm as "true" or "false." We quantified the relative reduction in workload assuming "false" sECGs were ignored. The remote monitoring workload from five hospitals with established remote monitoring routines was evaluated. Loss in sensitivity was estimated by testing a sample of 2000 sECGs against a clinical board of three physicians.

Results

Of our population of 368 patients, 42% had an indication for syncope or pre-syncope and 31% for cryptogenic stroke. Within 418.5 patient-years of follow-up, 143,096 remote monitoring transmissions contained 61,517 sECGs. SmartECG filtered 42.8% of all sECGs as "false," reducing the number per patient-year from 147 to 84. In five hospitals, nine trained reviewers inspected on average 105 sECGs per working hour. This results in an annual working time per patient of 83 min without SmartECG, and 48 min with SmartECG. The loss of sensitivity is estimated as 2.6%. In the majority of cases where true arrhythmias were rejected, SmartECG classified the same type of arrhythmia as "true" before or within 3 days of the falsely rejected sECG.

Conclusion

SmartECG increases efficiency in long-term arrhythmia monitoring using ICMs. The reduction of workload by SmartECG is meaningful and the risk of missing a relevant arrhythmia due to incorrect filtering by the algorithm is limited.

Improved diagnostic performance of insertable cardiac monitors by an artificial intelligence-based algorithm

AIMS

The increasing use of insertable cardiac monitors (ICM) produces a high rate of false positive (FP) diagnoses. Their verification results in a high workload for caregivers. We evaluated the performance of an artificial intelligence (AI)-based ILR-ECG Analyzer™ (ILR-ECG-A). This machine-learning algorithm reclassifies ICM-transmitted events to minimize the rate of FP diagnoses, while preserving device sensitivity.

METHODS AND RESULTS

We selected 546 recipients of ICM followed by the Implicity™ monitoring platform. To avoid clusterization, a single episode per ICM abnormal diagnosis (e.g. asystole, bradycardia, atrial tachycardia (AT)/atrial fibrillation (AF), ventricular tachycardia, artefact) was selected per patient, and analyzed by the ILR-ECG-A, applying the same diagnoses as the ICM. All episodes were reviewed by an adjudication committee (AC) and the results were compared. Among 879 episodes classified as abnormal by the ICM, 80 (9.1%) were adjudicated as 'Artefacts', 283 (32.2%) as FP, and 516 (58.7%) as 'abnormal' by the AC. The algorithm reclassified 215 of the 283 FP as normal (76.0%), and confirmed 509 of the 516 episodes as abnormal (98.6%). Seven undiagnosed false negatives were adjudicated as AT or non-specific abnormality. The overall diagnostic specificity was 76.0% and the sensitivity was 98.6%.

CONCLUSION

The new AI-based ILR-ECG-A lowered the rate of FP ICM diagnoses significantly while retaining a > 98% sensitivity. This will likely alleviate considerably the clinical burden represented by the review of ICM events.

Atrial fibrillation in embolic stroke of undetermined source: role of advanced imaging of left atrial function

AIMS

Atrial fibrillation (AF) is detected in over 30% of patients following an embolic stroke of undetermined source (ESUS) when monitored with an implantable loop recorder (ILR). Identifying AF in ESUS survivors has significant therapeutic implications, and AF risk is essential to guide screening with long-term monitoring. The present study aimed to establish the role of left atrial (LA) function in subsequent AF identification and develop a risk model for AF in ESUS.

METHODS AND RESULTS

We conducted a single-centre retrospective case-control study including all patients with ESUS referred to our institution for ILR implantation from December 2009 to September 2019. We recorded clinical variables at baseline and analysed transthoracic echocardiograms in sinus rhythm. Univariate and multivariable analyses were performed to inform variables associated with AF. Lasso regression analysis was used to develop a risk prediction model for AF. The risk model was internally validated using bootstrapping. Three hundred and twenty-three patients with ESUS underwent ILR implantation. In the ESUS population, 293 had a stroke, whereas 30 had suffered a transient ischaemic attack as adjudicated by a senior stroke physician. Atrial fibrillation of any duration was detected in 47.1%. The mean follow-up was 710 days. Following lasso regression with backwards elimination, we combined increasing lateral PA (the time interval from the beginning of the P wave on the surface electrocardiogram to the beginning of the A' wave on pulsed wave tissue Doppler of the lateral mitral annulus) [odds ratio (OR) 1.011], increasing Age (OR 1.035), higher Diastolic blood pressure (OR 1.027), and abnormal LA reservoir Strain (OR 0.973) into a new PADS score. The probability of identifying AF can be estimated using the formula. Model discrimination was good [area under the curve (AUC) 0.72]. The PADS score was internally validated using bootstrapping with 1000 samples of 150 patients showing consistent results with an AUC of 0.73.

CONCLUSION

The novel PADS score can identify the risk of AF on prolonged monitoring with ILR following ESUS and should be considered a dedicated risk stratification tool for decision-making regarding the screening strategy for AF in stroke.

Predictors of Atrial Fibrillation in Patients with Embolic Stroke of Unknown Etiology and Implantable Loop Recorders-Further Insights of the TRACK AF Study on the Role of ECG and Echocardiography

Aims-Electrocardiography (ECG) and echocardiographic left atrial (LA) parameters may be helpful to assess the risk of atrial fibrillation (AF) in embolic stroke of unknown etiology (ESUS) and could therefore guide intensity of ECG monitoring. Methods-1153 consecutive patients with ischemic stroke or transient ischemic attack (TIA) were analyzed. An internal loop recorder (ILR) was implanted in 104 consecutive patients with ESUS. Multiple morphologic P-wave parameters in baseline 12-channel ECG and echocardiographic LA parameters were measured and analyzed in patients with and without ILR-detected AF. Using logistic regression, we evaluated the predictive value of several ECG parameters and LA dimensions on the occurrence of AF. Results-In 20 of 104 (19%) patients, AF was diagnosed by ILR during a mean monitoring time of 575 (IQR 470-580) days. Patients with AF were significantly older (72 (67-75) vs. 60 (52-72) years; p = 0.001) and premature atrial contractions (PAC) were more frequently observed (40% vs. 2%; p < 0.001) during baseline ECG. All morphologic P-wave parameters did not show a significant difference between groups. There was a non-significant trend towards a larger LA volume index (31 (24-36) vs. 29 (25-37) mL/m2; p = 0.09) in AF patients. Conclusions-Age and PAC are independently associated with incident AF in ESUS and could be used as markers for selecting patients that may benefit from more extensive rhythm monitoring or ILR implantation. In our consecutive cohort of patients with ESUS, neither morphological P-wave parameters nor LA size were predictive of AF.

Heart rate characteristic based modelling of atrial fibrillatory rate using implanted cardiac monitor data

Objective. The objective of the present study is to investigate the feasibility of using heart rate characteristics to estimate atrial fibrillatory rate (AFR) in a cohort of atrial fibrillation (AF) patients continuously monitored with an implantable cardiac monitor. We will use a mixed model approach to investigate population effect and patient specific effects of heart rate characteristics on AFR, and will correct for the effect of previous ablations, episode duration, and onset date and time.Approach. The f-wave signals, from which AFR is estimated, were extracted using a QRST cancellation process of the AF episodes in a cohort of 99 patients (67% male; 57 ± 12 years) monitored for 9.2(0.2-24.3) months as median(min-max). The AFR from 2453 f-wave signals included in the analysis was estimated using a model-based approach. The association between AFR and heart rate characteristics, prior ablations, and episode-related features were modelled using fixed-effect and mixed-effect modelling approaches.Main results. The mixed-effect models had a better fit to the data than fixed-effect models showing h.c. of determination (R2 = 0.49 versusR2 = 0.04) when relating the variations of AFR to the heart rate features. However, when correcting for the other factors, the mixed-effect model showed the best fit (R2 = 0.04). AFR was found to be significantly affected by previous catheter ablations (p< 0.05), episode duration (p< 0.05), and irregularity of theRRinterval series (p< 0.05).Significance. Mixed-effect models are more suitable for AFR modelling. AFR was shown to be faster in episodes with longer duration, less organizedRRintervals and after several ablation procedures.

Cost-effectiveness of an insertable cardiac monitor in a high-risk population in the US

BACKGROUND

Insertable cardiac monitors (ICMs) are a clinically effective means of detecting atrial fibrillation (AF) in high-risk patients, and guiding the initiation of non-vitamin K oral anticoagulants (NOACs). Their cost-effectiveness from a US clinical payer perspective is not yet known. The objective of this study was to evaluate the cost-effectiveness of ICMs compared to standard of care (SoC) for detecting AF in patients at high risk of stroke (CHADS₂ ≥ 2), in the US.

METHODS

Using patient data from the REVEAL AF trial (n = 393, average CHADS₂ score = 2.9), a Markov model estimated the lifetime costs and benefits of detecting AF with an ICM or with SoC (specifically intermittent use of electrocardiograms and 24-h Holter monitors). Ischemic and hemorrhagic strokes, intra- and extra-cranial hemorrhages, and minor bleeds were modelled. Diagnostic and device costs, costs of treating stroke and bleeding events and medical therapy-specifically costs of NOACs were included. Costs and health outcomes, measured as quality-adjusted life years (QALYs), were discounted at 3% per annum, in line with standard practice in the US setting. One-way deterministic and probabilistic sensitivity analyses (PSA) were undertaken.

RESULTS

Lifetime per-patient cost for ICM was $31,116 versus $25,330 for SoC. ICMs generated a total of 7.75 QALYs versus 7.59 for SoC, with 34 fewer strokes projected per 1000 patients. The model estimates a number needed to treat of 29 per stroke avoided. The incremental cost-effectiveness ratio was $35,528 per QALY gained. ICMs were cost-effective in 75% of PSA simulations, using a $50,000 per QALY threshold, and a 100% probability of being cost-effective at a WTP threshold of $150,000 per QALY.

CONCLUSIONS

The use of ICMs to identify AF in a high-risk population is likely to be cost-effective in the US healthcare setting.

An ensemble of features based deep learning neural network for reduction of inappropriate atrial fibrillation detection in implantable cardiac monitors

Background

Multiple studies have reported on classification of raw electrocardiograms (ECGs) using convolutional neural networks (CNNs).

Objective

We investigated an application-specific CNN using a custom ensemble of features designed based on characteristics of the ECG during atrial fibrillation (AF) to reduce inappropriate AF detections in implantable cardiac monitors (ICMs).

Methods

An ensemble of features was developed and combined to form an input signal for the CNN. The features were based on the morphological characteristics of AF, incoherence of RR intervals, and the fact that AF begets more AF. A custom CNN model and the RESNET18 model were trained using ICM-detected AF episodes that were adjudicated to be true AF or false detections. The trained models were evaluated using a test dataset from independent patients.

Results

The training and validation datasets consisted of 31,757 AF episodes (2516 patients) and 28,506 false episodes (2126 patients). The validation set (20% randomly chosen episodes of each type) had an area under the curve of 0.996 for custom CNN (0.993 for RESNET18). Thresholds were chosen to obtain a relative sensitivity and specificity of 99.2% and 92.8%, respectively (99.2% and 87.9% for RESNET18, respectively). The performance in the independent test set (4546 AF episodes from 418 patients; 5384 false episodes from 605 patients) showed an area under the curve of 0.993 (0.991 for RESNET18) and relative sensitivity and specificity of 98.7% and 91.4%, respectively, at chosen thresholds (98.9% and 88.2% for RESNET18, respectively).

Conclusion

An ensemble of features-based CNNs was developed that reduced inappropriate AF detection in ICMs by over 90% while preserving sensitivity.

Atrial fibrillation: focus on monitoring strategies after cryptogenic stroke

Atrial fibrillation (AF) is responsible for up to one-third of ischemic strokes, with stroke potentially being the first manifestation of a previously undetected AF. Given the efficacy of oral anticoagulants in preventing AF-related ischemic events, searching for unknown AF after stroke requires a comprehensive diagnostic workup. Prospective data have demonstrated the benefits of long-term cardiac monitoring to identify AF in association with cryptogenic stroke, as most strokes are presumed to result from AF. However, strategies of empirical anticoagulation using oral anticoagulants following cryptogenic stroke failed to improve outcomes. We herein summarize contemporary evidence and knowledge gaps on searching for AF after a stroke and the potential secondary prevention strategies to prevent further recurrences.

Utility of a novel wearable electrode embedded in an undershirt for electrocardiogram monitoring and detection of arrhythmias

Background

A 12-lead electrocardiogram (ECG) and Holter ECG have been established as gold standards for detection of arrhythmias. Recently, wearable ECG monitoring devices have been available. Our purpose of the present study was to investigate whether a novel wearable electrode embedded in an undershirt is useful for ECG monitoring and detection of arrhythmias.

Methods

We studied 31 consecutive hospitalized patients who underwent catheter ablation of tachyarrhythmias. Patients equipped a wearable electrode and a lead CM5 of Holter ECG simultaneously, and total heart beats, maximum heart rate (HR), mean HR, minimum HR, detections of arrhythmias, such as atrial fibrillation, non-sustained ventricular tachycardia, and premature ventricular contractions (Lown’s grade >II), were compared between the two methods using a Holter ECG analysis software.

Results

Median recording time of ECG by wearable electrodes was 12.6 hours. Strong correlations between the two methods were observed in total heart beats (R = 0.999, P <0.001), maximum HR (R = 0.997, P <0.001), mean HR (R = 0.999, P <0.001), minimum HR (R = 0.989, P <0.001) and QRS duration (R = 0.900, P <0.001). Bland-Altman analysis showed excellent concordance between each parameter measured by two methods. In addition, the detection of atrial fibrillation (nine events), non-sustained ventricular tachycardia (two events), and premature ventricular contractions of Lown’s grade >II (five events) were concordant in two methods. In addition, there were no significant difference in parameters of time-domain and frequency-domain analyses of heart rate variability between the two methods.

Conclusions

The usefulness of a novel electrode embedded in an undershirt is equivalent to that of a Holter ECG in monitoring the ECG and detection of arrythmias.

Artificial intelligence augments detection accuracy of cardiac insertable cardiac monitors: Results from a pilot prospective observational study

Background

Insertable cardiac monitors (ICMs) are indicated for long-term monitoring of patients with unexplained syncope or who are at risk for cardiac arrhythmias. The volume of ICM-transmitted information may result in long data review times to identify true and clinically relevant arrhythmias.

Objective

The purpose of this study was to evaluate whether artificial intelligence (AI) may improve ICM detection accuracy.

Methods

We performed a retrospective analysis of consecutive patients implanted with the Confirm Rx^TM ICM (Abbott) and followed in a prospective observational study. This device continuously monitors subcutaneous electrocardiograms (SECGs) and transmits to clinicians information about detected arrhythmias and patient-activated symptomatic episodes. All SECGs were classified by expert electrophysiologists and by the Willem^TM AI algorithm (IDOVEN).

Results

During mean follow-up of 23 months, of 20 ICM patients (mean age 68 ± 12 years; 50% women), 19 had 2261 SECGs recordings associated with cardiac arrhythmia detections or patient symptoms. True arrhythmias occurred in 11 patients: asystoles in 2, bradycardias in 3, ventricular tachycardias in 4, and atrial tachyarrhythmias (atrial tachycardia/atrial fibrillation [AT/AF]) in 10; with 6 patients having >1 arrhythmia type. AI algorithm overall accuracy for arrhythmia classification was 95.4%, with 97.19% sensitivity, 94.52% specificity, 89.74% positive predictive value, and 98.55% negative predictive value. Application of AI would have reduced the number of false-positive results by 98.0% overall: 94.0% for AT/AF, 87.5% for ventricular tachycardia, 99.5% for bradycardia, and 98.8% for asystole.

Conclusion

Application of AI to ICM-detected episodes is associated with high classification accuracy and may significantly reduce health care staff workload by triaging ICM data.

Prediction of occult atrial fibrillation in patients after cryptogenic stroke and transient ischaemic attack: PROACTIA

AIMS

Studies with implantable cardiac monitors (ICMs) show that one-third of patients with cryptogenic stroke/transient ischaemic attack (TIA) have episodes of subclinical atrial fibrillation (SCAF) and benefit switching from antiplatelet- to anticoagulant therapy. However, ICMs are costly and resource demanding. We aimed to build a score based on participant's baseline characteristics that could assess individual risk of SCAF.

METHODS AND RESULTS

In a prospective study, 236 eligible patients with a final diagnosis of cryptogenic stroke/TIA had an ICM implantated during the index hospitalization. Pre-specified evaluated variables were: CHA2DS2-VASc, P-wave duration, P-wave morphology, premature atrial beats (PAC)/24 h, supraventricular tachycardia/24 h, left atrial end-systolic volume index (LAVI), Troponin-T, NT-proBNP, and D-dimer. SCAF was detected in 84 patients (36%). All pre-specified variables were significantly associated with SCAF detection in univariate analysis. P-wave duration, followed by PAC/24 h, NT-proBNP, and LAVI, had the largest ratio of SCAF prevalence between its upper and lower quartiles (3.3, vs. 3.2, vs. 3.1 vs. 2.8, respectively). However, in a multivariate analysis, only PAC/24t, P-wave duration, P-wave morphology, and LAVIs remained significant predictors and were included in the PROACTIA score. Subclinical atrial fibrillation prevalence was 75% in the highest vs. 10% in the lowest quartile of the PROACTIA score with a 10-fold higher number of patients with an atrial fibrillation burden >6 h in the highest vs. the lowest quartile.

CONCLUSION

The PROACTIA score can identify patients with cryptogenic stroke/TIA at risk of subsequent SCAF detection. The large difference in SCAF prevalence between groups may provide a basis for future tailored therapy.

CLINICAL TRIAL REGISTRATION

Clinical Trial Registration: ClinicalTrials.gov; NCT02725944.

Impact of Atrial Fibrillation Ablation on Activity Minutes in Patients With Cardiac Implantable Electronic Devices

BACKGROUND

Impaired quality of life due to atrial fibrillation (AF), which often includes decreased activity level, is an indication for ablation. However, the impact of ablation for AF on activity is poorly understood.

OBJECTIVE

To assess the impact of ablation on activity minutes per day using continuous accelerometer data from cardiac implantable electronic devices (CIED).

METHODS

Using the Optum® Health Record dataset (2007-2019) linked with the Medtronic CareLink® database, we identified patients who had a CIED with AF detection and accelerometer capabilities. Patients with a device that transmitted heart rhythm and activity data ≥ 3 months prior to- and ≥ 12 months following ablation were included in analysis. The associations between ablation and activity minutes were assessed in each CIED type.

RESULTS

Of 4297 eligible patients who underwent AF ablation, 409 (9.5%) (65% Male, 67.3±9.8 years, 64% paroxysmal AF) were included in analysis. The average AF burden and activity minutes per day pre-ablation were 30.9±37.4% and 175±99 minutes, respectively. Following ablation, relative AF burden decreased by 75.1±53.2% (p<0.001). There was no change in activity minutes per day following ablation in the entire cohort (average change: -0.10±36.2 min, p=0.96). There were also no clinically significant changes in activity minutes post-ablation in subgroups based on CIED, season of ablation, quartile of AF burden change, and quartile of age at the time of ablation.

CONCLUSION

There were no clinically significant changes in activity minutes per day in patients with CIEDs following ablation for AF.

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.

Reflections on the usefulness of today's atrial fibrillation ablation procedure endpoints and patient-reported outcomes

The improvement of Patient-reported outcomes, such as health-related quality of life, is the main indication for atrial fibrillation ablation. Despite this guideline derived indication for an AF ablation procedure the current standardized primary endpoint in AF ablation trials is still rhythm-related, and primarily a 30-second long AF episode. The review presents reflections on the non-rational arguments of using rhythm related endpoints rather than Patient-reported outcomes in AF ablation procedure trials despite the mismatch between many of the rhythm related variables and symptoms. Arguments for health-related quality of life as the most optimal primary endpoint in clinical trials are presented while atrial fibrillation burden is presented as the most optimal electrical complementary endpoint, apart from being the major variable in mechanistic trials.

Atrial fibrillation signatures on intracardiac electrograms identified by deep learning

BACKGROUND

Automatic detection of atrial fibrillation (AF) by cardiac devices is increasingly common yet suboptimally groups AF, flutter or tachycardia (AT) together as 'high rate events'. This may delay or misdirect therapy.

OBJECTIVE

We hypothesized that deep learning (DL) can accurately classify AF from AT by revealing electrogram (EGM) signatures.

METHODS

We studied 86 patients in whom the diagnosis of AF or AT was established at electrophysiological study (25 female, 65 ± 11 years). Custom DL architectures were trained to identify AF using N = 29,340 unipolar and N = 23,760 bipolar EGM segments. We compared DL to traditional classifiers based on rate or regularity. We explained DL using computer models to assess the impact of controlled variations in shape, rate and timing on AF/AT classification in 246,067 EGMs reconstructed from clinical data.

RESULTS

DL identified AF with AUC of 0.97 ± 0.04 (unipolar) and 0.92 ± 0.09 (bipolar). Rule-based classifiers misclassified ∼10-12% of cases. DL classification was explained by regularity in EGM shape (13%) or timing (26%), and rate (60%; p < 0.001), and also by a set of unipolar EGM shapes that classified as AF independent of rate or regularity. Overall, the optimal AF 'fingerprint' comprised these specific EGM shapes, >15% timing variation, <0.48 correlation in beat-to-beat EGM shapes and CL < 190 ms (p < 0.001).

CONCLUSIONS

Deep learning of intracardiac EGMs can identify AF or AT via signatures of rate, regularity in timing or shape, and specific EGM shapes. Future work should examine if these signatures differ between different clinical subpopulations with AF.

Programming Optimization in Implantable Cardiac Monitors to Reduce False-Positive Arrhythmia Alerts: A Call for Research

No studies have investigated whether optimizing implantable cardiac monitors (ICM) programming can reduce false-positive (FP) alerts. We identified patients implanted with an ICM (BIOMONITOR III) who had more than 10 FP alerts in a 1-month retrospective period. Uniform adjustments of settings were performed based on the mechanism of FP triggers and assessed at 1 month. Eight patients (mean age 57.5 ± 23.2 years; 37% female) were enrolled. In 4 patients, FPs were caused by undersensing of low-amplitude premature ventricular contractions (PVCs). No further false bradycardia was observed with a more aggressive decay of the dynamic sensing threshold. Furthermore, false atrial fibrillation (AF) alerts decreased in 2 of 3 patients. Two patients had undersensing of R waves after high-amplitude PVCs; false bradycardia episodes disappeared or were significantly reduced by limiting the initial value of the sensing threshold. Finally, the presence of atrial ectopic activity or irregular sinus rhythm generated false alerts of AF in 2 patients that were reduced by increasing the R-R variability limit and the confirmation time. In conclusion, adjustments to nominal settings can reduce the number of FP episodes in ICM patients. More research is needed to provide practical recommendations and assess the value of extended ICM programmability.

Implantable Loop Recorder Monitoring and the Incidence of Previously Unrecognized Atrial Fibrillation in Patients on Hemodialysis

INTRODUCTION

Atrial fibrillation (AF) is common in patients with kidney failure on hemodialysis (KF-HD). We determined both AF incidence and burden in patients with KF-HD using implantable loop recorder (ILR) monitoring.

METHODS

Patients with KF-HD were enrolled and received an ILR. In 6 monitoring months, the incidence of AF events lasting ≥6 minutes was captured. Demographic, clinical, and dialysis characteristics were collected, and associations with incident AF were estimated using negative binomial regression models and expressed as incidence rate ratios and 95% CIs.

RESULTS

We enrolled 66 patients with KF-HD (mean age = 56 years, 70% male); 59 (90%) were without previously diagnosed AF. AF lasting ≥6 minutes was detected in 18 of 59 subjects (31%) without previously diagnosed AF and in 5 of 7 subjects (71%) with a previous AF diagnosis. Among the 23 with detected AF, episodes were present on 16% of patient days. Although 14 of 23 patients (61%) had AF on <5% of monitored days, the average duration of AF episodes was <1 hour in 13 of 23 patients (52%). Among patients with AF ≥6 minutes, 19 of 23 (83%) had a CHA2DS2-VASc score ≥2. When investigating individual HD parameters, higher dialysate calcium (>2.5 vs. 2.5 mEq/l: incidence rate ratio = 0.62; 95% CI, 0.48-0.80) was associated with lower AF risk whereas higher dialysate bicarbonate concentrations (>35 vs. 35 mEq/l: incidence rate ratio = 3.18; 95% CI, 1.13-8.94) were associated with higher AF risk.

CONCLUSION

New AF was detected in approximately one-third of patients with KF-HD. AF affects a substantial proportion of patient days and may be an underappreciated cause of stroke in KF-HD.

Critical appraisal of technologies to assess electrical activity during atrial fibrillation: a position paper from the European Heart Rhythm Association and European Society of Cardiology Working Group on eCardiology in collaboration with the Heart Rhythm Society, Asia Pacific Heart Rhythm Society, Latin American Heart Rhythm Society and Computing in Cardiology

We aim to provide a critical appraisal of basic concepts underlying signal recording and processing technologies applied for (i) atrial fibrillation (AF) mapping to unravel AF mechanisms and/or identifying target sites for AF therapy and (ii) AF detection, to optimize usage of technologies, stimulate research aimed at closing knowledge gaps, and developing ideal AF recording and processing technologies. Recording and processing techniques for assessment of electrical activity during AF essential for diagnosis and guiding ablative therapy including body surface electrocardiograms (ECG) and endo- or epicardial electrograms (EGM) are evaluated. Discussion of (i) differences in uni-, bi-, and multi-polar (omnipolar/Laplacian) recording modes, (ii) impact of recording technologies on EGM morphology, (iii) global or local mapping using various types of EGM involving signal processing techniques including isochronal-, voltage- fractionation-, dipole density-, and rotor mapping, enabling derivation of parameters like atrial rate, entropy, conduction velocity/direction, (iv) value of epicardial and optical mapping, (v) AF detection by cardiac implantable electronic devices containing various detection algorithms applicable to stored EGMs, (vi) contribution of machine learning (ML) to further improvement of signals processing technologies. Recording and processing of EGM (or ECG) are the cornerstones of (body surface) mapping of AF. Currently available AF recording and processing technologies are mainly restricted to specific applications or have technological limitations. Improvements in AF mapping by obtaining highest fidelity source signals (e.g. catheter-electrode combinations) for signal processing (e.g. filtering, digitization, and noise elimination) is of utmost importance. Novel acquisition instruments (multi-polar catheters combined with improved physical modelling and ML techniques) will enable enhanced and automated interpretation of EGM recordings in the near future.

Automatic Mobile Health Arrhythmia Monitoring for the Detection of Atrial Fibrillation: Prospective Feasibility, Accuracy, and User Experience Study

Background

Atrial fibrillation (AF) is the most common tachyarrhythmia and associated with a risk of stroke. The detection and diagnosis of AF represent a major clinical challenge due to AF’s asymptomatic and intermittent nature. Novel consumer-grade mobile health (mHealth) products with automatic arrhythmia detection could be an option for long-term electrocardiogram (ECG)-based rhythm monitoring and AF detection.

Objective

We evaluated the feasibility and accuracy of a wearable automated mHealth arrhythmia monitoring system, including a consumer-grade, single-lead heart rate belt ECG device (heart belt), a mobile phone application, and a cloud service with an artificial intelligence (AI) arrhythmia detection algorithm for AF detection. The specific aim of this proof-of-concept study was to test the feasibility of the entire sequence of operations from ECG recording to AI arrhythmia analysis and ultimately to final AF detection.

Methods

Patients (n=159) with an AF (n=73) or sinus rhythm (n=86) were recruited from the emergency department. A single-lead heart belt ECG was recorded for 24 hours. Simultaneously registered 3-lead ECGs (Holter) served as the gold standard for the final rhythm diagnostics and as a reference device in a user experience survey with patients over 65 years of age (high-risk group).

Results

The heart belt provided a high-quality ECG recording for visual interpretation resulting in 100% accuracy, sensitivity, and specificity of AF detection. The accuracy of AF detection with the automatic AI arrhythmia detection from the heart belt ECG recording was also high (97.5%), and the sensitivity and specificity were 100% and 95.4%, respectively. The correlation between the automatic estimated AF burden and the true AF burden from Holter recording was >0.99 with a mean burden error of 0.05 (SD 0.26) hours. The heart belt demonstrated good user experience and did not significantly interfere with the patient’s daily activities. The patients preferred the heart belt over Holter ECG for rhythm monitoring (85/110, 77% heart belt vs 77/109, 71% Holter, P=.049).

Conclusions

A consumer-grade, single-lead ECG heart belt provided good-quality ECG for rhythm diagnosis. The mHealth arrhythmia monitoring system, consisting of heart-belt ECG, a mobile phone application, and an automated AF detection achieved AF detection with high accuracy, sensitivity, and specificity. In addition, the mHealth arrhythmia monitoring system showed good user experience.

Trial Registration

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

The predictive role of early recurrences of atrial arrhythmias after pulmonary vein cryoballoon ablation. Is blanking period an outdated concept? Insights from 12-month continuous cardiac monitoring

Background

Early recurrences of atrial arrhythmias (ERAA) after atrial fibrillation (AF) catheter ablation do not predict procedural failure. A well-demarcated homogeneous lesion delivered by cryoballoon is less arrhythmogenic, and the recommended three-months blanking period may not refer to cryoballoon ablation (CBA).

Objective

We aimed to evaluate the predictive role of ERAA after second-generation CBA using an implantable loop recorder.

Methods

This prospective observational study enrolled 100 patients (58 males, median age 58) with paroxysmal/persistent AF undergoing pulmonary vein (PV) CBA using second-generation cryoballoon with simultaneous ECG loop recorder implantation. The duration of follow-up was 12 months, with scheduled visits at 3, 6 and 12 months.

Results

99 patients from 100 completed the 12-month follow-up period. ERAA occurred in 31.3 % of patients. 83.9 % of patients with ERAA also developed late recurrences. The 12-month freedom from AF in patients with ERAA was significantly lower than in those without ERAA (p < 0.0001). Non-paroxysmal AF and longer arrhythmia history were associated with increased risk of both early (HR 3.27; 95 % CI 1.32–8.08; p = 0.010 and HR 1.0147; 95 % CI 1.008–1.086; p = 0.015, respectively) and late recurrences (HR 3.89; 95 % CI 1.67–9.04; p = 0.002 and HR 1.0142; 95 % CI 1.007–1.078; p = 0.019, respectively) of AF. ERAA were another predictor for procedural failure (HR 15.2; 95 % CI (6.42–35.99; p = 0.019).

Conclusions

ERAA occurred in the third of the patients after PV second-generation CBA and are strongly associated with procedural failure. Longer duration of AF history and persistent AF are independent predictors of AF’s early and late recurrence.

Detection of subclinical atrial fibrillation after cryptogenic stroke using implantable cardiac monitors

BACKGROUND

Implantable cardiac monitor (ICM) revealed subclinical atrial fibrillation (SCAF) in up to 30% of cryptogenic stroke (CS) patients in randomized trials. However, real world data are limited.

OBJECTIVES

We investigated SCAF occurrence, treatments, clinical outcomes and predictors of SCAF in a multicenter real-world population subjected to ICM after CS.

METHODS

From September 2016 to November 2019, 20 Italian centers collected data of consecutive patients receiving ICM after CS and followed with remote and outpatient follow-up according to clinical practice. All device-detected AF events were confirmed by the cardiologist to diagnose SCAF.

RESULTS

ICM was implanted in 334 CS patients (mean age±SD 67.4±11.5 years, 129 (38.6%) females, 242 (76.1%) with CHA₂DS₂-VASC score≥4). During a follow-up of 23.6 (IQR 14.6-31.5) months, SCAF was diagnosed in 92 (27.5%) patients. First episode was asymptomatic in 81 (88.1%). SCAF daily burden ≥5 minutes was 22.0%, 24.1% and 31.5% at 6, 12, and 24 months after ICM implantation. Median time to first day with AF was 60 (IQR 18-140) days. Female gender, age>69 years, PR interval>160 ms and cortical-subcortical infarct type at enrolment were independently associated with an increased risk of SCAF.

CONCLUSIONS

In a real-world population, ICM detected SCAF in more than a quarter of CS patients. This experience confirms the relevance of implanting CS patients, for maximizing the possibilities to detect AF, following failure of Holter monitoring, according to guidelines. However, there is need to demonstrate that shift to oral anticoagulation following SCAF detection is associated with reduced risk of recurrent stroke.

Clinical Significance of the Head-Up Tilt Test in Improving Prognosis in Patients with Possible Neurally Mediated Syncope

Simple Summary

Several diseases can cause syncope, which is commonly known as fainting; however, syncope triggered by a reflex mechanism, also termed neurally mediated syncope (NMS), is one of the most common forms. While NMS is considered a benign disease, it can cause critical clinical events, such as severe trauma due to syncope. The head-up tilt test (HUTT) is one of the modalities for the diagnosis of NMS. The clinical significance of HUTT in the prognosis of NMS, such as recurrence rate of syncope and mortality, are still to be elucidated. This research aimed to clarify the value of HUTT for the diagnosis of NMS, and to investigate the prognosis of patients with NMS by analyzing the data of 101 patients with syncope and their close long-term (four years at the longest) follow-up. Furthermore, as insertable cardiac monitors (ICMs) are considered effective in patients with syncope, this study also aimed to evaluate the usefulness of ICM in patients with negative HUTT results. Finally, our research contributes to the improvement of the clinical management for patients with syncope.

Abstract

Syncope is commonly encountered in daily clinical practice. Depending on its etiology (benign or life-threatening conditions or environmental triggers), syncope can be neurally mediated (reflex), cardiac, or orthostatic. Furthermore, neurologic disease can cause symptoms that mimic syncope. However, there is limited research on neurally mediated syncope (NMS), which is considered a benign disorder, and close follow-ups are rarely performed. NMS can cause serious clinical events, including severe trauma and car accidents. The head-up tilt test (HUTT) is the gold standard for diagnosing NMS; however, its clinical significance remains unknown, and its relevance to NMS prognosis requires further research. This retrospective study aimed to assess the clinical significance of the HUTT for NMS. We reviewed the charts of 101 patients who underwent HUTT at Tokai University Hospital in Japan between January 2016 and March 2019. During the HUTT, 72 patients (69.2%) experienced syncope. Patients were followed up for 886.1 ± 457.7 days (interquartile range: 518–1293 days). The syncope recurrence rate was 16.9%; however, no significant difference was observed between the two groups (HUTT positive vs. negative) (13.8% vs. 18.1%, p = 0.772). Four of 29 (13.9%) and two of 72 (2.8%) patients in the negative and positive HUTT groups, respectively, experienced cardiac events (p = 0.019). Negative HUTT results may assist in anticipating unexpected clinical events within a few years. A negative HUTT result may allow us to reconsider the NMS diagnosis based on clinical information. Close outpatient follow-up of patients with negative HUTT results is warranted.

Implantable loop recorder for augmenting detection of new-onset atrial fibrillation after typical atrial flutter ablation

Background

Patients with typical atrial flutter (AFL) undergoing successful cavotricuspid isthmus ablation remain at risk for future development of new-onset atrial fibrillation (AF). Conventional monitoring (CM) techniques have shown AF incidence rates of 18%–50% in these patients.

Objectives

To evaluate whether continuous monitoring using implantable loop recorders (ILRs) would enhance AF detection in this patient population.

Methods

Veteran patients undergoing AFL ablation between 2002 and 2019 who completed at least 6 months of follow-up after the ablation procedure were included. We compared new-onset AF detection between those who underwent CM and those who received ILRs immediately following AFL ablation.

Results

A total of 217 patients (age: 66 ± 9 years; all male) participated. CM was used in 172 (79%) and ILR in 45 (21%) patients. Median follow-up duration after ablation was 4.1 years. Seventy-nine patients (36%) developed new-onset AF, which was detected by CM in 51 and ILR in 28 (30% vs 62%, respectively, P < .001). AF detection occurred at 7.7 months (IQR: 4.7–17.5) after AFL ablation in the ILR group vs 41 months (IQR: 23–72) in the CM group (P < .001). Eleven patients (5%) experienced cerebrovascular events (all in the CM group) and only 4 of these patients (36%) were on long-term anticoagulation.

Conclusion

Patients undergoing AFL ablation remain at an increased risk of developing new-onset AF, which is detected sooner and more frequently by ILR than by CM. Improving AF detection may allow optimization of rhythm management strategies and anticoagulation in this patient population.

Cost-effectiveness of insertable cardiac monitors for diagnosis of atrial fibrillation in cryptogenic stroke in Australia

INTRODUCTION

Detection of atrial fibrillation (AF) is required to initiate oral anticoagulation (OAC) after cryptogenic stroke (CS). However, paroxysmal AF can be difficult to diagnose with short term cardiac monitoring. Taking an Australian payer perspective, we evaluated whether long-term continuous monitoring for 3 years with an insertable cardiac monitor (ICM) is cost-effective for preventing recurrent stroke in patients with CS.

METHODS

A lifetime Markov model was developed to simulate the follow-up of patients, comparing long-term continuous monitoring with an ICM to monitoring by conventional care. We used a linked evidence approach to estimate the rates of recurrent stroke when AF detection leads to initiation of OAC, as detected using ICM during the lifetime of the device or as detected using usual care. All diagnostic and patient management costs were modeled. Other model inputs were determined by literature review. Probabilistic sensitivity analysis (PSA) was undertaken to explore the effect of parameter uncertainty according to CHADS2 score and OAC treatment effect.

RESULTS

In the base-case analysis, the model predicted an incremental cost-effectiveness ratio (ICER) of A$29 570 per quality-adjusted life year (QALY). Among CHADS2 subgroups analyses, the ICER ranged from A$26 342/QALY (CHADS2 = 6) to A$42 967/QALY (CHADS2 = 2). PSA suggested that the probabilities of ICM strategy being cost-effective were 53.4% and 78.7%, at thresholds of $30 000 (highly cost-effective) and $50 000 per QALY (cost-effective), respectively.

CONCLUSIONS

Long-term continuous monitoring with an ICM is a cost-effective intervention to prevent recurrent stroke in patients following CS in the Australian context.

Comparison of postprocedural new-onset atrial fibrillation between transcatheter and surgical aortic valve replacement: A systematic review and meta-analysis based on 16 randomized controlled trials

BACKGROUND

Presently, transcatheter aortic valve replacement (TAVR) as an effective and convenient intervention has been adopted extensively for patients with severe aortic disease. However, after surgical aortic valve replacement (SAVR) and TAVR, the incidence of new-onset atrial fibrillation (NOAF) is prevalently found. This meta-analysis was designed to comprehensively compare the incidence of NOAF at different times after TAVR and SAVR for patients with severe aortic disease.

METHODS

A systematic search of PubMed, Embase, Cochrane Library, and Web of Science up to October 1, 2020 was conducted for relevant studies that comparing TAVR and SAVR in the treatment of severe aortic disease. The primary outcomes were the incidence of NOAF with early, midterm and long term follow-up. The secondary outcomes included permanent pacemaker (PM) implantation, myocardial infarction (MI), cardiogenic shock, as well as mortality and other complications. Two reviewers assessed trial quality and extracted the data independently. All statistical analyses were performed using the standard statistical procedures provided in Review Manager 5.2.

RESULTS

A total of 16 studies including 13,310 patients were identified. The pooled results indicated that, compared with SAVR, TAVR experienced a significantly lower incidence of 30-day/in-hospital, 1-year, 2-year, and 5-year NOAF, with pooled risk ratios (RRs) of 0.31 (95% confidence interval [CI] 0.23-0.41; 5725 pts), 0.30 (95% CI 0.24-0.39; 6321 pts), 0.48 (95% CI 0.38-0.61; 3441 pts), and 0.45 (95% CI 0.37-0.55; 2268 pts) respectively. In addition, TAVR showed lower incidence of MI (RR 0.62; 95% CI 0.40-0.97) and cardiogenic shock (RR 0.34; 95% CI 0.19-0.59), but higher incidence of permanent PM (RR 3.16; 95% CI 1.61-6.21) and major vascular complications (RR 2.22; 95% CI 1.14-4.32) at 30-day/in-hospital. At 1- and 2-year after procedure, compared with SAVR, TAVR experienced a significantly higher incidence of neurological events, transient ischemic attacks (TIA), permanent PM, and major vascular complications, respectively. At 5-year after procedure, compared with SAVR, TAVR experienced a significantly higher incidence of TIA and re-intervention respectively. There was no difference in 30-day, 1-year, 2-year, and 5-year all-cause or cardiovascular mortality as well as stroke between TAVR and SAVR.

CONCLUSIONS

Our analysis showed that TAVR was superior to SAVR in decreasing the both short and long term postprocedural NOAF. TAVR was equal to SAVR in early, midterm and long term mortality. In addition, TAVR showed lower incidence of 30-day/in-hospital MI and cardiogenic shock after procedure. However, pooled results showed that TAVR was inferior to SAVR in reducing permanent pacemaker implantation, neurological events, TIA, major vascular complications, and re-intervention.

Atrial fibrillation recurrence and spontaneous conversion to sinus rhythm after cardiac surgery: Insights from 426 patients with continuous rhythm monitoring

INTRODUCTION

Cardiac surgery may influence occurrence and persistence of atrial fibrillation (AF). In patients with a history of cardiac surgery and postoperative pacemaker or implantable cardioverter defibrillator implantation we attempted to quantify AF characteristics and investigate factors that influence AF recurrence.

METHODS

In 426 patients (319 male; age: 73 SD: 9 years) with a history of cardiac surgery (364 CABG; 69 mitral valve; 57 aortic valve and 59 combination procedures) the heart rhythm history (mean: 351 days SD: 54 days) was reconstructed and investigated for AF recurrence patterns.

RESULTS

AF developed and subsequently recurred in 75% of patients (n = 320). The mean AF burden in these patients was 0.21 (21% of the total observed time spent in AF) and 4085 episodes of AF were observed and analyzed. AF episodes spontaneously terminated within 24 h (n = 2509), 48 h (n = 700), 72 h (n = 279), and 1 week (n = 31). The probability of spontaneous conversion to sinus rhythm (SR) decreased with time spent in AF and plateaued after approximately 7 days. Patient age, LVEF and presence of coronary artery disease significantly influenced the probability of spontaneous conversion to SR. Type of cardiac surgery also significantly influenced AF episode characteristics.

CONCLUSION

AF episodes are common in patients with a history of cardiac surgery. Spontaneous conversion to SR diminishes with increasing time spent in AF and is influenced by AF characteristics and several patient-related factors. Continuous monitoring can provide detailed information about AF recurrence that may immensely improve our understanding and influence the clinical management of AF.

The RITHMI study: diagnostic ability of a heart rhythm monitor for automatic detection of atrial fibrillation

INTRODUCTION AND OBJECTIVES

Early detection of atrial fibrillation (AF) is a priority to reduce embolic events by initiating oral anticoagulation therapy. The aim of this study was to evaluate the diagnostic ability of a wrist device designed for automatic AF detection.

METHODS

RITHMI is a prospective, comparative, observational study that included 167 patients referred to a cardiology outpatient clinic for a general consultation or for electrical cardioversion. The study evaluated the ability of a wrist monitor that uses a photoplethysmography (PPG) signal and an electrocardiographic lead to automatically detect AF compared with diagnosis established by 2 cardiologists using the 12-lead electrocardiogram.

RESULTS

The AF detection algorithm based on the PPG signal had a sensitivity of 91% and a specificity of 96% (diagnostic accuracy: 93%). The automatic algorithm based on the electrocardiographic signal had a sensitivity of 94% and a specificity of 96% (diagnostic accuracy: 95%). The 2 algorithms concurred in the diagnosis in 96% of the cases. Overall, the monitor had a sensitivity and specificity of 95% (diagnostic accuracy: 95% and Kappa index: 0.98).

CONCLUSIONS

This study shows that automatic AF detection through the use of a heart rhythm monitor incorporating sensors and algorithms that analyze the PPG signal and the electrocardiographic signal corresponding to lead I is feasible and has high diagnostic accuracy.

Subcutaneous cardiac rhythm monitors: state of the art review

Introduction: Subcutaneous cardiac rhythm monitors (SCRMs) provide continuous ambulatory electrocardiographic monitoring for surveillance of known and identification of infrequent arrhythmias. SCRMs have proven to be helpful for the evaluation of unexplained symptoms and correlation with intermittent cardiac arrhythmias. Successful functioning of SCRM is dependent on accurate detection and successful transmission of the data to the device clinic. As the use of SCRM is steadily increasing, the amount of data that requires timely adjudication requires substantial resources. Newer algorithms for accurate detection and modified workflow systems have been proposed by physicians and the manufacturers to circumvent the issue of data deluge.Areas covered: This paper provides an overview of the various aspects of ambulatory rhythm monitoring with SCRMs including indications, implantation techniques, programming strategies, troubleshooting for issue of false positive and intermittent connectivity and strategies to circumvent data deluge.Expert opinion: SCRM is an invaluable technology for prolonged rhythm monitoring. The clinical benefits from SCRM hinge on accurate arrhythmia detection, reliable transmission of the data and timely adjudication for possible intervention. Further improvement in SCRM technology is needed to minimize false-positive detection, improve connectivity to the central web-based server, and devise strategies to minimize data deluge.

Heart Rate Variability and Clinical Features as Predictors of Atrial Fibrillation Recurrence After Catheter Ablation: A Pilot Study

Single-procedure catheter ablation success rate is as low as 52% in atrial fibrillation (AF) patients. This study evaluated the feasibility of using clinical data and heart rate variability (HRV) features extracted from an implantable cardiac monitor (ICM) to predict recurrences in patients prior to undergoing catheter ablation for AF. HRV-derived features were extracted from the 500 beats preceding the AF onset and from the first 2 min of the last AF episode recorded by an ICM of 74 patients (67% male; 57 ± 12 years; 26% non-paroxysmal AF; 57% AF recurrence) before undergoing their first AF catheter ablation. Two types of classification algorithm were studied to predict AF recurrence: single classifiers including support vector machines, classification and regression trees, and K-nearest neighbor classifiers as well as ensemble classifiers. The sequential forward floating search algorithm was used to select the optimum feature set for each classification method. The optimum weighted voting method, which used an optimum combination of the single classifiers, was the best overall classifier (accuracy = 0.82, sensitivity = 0.76, and specificity = 0.87). Clinical and HRV features can be used to predict rhythm outcome using an ensemble classifier which would enable a more effective pre-ablation patient triage that could reduce the economic and personal burden of the procedure by increasing the success rate of first catheter ablation.

Implantable cardiac monitors to detect atrial fibrillation after cryptogenic stroke: a systematic review and economic evaluation

BACKGROUND

Cryptogenic stroke is a stroke for which no cause is identified after standard diagnostic tests. Long-term implantable cardiac monitors may be better at diagnosing atrial fibrillation and provide an opportunity to reduce the risk of stroke recurrence with anticoagulants.

OBJECTIVES

The objectives were to assess the diagnostic test accuracy, clinical effectiveness and cost-effectiveness of three implantable monitors [BioMonitor 2-AF™ (Biotronik SE & Co. KG, Berlin, Germany), Confirm Rx™ (Abbott Laboratories, Lake Bluff, IL, USA) and Reveal LINQ™ (Medtronic plc, Minneapolis, MN, USA)] in patients who have had a cryptogenic stroke and for whom no atrial fibrillation is detected after 24 hours of external electrocardiographic monitoring.

DATA SOURCES

MEDLINE, EMBASE, The Cochrane Library, Database of Abstracts of Reviews of Effects and Health Technology Assessment databases were searched from inception until September 2018.

REVIEW METHODS

A systematic review was undertaken. Two reviewers agreed on studies for inclusion and performed quality assessment using the Cochrane Risk of Bias 2.0 tool. Results were discussed narratively because there were insufficient data for synthesis. A two-stage de novo economic model was developed: (1) a short-term patient flow model to identify cryptogenic stroke patients who have had atrial fibrillation detected and been prescribed anticoagulation treatment (rather than remaining on antiplatelet treatment) and (2) a long-term Markov model that captured the lifetime costs and benefits of patients on either anticoagulation or antiplatelet treatment.

RESULTS

One randomised controlled trial, Cryptogenic Stroke and underlying Atrial Fibrillation (CRYSTAL-AF) (Sanna T, Diener HC, Passman RS, Di Lazzaro V, Bernstein RA, Morillo CA, et al. Cryptogenic stroke and underlying atrial fibrillation. N Engl J Med 2014;370:2478-86), was identified, and no diagnostic test accuracy study was identified. The CRYSTAL-AF trial compared the Reveal™ XT (a Reveal LINQ predecessor) (Medtronic plc) monitor with standard of care monitoring. Twenty-six single-arm observational studies for the Reveal devices were also identified. The only data for BioMonitor 2-AF or Confirm Rx were from mixed population studies supplied by the companies. Atrial fibrillation detection in the CRYSTAL-AF trial was higher with the Reveal XT than with standard monitoring at all time points. By 36 months, atrial fibrillation was detected in 19% of patients with an implantable cardiac monitor and in 2.3% of patients receiving conventional follow-up. The 26 observational studies demonstrated that, even in a cryptogenic stroke population, atrial fibrillation detection rates are highly variable and most cases are asymptomatic; therefore, they probably would not have been picked up without an implantable cardiac monitor. Device-related adverse events, such as pain and infection, were low in all studies. The de novo economic model produced incremental cost effectiveness ratios comparing implantable cardiac monitors with standard of care monitoring to detect atrial fibrillation in cryptogenic stroke patients based on data for the Reveal XT device, which can be related to Reveal LINQ. The BioMonitor 2-AF and Confirm RX were included in the analysis by making a strong assumption of equivalence with Reveal LINQ. The results indicate that implantable cardiac monitors could be considered cost-effective at a £20,000-30,000 threshold. When each device is compared incrementally, BioMonitor 2-AF dominates Reveal LINQ and Confirm RX.

LIMITATIONS

The cost-effectiveness analysis for implantable cardiac monitors is based on a strong assumption of clinical equivalence and should be interpreted with caution.

CONCLUSIONS

All three implantable cardiac monitors could be considered cost-effective at a £20,000-30,000 threshold, compared with standard of care monitoring, for cryptogenic stroke patients with no atrial fibrillation detected after 24 hours of external electrocardiographic monitoring; however, further clinical studies are required to confirm their efficacy in cryptogenic stroke patients.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42018109216.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 24, No. 5. See the NIHR Journals Library website for further project information.

Atrial fibrillation burden, episode duration and frequency in relation to quality of life in patients with implantable cardiac monitor

•

Assessing the relationship between atrial fibrillation and quality of life.

•

Implantable loop recorders assessed rhythm continuously in symptomatic patients.

•

Atrial fibrillation burden, episode duration and frequency were included.

•

Higher atrial fibrillation burden was associated with impaired quality of life.

Aims

To assess the relation between atrial fibrillation (AF) characteristics and health-related quality of life (QoL), and which AF characteristic had the greatest impact.

Method

The AF characteristics burden (percentage of time in AF), duration and number of AF episodes/month were obtained from implantable cardiac monitors during the 2-month run-in period in 150 patients included in the randomized CAPTAF trial comparing early ablation and antiarrhythmic drug therapy. The QoL was measured by the General Health and Vitality dimensions of the 36-Item Short-Form Health Survey. AF characteristics were analysed continuously and in quartiles (Q1-Q4).

Results

Greater AF burden (p = 0.003) and longer AF episodes (p = 0.013) were associated with impaired QoL (Vitality score only) in simple linear regression analyses. Greater AF burden was, however, the only AF characteristic associated with lower QoL, when adjusted for sex, type of AF, hypertension, heart rate above 110 beats per minute during AF, and beta-blocker use in multiple linear regression analyses. For every 10% increase in AF burden there was a 1.34-point decrease of Vitality score (95% confidence interval (CI) −2.67 to −0.02, p = 0.047). The Vitality score was 12 points lower (95% CI −22.73 to −1.27, p = 0.03) in patients with an AF burden > 33% (Q4) versus those with < 0.45% (Q1), but only in unadjusted analysis.

Conclusion

AF burden had a greater impact on QoL (Vitality), than the duration and number of AF episodes, corroborating that AF burden may be the preferred outcome measure of rhythm control in trials including relatively healthy AF populations.

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.

Validation of Adhesive Single-Lead ECG Device Compared with Holter Monitoring among Non-Atrial Fibrillation Patients

There are few reports on head-to-head comparisons of electrocardiogram (ECG) monitoring between adhesive single-lead and Holter devices for arrhythmias other than atrial fibrillation (AF). This study aimed to compare 24 h ECG monitoring between the two devices in patients with general arrhythmia. Twenty-nine non-AF patients with a workup of pre-diagnosed arrhythmias or suspicious arrhythmic episodes were evaluated. Each participant wore both devices simultaneously, and the cardiac rhythm was monitored for 24 h. Selective ECG parameters were compared between the two devices. Two cardiologists independently compared the diagnoses of each device. The two most frequent monitoring indications were workup of premature atrial contractions (41.4%) and suspicious arrhythmia-related symptoms (37.9%). The single-lead device had a higher noise burden than the Holter device (0.04 ± 0.05% vs. 0.01 ± 0.01%, p = 0.024). The number of total QRS complexes, ventricular ectopic beats, and supraventricular ectopic beats showed an excellent degree of agreement between the two devices (intraclass correlation coefficients = 0.991, 1.000, and 0.987, respectively). In addition, the minimum/average/maximum heart rates showed an excellent degree of agreement. The two cardiologists made coherent diagnoses for all 29 participants using both monitoring methods. In conclusion, the single-lead adhesive device could be an acceptable alternative for ambulatory ECG monitoring in patients with general arrhythmia.

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

Supplemental Digital Content is available in the text.

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.

AI Filter Improves Positive Predictive Value of Atrial Fibrillation Detection by an Implantable Loop Recorder

OBJECTIVES

The purpose of this study was to determine whether incorporation of a 2-part artificial intelligence (AI) filter can improve the positive predictive value (PPV) of implantable loop recorder (ILR)-detected atrial fibrillation (AF) episodes.

BACKGROUND

ILRs can detect AF. Devices transmit data daily. It is critical that the PPV of ILR-detected AF events be high.

METHODS

In total, 1,500 AF episodes were evaluated from patients with cryptogenic stroke or known AF who underwent ILR implantation (Reveal LINQ, Medtronic, Minneapolis, Minnesota). Each episode was annotated as either a true or false AF episode to determine the PPV. A 2-part AI-based filter (Cardiologs, Paris, France) was then employed using a deep neural network (DNN) for AF detection. The impact of this DNN filter on the PPV was then assessed.

RESULTS

The cohort included 425 patients (mean age 69 ± 10 years; 62% men) with an ILR. After excluding 17 (1.1%) uninterpretable electrocardiograms, 800 (53.9%) of the remaining 1,483 episodes were manually adjudicated to represent an actual atrial arrhythmia. The PPV of ILR-detected AF episodes was 53.9% (95% confidence interval (CI): 51.4% to 56.5%), which increased to 74.5% (95% CI: 71.8% to 77.0%; p < 0.001) following use of the DNN filter. The increase was greatest for AF episodes ≤30 min. The most common reason for a false-positive AF event was premature atrial contractions. There was a negligible failure to identify true AF episodes.

CONCLUSIONS

Despite currently available ILR programming options, designed to maximize PPV in a given population, false-positive AF episodes remain common. An AI-based solution may significantly reduce the time and effort needed to adjudicate these false-positive events.

Levothyroxine dose and risk of atrial fibrillation: A nested case-control study

Contemporary data on the effect of levothyroxine dose on the occurrence of atrial fibrillation (AF) are lacking, particularly in the older population. Our objective was to determine the effect of cumulative levothyroxine exposure on risk of AF and ischemic stroke in older adults.

METHODS

We conducted a population-based observational study using health care databases from Ontario, Canada. We identified adults aged ≥66 years without a history of AF who filled at least 1 levothyroxine prescription between April 1, 2007, and March 31, 2016. Cases were defined as cohort members who had incident AF (emergency room visit or hospitalization) between the date of first levothyroxine prescription and December 31, 2017. Index date was date of AF. Cases were matched with up to 5 controls without AF on the same index date. Secondary outcome was ischemic stroke. Cumulative levothyroxine exposure was estimated based on total milligrams of levothyroxine dispensed in the year prior to index date. Using nested case-control approach, we compared outcomes between older adults who received high (≥0.125 mg/d), medium (0.075-0.125 mg/d), or low (0-0.075 mg/d) cumulative levothyroxine dose. We compared outcomes between current, recent past, and remote past levothyroxine use.

RESULTS

Of 183,360 older adults treated with levothyroxine (mean age 82 years; 72% women), 30,560 (16.1%) had an episode of AF. Compared to low levothyroxine exposure, high and medium exposure was associated with significantly increased risk of AF after adjustment for covariates (adjusted odds ratio [aOR] 1.29, 95% CI 1.23-1.35; aOR 1.08, 95% CI 1.04-1.11; respectively). No association was observed between levothyroxine exposure and ischemic stroke. Compared with current levothyroxine use, older adults with remote levothyroxine use had lower risks of AF (aOR 0.56, 95% CI 0.52-0.59) and ischemic stroke (aOR 0.61, 95% CI 0.56-0.67).

CONCLUSIONS

Among older persons treated with levothyroxine, levothyroxine at doses >0.075 mg/d is associated with an increased risk of AF compared to lower exposure.

2021 ISHNE/HRS/EHRA/APHRS Collaborative Statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals

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.

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.