Utility and limitations of long-term monitoring of atrial fibrillation using an implantable loop recorder

Early atrial fibrillation recurrence post catheter ablation: Analysis from insertable cardiac monitor in the era of optimized radiofrequency ablation

BACKGROUND

Early recurrence of atrial tachyarrhythmia (ERAT) is associated with ablation-induced proarrhythmogenic inflammation; however, existing studies used intermittent monitoring or nonoptimized radiofrequency (RF) applications (noncontiguous or without ablation index target value).

OBJECTIVE

The purpose of this study was to investigate the relationship between ERAT and late recurrence based on insertable cardiac monitor (ICM) data.

METHODS

We compiled data from Close-To-Cure and Close Maze studies, which enrolled patients who underwent RF ablation for paroxysmal or persistent atrial fibrillation (AF). All patients were implanted with an ICM 2-3 months before ablation.

RESULTS

We studied 165 patients (104 with paroxysmal AF, 61 with persistent AF). Over the 1-year follow-up period, 41 of the patients experienced late recurrence. The risk of late recurrence was higher in patients experiencing ERAT (hazard ratio [HR] 6.2; 95% confidence interval [CI] 3.0-13.0), with negative and positive predictive values of 90.5% and 45.7%, respectively. Median burden of AF during the blanking period was significantly higher in patients with late recurrence (7.9% [0.0%-99.6%]) compared to those without recurrence (0.0% [0.0%-6.0]; P <.001). For each 1% increase in AF burden during the blanking period, late recurrence increased by 4.6% (HR 1.046; 95% CI 1.035-1.059). The best tradeoff for predicting AF from ERAT occurrence was AF burden of 0.6% and last ERAT at 64 days.

CONCLUSION

In patients ablated for paroxysmal and persistent AF with a durable RF lesion set and implanted with a continuous monitoring device, postablation early AF recurrence and burden significantly predict late recurrence. The post-AF ablation blanking period should be reduced to 2 months.

Trajectory change of left ventricular ejection fraction after rhythm control for atrial fibrillation in heart failure

AIMS

Rhythm control therapy has shown great benefits for patients with atrial fibrillation (AF) and heart failure (HF). However, few studies have evaluated the effects of rhythm control on left ventricular ejection fraction (LVEF) trajectory across the whole HF spectrum. Our study explored the prevalence and predictors of LVEF trajectory changes and their prognostic implications following rhythm control.

METHODS AND RESULTS

Depending on the treatment strategy, the cohort was classified into rhythm and rate control groups. Alterations in HF types and LVEF trajectory were recorded. The observational endpoints were all-cause mortality and HF-related admission. Predictors of LVEF trajectory improvement in the rhythm control group were evaluated. After matching, the two groups had similar age [mean age (years): rhythm/rate control: 63.96/65.13] and gender [male: rhythm/rate control: n = 228 (55.6%)/233 (56.8%)]. Based on baseline LVEF measurement, the post-matched cohort had 490 HF with preserved ejection fraction (rhythm/rate control: n = 260/230; median LVEF: 58.00%/57.00%), 99 HF with mildly reduced ejection fraction (rhythm/rate control: n = 50/49; median LVEF: 45.00%/46.00%), and 231 HF with reduced ejection fraction (rhythm/rate control: n = 100/131; median LVEF: 32.50%/33.00%). Trajectory analysis found that the rhythm control group had a greater percentage of LVEF trajectory improvement than the rate control group [80 (53.3%) vs. 71 (39.4%), P = 0.012]. Cox regression analysis also showed that the rhythm control group was more likely to have improved LVEF trajectory compared with the rate control group {hazard ratio [HR] 1.671 [95% confidence interval (CI) 1.196-2.335], P = 0.003}. In the survival analysis, the rhythm control group experienced significant lower risks of all-cause mortality [HR 0.600 (95% CI 0.366-0.983), P = 0.043] and HF-related admission [HR 0.611 (95% CI 0.496-0.753), P < 0.001]. In the rhythm control subgroup, E/e' [odds ratio (OR) 0.878 (95% CI 0.792-0.974), P = 0.014], left ventricular end-diastolic diameter [OR 0.874 (95% CI 0.777-0.983), P = 0.024], and CHA2DS2-VASc score (congestive HF, hypertension, age ≥75 years, diabetes mellitus, stroke or transient ischaemic attack, vascular disease, age 65-74 years, and sex category) [OR 0.647 (95% CI 0.438-0.955), P = 0.028] were identified as three independent predictors of LVEF trajectory improvement.

CONCLUSIONS

Rhythm control is associated with improved LVEF trajectory and clinical outcomes and may thus be considered the optimal therapeutic strategy for patients with both HF and AF.

Prolonged mHealth-Based Arrhythmia Monitoring in Patients With Hypertrophic Cardiomyopathy (HCM-PATCH): Protocol for a Single-Center Cohort Study

BACKGROUND

Patients with hypertrophic cardiomyopathy (HCM) are at increased risk of sudden cardiac death (SCD) due to ventricular arrhythmias and other arrhythmias. Screening for arrhythmias is mandatory to assess the individual SCD risk, but long-term electrocardiography (ECG) is rarely performed in routine clinical practice. Intensified monitoring may increase the detection rate of ventricular arrhythmias and identify more patients with an increased SCD risk who are potential candidates for the primary prophylactic implantation of an implantable cardioverter-defibrillator. To date, reliable data on the clinical benefit of prolonged arrhythmia monitoring in patients with HCM are rare.

OBJECTIVE

This prospective study aims to measure the prevalence of ventricular arrhythmias in patients with HCM observed by mobile health (mHealth)-based continuous rhythm monitoring over 14 days compared to standard practice (a 24- and 48-h long-term ECG). The frequency of ventricular arrhythmias in this 14-day period is compared with the frequency in the first 24 or 48 hours for the same patient (intraindividual comparison).

METHODS

Following the sample size calculation, 34 patients with a low or intermediate risk for SCD, assessed by the HCM Risk-SCD calculator, will need to be recruited in this single-center cohort study between June 2023 and February 2024. All patients will receive an ECG patch that records their heart activity over 14 days. In addition, cardiac magnetic resonance imaging and genetic testing data will be integrated into risk stratification. All patients will be asked to complete questionnaires about their symptoms; previous therapy; family history; and, at the end of the study, their experience with the ECG patch-based monitoring.

RESULTS

The Hypertrophic Cardiomyopathy: Clinical Impact of a Prolonged mHealth-Based Arrhythmia Monitoring by Single-Channel ECG (HCM-PATCH) study investigates the prevalence of nonsustained ventricular tachycardia (ie, ≥3 consecutive ventricular beats at a rate of 120 beats per minute, lasting for <30 seconds) in low- to intermediate-risk patients with HCM (according to the HCM Risk-SCD calculator) with additional mHealth-based prolonged rhythm monitoring. The study was funded by third-party funding from the Department of Cardiology and Intensive Care Medicine, University Hospital Ostwestfalen-Lippe of Bielefeld University in June 2023 and approved by the institutional review board in May 2023. Data collection began in June 2023, and we plan to end the study in February 2024. Of the 34 patients, 26 have been recruited. Data analysis has not yet taken place. Publication of the results is planned for the fall of 2024.

CONCLUSIONS

Prolonged mHealth-based rhythm monitoring could lead to differences in the prevalence of arrhythmias compared to 24- and 48-hour long-term ECGs. This may lead to improved identification of patients at high risk and trigger therapeutic interventions that may provide better protection from SCD or atrial fibrillation-related complications such as embolic stroke.

TRIAL REGISTRATION

Deutsches Register Klinischer Studien DRKS00032144; https://tinyurl.com/498bkrx8.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/52035.

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.

Technology engagement is associated with higher perceived physical well-being in stroke patients prescribed smartwatches for atrial fibrillation detection

Background

Increasing ownership of smartphones among Americans provides an opportunity to use these technologies to manage medical conditions. We examine the influence of baseline smartwatch ownership on changes in self-reported anxiety, patient engagement, and health-related quality of life when prescribed smartwatch for AF detection.

Method

We performed a post-hoc secondary analysis of the Pulsewatch study (NCT03761394), a clinical trial in which 120 participants were randomized to receive a smartwatch-smartphone app dyad and ECG patch monitor compared to an ECG patch monitor alone to establish the accuracy of the smartwatch-smartphone app dyad for detection of AF. At baseline, 14 days, and 44 days, participants completed the Generalized Anxiety Disorder-7 survey, the Health Survey SF-12, and the Consumer Health Activation Index. Mixed-effects linear regression models using repeated measures with anxiety, patient activation, physical and mental health status as outcomes were used to examine their association with smartwatch ownership at baseline.

Results

Ninety-six participants, primarily White with high income and tertiary education, were randomized to receive a study smartwatch-smartphone dyad. Twenty-four (25%) participants previously owned a smartwatch. Compared to those who did not previously own a smartwatch, smartwatch owners reported significant greater increase in their self-reported physical health (β = 5.07, P < 0.05), no differences in anxiety (β = 0.92, P = 0.33), mental health (β = -2.42, P = 0.16), or patient activation (β = 1.86, P = 0.54).

Conclusions

Participants who own a smartwatch at baseline reported a greater positive change in self-reported physical health, but not in anxiety, patient activation, or self-reported mental health over the study period.

Left atrial area index provides the best prediction of atrial fibrillation in ischemic stroke patients: results from the LAETITIA observational study

Background and aims

Left atrial (LA) enlargement has been repeatedly shown to be associated with the diagnosis of atrial fibrillation (AF). In clinical practice, several parameters are available to determine LA enlargement: LA diameter index (LADI), LA area index (LAAI), or LA volume index (LAVI). We investigated the predictive power of these individual LA parameters for AF in patients with acute ischemic stroke or transient ischemic attack (TIA).

Methods

LAETITIA is a retrospective observational study that reflects the clinical reality of acute stroke care in Germany. Consecutive patient cases with acute ischemic cerebrovascular event (CVE) in 2019 and 2020 were identified from the Mannheim stroke database. Predictive power of each LA parameter was determined by the area under the curve (AUC) of receiver operating characteristic curves. A cutoff value was determined. A multiple logistic regression analysis was performed to confirm the strongest LA parameter as an independent predictor of AF in patients with acute ischemic CVE.

Results

A total of 1,910 patient cases were included. In all, 82.0% of patients had suffered a stroke and 18.0% had a TIA. Patients presented with a distinct cardiovascular risk profile (reflected by a CHA2DS2-VASc score ≥2 prior to hospital admission in 85.3% of patients) and were moderately affected on admission [median NIHSS score 3 (1; 8)]. In total, 19.5% of patients had pre-existing AF, and 8.0% were newly diagnosed with AF. LAAI had the greatest AUC of 0.748, LADI of 0.706, and LAVI of 0.719 (each p < 0.001 vs. diagonal line; AUC-LAAI vs. AUC-LADI p = 0.030, AUC-LAAI vs. AUC-LAVI p = 0.004). LAAI, increasing NIHSS score on admission, and systolic heart failure were identified as independent predictors of AF in patients with acute ischemic CVE. To achieve a clinically relevant specificity of 70%, a cutoff value of ≥10.3 cm2/m2 was determined for LAAI (sensitivity of 69.8%).

Conclusion

LAAI revealed the best prediction of AF in patients with acute ischemic CVE and was confirmed as an independent risk factor. An LAAI cutoff value of 10.3 cm2/m2 could serve as an inclusion criterion for intensified AF screening in patients with embolic stroke of undetermined source in subsequent studies.

Predicting Future Incidences of Cardiac Arrhythmias Using Discrete Heartbeats from Normal Sinus Rhythm ECG Signals via Deep Learning Methods

This study aims to compare the effectiveness of using discrete heartbeats versus an entire 12-lead electrocardiogram (ECG) as the input for predicting future occurrences of arrhythmia and atrial fibrillation using deep learning models. Experiments were conducted using two types of inputs: a combination of discrete heartbeats extracted from 12-lead ECG and an entire 12-lead ECG signal of 10 s. This study utilized 326,904 ECG signals from 134,447 patients and categorized them into three groups: true-normal sinus rhythm (T-NSR), atrial fibrillation-normal sinus rhythm (AF-NSR), and clinically important arrhythmia-normal sinus rhythm (CIA-NSR). The T-NSR group comprised patients with at least three normal rhythms in a year and no atrial fibrillation or arrhythmias history. Clinically important arrhythmia included atrial fibrillation, atrial flutter, atrial premature contraction, atrial tachycardia, ventricular premature contraction, ventricular tachycardia, right and left bundle branch block, and atrioventricular block over the second degree. The AF-NSR group included normal sinus rhythm paired with atrial fibrillation or atrial flutter within 14 days, and the CIA-NSR group comprised normal sinus rhythm paired with CIA occurring within 14 days. Three deep learning models, ResNet-18, LSTM, and Transformer-based models, were utilized to distinguish T-NSR from AF-NSR and T-NSR from CIA-NSR. The experiments demonstrated the potential of using discrete heartbeats in predicting future arrhythmia and atrial fibrillation incidences extracted from 12-lead electrocardiogram (ECG) signals alone, without any additional patient information. The analysis reveals that these discrete heartbeats contain subtle patterns that deep learning models can identify. Focusing on discrete heartbeats may lead to more timely and accurate diagnoses of these conditions, improving patient outcomes and enabling automated diagnosis using ECG signals as a biomarker.

Data deluge from remote monitoring of cardiac implantable electronic devices and importance of clinical stratification

Background

Remote monitoring (RM) has been accepted as a standard of care for follow-up of patients with cardiac implantable electronic devices (CIEDs). However, the resulting data deluge poses major challenge to device clinics.

Objective

This study aimed to quantify the data deluge from CIED and stratify these data based on clinical relevance.

Methods

The study included patients from 67 device clinics across the United States being remotely monitored by Octagos Health. The CIEDs included implantable loop recorders, pacemakers, implantable cardioverter-defibrillators, cardiac resynchronization therapy defibrillators, and cardiac resynchronization therapy pacemakers. Transmissions were either dismissed before reaching the clinical practice if they were repetitive or redundant or were forwarded if they were either clinically relevant or actionable transmission (alert). The alerts were further classified as level 1, 2, or 3 based on clinical urgency.

Results

A total of 32,721 patients with CIEDs were included. There were 14,465 (44.2%) patients with pacemakers, 8381 (25.6%) with implantable loop recorders, 5351 (16.4%) with implantable cardioverter-defibrillators, 3531 (10.8%) with cardiac resynchronization therapy defibrillators, and 993 (3%) with cardiac resynchronization therapy pacemakers. Over a period of 2 years of RM, 384,796 transmissions were received. Of these, 220,049 (57%) transmissions were dismissed, as they were either redundant or repetitive. Only 164,747 (43%) transmissions were transmitted to the clinicians, of which only 13% (n = 50,440) had clinical alerts, while 30.6% (n = 114,307) were routine transmissions.

Conclusion

Our study shows that data deluge from RM of CIEDs can be streamlined by utilization of appropriate screening strategies that will enhance efficiency of device clinics and provide better patient care.

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.

Atrial fibrillation episode patterns as predictor of clinical outcome of catheter ablation

Methods for characterization of atrial fibrillation (AF) episode patterns have been introduced without establishing clinical significance. This study investigates, for the first time, whether post-ablation recurrence of AF can be predicted by evaluating episode patterns. The dataset comprises of 54 patients (age 56 ± 11 years; 67% men), with an implantable cardiac monitor, before undergoing the first AF catheter ablation. Two parameters of the alternating bivariate Hawkes model were used to characterize the pattern: AF dominance during the monitoring period (log(mu)) and temporal aggregation of episodes (beta1). Moreover, AF burden and AF density, a parameter characterizing aggregation of AF burden, were studied. The four parameters were computed from an average of 29 AF episodes before ablation. The risk of AF recurrence after catheter ablation using the Hawkes parameters log(mu) and beta1, AF burden, and AF density was evaluated. While the combination of AF burden and AF density is related to a non-significant hazard ratio, the combination of log(mu) and beta1 is related to a hazard ratio of 1.95 (1.03-3.70; p < 0.05). The Hawkes parameters showed increased risk of AF recurrence within 1 year after the procedure for patients with high AF dominance and high episode aggregation and may be used for pre-ablation risk assessment.

Insertable cardiac monitor with a long sensing vector: Impact of obesity on sensing quality and safety

Background

Fat layers in obese patients can impair R-wave detection and diagnostic performance of a subcutaneous insertable cardiac monitor (ICM). We compared safety and ICM sensing quality between obese patients [body mass index (BMI) ≥ 30 kg/m²] and normal-weight controls (BMI <30 kg/m²) in terms of R-wave amplitude and time in noise mode (noise burden) detected by a long-sensing-vector ICM.

Materials and methods

Patients from two multicentre, non-randomized clinical registries are included in the present analysis on January 31, 2022 (data freeze), if the follow-up period was at least 90 days after ICM insertion, including daily remote monitoring. The R-wave amplitudes and daily noise burden averaged intraindividually for days 61-90 and days 1-90, respectively, were compared between obese patients (n = 104) and unmatched (n = 268) and a nearest-neighbour propensity score (PS) matched (n = 69) normal-weight controls.

Results

The average R-wave amplitude was significantly lower in obese (median 0.46 mV) than in normal-weight unmatched (0.70 mV, P < 0.0001) or PS-matched (0.60 mV, P = 0.003) patients. The median noise burden was 1.0% in obese patients, which was not significantly higher than in unmatched (0.7%; P = 0.056) or PS-matched (0.8%; P = 0.133) controls. The rate of adverse device effects during the first 90 days did not differ significantly between groups.

Conclusion

Although increased BMI was associated with reduced signal amplitude, also in obese patients the median R-wave amplitude was >0.3 mV, a value which is generally accepted as the minimum level for adequate R-wave detection. The noise burden and adverse event rates did not differ significantly between obese and normal-weight patients.Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04075084 and NCT04198220.

Implantable loop recorders in patients with atrial fibrillation

INTRODUCTION

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

AREAS COVERED

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

EXPERT OPINION

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

Wearables in Sports Cardiology

The expanding array and adoption of consumer health wearables is creating a new dynamic to the patient-health-care provider relationship. Providers are increasingly tasked with integrating the biometric data collected from their patients into clinical care. Further, a growing body of evidence is supporting the provider-driven utility of wearables in the screening, diagnosis, and monitoring of cardiovascular disease. Here we highlight existing and emerging wearable health technologies and the potential applications for use within sports cardiology. We additionally highlight how wearables can advance the remote cardiovascular care of patients within the context of the COVID-19 pandemic. Finally, despite these promising advances, we acknowledge some of the significant challenges that remain before wearables can be routinely incorporated into clinical care.

European Stroke Organisation (ESO) guideline on screening for subclinical atrial fibrillation after stroke or transient ischaemic attack of undetermined origin

We aimed to provide practical recommendations for the screening of subclinical atrial fibrillation (AF) in patients with ischaemic stroke or transient ischaemic attack (TIA) of undetermined origin. These guidelines are based on the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) methodology. Five relevant Population, Intervention, Comparator, Outcome questions were defined by a multidisciplinary module working group (MWG).

Longer duration of cardiac rhythm monitoring increases the detection of subclinical AF, but the optimal monitoring length is yet to be defined. We advise longer monitoring to increase the rate of anticoagulation, but whether longer monitoring improves clinical outcomes needs to be addressed. AF detection does not differ from in- or out-patient ECG-monitoring with similar monitoring duration, so we consider it reasonable to initiate in-hospital monitoring as soon as possible and continue with outpatient monitoring for more than 48h. Although insertable loop recorders (ILR) increase AF detection based on their longer monitoring duration, comparison with non-implantable ECG devices for similar monitoring time is lacking. We suggest the use of implantable devices, if feasible, for AF detection instead of non- implantable devices to increase the detection of subclinical AF. There is weak evidence of a useful role for blood, ECG, and brain imaging biomarkers for the identification of patients at high risk of AF. In patients with patent foramen ovale, we found insufficient evidence from RCT, but prolonged cardiac monitoring in patients >55 years is advisable for subclinical AF detection. To conclude, in adult patients with ischaemic stroke or TIA of undetermined origin, we recommend longer duration of cardiac rhythm monitoring of more than 48h and if feasible with IRL to increase the detection of subclinical AF.

The BIOMONITOR III Injectable Cardiac Monitor: Clinical Experience with a Novel Injectable Cardiac Monitor

Background: Injectable cardiac monitors (ICMs) are leadless subcutaneous devices for long-term monitoring of arrhythmias. The BIOTRONIK BIOMONITOR III is a novel ICM with a miniaturized profile, long sensing vector, and simplified implantation technique. Methods: R-wave amplitude was recorded immediately after implantation, the day after implantation, and after 3 months. Follow-up was scheduled after 3 months or after an event. All data from the ICM were retrieved. The anatomical position of the ICM was determined post-implantation and after 3 months. A patient questionnaire was conducted after 3 months. Results: In 36 patients (mean age 67 ± 13 years; 40% male) an ICM was inserted. Six patients were not included in the final analysis. The median time from skin cut to wound closure was 6 [IQR 5–7] minutes. Mean R-wave amplitude increased over time (0.73 ± 32 mV vs. 0.78 ± 0.38 mV vs. 0.81 ± 0.39 mV; p = ns). Three months after implantation, the ICM was in an anatomically stable position. In 14 (47%) patients, true episodes were detected. False arrhythmia alerts were detected in 13 (43%) patients. The total number of false detections was low, and the patient satisfaction rate was high. Conclusion: Implantation of the novel BIOMONITOR III is fast and uncomplicated; its sensing characteristics are excellent and improve over time, and patient satisfaction is high.

Reducing the Electrogram Review Burden Imposed by Insertable Cardiac Monitors

BACKGROUND

Insertable cardiac monitors (ICMs) are essential for ambulatory arrhythmia diagnosis. However, definitive diagnoses still require time-consuming, manual adjudication of electrograms (EGMs).

OBJECTIVE

To evaluate the clinical impact of selecting only key EGMs for review.

METHODS

Retrospective analyses of randomly selected Abbott Confirm Rx^TM devices with ≥90 days of remote transmission history was performed, with each EGM adjudicated as true or false positive (TP, FP). For each device, up to 3 "key EGMs" per arrhythmia type per day were prioritized for review based on ventricular rate and episode duration. The reduction in EGMs and TP days (patient-days with at least 1 TP EGM), and any diagnostic delay (from the first TP), were calculated vs. reviewing all EGMs.

RESULTS

In 1,000 ICMs over a median duration of 8.1 months, at least one atrial fibrillation (AF), tachycardia, bradycardia, or pause EGM was transmitted by 424, 343, 190, and 325 devices, respectively, with a total of 95716 EGMs. Approximately 90% of episodes were contributed by 25% of patients. Key EGM selection reduced EGM review burden by 43%, 66%, 77%, and 50% (55% overall), while reducing TP days by 0.8%, 2.1%, 0.2%, and 0.0%, respectively. Despite reviewing fewer EGMs, 99% of devices with a TP EGM were ultimately diagnosed on the same day vs. reviewing all EGMs.

CONCLUSIONS

Key EGM selection reduced the EGM review substantially with no delay-to-diagnosis in 99% of patients exhibiting true arrhythmias. Implementing these rules in the Abbott patient care network may accelerate clinical workflow without compromising diagnostic timelines. This article is protected by copyright. All rights reserved.

Temporal Association of Atrial Fibrillation With Cardiac Implanted Electronic Device Detected Heart Failure Status

OBJECTIVES

This study sought to investigate the temporal association between changes in physiologic heart failure (HF) sensors, atrial fibrillation (AF) progression, and clinical HF in patients with cardiac resynchronization therapy implantable defibrillators (CRT-D) designed to monitor AF and HF daily.

BACKGROUND

AF is a common comorbidity in HF; however, it is unclear if HF triggers AF, or vice-versa. Current implantable cardiac devices have sensors capable of quantifying HF status, which permits a greater understanding of the impact of AF on HF status and may help guide treatment.

METHODS

The MultiSENSE (Multisensor Chronic Evaluation in Ambulatory Heart Failure Patients) study collected multiple sensor data indicative of HF status in patients with CRT-D followed for up to 12 months. Patients were grouped according to their longest daily AF burden: 1) at least 24 hours of AF (HIGH AF); 2) between 6 minutes and 24 hours (MID AF); and 3) <6 minutes (NO AF). Sensor data were aligned to the first qualifying AF event or a randomly selected day for patients in the NO AF group.

RESULTS

Among 869 patients with daily AF data available, 98 patients had HIGH AF, 141 patients MID AF, and 630 patients NO AF. At baseline, history of AF, N-terminal pro hormone B-type natriuretic peptide and device-measured S3 were associated with development of AF. HeartLogic index increased before AF onset (Δ HeartLogic = 9.83 ± 2.49; P < 0.001). Multivariable time-dependent Cox regression showed an increased risk for HF events following a 24-hour AF episode compared with no 24-hour AF (hazard ratio: 1.96; 95% confidence interval: 1.03-3.74).

CONCLUSIONS

Device-measured HF indicators worsened before AF onset, whereas clinical HF deterioration only became apparent after AF occurred. Thus, the sensitivity of methods to ascertain AF and HF status appear to influence the direction of perceived causality. (Multisensor Chronic Evaluation in Ambulatory Heart Failure Patients [MultiSENSE]; NCT01128166).

Cryptogenic Stroke and Embolic Stroke of Undetermined Source: Risk Factors and Approaches for Detection of Atrial Fibrillation

BACKGROUND

Stroke is a problem worldwide because of its high mortality and disability rates. Almost 90% of strokes are ischemic, and more than half of the deaths are caused by an ischemic stroke. Most risk factors for stroke are manageable so that it can be avoided with proper prevention. Despite the success in determining the causes of stroke in recent years, selectively, the "culprit" causing stroke remains unsolved. In such cases, a diagnosis of undetermined etiology (cryptogenic stroke) or embolic stroke of undetermined source (ESUS) is generated, resulting the prevention of a recurrent cerebrovascular occurrence impossible. Atrial fibrillation (AF) can be a cause of stroke by causing blood clots in the chambers of the heart.

PURPOSE

The aim was to determine the optimal method of heart rate monitoring in patients with ischemic stroke, as methods and approaches for detecting AF are very diverse, but there is still no single opinion, which would be universal.

PROCEDURES

In our review, we consider epidemiology, risk factors for the stroke of undetermined etiology, as well as analytical methods for detecting heart rhythm disturbances in this category of patients.

FINDINGS

Atrial fibrillation (AF) is detected by thorough monitoring of heart rate of patients with cryptogenic stroke and ESUS can be diagnosed in up to 46% of patients. .

CONCLUSION

After AF detection, consideration should be given to prescribing anticoagulants, instead of antiplatelet agents, for the secondary prevention of stroke.

Subcutaneouscardiac Rhythm Monitors: A Comprehensive Review

Subcutaneous loop recorders (SCRMs) are subcutaneous electronic devices which have revolutionized the field of arrhythmia detection. They have become increasingly appealing due to advances such as miniaturization of device, longer battery life, bluetooth capabilities and relatively simple implantation technique without the need for complex surgical suites. They can be implanted in the office, patient bedside without the need to go to the operating room. One of the most common indications for their implantation is detection of atrial fibrillation (AF) after a cryptogenic stroke. They have also been utilized for assessing the success of rhythm control strategies such post pulmonary venous isolation. More recently studies have assessed the utility of SCRMs for detecting silent AF in at risk populations such as patients with sleep apnea or those on hemodialysis. In this paper, we review the evolution of SCRMs, the clinical studies assessing their value for different indications, their role incurrent clinical practice and future avenues in the era of smart wearable devices like apple watch etc.

Use of Smartphones and Wearables for Arrhythmia Monitoring

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

Implantable Loop Recorders-Syncope, Cryptogenic Stroke, Atrial Fibrillation

The implantable loop recorder (ILR) is a subcutaneous, single-lead, electrocardiographic (ECG) monitoring device used for diagnosis in patients with recurrent, unexplained episodes of palpitations or syncope, for long-term monitoring in patients at risk for atrial fibrillation (AF), and to guide clinical management in patients with known AF. These devices are capable of storing and transmitting ECG data automatically in response to a significant bradyarrhythmia or tachyarrhythmia or in response to patient activation. This document aims to review the clinical utility of ILRs for arrhythmia monitoring in common clinical situations such as syncope, cryptogenic stroke, and management of patients with known AF.

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.

Cardiac events monitoring

Cardiac events recorders have been developed in order to record the heart rhythm during symptoms such as palpitations or presyncope, to first make a diagnosis, and subsequently drive the treatment strategy. In other circumstances, they can be also used in asymptomatic patients (to record silent atrial fibrillation for instance). Because they are non-invasive, potentially cost-saving and relatively easy to use, the external rhythm recording devices have shown some great advances in the last years, spreading from photoplethysmographic technique to real ECG reconstruction. Technological advances in the field of microelectronics, as well as in the field of data transmission have contributed to their widespread use in cardiology. The trend for miniaturization was also expanded to the implantable recorders. This paper will review will review advantages and limitations of the different existing available well-established recording devices, as well as the last technological developments in terms of ECG recordings.

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.

Resource Use and Economic Implications of Remote Monitoring With Subcutaneous Cardiac Rhythm Monitors

OBJECTIVES

This study reports resource use and economic implications of rhythm monitoring with subcutaneous cardiac rhythm monitors (SCRMs).

BACKGROUND

SCRMs generate a substantial amount of data that requires timely adjudication for appropriate clinical care. Resource use for SCRM monitoring is not known.

METHODS

The study included consecutive transmissions during 4 weeks from 1,811 SCRMs. Resource use was quantified by assessment of time commitment of device clinic personnel and electrophysiologists for data adjudication. Incidence and characteristics of false positive (FP) episodes were assessed. Impact of custom programming for arrhythmia detection on incidence of FP episodes and resource use was analyzed.

RESULTS

A total of 1,457 transmissions (alerts = 462; full downloads = 995) were received during study period. Average device clinic personnel time for adjudication of 1 transmission was 15 ± 6 min. This totaled to 364 h spent (2.3 full-time staff) over the 4-week period, which translated into a salary cost of $12,000 U.S. dollars (USD). Average time spent by an electrophysiologist for 1 transmission was 1.5 ± 1 min and totaled to 37 h for 4 weeks, which translated into an estimated cost of $9,600 USD. Of 1,457 total transmissions, 512 (35%) represented multiple transmissions from the same patients, which resulted in no additional reimbursement. Incidence of FP episodes in the entire cohort was 50% and was variable in alert (60%) and full download (49%) (p = 0.04) transmissions. When SCRMs with manufacturer suggested nominal programming and institutional custom programming were compared, there was a reduction in FP episodes (55% vs. 16%; p = 0.01), which translated to a 34% reduction in resource use for data adjudication.

CONCLUSIONS

SCRM data adjudication requires significant resources. Custom programming for SCRMs may overcome the data deluge.

A Review on the State of the Art in Atrial Fibrillation Detection Enabled by Machine Learning

Atrial Fibrillation (AF) the most commonly occurring type of cardiac arrhythmia is one of the main causes of morbidity and mortality worldwide. The timely diagnosis of AF is an equally important and challenging task because of its asymptomatic and episodic nature. In this paper, state-of-the-art ECG data-based machine learning models and signal processing techniques applied for auto diagnosis of AF are reviewed. Moreover, key biomarkers of AF on ECG and the common methods and equipment used for the collection of ECG data are discussed. Besides that, the modern wearable and implantable ECG sensing technologies used for gathering AF data are presented briefly. In the end, key challenges associated with the development of auto diagnosis solutions of AF are also highlighted. This is the first review paper of its kind that comprehensively presents a discussion on all these aspects related to AF auto-diagnosis in one place. It is observed that there is a dire need for low energy and low cost but accurate auto diagnosis solutions for the proactive management of AF.

Diagnostic Accuracy and Safety of Confirm Rx™ Insertable Cardiac Monitor in Pediatric Patients

Insertable cardiac monitors (ICM) are subcutaneously implanted devices that monitor a patient's heart rate and rhythm (Rossano in Pediatrics 112(3):e228, 2003). The diagnostic accuracy and safety of the Confirm Rx^TM (Abbott, Minneapolis, MN) ICM in pediatric patients is unknown. This is a single center, retrospective, IRB-approved review of patients ≤ 21 years implanted with Confirm Rx^TM ICMs from 2017 to 2020. Data collected included demographics, indications, presence of P-wave and R-wave amplitude at implantation and follow-up, number/appropriateness of transmissions pre and post implementation of SharpSense^TM technology, reprogramming to improve accuracy, time from implantation to arrhythmia detection, and complications. There were 29 patients (median age: 8 years, 59% females). P-waves were identified in all patients and average R-wave amplitude was 0.85 mV (0.26-1.03 mV). There was no significant difference in R-wave amplitude based on size (BSA ≥ 1.5 m²: 0.76 mV, < 1.5 m²: 0.91 mV) or congenital heart disease (+CHD: 0.86 mV, -CHD: 0.85 mV). Arrhythmias identified were the following: wide complex tachycardia (1), supraventricular tachycardia (4), bradycardia/sinus pause (3), and premature ventricular contraction (1). SharpSense^TM implementation decreased the false-positive rate in device-initiated transmissions (55.4% to 0%, p < 0.00001). Average time from implantation to arrhythmia detection was 2.63 months (range: 0-8.8). A single complication of cellulitis occurred. Confirm Rx^TM is appropriate for implant in pediatric patients regardless of age, BSA, or CHD. Implementation of SharpSense™ technology dramatically decreased the false-positive rate. Follow-up studies could utilize additional monitoring devices to provide analysis on potential events that the Confirm Rx^TM ICM missed.

Cardiac Implantable Electronic Miniaturized and Micro Devices

Advancement in the miniaturization of high-density power sources, electronic circuits, and communication technologies enabled the construction of miniaturized electronic devices, implanted directly in the heart. These include pacing devices to prevent low heart rates or terminate heart rhythm abnormalities ('arrhythmias'), long-term rhythm monitoring devices for arrhythmia detection in unexplained syncope cases, and heart failure (HF) hemodynamic monitoring devices, enabling the real-time monitoring of cardiac pressures to detect and alert for early fluid overload. These devices were shown to prevent HF hospitalizations and improve HF patients' life quality. Pacing devices include permanent pacemakers (PPM) that maintain normal heart rates, defibrillators that are capable of fast detection and the termination of life-threatening arrhythmias, and cardiac re-synchronization devices that improve cardiac function and the survival of HF patients. Traditionally, these devices are implanted via the venous system ('endovascular') using conductors ('endovascular leads/electrodes') that connect the subcutaneous device battery to the appropriate cardiac chamber. These leads are a potential source of multiple problems, including lead-failure and systemic infection resulting from the lifelong exposure of these leads to bacteria within the venous system. One of the important cardiac innovations in the last decade was the development of a leadless PPM functioning without venous leads, thus circumventing most endovascular PPM-related problems. Leadless PPM's consist of a single device, including a miniaturized power source, electronic chips, and fixating mechanism, directly implanted into the cardiac muscle. Only rare device-related problems and almost no systemic infections occur with these devices. Current leadless PPM's sense and pace only the ventricle. However, a novel leadless device that is capable of sensing both atrium and ventricle was recently FDA approved and miniaturized devices that are designed to synchronize right and left ventricles, using novel intra-body inner-device communication technologies, are under final experiments. This review will cover these novel implantable miniaturized cardiac devices and the basic algorithms and technologies that underlie their development. Advancement in the miniaturization of high-density power sources, electronic circuits, and communication technologies enabled the construction of miniaturized electronic devices, implanted directly in the heart. These include pacing devices to prevent low heart rates or terminate heart rhythm abnormalities ('arrhythmias'), long-term rhythm monitoring devices for arrhythmia detection in unexplained syncope cases, and heart failure (HF) hemodynamic monitoring devices, enabling the real-time monitoring of cardiac pressures to detect and alert early fluid overload. These devices were shown to prevent HF hospitalizations and improve HF patients' life quality. Pacing devices include permanent pacemakers (PPM) that maintain normal heart rates, defibrillators that are capable of fast detection and termination of life-threatening arrhythmias, and cardiac re-synchronization devices that improve cardiac function and survival of HF patients. Traditionally, these devices are implanted via the venous system ('endovascular') using conductors ('endovascular leads/electrodes') that connect the subcutaneous device battery to the appropriate cardiac chamber. These leads are a potential source of multiple problems, including lead-failure and systemic infection that result from the lifelong exposure of these leads to bacteria within the venous system. The development of a leadless PPM functioning without venous leads was one of the important cardiac innovations in the last decade, thus circumventing most endovascular PPM-related problems. Leadless PPM's consist of a single device, including a miniaturized power source, electronic chips, and fixating mechanism, implanted directly into the cardiac muscle. Only rare device-related problems and almost no systemic infections occur with these devices. Current leadless PPM's sense and pace only the ventricle. However, a novel leadless device that is capable of sensing both atrium and ventricle was recently FDA approved and miniaturized devices designed to synchronize right and left ventricles, using novel intra-body inner-device communication technologies, are under final experiments. This review will cover these novel implantable miniaturized cardiac devices and the basic algorithms and technologies that underlie their development.

Modeling and Estimation of Temporal Episode Patterns in Paroxysmal Atrial Fibrillation

OBJECTIVE

The present study proposes a model-based, statistical approach to characterizing episode patterns in paroxysmal atrial fibrillation (AF). Thanks to the rapid advancement of noninvasive monitoring technology, the proposed approach should become increasingly relevant in clinical practice.

METHODS

History-dependent point process modeling is employed to characterize AF episode patterns, using a novel alternating, bivariate Hawkes self-exciting model. In addition, a modified version of a recently proposed statistical model to simulate AF progression throughout a lifetime is considered, involving non-Markovian rhythm switching and survival functions. For each model, the maximum likelihood estimator is derived and used to find the model parameters from observed data.

RESULTS

Using three databases with a total of 59 long-term ECG recordings, the goodness-of-fit analysis demonstrates that the proposed alternating, bivariate Hawkes model fits SR-to-AF transitions in 40 recordings and AF-to-SR transitions in 51; the corresponding numbers for the AF model with non-Markovian rhythm switching are 40 and 11, respectively. Moreover, the results indicate that the model parameters related to AF episode clustering, i.e., aggregation of temporal AF episodes, provide information complementary to the well-known clinical parameter AF burden.

CONCLUSION

Point process modeling provides a detailed characterization of the occurrence pattern of AF episodes that may improve the understanding of arrhythmia progression.

Accuracy of implantable loop recorders for detecting atrial tachyarrhythmias after atrial fibrillation catheter ablation

Background

Implantable loop recorders (ILRs) can provide an enhanced possibility to detect atrial fibrillation (AF), but the accuracy, especially the positive predictive value (PPV), is controversial. This study aimed to evaluate the accuracy of ILRs for detecting AF through a comparison with Holter.

Method and results

Thirteen patients who underwent AF ablation were enrolled. ILRs were implanted in all patients, who were scheduled to have Holter monitorings after the procedure. The incidence of AF was compared between the two modalities and analyzed for any correlations. A total of 51 Holters (67,985.5 min) and concomitant ILRs were available for the comparison. The judgment of the presence of AF did not perfectly correlate between the ILR and Holter (Kappa = 0.866, P < 0.001). In the ILR data, the sensitivity of detecting AF on the Holter was 81.6% (95% confidence interval [CI] 0.812–0.820; P < 0.001). The specificity was 99.9% (95% CI 0.998–0.999; P < 0.001). When the ILR detected AF, the PPV was 99.5% (95% CI 0.994–0.995), but the ILR did not detect AF, and the negative predictive value was 94.2% (95% CI 0.941–0.944). A separate analysis of AF/atrial tachycardia (AT) showed that the AT detection rate of the ILR was 2.3%.

Conclusion

The ILR had a low false positive value and high PPV for AF events. However, it was limited in identifying AT.

Predictive value of P wave terminal force in lead V1 for atrial fibrillation: A meta-analysis

Background

Several studies have explored the association between P wave terminal force in lead V1 (PTFV1) and risk of atrial fibrillation (AF) occurrence, but the results were controversial. This meta‐analysis aimed to examine whether abnormal PTFV1 could predict AF occurrence.

Methods

We searched PubMed, Embase, and Cochrane Library databases for articles published before August 25, 2018. Pooled odds ratios (ORs) of AF occurrence were calculated using random‐effects models to explore the significance of PTFV1.

Results

A total of 12 studies examining 51,372 participants were included, with 9 studies analyzing PTFV1 as a categorical variable and 4 studies analyzing PTFV1 as a continuous variable. As a categorical variable, abnormal PTFV1 (>0.04 mm s) was significantly associated with AF occurrence with a pooled OR of 1.39 (95% confidence interval [CI] 1.08–1.79, p = .01). Subgroup analysis found that ORs of studies in hemodialysis patients (OR = 4.89, 95% CI 2.54–9.90, p < .001) and acute ischemic stroke patients (OR = 1.60, 95% CI 1.14–2.25, p = .007) were higher than general population (OR = 1.15, 95% CI 1.03–1.29, p = .01). Studies from Europe (OR = 1.05, 95% CI 0.91–1.20, p = .51) yielded lower OR of endpoints compared with Asia (OR = 1.89, 95% CI 1.38–2.60, p < .001) and United States (OR = 1.43, 95% CI 1.19–1.72, p < .001). As a continuous variable, PTFV1 was also significantly associated with AF occurrence with a polled OR per 1 standard deviation (SD) change of 1.27 (95% CI 1.02–1.59, p = .03).

Conclusions

PTFV1 was significantly associated with the risk of AF and was considered to be a good predictor of AF occurrence in population with or without cardiovascular diseases.

Long-term impact of catheter ablation on arrhythmia burden in low-risk patients with paroxysmal atrial fibrillation: The CLOSE to CURE study

BACKGROUND

Few studies evaluated the impact of catheter ablation (CA) on atrial tachyarrhythmia (ATA) burden in paroxysmal atrial fibrillation (AF).

OBJECTIVE

In the prospective, patient-controlled CLOSE to CURE study, we determined the longer-term impact of optimized CA on ATA burden by using an insertable cardiac monitor (ICM).

METHODS

A total of 105 patients with paroxysmal AF were implanted with an ICM 65 (interquartile range [IQR] 61-78) days before CA. CA consisted of contact force-guided pulmonary vein isolation targeting an intertag distance of ≤6 mm and a region-specific ablation index. The primary end point was reduction in ICM-detected ATA burden; secondary end points were single-procedure freedom from ATA, quality of life, and adverse events.

RESULTS

The mean age was 62 ± 8 years; the median CHA₂DS₂-VASc score was 1 (IQR 1-2); and the median left atrial diameter was 43 (IQR 39-43) mm. After pulmonary vein isolation (1.13 ± 0.39 procedures per patient), median ATA burden decreased from 2.68% (IQR 0.09%-15.02%) at baseline to 0% (IQR 0%-0%) during the first year and to 0% (IQR 0%-0%) during the second year (reduction in ATA burden 100% [IQR 100%-100%]; P < .001). Single-procedure freedom from any ATA was 87% at 1 year and 78% at 2 years. Quality of life improved significantly across all scores. Adverse events occurred in 5 patients (4.8%).

CONCLUSION

CA has become an effective procedure in paroxysmal AF, with a major impact on ICM-detected ATA burden. Whereas conventional survival analysis suggests a progressive decline in efficacy, we observed that burden reduction is maintained at longer follow-up. These data imply that ATA burden is a more optimal end point for assessing ablation efficacy.

Detection of atrial fibrillation using an implantable loop recorder following cryptogenic stroke: implications for post-stroke electrocardiographic monitoring

PURPOSE

Approximately 10-40% of strokes are cryptogenic (CS). Long-term electrocardiographic (ECG) monitoring has been recommended in these patients to search for atrial fibrillation (AF). An unresolved issue is whether ambulatory ECG (AECG) monitoring should be performed first, followed by an implantable loop recorder (ILR) if AECG monitoring is non-diagnostic, or whether long-term ECG monitoring should be initiated using ILRs from the onset. The purpose of this study was to assess, using an ILR, AF incidence in the first month after CS.

METHODS

We enrolled consecutive CS patients referred for an ILR. All patients were monitored via in-hospital continuous telemetry from admission until the ILR (Medtronic [Minneapolis, MN] LINQ™) was implanted. The duration and overall burden of all AF episodes ≥ 2 min was determined.

RESULTS

The cohort included 343 patients (68 ± 11 years, CHA₂DS₂-VASc 3.5 ± 1.7). The time between stroke and ILR was 3.7 ± 1.5 days. During the first 30 days, only 18 (5%) patients had AF. All episodes were paroxysmal, lasting from 2 min to 67 h and 24 min. The median AF burden was 0.85% (IQR 0.52, 10.75). During 1 year of follow-up, 67 (21%) patients had AF.

CONCLUSION

The likelihood of AF detection by an ILR in the first month post-CS is low. Thus, the diagnostic yield of 30 days of AECG monitoring is likely to be limited. These data suggest a rationale for proceeding directly to ILR implantation prior to hospital discharge in CS patients, as many have AF detected during longer follow-up.

The Miniaturization of Cardiac Implantable Electronic Devices: Advances in Diagnostic and Therapeutic Modalities

The Fourth Industrial Revolution, characterized by an unprecedented fusion of technologies that is blurring the lines between the physical, digital, and biological spheres, continues the trend to manufacture ever smaller mechanical, optical and electronic products and devices. In this manuscript, we outline the way cardiac implantable electronic devices (CIEDs) have evolved into remarkably smaller units with greatly enhanced applicability and capabilities.

Duration of Implantable Cardiac Monitoring and Detection of Atrial Fibrillation in Ischemic Stroke Patients: A Systematic Review and Meta-Analysis

BACKGROUND AND PURPOSE

Current guidelines do not provide firm directions on atrial fibrillation (AF) screening after ischemic stroke (IS). We sought to investigate the association of implantable cardiac monitoring (ICM) duration with the yield of AF detection in IS patients.

METHODS

We included studies reporting AF detection rates by ICM in IS patients with negative initial AF screening. We excluded studies reporting prolonged cardiac monitoring with devices other than ICM, not providing AF detection rates or monitoring duration, and reporting overlapping data for the same population. The random-effects model was used for all pooled estimates and meta-regression analyses.

RESULTS

We included 28 studies (4,531 patients, mean age 65 years). In meta-regression analyses, the proportion of AF detection by ICM was independently associated with monitoring duration (coefficient=0.015; 95% confidence interval [CI], 0.005 to 0.024) and mean patient age (coefficient=0.009; 95% CI, 0.003 to 0.015). No associations were detected with other patient characteristics, including IS subtype (cryptogenic vs. embolic stroke of undetermined source) or time from IS onset to CM implantation. In subgroup analyses, significant differences (P<0.001) in the AF detection rates were found for ICM duration (<6 months: 5% [95% CI, 3% to 6%]; ≥6 and ≤12 months: 21% [95% CI, 16% to 25%]; >12 and ≤24 months: 26% [95% CI, 22% to 31%]; >24 months: 34% [95% CI, 29% to 39%]).

CONCLUSION

s Extended duration of ICM monitoring and increased patient age are factors that substantially increase AF detection in IS patients with initial negative AF screening.

Advanced Cardiac Signal Recording

Implantable loop recorders allow prolonged and continuous single-lead electrocardiogram recording, with the pivotal addition of remote monitoring. They have significantly shortened time to electrocardiographic diagnosis and appropriate therapy of many bradyarrhythmias/tachyarrhythmias and proved helpful in arrhythmia burden definition, offering invaluable information in the diagnostic workup for syncope and atrial fibrillation. Advanced cardiac signal recording is also possible by transesophageal catheters. They have been used to orient diagnosis during wide and narrow QRS complex tachycardias and also to perform minimally invasive pacing. Intracardiac electrophysiologic study remains, however, essential for diagnosis of several arrhythmias in the perspective of curative catheter ablation.