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Background P-wave visibility is useful for diagnosis of atrial arrhythmias via insertable cardiac monitors (ICM). Purpose To compare the sensing capability of ICM with different vector length: Medtronic REVEAL LINQ (45mm) vs. Biotronik Biomonitor BMIII (75mm). Methods We accessed de-identified remote monitoring transmissions from n=40 patients with BMIII from Biotronik for comparison with n=80 gender- and body mass index (BMI)-matched patients with REVEAL LINQ. Digital measurement of calibrated ICM electrograms was performed using DigitizeIt© (V2.3.3, Germany) of 5 consecutive P-QRS complexes by 3 investigators independently. P-wave amplitude was measured from baseline to peak and R-wave amplitude was measured from peak-to-peak. Further, we evaluated the impact of BMI on P-wave visibility. Results Patients in both groups are well matched for gender and BMI (53% male, mean BMI 26.7 kg/m2; both p=NS). P-wave and R-wave amplitude were 89% & 20% larger in the BMIII vs. LINQ (0.072±0.039 vs. 0.038±0.022mV, p=0.0001; & 0.83±0.42 vs. 0.69±0.45mV, p=0.095 respectively; Figure). Consequently, the P/R-wave ratio was 44% greater for the BMIII (p=0.002). Multivariate regression analysis showed that increasing BMI, female gender and LINQ were independently associated with lower P-wave amplitude (all P Conclusion The longer ICM sensing vector of BMIII yielded considerable larger P-wave amplitude than LINQ, that was not impacted by increasing BMI. Better P-wave visibility may improve clinical decision-making after device-detected arrhythmias while further studies are needed to determine its impact on clinical outcomes. P-wave visibility comparison of ICMs Funding Acknowledgement Type of funding source: None

Background Atrial fibrillation (AF) is a well-known risk factor for ischemic stroke with a reported increased incidence range of 2.5 to 5-fold. However, it is not well established whether treatment of cryptogenic stroke patients with AF detected by insertable cardiac monitors (ICM) reduces the risk of recurrent stroke. Objective To compare recurrent stroke rates between cryptogenic stroke patients who have AF detected by ICMs and thus started on oral anticoagulation (OAC) treatment and those without detected AF. Methods We performed a retrospective analysis of consecutive patients who received an ICM for the purpose of AF monitoring following a cryptogenic stroke between July 2015 and March 2019. Patients with prior documented AF history were excluded. We calculated the rates of AF detection and OAC initiation. We also compared recurrent stroke rates between patients with and without AF detected. Results A total of 298 cryptogenic stroke patients receiving an ICM and home remote monitoring were studied (mean age: 77 SD: 11.7; Female/Male: 147 (49%)/151; virtual CHA2DS2-VASc: 4.96 SD: 1.28). AF was newly detected in 91 (29.6%) patients over a mean follow-up of 46 months. Of these patients 68 (72.4%) were started on OAC, 12 (15.3%) were already on OAC and 11 (12.2%) remained not anticoagulated. Of the total patients evaluated, 22 patients (7.3%) developed recurrent strokes for an annualized stroke rate of 1.926%. Of those, 8 occurred among the 91 patients with newly detected AF, for an annualized stroke rate of 1.72%. The remining 14 recurrent strokes occurred among the 207 patients without AF detected, for an annualized stroke rate of 1.76%; (p=0.87). One recurrent stroke occurred in an AF patient not anticoagulated due to a prior bleeding event. No hemorrhagic strokes were reported in the AF-OAC group. Conclusion Our study found that newly AF was detected by ICM in almost 1/3 (29%) of cryptogenic stroke patients (consistent with previous studies), and the vast majority of them (88%) accordingly received oral anticoagulation. There was not a significant difference in recurrent stroke rates among patients with AF detected on OAC and those without AF detected. This suggests that rigorous arrhythmia monitoring with ICMs can help identify cryptogenic stroke patients with new AF and initiate oral anticoagulation accordingly, to reduce their risk of recurrent stroke to background levels. Annualized Stroke Risk Funding Acknowledgement Type of funding source: None

Background/Introduction The primary goal of monitoring for atrial fibrillation (AF) after cryptogenic stroke (CS) is secondary stroke prevention. Therefore, long-term monitoring of CS patients with insertable cardiac monitors (ICMs) is likely important to ensure appropriate secondary stroke prevention therapy, regardless of when AF is detected after the index event. However, long-term data on the incidence and duration of AF from real-world populations are sparse. Purpose To investigate the long-term incidence and duration of AF episodes in real-world clinical practice among a large population of patients with ICMs placed for AF detection following CS. Methods We included patients from a large device manufacturer's database who received an ICM for the purpose of AF detection following CS and were monitored for up to 3 years. All detected AF episodes (≥2 minutes) were adjudicated. We quantified the AF detection rate for various episode duration thresholds using Kaplan-Meier survival estimates, analyzed the maximum duration of AF episodes, and measured the time to initial AF detection. Results A total of 1247 patients (65.3±13.0 years, 53% male) were included and followed for 763±362 days. AF episodes (n=5456) were detected in 257 patients, resulting in a median frequency of 5 episodes [IQR 2–19] per patient. At 3 years, the AF detection rate for episodes ≥2 minutes was 24.2%. The AF detection rates at 3 years for episodes ≥6 minutes, ≥30 minutes, and ≥1 hour were 22.4%, 20.6%, and 19.1%, respectively. The median duration of the longest detected AF episode was 4.4 [IQR 1.2–13.9] hours and the median time to AF detection was 129 [IQR 45–354] days. Conclusion AF episodes were detected via ICMs in approximately one-quarter of CS patients within 3 years of follow-up. More than 75% of patients with AF detected had episodes lasting ≥1 hour and half had episodes lasting ≥4 hours. Detection of the first AF episode typically occurred beyond the range of conventional ambulatory monitors. Long-term surveillance of CS patients is likely important given the appreciable incidence, frequency, and duration of these AF episodes. Funding Acknowledgement Type of funding source: None

Background The population with cardiac implantable electronic devices (CIEDs) is growing, creating workload for device clinics to manage these patients. However, the CIED follow-up workflow is poorly understood. This study sought to characterize the workflow and staff time for CIED patient management. Methods A time and motion workflow evaluation was performed in 6 U.S. CIED clinics, which manage an average of 4,217 patients. Each task involved in CIED management was repeatedly timed, including all manufacturers, during 1 business week at each clinic. Mean staff time for a remote transmission and an in-person visit were calculated, including all clinical and administrative (e.g: scheduling, documentation) activities related to the encounter. Annual staff time for follow-up of 1 patient was modeled using CIED transmission data for the 6 clinics, guidelines for CIED follow-up, and published literature. Results 124 clinic visits and 1,374 remote monitoring activities were observed. Staff time required per remote transmission ranged from 12.1–13.4 minutes (depending on the CIED type), and time per visit was 43.4–51.0 minutes. Including all remote and in-person follow-ups, the estimated total staff time per year to manage one pacemaker, ICD, CRT, and ICM patient was 2.3, 2.4, 2.4, and 9.3 hours, respectively (Table 1). Conclusion CIED clinic workflow is complex and requires significant staff time. Remote monitoring is an efficient complement to in-office visits, allowing for continuous follow-up of patients. Future research should examine heterogeneity in clinic processes to identify the most efficient workflow. Funding Acknowledgement Type of funding source: Private company. Main funding source(s): Medtronic

Background Cloud-based solutions offer the ability to centrally and continuously enhance detection algorithms for arrhythmias such as Atrial Fibrillation (AF) based on generated data. Methods The Coala Heart Monitor (Coala) system was evaluated by manual interpretation of 1,000 consecutive anonymous printouts of chest- and thumb-ECG waveforms, without any exclusion. The anonymized printouts were blinded from algorithm analysis, apart from gender and age within a 10-year span. The recordings were derived from actual Coala users in Sweden with no training, control or influence, under a defined time period. The prevalence of cardiac conditions in the user population was unknown. The blinded recordings were manually interpreted by a trained cardiologist. The interpretation was compared with the automatic analysis performed by an algorithm in the Coala Cloud to evaluate ECG signal performance and calculate performance metrics. An enhanced algorithm utilizing P-wave detection was then evaluated on the data set and compared with the performance metrics of the existing algorithm. Results Metric Results with current algorithm Results with enhanced algorithm Prevalence of AF in the recordings 14.4% (143 of 990 recordings) 14.4% (143 of 990 recordings) Sensitivity for detecting AF 0.972 (95% CI = 0.930–0.992) 0.951 Specificity for detecting AF 0.946 (95% CI = 0.928–0.960) 0.976 Negative predictive value for detecting AF 0.995 (95% CI = 0.987–0.999) 0.992 Positive predictive value for detecting AF 0.751 (95% CI = 0.683–0.812) 0.872 Accuracy 0.950 0.973 Conclusion The enhanced algorithm was found to improve the Positive Predictive Value for detecting AF as compared to the existing algorithm (0.872 vs 0.751). The reduced sensitivity for the enhanced algorithm was due to 3 consecutive recordings from a single individual who had misplaced the Coala with corresponding altered morphology of the ECG signal. The recordings were still reported as having an irregular rhythm by the algorithm. The evolution demonstrates that cloud-based systems offer an ability to enhance detection accuracy by using reference data to train algorithms.

Introduction Current European guidelines recommend the use of insertable cardiac monitors (ICMs) in the early phase of evaluation for patients with recurrent, unexplained syncope and a likelihood of recurrence during the device battery life. The ongoing Reveal LINQ Registry collects real-world data on clinical actions guided by the insertable cardiac monitor (ICM) in these patients. Purpose To characterize ICM-guided diagnosis and treatment of syncope patients in Europe. Methods The Reveal LINQ Registry is a prospective, observational, multi-center study evaluating real-world performance of the ICM. Patients from European centres who had syncope indicated as the reason for ICM implant were included in the analysis. Kaplan-Meier methods were used to determine the percentage of patients receiving treatment. Results In total, 139 patients from 12 centres [Portugal (78); The Netherlands (30); Belgium (12); Italy (10); Germany (5); United Kingdom (4)] received an ICM to monitor for unexplained syncope and had at least one follow-up visit. The mean age was 61.2 and 51.1% were female. During a mean follow-up time of 11.2 months, 31 patients experienced at least one recurrent syncope event classified as: cardiac (9), vasovagal (4), idiopathic (8) and unknown (10). An arrhythmia was diagnosed in 14 (45.2%) patients with a recurrent event and clinical actions were taken in 12 (38.7%) patients (10 IPGs, and 2 AF ablations). Among patients without a recurrence, 25 (23.1%) had an arrhythmia diagnosed and 20 (18.5%) had a clinical action taken (13 therapeutic device implants, 4 ablations, and 3 medication changes). Overall, the rate of clinical actions was 32.6% after 18 months of ICM follow-up in the unexplained syncope population (Figure). Time to treatment Conclusion Clinical actions are taken in approximately one third of unexplained syncope patients monitored with an ICM after 18 months of follow up. Acknowledgement/Funding Medtronic