Real-world performance of an enhanced atrial fibrillation detection algorithm in an insertable cardiac monitor

Mittal, Suneet; Sarkar, Shantanu; Koehler, Jodi; Warman, Eddy; Tomson, Todd T.; Passman, Rod

doi:10.1016/j.hrthm.2016.05.010

Cited by 80 publications

(56 citation statements)

References 19 publications

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“…The majority of inappropriate detections were caused by irregular rhythms detected as AF. One possibility to improve the performance of AF detection is to extend the minimum duration for an AF episode to be detected . Unfortunately, the fact that our device programming was not standardized and our limited sample size limits our ability to report on differences in performance depending on detection criteria.…”

Section: Discussionmentioning

confidence: 99%

“…In the duration‐based approach, Reveal LINQ showed 98.4% sensitivity and 99.5% specificity, compared with 93.6% and 99.2% for the BioMonitor 2, respectively (Table ). However, real‐world performance of devices is often worse than in controlled trials and depends on the AF incidence in the monitored population, the programmed sensitivity of AF algorithm, and the duration of detected AF episodes …”

Section: Discussionmentioning

confidence: 99%

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Clinical evaluation of a small implantable cardiac monitor with a long sensing vector

Piorkowski¹,

Busch

Nölker

et al. 2019

Pacing Clinical Electrophis

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IntroductionWe conducted this study to show the safety and efficacy of a new implantable cardiac monitor (ICM), the BioMonitor 2 (Biotronik SE & Co. KG; Berlin, Germany), and to describe the arrhythmia detection performance.MethodsThe BioMonitor 2 has an extended sensing vector and is implanted close to the heart. It can transmit up to six subcutaneous electrocardiogram strips by Home Monitoring each day. We enrolled 92 patients with a standard device indication for an ICM in a single‐arm, multicenter prospective trial. Patients were followed for 3 months, and 48‐h Holter recordings were used to evaluate the arrhythmia detection performance.ResultsOne patient withdrew consent and in one patient, the implantation failed. Two study device‐related serious adverse events were reported, satisfying the primary safety hypothesis. Implantations took 7.4 ± 4.4 min from skin cut to suture. At 1 week, the R‐wave amplitude was 0.75 ± 0.53 mV. In the 82 patients with completed Holter recordings, all patients with arrhythmias were correctly identified. False positive detections of arrhythmia were mostly irregular rhythms wrongly detected as atrial fibrillation (episode‐based positive predictive value 72.5%). Daily Home Monitoring transmission was 94.9% successful.ConclusionSafety and efficacy of the new device has been demonstrated. The detected R‐wave amplitudes are large, leading to a low level of inappropriate detections due to over‐ or undersensing.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Clinical evaluation of a small implantable cardiac monitor with a long sensing vector

Piorkowski¹,

Busch

Nölker

et al. 2019

Pacing Clinical Electrophis

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“…AFRs with 98% success rate were distinguished. S. Mittal et al (2016) performed AF detection from ECG signals at various time intervals. As a result, they achieved success rates changing between 39% and 96%.…”

Section: Scientific Literature Scanningmentioning

confidence: 99%

Atri̇yal Fi̇bri̇lasyonun Rr Araliği İle Otomati̇k Tespi̇ti̇

Güzeler

Bilgin

2019

Mühendislik Bilimleri Ve Tasarım Dergisi

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Heart diseases are rapidly increasing worldwide and in our country. This increase causes difficulties in the diagnosis processes of heart diseases. Considering these problems, the studies of engineering applications related to medical science give effective results in terms of solutions. By means of engineering devices and algorithms, positive contributions are made to medical applications. These contributions assist physicians especially in the diagnosis stages and speed up these processes. In this study, a new algorithm is developped so that Atrial Fibrillation (AF), which is the most common type of arrhythmia encountered, can be automatically detected at a high success rate. Electrocardiogram (ECG) data used in this study were obtained from physiobank ATM database. 31 samples of Atrial Fibrillation Rhythm (AFR) and 31 samples of Normal Sinus Rhythm (NSR) were obtained from this database. RR Interval (RRI) sequences being 12 hours long are used in the study. The change of the RRI sequences is an important parameter for AF. The RRI sequences are re-sampled using signal pre-processing techniques. The Discrete Wavelet Transform (DWT) was then applied to the resampled signals. In this way, feature extraction process is performed and the wavelet energies of these signals are visually examined with boxplot. The wavelet energies of the RRI sequences are classified by the Support Vector Machine (SVM). Finally, AFR and NSR are successfully separated as 99.60% achievement.

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“…As AF-detection algorithms are based primarily on R-R interval irregularities, false positives due to premature beats are not uncommon, particularly with short episodes. 21 Furthermore, the devices are insensitive to AF episodes o2 min. However, ICM use in post-ablation patients is increasing both for research and clinical care indications and offers an attractive alternative to standard external monitoring, particularly if the information is necessary for clinical decision making.…”

Section: Af Monitoring and Management Using Implantable And Wearable mentioning

confidence: 99%

Monitoring for AF: Identifying the Burden of Atrial Fibrillation and Assessing Post-Ablation

Passman¹

2017

JICRM

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ABSTRACT. The management of atrial fibrillation (AF) is among the most challenging aspects of cardiology and uncertainties abound concerning stroke assessment and stroke risk reduction. Currently, AF is viewed as a dichotomous variable (fully present or absent) when it comes to stroke risk; there is no regard to the amount of AF either spontaneously or due to rhythm control strategies. For this reason, monitoring in patients with a known AF history, particularly after ablation, has focused on easily measured outcomes such as time to recurrence. However, emerging data suggest that thresholds exist between stroke risk and AF quantity as measured by either duration or burden. As a result, there is an increasing interest in long-term continuous monitoring following a rhythm control strategy to assess efficacy beyond typical symptom reduction. Insertable cardiac monitors (ICMs) with AF-sensing algorithms and remote data transmission capabilities can be used for this purpose, and wearable devices with similar functions are on the horizon. In addition to their diagnostic potential, these tools are also being used therapeutically with efforts to target anticoagulation therapy only in response to AF episodes.

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Real-world performance of an enhanced atrial fibrillation detection algorithm in an insertable cardiac monitor

Abstract: The performance of LINQ ICM is dependent on the AF incidence rate in the population being monitored, the programmed sensitivity of AF algorithm, and the duration of detected AF episodes.

Cited by 80 publications

References 19 publications

Clinical evaluation of a small implantable cardiac monitor with a long sensing vector

Clinical evaluation of a small implantable cardiac monitor with a long sensing vector

Atri̇yal Fi̇bri̇lasyonun Rr Araliği İle Otomati̇k Tespi̇ti̇

Monitoring for AF: Identifying the Burden of Atrial Fibrillation and Assessing Post-Ablation

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