New implantable cardiac monitor with three-lead ECG and active noise detection

Lauschke, Joerg; Busch, Mathias; Haverkamp, Wilhelm; Bulava, Alan; Schneider, Regina; Andresen, Dietrich; Nägele, Herbert; Israel, Carsten W.; Hindricks, Gerhard; Bänsch, Dietmar

doi:10.1007/s00059-016-4492-7

Cited by 14 publications

(18 citation statements)

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“…As in this study, most of the studies were conducted using external Holter monitoring as a criterion standard for the presence or absence of AF. Biotronik ILRs have evaluated the performance of AF algorithms through two separate studies [22,23]. As most of the AF episodes confirmed on the Holter were detected on the ILR, they showed a high sensitivity of more than 90%.…”

Section: Discussionmentioning

confidence: 99%

“…The improved detection of AF occurrence and AF characterization compared to intermittent ECG monitoring could significantly impact the clinical treatment decisions [16]. However, many studies on AF detection using ILRs have shown a lower-than-expected positive predictive value (PPV) due to a higher rate of false positive episodes [22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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“…ECG is a field of rapid development of carriable devices, including implantable ones. [36][37][38][39] Some devices such as implantable cardioverter defibrillators require real-time classification of ECG data, which is a possible field of AI application. 40 These devices usually possess limited computational resources.…”

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confidence: 99%

Application of Neural Networks to 12-Lead Electrocardiography　― Current Status and Future Directions ―

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AI is a broad term representing the replication of human "intelligence" with machines that include but are not limited to computers. In the current medical field, the term "AI" mainly refers to a complex machine-learning model that automatically extracts information from data and which is, in most cases, based on an NN. Therefore, in this article, the term "AI" will be used to refer to such statistical models and the methods to create them. The use of AI is in rapid development in many areas such as image recognition, 9 language recognition 10 and automatic driving. 11 In particular, in the image recognition field, AI has achieved results exceeding human ability in speed and accuracy. The technology has received attention from the medical field because it may extend the utilization of complex medical data beyond the limit of human brain function that is unable to handle high-dimension data. 12,13 As expected, the application of AI to medical still-images has been greatly successful, 7,14,15 but AI has also produced striking results in other tasks such as electronic digitalized health record analysis, 16,17 and prediction of clinical outcome from ECG. 1,18-33 Of note, AI applied to the interpretation

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“…Unfortunately, using time-limited cardiac monitoring, such as the Holter monitor and external loop recorder (Seidl et al, 2000; Solbiati et al, 2016), the episodic and random nature of the arrhythmias and associated outcomes may not be captured. The ICM is one of the latest devices in long-term cardiac monitoring and may remain implanted for up to four years (Lauschke et al, 2016; Mittal et al, 2015), increasing the chances of capturing the heart rhythm at the time of the episode. The diagnostic yield of an ICM in undiagnosed syncope is between 43% and 52% compared to a device such as a Holter monitor, which only yields 6% to 20% detection (Kanters et al, 2016).…”

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confidence: 99%

Living with an Insertable Cardiac Monitor: Influences on Self-Care Management

et al. 2020

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The insertable cardiac monitor (ICM) is technology for diagnosing cardiac arrhythmias. The perception of those living with the device and how this relates to self-care management is unknown. The aim of this study was to explore the experiences of those with undiagnosed cardiac symptoms living with an ICM. This study used a qualitative descriptive design. Analysis of data was by intraparticipant analysis, interparticipant analysis, and interrelationships. Three global categories emerged: (a) influences on self-care, (b) dealing and (c) monitoring. Self-care management after insertion of the ICM was determined by the participant’s perception of health, what symptoms they were experiencing and whether there was a positive or negative experience with the clinician. Many indicated little to no regular communication regarding symptoms and ICM results. Increasing communication relevant to management of health and long-term findings may assist in enhancing physical and psychological health.

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New implantable cardiac monitor with three-lead ECG and active noise detection

Abstract: BioMonitor effectively detects patients with bradycardia, tachycardia, AF, or asystole. Active noise detection seems to reduce the transmission of meaningless data without diminishing the positive predictive value of the device.

Cited by 14 publications

References 4 publications

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

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

Application of Neural Networks to 12-Lead Electrocardiography　― Current Status and Future Directions ―

Living with an Insertable Cardiac Monitor: Influences on Self-Care Management

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New implantable cardiac monitor with three-lead ECG and active noise detection

Abstract: BioMonitor effectively detects patients with bradycardia, tachycardia, AF, or asystole. Active noise detection seems to reduce the transmission of meaningless data without diminishing the positive predictive value of the device.

Cited by 14 publications

References 4 publications

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

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

Application of Neural Networks to 12-Lead Electrocardiography ― Current Status and Future Directions ―

Living with an Insertable Cardiac Monitor: Influences on Self-Care Management

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Product

Resources

About

Application of Neural Networks to 12-Lead Electrocardiography　― Current Status and Future Directions ―