Implantable loop recorder in clinical practice

Management of Anesthesia for Procedures in the Cardiac Electrophysiology Laboratory

The complexity of cardiac electrophysiology procedures has increased significantly over the past three decades. Anesthesia requirements of these procedures can be different based on patient- and procedure-specific factors. This manuscript outlines various anesthesia strategies for cardiac implantable electronic devices and electrophysiology procedures including pre-procedural, procedural and post-procedural management. A team-based approach with collaboration between cardiac electrophysiologists and anesthesiologists is required with careful pre-procedural and intra-procedural planning. Given the recent advances in electrophysiology, there is a need for specialized cardiac electrophysiology anesthesia care to improve the efficacy and safety of the procedures.

Assessing the efficacy of machine learning algorithms for syncope classification: A systematic review

Syncope is a transient loss of consciousness with rapid onset. The aims of the study were to systematically evaluate available machine learning (ML) algorithm for supporting syncope diagnosis to determine their performance compared to existing point scoring protocols. We systematically searched IEEE Xplore, Web of Science, and Elsevier for English articles (Jan 2011 - Sep 2021) on individuals aged five and above, employing ML algorithms in syncope detection with Head-up titl table test (HUTT)-monitored hemodynamic parameters and reported metrics. Extracted data encompassed subject count, age range, syncope protocols, ML type, hemodynamic parameters, and performance metrics. Of the 6301 studies initially identified, 10 studies, involving 1205 participants aged 5 to 82 years, met the inclusion criteria, and formed the basis for it. Selected studies must use ML algorithms in syncope detection with hemodynamic parameters recorded throughout HUTT. The overall ML algorithm performance achieved a sensitivity of 88.8% (95% CI: 79.4-96.1%), specificity of 81.5% (95% CI: 69.8-92.8%) and accuracy of 85.8% (95% CI: 78.6-92.8%). Machine learning improves syncope diagnosis compared to traditional scoring, requiring fewer parameters. Future enhancements with larger databases are anticipated. Integrating ML can curb needless admissions, refine diagnostics, and enhance the quality of life for syncope patients.

Machine Learning Modeling to Predict Atrial Fibrillation Detection in Embolic Stroke of Undetermined Source Patients

BACKGROUND

In patients with embolic stroke of undetermined source (ESUS), occult atrial fibrillation (AF) has been implicated as a key source of cardioembolism. However, only a minority acquire implantable cardiac loop recorders (ILRs) to detect occult paroxysmal AF, partly due to financial cost and procedural inconvenience. Without the initiation of appropriate anticoagulation, these patients are at risk of increased ischemic stroke recurrence. Hence, cost-effective and accurate methods of predicting AF in ESUS patients are highly sought after.

OBJECTIVE

We aimed to incorporate clinical and echocardiography data into machine learning (ML) algorithms for AF prediction on ILRs in ESUS.

METHODS

This was a single-center cohort study that included 157 consecutive patients diagnosed with ESUS from October 2014 to October 2017 who had ILR evaluation. We developed four ML models, with hyperparameters tuned, to predict AF detection on an ILR.

RESULTS

The median age of the cohort was 67 (IQR 59-74) years old and the median monitoring duration was 1051 (IQR 478-1287) days. Of the 157 patients, 32 (20.4%) had occult AF detected on the ILR. Support vector machine predicted for AF with a 95% confidence interval area under the receiver operating characteristic curve (AUC) of 0.736-0.737, multilayer perceptron with an AUC of 0.697-0.708, XGBoost with an AUC of 0.697-0.697, and random forest with an AUC of 0.663-0.674. ML feature importance found that age, HDL-C, and admitting heart rate were important non-echocardiography variables, while peak mitral A-wave velocity and left atrial volume were important echocardiography parameters aiding this prediction.

CONCLUSION

Machine learning modeling incorporating clinical and echocardiographic variables predicted AF in ESUS patients with moderate accuracy.

Repositioning of the Insertable Cardiac Monitor Through the Same Incision to Avoid T-wave Oversensing

Insertable cardiac monitor (ICM), used for long-term heart rhythm monitoring, often experiences diagnostic challenges such as T-wave oversensing, leading to false positives. This case report presents a novel approach to rectifying T-wave oversensing in ICM implantations. In this case, we are sharing a 38-year-old female with recurrent syncopal episodes who underwent ICM implantation (LUX-Dx™, ICM-Boston Scientific, Marlborough, United States). Post-implantation, T-wave oversensing was detected. Instead of the usual readjustment or reinsertion, we employed a non-invasive method of repositioning the ICM at a 45-degree angle toward the right side of the heart through the existing incision. This effectively resolved the oversensing issue without complications or the need for a new incision. ICMs are vital in linking symptoms to arrhythmias, especially in cases where standard diagnostic tools fall short. Despite their utility, ICMs are susceptible to T-wave oversensing due to subcutaneous placement. Our case demonstrates a successful alternative approach to address this, enhancing ICM's diagnostic accuracy without invasive procedures. This case highlights the potential of repositioning ICMs as a simple, non-invasive solution to overcome T-wave oversensing issues. It calls for further research and discussion within the medical community to explore its wider applicability, thereby improving ICM efficacy in clinical practice. The patient experienced no complications following the procedure during the three-month visit with appropriate sensing, validating this approach as a feasible option in similar cases.

A combination of logical judging circuit and water-resistant ultrathin film PEDOT: PSS electrode for noninvasive ECG measurement

Heart disease-related deaths have increased in recent decades, with most patients dying of sudden cardiac arrest. In such instances, the effect of regular electrocardiogram (ECG) measurements is minimal. Therefore, long-term ECG monitoring has become increasingly important. In this paper, we report a non-adhesive high accuracy ECG monitoring system that can be used in various scenarios without interfering with daily activities. The ECG ultra-thin film electrode is made by water-resistant material based on poly(3,4-ethylenedioxythiophene) poly(4-styrenesulfonate) (PEDOT: PSS) electrode doped with ethylene glycol (EG) and xylitol, to improve the noise signal caused by sweat. The optimal ratio of the three ingredients of PEDOT: PSS/xylitol/EG was determined experimentally to accommodate the ECG monitoring. By using the proposed selectively closed multi-channel single-lead logic circuit, the noise of ECG signal received from the proposed film electrode can be successfully reduced during broad-area electrode measurements, thus to improve ECG measurement accuracy.

Monitoring of Remotely Reprogrammable Implantable Loop Recorders With Algorithms to Reduce False-Positive Alerts

BACKGROUND

Implantable loop recorders (ILRs) are increasingly placed for arrhythmia detection. However, historically, ≈75% of ILR alerts are false positives, requiring significant time and effort for adjudication. The LINQII and LUX-Dx are remotely reprogrammable ILRs with dual-stage algorithms using artificial intelligence to reduce false positives, but their utility in routine clinical practice has not been studied.

METHODS AND RESULTS

We identified patients with the LINQII and LUX-Dx who were monitored by the Veterans Affairs National Cardiac Device Surveillance Program between March and June 2022. ILR programming was customized on the basis of implant indication. All alerts and every 90-day scheduled transmissions were manually reviewed. ILRs were remotely reprogrammed, as appropriate, after false-positive alerts or 2 consecutive same-type alerts, unless there was ongoing clinical need for that alert. Outcomes were total number of transmissions and false positives. We performed medical record review to determine if patients experienced any adverse clinical events, including hospitalization and mortality. Among 117 LINQII patients, there were 239 total alerts, 43 (18.0%) of which were false positives. Among 105 LUX-Dx patients, there were 300 total alerts, 115 (38.3%) of which were false positives. LINQIIs were reprogrammed 22 times, resulting in a decrease in median alerts/day from 0.13 to 0.03. LUX-Dx ILRs were reprogrammed 52 times, resulting in a decrease from 0.15 to 0.01 median alerts/day. There were no adverse clinical events that could have been identified by superior or earlier arrhythmia detection.

CONCLUSIONS

ILRs with artificial intelligence algorithms and remote reprogramming ability are associated with reduced alert burden because of higher true-positive rates than prior ILRs, without missing potentially consequential arrhythmias.

False-positive alarms in patients with implantable loop recorder followed by remote monitoring: A systematic review

Remote Monitoring (RM) has been shown to provide useful information about arrhythmic events in patients with implantable loop recorders (ILRs), however there is few and conflicting data about the false positive (FP) alarms burden and characteristics among ILR recipients. The aim of the present systematic review was to evaluate incidence and characteristics of FP alarms among ILR patients followed by RM. We developed a systematic research in Embase, MEDLINE and PubMed databases and selected all papers focused on false positive ILR transmissions published from June 1, 2013 to June 1, 2023. Case reports, meeting summaries, posters and simple reviews were excluded. Twelve reports were finally selected, including five prospective and seven retrospective studies. Information about population characteristics, device type and setting, overall transmissions and FP alarms and any adopted strategies to reduce them were extracted from an overall population of 3.305 patients. FP alarms were 59.7% of the overall remote transmissions and were found in 1/5 of the analyzed population. FP alarms for atrial fibrillation were the most common cause of false transmissions and were mainly due to premature atrial and ventricular complexes. No clinical predictors of FP alarms were identified, except for nonparasternal ILR implantation site. Since the overload work due to FP alarms might reduce the benefit of remote monitoring of ILR patients, the device optimization is an important step until an help from machine-learning algorithms is available.

Breast MRI in patients with implantable loop recorder: initial experience

OBJECTIVES

To investigate the feasibility of breast MRI exams and guided biopsies in patients with an implantable loop recorder (ILR) as well as the impact ILRs may have on image interpretation.

MATERIALS AND METHODS

This retrospective study examined breast MRIs of patients with ILR, from April 2008 to September 2022. Radiological reports and electronic medical records were reviewed for demographic characteristics, safety concerns, and imaging findings. MR images were analyzed and compared statistically for artifact quantification on the various pulse sequences.

RESULTS

Overall, 40/82,778 (0.049%) MRIs during the study period included ILR. All MRIs were completed without early termination. No patient-related or device-related adverse events occurred. ILRs were most commonly located in the left lower-inner quadrant (64.6%). The main artifact was a signal intensity (SI) void in a dipole formation in the ILR bed with or without areas of peripheral high SI. Artifacts appeared greatest in the cranio-caudal axis (p < 0.001), followed by the anterior-posterior axis (p < 0.001), and then the right-left axis. High peripheral rim-like SI artifacts appeared on the post-contrast and subtracted T1-weighted images, mimicking suspicious enhancement. Artifacts were most prominent on diffusion-weighted (p < 0.001), followed by T2-weighted and T1-weighted images. In eight patients, suspicious findings were found on MRI, resulting in four additional malignant lesions. Of six patients with left breast cancer, the tumor was completely visible in five cases and partially obscured in one.

CONCLUSION

Breast MRI is feasible and safe among patients with ILR and may provide a significant diagnostic value, albeit with localized, characteristic artifacts.

CLINICAL RELEVANCE STATEMENT

Indicated breast MRI exams and guided biopsies can be safely performed in patients with implantable loop recorder. Nevertheless, radiologists should be aware of associated limitations including limited assessment of the inner left breast and pseudo-enhancement artifacts.

KEY POINTS

• Breast MRI in patients with an implantable loop recorder is an infrequent, feasible, and safe procedure. • Despite limited breast visualization of the implantable loop recorder bed and characteristic artifacts, MRI depicted additional lesions in 8/40 (20%) of cases, half of which were malignant. • Breast MRI in patients with an implantable loop recorder should be performed when indicated, taking into consideration typical associated artifacts.

Survey of Transfer Learning Approaches in the Machine Learning of Digital Health Sensing Data

Machine learning and digital health sensing data have led to numerous research achievements aimed at improving digital health technology. However, using machine learning in digital health poses challenges related to data availability, such as incomplete, unstructured, and fragmented data, as well as issues related to data privacy, security, and data format standardization. Furthermore, there is a risk of bias and discrimination in machine learning models. Thus, developing an accurate prediction model from scratch can be an expensive and complicated task that often requires extensive experiments and complex computations. Transfer learning methods have emerged as a feasible solution to address these issues by transferring knowledge from a previously trained task to develop high-performance prediction models for a new task. This survey paper provides a comprehensive study of the effectiveness of transfer learning for digital health applications to enhance the accuracy and efficiency of diagnoses and prognoses, as well as to improve healthcare services. The first part of this survey paper presents and discusses the most common digital health sensing technologies as valuable data resources for machine learning applications, including transfer learning. The second part discusses the meaning of transfer learning, clarifying the categories and types of knowledge transfer. It also explains transfer learning methods and strategies, and their role in addressing the challenges in developing accurate machine learning models, specifically on digital health sensing data. These methods include feature extraction, fine-tuning, domain adaptation, multitask learning, federated learning, and few-/single-/zero-shot learning. This survey paper highlights the key features of each transfer learning method and strategy, and discusses the limitations and challenges of using transfer learning for digital health applications. Overall, this paper is a comprehensive survey of transfer learning methods on digital health sensing data which aims to inspire researchers to gain knowledge of transfer learning approaches and their applications in digital health, enhance the current transfer learning approaches in digital health, develop new transfer learning strategies to overcome the current limitations, and apply them to a variety of digital health technologies.

Artificial intelligence in rheumatoid arthritis: potential applications and future implications

The widespread adoption of digital health records, coupled with the rise of advanced diagnostic testing, has resulted in an explosion of patient data, comparable in scope to genomic datasets. This vast information repository offers significant potential for improving patient outcomes and decision-making, provided one can extract meaningful insights from it. This is where artificial intelligence (AI) tools like machine learning (ML) and deep learning come into play, helping us leverage these enormous datasets to predict outcomes and make informed decisions. AI models can be trained to analyze and interpret patient data, including physician notes, laboratory testing, and imaging, to aid in the management of patients with rheumatic diseases. As one of the most common autoimmune diseases, rheumatoid arthritis (RA) has attracted considerable attention, particularly concerning the evolution of diagnostic techniques and therapeutic interventions. Our aim is to underscore those areas where AI, according to recent research, demonstrates promising potential to enhance the management of patients with RA.

Identification of acute ST-elevation myocardial infarction via remote implantable loop recorder monitor

The indications for the use of implantable loop recorders include the evaluation of unexplained palpitations and syncope, embolic stroke of undetermined source, dizziness and lightheadedness presumed to be due to arrhythmogenic etiology, and for atrial fibrillation to guide antiarrhythmic drug therapy or catheter ablation efficacy. Long-term monitoring is especially beneficial if symptoms occur sporadically or are asymptomatic in nature. This is the first case to our knowledge of an acute ST-elevation myocardial infarction which was identified from remote monitoring of an implantable loop recorder through a device clinic.

Novel algorithms improve arrhythmia detection accuracy in insertable cardiac monitors

INTRODUCTION

Insertable cardiac monitors (ICMs) are commonly used to diagnose cardiac arrhythmias. False detections in the latest ICM systems remain an issue, primarily due to inaccurate R-wave sensing. New discrimination algorithms were developed and tested to reduce false detections of atrial fibrillation (AF), pause, and tachycardia episodes in ICMs.

METHODS

Stored electrograms (EGMs) of AF, pause, and tachycardia episodes detected by Abbott Confirm Rx™ ICMs were extracted from the Merlin.net™ Patient Care Network, and manually adjudicated to establish independent training and testing datasets. New discrimination algorithms were developed to reject false episodes due to inaccurate R-wave sensing, P-wave identification, and R-R interval patterns. The performance of these new algorithms was quantified by false positive reduction (FPR) and true positive maintenance (TPM), relative to the existing algorithms.

RESULTS

The new AF detection algorithm was trained on 5911 EGMs from 744 devices, resulting in 66.9% FPR and 97.8% TPM. In the testing data set of 1354 EGMs from 119 devices, this algorithm achieved 45.8% FPR and 97.0% TPM. The new pause algorithm was trained on 7178 EGMs from 1490 devices, resulting in 70.9% FPR and 98.7% TPM. In the testing data set of 1442 EGMs from 340 devices, this algorithm achieved 74.4% FPR and 99.3% TPM. The new tachycardia algorithm was trained on 520 EGMs from 204 devices, resulting in 57.0% FPR and 96.6% TPM. In the testing data set of 459 EGMs from 237 devices, this algorithm achieved 57.9% FPR and 96.5% TPM.

CONCLUSION

The new algorithms substantially reduced false AF, pause, and tachycardia episodes while maintaining the majority of true arrhythmia episodes detected by the Abbott ICM algorithms that exist today. Implementing these algorithms in the next-generation ICM systems may lead to improved detection accuracy, in-clinic efficiency, and device battery longevity.

The use of digital health in heart rhythm care

INTRODUCTION

Digital health is a broad term that includes telecommunication technologies to collect, share and manipulate health information to improve patient health and health care services. With the growing use of wearables, artificial intelligence, machine learning, and other novel technologies, digital health is particularly relevant to the field of cardiac arrhythmias, with roles pertinent to education, prevention, diagnosis, management, prognosis, and surveillance.

AREAS COVERED

This review summarizes information on the clinical use of digital health technology in arrhythmia care and discusses its opportunities and challenges.

EXPERT OPINION

Digital health has begun to play an essential role in arrhythmia care regarding diagnostics, long-term monitoring, patient education and shared decision making, management, medication adherence, and research. Despite remarkable advances, integrating digital health technologies into healthcare faces challenges, including patient usability, privacy, system interoperability, physician liability, analysis and incorporation of the huge amount of real-time information from wearables, and reimbursement. Successful implementation of digital health technologies requires clear objectives and deep changes to existing workflows and responsibilities.

Subcutaneous mechano-electrocardiogram (MECG) sensor for complementary cardiac diagnosis

Since the heart pumps out the blood through the excitation-contraction coupling, simultaneous monitoring of the electrical and mechanical characteristics is beneficial for comprehensive diagnosis of cardiac disorders. Currently, these characteristics are monitored separately with electrocardiogram (ECG) and medical imaging techniques. This work presents a fully implantable device named mechano-electrocardiogram (MECG) sensor that can measure mechanocardiogram (MCG) and ECG together. The key to the success is fabrication of permeable electrodes on a single low-modulus porous nanofiber mat, which helps immediate adhesion of the sensor on the tissue. A strain-insensitive electrode is used as the ECG electrode and a strain-sensitive electrode is used for MCG. The MECG device is implanted subcutaneously in the skin above the heart of the rat. Through a vasopressor (phenylephrine) injection test, the MECG signals indicate that the MCG amplitude is related with blood pressure and the ECG peak interval is more related with heart rate. These results confirm that the MECG device is clinically meaningful for continuous and comprehensive monitoring of the electrical and mechanical characteristics of the heart.

Creating a data dictionary for pediatric autonomic disorders

PURPOSE

Whether evaluating patients clinically, documenting care in the electronic health record, performing research, or communicating with administrative agencies, the use of a common set of terms and definitions is vital to ensure appropriate use of language. At a 2017 meeting of the Pediatric Section of the American Autonomic Society, it was determined that an autonomic data dictionary comprising aspects of evaluation and management of pediatric patients with autonomic disorders would be an important resource for multiple stakeholders.

METHODS

Our group created the list of terms for the dictionary. Definitions were prioritized to be obtained from established sources with which to harmonize. Some definitions needed mild modification from original sources. The next tier of sources included published consensus statements, followed by Internet sources. In the absence of appropriate sources, we created a definition.

RESULTS

A total of 589 terms were listed and defined in the dictionary. Terms were organized by Signs/Symptoms, Triggers, Co-morbid Disorders, Family History, Medications, Medical Devices, Physical Examination Findings, Testing, and Diagnoses.

CONCLUSION

Creation of this data dictionary becomes the foundation of future clinical care and investigative research in pediatric autonomic disorders, and can be used as a building block for a subsequent adult autonomic data dictionary.

Implantable loop recorder detection for atrial fibrillation to prevent stroke in high-risk patients

ABSTRACT

Implantable loop recorders (ILRs) are cardiac-monitoring devices that detect dangerous dysrhythmias, such as atrial fibrillation (AF). This article discusses whether ILRs can prevent strokes in high-risk patients by detecting AF.

Effectiveness of implantable loop recorder and Holter electrocardiographic monitoring for the detection of arrhythmias in patients with peripartum cardiomyopathy

BACKGROUND

Patients with peripartum cardiomyopathy (PPCM) are at increased risk of sudden cardiac death (SCD). However, the exact underlying mechanisms of SCD in PPCM remain unknown. By means of extended electrocardiographic monitoring, we aimed to systematically characterize the burden of arrhythmias occurring in patients with newly diagnosed PPCM.

METHODS AND RESULTS

Twenty-five consecutive women with PPCM were included in this single-centre, prospective clinical trial and randomised to receiving either 24 h-Holter ECG monitoring followed by implantable loop recorder implantation (ILR; REVEAL XT, Medtronic^®) or 24 h-Holter ECG monitoring alone. ILR + 24 h-Holter monitoring had a higher yield of arrhythmic events compared to 24 h-Holter monitoring alone (40% vs 6.7%, p = 0.041). Non-sustained ventricular tachycardia (NSVT) occurred in four patients (16%, in three patients detected by 24 h-Holter, and multiple episodes detected by ILR in one patient). One patient deceased from third-degree AV block with an escape rhythm that failed. All arrhythmic events occurred in patients with a severely impaired LV systolic function.

CONCLUSIONS

We found a high prevalence of potentially life-threatening arrhythmic events in patients with newly diagnosed PPCM. These included both brady- and tachyarrhythmias. Our results highlight the importance of extended electrocardiographic monitoring, especially in those with severely impaired LV systolic function. In this regard, ILR in addition to 24 h-Holter monitoring had a higher yield of VAs as compared to 24 h-Holter monitoring alone. In settings where WCDs are not readily available, ILR monitoring should be considered in patients with severely impaired LV systolic dysfunction, especially after uneventful 24 h-Holter monitoring.

TRIAL REGISTRATION

Pan African Clinical Trials Registry: PACTR202104866174807. Extended electrocardiographic monitoring for the detection of arrhythmias in PPCM. (CHB, complete heart block/third degree AV block; ECG, electrocardiogram; ILR, implantable loop recorder; NSVT, non-sustained ventricular tachycardia; PPCM, peripartum cardiomyopathy).

Diagnostic yield of an insertable cardiac monitor in a large patient population

Background

Insertable cardiac monitors (ICMs) are increasingly used for cardiac rhythm diagnosis with expanding indications. Little has been reported about their use and efficacy.

Objective

The study sought to evaluate the clinical utility of a novel ICM (Biotronik BIOMONITOR III) including the time to diagnosis in unselected patients with different ICM indications.

Methods

Patients from 2 prospective clinical studies were included to determine the diagnostic yield of the ICM. The primary endpoint was time to clinical diagnosis per implant indication or to the first change in atrial fibrillation (AF) therapy.

Results

A total of 632 patients were included with a mean follow-up of 233 ± 168 days. Of 384 patients with (pre)syncope, 34.2% had a diagnosis at 1 year. The most frequent therapy was permanent pacemaker implantation. Of 133 patients with cryptogenic stroke, 16.6% had an AF diagnosis at 1 year, resulting in oral anticoagulation. Of 49 patients with an indication for AF monitoring, 41.0% had a relevant change in AF therapy based on ICM data at 1 year. Of 66 patients with other indications, 35.4% received a rhythm diagnosis at 1 year. Moreover, 6.5% of the cohort had additional diagnoses: 26 of 384 patients with syncope, 8 of 133 patients with cryptogenic stroke, and 7 of 49 patients with AF monitoring.

Conclusion

In a large unselected patient population with heterogeneous ICM indications, the primary endpoint of rhythm diagnosis was achieved in ∼1 in 4, and additional clinically relevant findings was achieved in 6.5% of patients at short-term follow-up.

Patients' Information Needs Related to a Monitoring Implant for Heart Failure: Co-designed Study Based on Affect Stories

BACKGROUND

RealWorld4Clinic is a European consortium that is currently developing an implantable monitoring device for acute heart failure prevention.

OBJECTIVE

This study aimed to identify the main issues and information needs related to this new cardiac implant from the patients' perspective.

METHODS

A total of 3 patient collaborators were recruited to help us design the study. During 4 remotely held meetings (each lasting for 2 hours), we defined the main questions and hypotheses together. Next, 26 additional interviews were conducted remotely to test these hypotheses. During both phases, we used affect stories, which are life narratives focusing on affect and the relationship between patients and the care ecosystem, to highlight the main social issues that should be addressed by the research according to the patients.

RESULTS

Context of diagnosis, age, and severity of illness strongly influence patient experience. However, these variables do not seem to influence the choice regarding being implanted, which relies mostly on the individual patient's trust in their physicians. It seems that the major cause of anxiety for the patient is not the implant but the disease itself, although some people may initially be concerned over the idea of becoming a cyborg. Remote monitoring of cardiac implants should draw on existing remote disease management programs focusing on a long-term relationship between the patient and their medical team.

CONCLUSIONS

Co-design with affect stories is a useful method for quickly identifying the main social issues related to information about a new health technology.

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.

Contemporary Considerations in the Evolution of Wearable Technology for Arrhythmia Detection

Arrhythmias are an increasingly common cause of hospital admissions worldwide. Late detection of arrhythmias is associated with a significantly increased risk of cardiovascular complications. Early identification and management of life-threatening arrhythmias is paramount to reduce mortality. Wearable technologies are now widespread among the general population, providing a continuous output of healthcare data. However, this data are not routinely integrated into clinical practice. Here, we begin by outlining the current landscape in wearable technology for aiding arrhythmia detection; we then consider the clinical impact of wearable technology for both clinicians and patients; we further highlight the latest and emerging trials in wearable technology for arrhythmia detection and finally postulate the wider implications of the expansion of such cardiac devices.

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.

Pre-deployment assessment of an AI model to assist radiologists in chest X-ray detection and identification of lead-less implanted electronic devices for pre-MRI safety screening: realized implementation needs and proposed operational solutions

Purpose

Chest X-ray (CXR) use in pre-MRI safety screening, such as for lead-less implanted electronic device (LLIED) recognition, is common. To assist CXR interpretation, we "pre-deployed" an artificial intelligence (AI) model to assess (1) accuracies in LLIED-type (and consequently safety-level) identification, (2) safety implications of LLIED nondetections or misidentifications, (3) infrastructural or workflow requirements, and (4) demands related to model adaptation to real-world conditions.

Approach

A two-tier cascading methodology for LLIED detection/localization and identification on a frontal CXR was applied to evaluate the performance of the original nine-class AI model. With the unexpected early appearance of LLIED types during simulated real-world trialing, retraining of a newer 12-class version preceded retrialing. A zero footprint (ZF) graphical user interface (GUI)/viewer with DICOM-based output was developed for inference-result display and adjudication, supporting end-user engagement and model continuous learning and/or modernization.

Results

During model testing or trialing using both the nine-class and 12-class models, robust detection/localization was consistently 100%, with mAP 0.99 from fivefold cross-validation. Safety-level categorization was high during both testing ( AUC ≥ 0.98 and ≥ 0.99 , respectively) and trialing (accuracy 98% and 97%, respectively). LLIED-type identifications by the two models during testing (1) were 98.9% and 99.5% overall correct and (2) consistently showed AUC ≥ 0.92 (1.00 for 8/9 and 9/12 LLIED-types, respectively). Pre-deployment trialing of both models demonstrated overall type-identification accuracies of 94.5% and 95%, respectively. Of the small number of misidentifications, none involved MRI-stringently conditional or MRI-unsafe types of LLIEDs. Optimized ZF GUI/viewer operations led to greater user-friendliness for radiologist engagement.

Conclusions

Our LLIED-related AI methodology supports (1) 100% detection sensitivity, (2) high identification (including MRI-safety) accuracy, and (3) future model deployment with facilitated inference-result display and adjudication for ongoing model adaptation to future real-world experiences.

Cerebral Seizures in an Adolescent with Jervell and Lange-Nielsen Syndrome: It May Not Be Epilepsy

A 13-year-old girl with Jervell and Lange-Nielsen syndrome associated congenital long QT syndrome (LQTS) and central deafness was admitted for generalized seizures. LQTS had been diagnosed after birth and confirmed at genetic testing. β-blocker treatment was immediately started. Despite this, since the age of 12 months, recurrent cerebral seizures occurred leading to the diagnosis of epilepsy. Anti-convulsive therapy was initiated but without success. At the last admission, nadolol dosage seemed infratherapeutic. Considering malignant ventricular arrhythmias as the cause of seizures, the β-blocker dosage was adjusted to weight and levels of magnesium and potassium optimized. Furthermore, the patient received an implantable Medtronic Reveal LINQ Recorder^®. Since then, the adolescent has been asymptomatic with no arrhythmia documented. LQTS is due to one or more mutations of genes coding for ion channels. It may induce malignant ventricular arrhythmias and is a major cause of sudden cardiac death in children. Generalized cerebral seizures are extra-cardiac manifestations caused by decreased cerebral perfusion during ventricular arrhythmia. They are commonly misinterpreted as manifestations of epilepsy. For any patient with known or unknown LQTS who presents seizures with resistance to anti-convulsive therapy, a cardiac electrophysiological investigation should be performed promptly to ensure etiological diagnosis and optimize treatment.

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

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

Will Smartphone Applications Replace the Insertable Cardiac Monitor in the Detection of Atrial Fibrillation? The First Comparison in a Case Report of a Cryptogenic Stroke Patient

Background and Case

This case report exemplifies the clinical application of non-invasive photoplethysmography (PPG)-based rhythm monitoring in the awakening mobile health (mHealth) era to detect symptomatic and asymptomatic paroxysmal atrial fibrillation (AF) in a cryptogenic stroke patient. Despite extensive diagnostic workup, the etiology remains unknown in one out of three ischemic strokes (i.e., cryptogenic stroke). Prolonged cardiac monitoring can reveal asymptomatic atrial fibrillation in up to one-third of this population. This case report describes a cryptogenic stroke patient who received prolonged cardiac monitoring with an insertable cardiac monitor (ICM) as standard of care. In the context of a clinical study, the patient simultaneously monitored his heart rhythm with a PPG-based smartphone application. AF was detected simultaneously on both the ICM and smartphone application after three days of monitoring. Similar AF burden was detected during follow-up (five episodes, median duration of 28 and 34 h on ICM and mHealth, respectively, p = 0.5). The detection prompted the initiation of oral anticoagulation and AF catheter ablation procedure.

Conclusion

This is the first report of the cryptogenic stroke patient in whom PPG-based mHealth was able to detect occurrence and burden of the symptomatic and asymptomatic paroxysmal AF episodes with similar precision as ICM. It accentuates the potential role of PPG-based mHealth in prolonged cardiac rhythm monitoring in cryptogenic stroke patients.

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.

Long-term Arrhythmia Detection Using an Implantable Loop Recorder in Patients Receiving Psychotropic Medication

This cohort study evaluates the incidence of arrhythmia in patients receiving psychotropic medication by monitoring of electrocardiographic findings using an implantable loop recorder.

New Generation Miniaturized Insertable Cardiac Monitor with a Long Sensing Vector: Insertion Procedure, Sensing Performance, and Home Monitoring Transmission Success in a Real-World Population

Background

Objective

Methods

Results

Conclusion

Current and future treatment approaches for Barth syndrome

Barth Syndrome is an X-linked disorder of mitochondrial cardiolipin metabolism caused by pathogenic variants in TAFAZZIN with pleiotropic effects including cardiomyopathy, neutropenia, growth delay, and skeletal myopathy. Management requires a multidisciplinary approach to the organ-specific manifestations including specialists from cardiology, hematology, nutrition, physical therapy, genetics, and metabolism. Currently, treatment is centered on management of specific clinical features, and is not targeted toward remediating the underlying biochemical defect. However, two clinical trials have been recently undertaken which target the mitochondrial pathology of this disease: a study to examine the effects of elamipretide, a cardiolipin targeted agent, and a study to examine the effects of bezafibrate, a peroxisome proliferator-activated receptor (PPAR) agonist. Treatments to directly target the defective TAFAZZIN pathway are under development, including enzyme and gene therapies.

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.

Cardiac implantable electronic devices and cybersecurity

INTRODUCTION

Many cardiac devices, such as implantable cardioverter-defibrillators (ICD) and pacemakers (PPM), often involve a remote connection to allow for data transfer and accessibility from the device to the medical clinic. These devices are vulnerable to cybersecurity threats and data breach.

AREAS COVERED

The FDA, device manufacturers and professional cardiology societies work in conjunction to assess and evaluate potential areas of weakness in medical devices and formulate software update improvements to strengthen patient safety. We undertook a literature review focusing on the history, progression, and improvements in monitoring of cybersecurity vulnerabilities surrounding cardiovascular medical devices.

EXPERT OPINION

Cardiac device cybersecurity will continue to evolve and progress as more research is conducted on potential areas of vulnerabilities. The standard procedure as of now is for multiple perspectives from the FDA, professional organizations, device manufacturers, physicians, and patients to review and analyze the effectiveness of cybersecurity safeguards for these devices. We believe this practice will continue as it equally involves all stakeholders in relation to the manufacturing, distribution, and use of these devices. As information technology capabilities expand, safer and secure medical devices and cardiac technology to prevent the threat of hacking will continue to expand and improve.

[Remote monitoring of implantable monitors : Towards coverage ? Evaluation of the procedure by the French National Authority for Health]

Implantable cardiac monitors are recommended and reimbursed in two specific cases: the etiological diagnosis of unexplained recurrent syncope and the etiological diagnosis of a cryptogenic ischemic stroke. According to the French National Authority for Health (HAS), remote monitoring "leads to early diagnosis and therapeutic care". However, remote tracking of these devices for diagnostic purposes is not included in the ETAPES program, which will end soon. This article presents a summary of the evaluation by HAS of the remote monitoring of implantable cardiac monitors. It also addresses the question of its reimbursement, as for therapeutic implantable devices.

Managing athletes with palpitations of unknown origin with an external loop recorder: a cohort study

BACKGROUND

Palpitations in athletes are usually benign, but the presence of major cardiac arrhythmias should be ruled out despite the infrequent appraisal of symptoms. External loop recorders (ELR) are promising to identify arrhythmias in these circumstances, but experiences in athletes are lacking. We aimed to investigate the feasibility and diagnostic yield of an ELR in athletes with unexplained palpitations in a cohort study.

METHODS

122 consecutive subjects (61 athletes and 61 sedentary controls) with sporadic palpitations and inconclusive diagnosis were enrolled and equipped with an ELR. Findings were categorized as major and minor arrhythmic findings, non-arrhythmic findings or negative monitoring.

RESULTS

Long-term ELR monitoring was feasible in all subjects, with median duration of 12 (11; 15) days. Major arrhythmic events during palpitations were found in 9 (14.8%) athletes: 7 experienced sustained paroxysmal supraventricular tachycardia, and 2 had non sustained ventricular tachycardia. Minor arrhythmic events (premature supraventricular or ventricular beats) were observed in 13 athletes (21.3%). Non-arrhythmic findings (i.e., sinus rhythm or sinus tachycardia) were recorded in 28 athletes (45.9%), whereas 11 (18%) had negative monitoring. In the sedentary group, arrhythmic events were similar for types and frequency to athletes. The diagnostic yield of loop monitoring was 82.8% in the overall population and 82.0% in the athlete's group.

CONCLUSIONS

In the management of an athlete symptomatic with unexplained palpitations after 24-hour ECG monitoring and stress test, ELR is an efficient tool to identify major arrhythmic events, which can be present in up to 10% of symptomatic athletes during practice and competition.

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.

Diagnostic value of implantable loop recorders in patients with unexplained syncope or palpitations

Background

The implantable loop recorder (ILR) is a small cardiac rhythm‐monitoring device. Our aim was to determine ILR diagnostic value in patients with unexplained syncope, presyncope, or palpitations suggesting cardiac arrhythmias.

Methods

This has been a retrospective, observational, single‐center study. We included 181 patients in whom ILR was implanted at the Clinical Center of Serbia between January 2006 and July 2019. An event was marked as diagnostic if it led to a diagnosis and ILR was considered diagnostic if it verified or excluded an arrhythmia as the cause of syncope or palpitations.

Results

The mean age was 51.8 ± 17.8 years and 94 (51.9%) were male. The mean follow‐up period was 20.2 ± 15.8 months. ILR was diagnostic in 98 patients (54.1%). There was no significant difference in diagnostic value of ILR in regard to the baseline patients’ characteristics. The mean time to occurrence of the diagnostic event was 11.1 ± 9.6 months. The time to occurrence of a diagnostic event did not differ significantly between patients who underwent basic as compared to extended diagnostics before ILR implantation.

Conclusions

ILR was able to achieve an etiological diagnosis in 54.1% of patients with unexplained syncope, presyncope, or palpitations suggesting cardiac arrhythmias. In a subgroup of patients with recurrent palpitations, ILR was significantly less diagnostic than in patients with syncope or presyncope. ILR should be implanted beforehand in syncope evaluation process.

Implications of wound healing on subcutaneous photovoltaic energy harvesting

OBJECTIVE

Implanted cardiac pacemakers must be regularly replaced due to depleted batteries. A possible alternative is proposed by subcutaneous photovoltaic energy harvesting. The bodys reaction to an implant can cause device encapsulation. Potential changes in spectral light transmission of skin can inuence the performance of subcutaneous photovoltaic cells and has not yet been studied in large animal studies.

METHODS

Subcutaneous implants measuring changes in the light reaching the implant were developed. Three pigs received those implants and were analyzed for seven weeks. Spectral measurements with known irradiation were performed to identify possible changes in the transparency of the tissues above the implant during the wound healing process. A histological analysis at the end of the trial investigated the skin tissue above the subcutaneous photovoltaic implants.

RESULTS

The implants measured decreasing light intensity and shifts in the lights spectrum during the initial wound healing phase. In a later stage of tissue recovery, the implants measured a generally reduced light intensity compared to the healthy tissue after implantation. The spectral distribution of the measured light at the end of the trial was similar to the rst measurements. The histological analysis showed subcutaneous granulation tissue formation for all devices.

CONCLUSION

The varying reduction of light intensity reaching the implants means that safety margins must be sufciently high to ensure the power. At the end of the wound healing process, the spectral distribution of the light reaching the implant is similar to healthy tissue. Signicance: Optimizations of spectral sensitivity of photovoltaic cells are possible.

Assessment of cardiac arrhythmias using long-term continuous monitoring in patients with pulmonary hypertension

BACKGROUND

Cardiac arrhythmias are considered a prominent phenomenon in patients with pulmonary hypertension (PH). Older studies reported that 8% to 35% of patients with PH had supraventricular tachycardia (SVT), associated with adverse outcomes. Still, these arrhythmias have only been investigated via short-term monitoring or limited electrocardiogram recordings.

METHODS

Patients without previous arrhythmias diagnosed with PH at a tertiary facility received an insertable cardiac monitor as part of a prospective cohort study. Baseline assessments included World Health Organization functional class, six-minute walk test, echocardiography, and cardiac magnetic resonance imaging.

RESULTS

Thirty-four patients with PH were included. Twenty-four patients had pulmonary arterial hypertension (PAH) and 10 had chronic thromboembolic PH (CTEPH). During 46 patient-years of continuous monitoring (median: 594 (range: 334-654) days per patient), 70 arrhythmia episodes were recorded in 13 patients (38%), with a median of two (range: 1-3) episodes and an arrhythmic burden median of 1.6 (range: 0.1-228) minutes per patient. SVTs were the most common arrhythmias, with 16% of episodes being atrial fibrillation and 84% being other types of SVTs. Additionally, three patients experienced bradycardias, including one resulting in syncope and subsequent pacemaker implantation. None of the patients had sustained ventricular arrhythmias.

CONCLUSIONS

Arrhythmias were seen in 38% of contemporary patients with PH during long-term continuous monitoring; however, the vast majority of episodes were short and self-limiting. Modern therapy may alleviate the development of arrhythmias in stable patients with PH. This study is the first study to deploy long-term continuous monitoring in patients with PH.

Supraventricular Tachycardia and Postural Orthostatic Tachycardia Syndrome Overlap: A Retrospective Study

Postural orthostatic tachycardia syndrome (POTS) and supraventricular tachycardia (SVT) are disease states with distinctive features but overlapping clinical manifestations. Currently, studies on the presence of underlying SVT in patients with POTS are lacking. This retrospective study analyzed 64 patients [mean age: 43 years; 41 (61%) women] who had a POTS diagnosis and were found to have concomitant SVT during rhythm monitoring from September 1, 2013 to September 30, 2019 at our Syncope and Autonomic Disorders Clinic. The outcomes assessed were changes in disease severity, frequency of symptoms, heart rate, and blood pressure between before and after SVT ablation. The most frequent types of SVT noted on the electrophysiologic study were atrioventricular nodal reentrant tachycardia (57.81%), atrial flutter (29.68%), atrioventricular reentrant tachycardia (9.37%), atrial tachycardia (1.56%), and junctional tachycardia (1.56%). After SVT ablation, all 64 patients experienced an improvement in symptoms. Palpitations and lightheadedness experienced the most improvement after the procedure (72% vs. 31%; p < 0.001 and 63% vs. 22%; p < 0.001, respectively). There was a significant improvement in the resting heart rate (81.1 ± 12.8 vs. 75.8 ± 15.6 bpm; p < 0.002), but the orthostatic tachycardia on standing persisted (93.6 ± 16.5 vs. 77.3 ± 19.8 bpm; p = 0.14). Underlying SVT in patients with POTS can be missed easily. A strong suspicion and long-term ambulatory cardiac rhythm monitoring can help in diagnosing the condition.

Potential of subdermal solar energy harvesting for medical device applications based on worldwide meteorological data

SIGNIFICANCE

Active implants require batteries as power supply. Their lifetime is limited and may require a second surgical intervention for replacement. Intracorporal energy harvesting techniques generate power within the body and supply the implant. Solar cells below the skin can be used to harvest energy from light.

AIM

To investigate the potential of subdermal solar energy harvesting.

APPROACH

We evaluated global radiation data for defined time slots and calculated the output power of a subdermal solar module based on skin and solar cell characteristics. We assumed solar exposure profiles based on daily habits for an implanted solar cell. The output power was calculated for skin types VI and I/II.

RESULTS

We show that the yearly mean power in most locations on Earth is sufficient to power modern cardiac pacemakers if 10 min midday solar irradiation is assumed. All skin types are suitable for solar harvesting. Moreover, we provide a software tool to predict patient-specific output power.

CONCLUSIONS

Subdermal solar energy harvesting is a viable alternative to primary batteries. The comparison to a human case study showed a good agreement of the results. The developed code is available open source to enable researchers to investigate further applications of subdermal solar harvesting.

Leadless and Wireless Cardiac Devices: The Next Frontier in Remote Patient Monitoring

In the last decade, advances in wireless and sensor technologies, and the implementation of telemedicine, have led to innovative digital health care for cardiac patients. Continuous monitoring of patients' biomedical signals, and acute changes in these signals, may result in timely, accurate diagnoses and implementation of early interventions. In this review, we discuss commonly used wireless and leadless cardiac devices including pulmonary artery pressure sensors, implantable loop recorders, leadless pacemakers and subcutaneous implantable cardioverter-defibrillators. We discuss the concept and function of each device, indications, methods of delivery, potential complications, consideration for implantation, and cost-effectiveness.

Newer Diagnostic and Cost-Effective Ways to Identify Asymptomatic Atrial Fibrillation for the Prevention of Stroke

Atrial fibrillation (Afib) is the most common and underestimated cardiac arrhythmia with a lifetime risk of >35% after the age of 55 years and the risk continues to rise exponentially. Afib leads to stasis of blood within the atria allowing clot formation and increasing the risk for systemic embolization leading to strokes. Outcomes due to Afib can improve significantly with appropriate treatment. Thus, the need for convenient, well-tolerated, cost-effective cardiac monitoring for Afib is needed. The study aims to evaluate the various newer devices and compare them with traditional Holter monitoring, keeping diagnostic yield, cost-effectiveness, and patients' convenience in mind. Though Holter monitoring is simple and non-expensive, it has major limitations including limited recording capacity, inability for real-time recordings, and inconvenience to patients. Zio Patch (iRhythm Technologies, Inc; San Francisco, CA) and other loop recording devices are patient-friendly, inexpensive, and can offer real-time data for longer days. More prospective studies are needed to evaluate the sensitivity, specificity, and the actual number of patients getting benefits from newer devices by diagnosing Afib sooner and start early prevention therapy.

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.

The mammographic appearance of the BioMonitor implantable loop recorder

The imaging appearance of implantable loop recorders (ILR's) have been described in literature (Steinberger and Margolies, 2017; Mayo and Leung, 2017; Tsau and Berger, 2004)^1-3; however, the mammographic appearance of the BioMonitor ILR produced by BIOTRONIK has not been described. It is important for radiologists interpreting breast imaging to become familiar with the appearance of different implantable cardiac devices on mammograms in order to create accurate reports and adjust imaging protocols to improve imaging quality and lessen patient discomfort as needed.