Current and Emerging Uses of Insertable Cardiac Monitors

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.

Associations of hypoglycemia, glycemic variability and risk of cardiac arrhythmias in insulin-treated patients with type 2 diabetes: a prospective, observational study

Background

Insulin-treated patients with type 2 diabetes (T2D) are at risk of hypoglycemia, which is associated with an increased risk of cardiovascular disease and mortality. Using a long-term monitoring approach, we investigated the association between episodes of hypoglycemia, glycemic variability and cardiac arrhythmias in a real-life setting.

Methods

Insulin-treated patients with T2D (N = 21, [mean ± SD] age 66.8 ± 9.6 years, BMI 30.1 ± 4.5 kg/m², HbA1c 6.8 ± 0.4% [51.0 ± 4.8 mmol/mol]) were included for a one-year observational study. Patients were monitored with continuous glucose monitoring ([mean ± SD] 118 ± 6 days) and an implantable cardiac monitor (ICM) during the study period.

Results

Time spend in hypoglycemia was higher during nighttime than during daytime ([median and interquartile range] 0.7% [0.7–2.7] vs. 0.4% [0.2–0.8]). The ICMs detected 724 episodes of potentially clinically significant arrhythmias in 12 (57%) participants, with atrial fibrillation and pauses accounting for 99% of the episodes. No association between hypoglycemia and cardiac arrhythmia was found during daytime. During nighttime, subject-specific hourly incidence of cardiac arrhythmias tended to increase with the occurrence of hypoglycemia (incident rate ratio [IRR] 1.70 [95% CI 0.36–8.01]) but only slightly with increasing time in hypoglycemia (IRR 1.04 [95% CI 0.89–1.22] per 5 min). Subject-specific incidence of cardiac arrhythmias during nighttime increased with increasing glycemic variability as estimated by coefficient of variation whereas it decreased during daytime (IRR 1.33 [95% CI 1.05–1.67] and IRR 0.77 [95% CI 0.59–0.99] per 5% absolute increase, respectively).

Conclusions

Cardiac arrhythmias were common in insulin-treated patients with T2D and were associated with glycemic variability, whereas arrhythmias were not strongly associated with hypoglycemia.

Trial registration: NCT03150030, ClinicalTrials.gov, registered May 11, 2017. https://clinicaltrials.gov/ct2/show/NCT03150030

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-021-01425-0.

Use of Smartphones and Wearables for Arrhythmia Monitoring

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

Non-Invasive Fetal Electrocardiogram Monitoring Techniques: Potential and Future Research Opportunities in Smart Textiles

During the pregnancy, fetal electrocardiogram (FECG) is deployed to analyze fetal heart rate (FHR) of the fetus to indicate the growth and health of the fetus to determine any abnormalities and prevent diseases. The fetal electrocardiogram monitoring can be carried out either invasively by placing the electrodes on the scalp of the fetus, involving the skin penetration and the risk of infection, or non-invasively by recording the fetal heart rate signal from the mother’s abdomen through a placement of electrodes deploying portable, wearable devices. Non-invasive fetal electrocardiogram (NIFECG) is an evolving technology in fetal surveillance because of the comfort to the pregnant women and being achieved remotely, specifically in the unprecedented circumstances such as pandemic or COVID-19. Textiles have been at the heart of human technological progress for thousands of years, with textile developments closely tied to key inventions that have shaped societies. The relatively recent invention of smart textiles is set to push boundaries again and has already opened the potential for garments relevant to medicine, and health monitoring. This paper aims to discuss the different technologies and methods used in non-invasive fetal electrocardiogram (NIFECG) monitoring as well as the potential and future research directions of NIFECG in the smart textiles area.

Efficacy and safety of dronedarone by atrial fibrillation history duration: Insights from the ATHENA study

Background

Atrial fibrillation/atrial flutter (AF/AFL) burden increases with increasing duration of AF/AFL history.

Hypothesis

Outcomes with dronedarone may also be impacted by duration of AF/AFL history.

Methods

In this post hoc analysis of ATHENA, efficacy and safety of dronedarone vs placebo were assessed in groups categorized by time from first known AF/AFL episode to randomization (ie, duration of AF/AFL history): <3 months (short), 3 to <24 months (intermediate), and ≥ 24 months (long).

Results

Of 2859 patients with data on duration of AF/AFL history, 45.3%, 29.6%, and 25.1% had short, intermediate, and long histories, respectively. Patients in the long history group had the highest prevalence of structural heart disease and were more likely to be in AF/AFL at baseline. Placebo‐treated patients in the long history group also had the highest incidence of AF/AFL recurrence and cardiovascular (CV) hospitalization during the study. The risk of first CV hospitalization/death from any cause was lower with dronedarone vs placebo in patients with short (hazard ratio, 0.79 [95% confidence interval: 0.65‐0.96]) and intermediate (0.72 [0.56‐0.92]) histories; a trend favoring dronedarone was also observed in patients with long history (0.84 [0.66‐1.07]). A similar pattern was observed for first AF/AFL recurrence. No new drug‐related safety issues were identified.

Conclusions

Patients with long AF/AFL history had the highest burden of AF/AFL at baseline and during the study. Dronedarone significantly improved efficacy vs placebo in patients with short and intermediate AF/AFL histories. While exploratory, these results support the potential value in initiating rhythm control treatment early in patients with AF/AFL.

Recent Progress in Flexible Wearable Sensors for Vital Sign Monitoring

With the development of flexible electronic materials, as well as the wide development and application of smartphones, the cloud, and wireless systems, flexible wearable sensor technology has a significant and far-reaching impact on the realization of personalized medical care and the reform of the consumer market in the future. However, due to the high requirements for accuracy, reliability, low power consumption, and less data error, the development of these potential areas is full of challenges. In order to solve these problems, this review mainly searches the literature from 2008 to May 2020, based on the PRISMA process. Based on them, this paper reviews the latest research progress of new flexible materials and different types of sensors for monitoring vital signs (including electrophysiological signals, body temperature, and respiratory frequency) in recent years. These materials and sensors can help realize accurate signal detection based on comfortable and sustainable observation, and may likely be applied to future daily clothing.

[Current limits of the long duration rhythmic holter: A real life study]

BACKGROUND

Syncope or stroke remain frequently without any explained diagnosis. Long duration holter ECG is an available tool to diagnose arrhythmias. However, this tool is subject to availability of the recorders.

AIM

Report a single center experience with long duration holter ECG in clinical practice, in the different cardiology and neurology indications, and to assess the different delays until achievement of a diagnosis.

METHODS AND RESULTS

The device (Sorin Spiderflash) was used for 48 patients between January 2018 and June 2018. The holter was applied for a mean duration of 10±4days. The mean age was 55+19 years-old. 20 patients (42%) were explored for a stroke or transient ischemic attack (TIA), 18 (36%) for palpitations, 6 (12%) for syncope and 4 (8%) for evaluation of arrhythmias management. An abnormality has been recorded in 11 (22%) patients and a treatment has been administered in 5 patients (10%). Regarding, the timing of the exam, the mean time between the index event and the indication was 39 days. The mean time between the indication and the availability of the device was 32 days. 16 Days was the mean time for lecture and 23 days was the mean time between the result and the appointment with the cardiologist and neurologist.

CONCLUSION

In this registry, the management of patients by non-invasive long duration holter ECG monitoring may be improved regarding the timing of the exams, their lecture and new appointments with the physicians.

Changes in Management Following Detection of Previously Unknown Atrial Fibrillation by an Insertable Cardiac Monitor (from the REVEAL AF Study)

The REVEAL AF study demonstrated a high incidence of previously undetected atrial fibrillation (AF) using insertable cardiac monitors (ICMs) in patients with risk factors for AF and stroke. This analysis evaluated whether ICM monitoring led to changes in clinical management after AF detection. Patients with CHADS₂ scores ≥3 (or =2 with ≥1 additional AF risk factor) but no history of AF received an ICM and were followed 18 to 30 months. Physicians recorded changes in clinical management in response to AF detection at scheduled (every 6 months) and unscheduled follow-up visits. Changes in clinical management included oral anticoagulation, rhythm or rate control pharmacotherapy, cardioversion, ablation, and cardiac subspecialist referral. In 387 patients who met inclusion criteria and received an ICM, AF was found in 115. A change in clinical management was taken in 87 patients with AF (76%). In 80 of these 87, a change was taken at the first visit after AF detection. In total, 31 patients (27%) with AF had ≥2 visits at which changes in clinical management were taken. The most common change was initiation of oral anticoagulation (n = 73, 63% of patients with AF). Patients with a change in clinical management at the first visit after AF detection tended to have longer AF episodes and a higher maximal daily AF burden compared with AF patients for whom no change was taken (longest episode: 52 vs 28 minutes; maximal daily AF burden:112 vs 23 minutes). Changes in management more frequently occurred at visits where patients reported AF-compatible symptoms (65% vs 46% of visits, p = 0.01). In conclusion, ICM monitoring to identify AF guides both immediate and long-term patient management in a population at high risk for stroke.

A Novel Wearable Device for Continuous Ambulatory ECG Recording: Proof of Concept and Assessment of Signal Quality

Diagnosis of arrhythmic disorders is challenging because of their short-lasting, intermittent character. Conventional technologies of noninvasive ambulatory rhythm monitoring are limited by modest sensitivity. We present a novel form of wearable electrocardiogram (ECG) sensors providing an alternative tool for long-term rhythm monitoring with the potential of increased sensitivity to detect intermittent or subclinical arrhythmia. The objective was to assess the signal quality and R-R coverage of a wearable ECG sensor system compared to a standard 3-lead Holter. In this phase-1 trial, healthy individuals underwent 24-h simultaneous rhythm monitoring using the OMsignal system together with a 3-lead Holter recording. The OMsignal system consists of a garment (bra or shirt) with integrated sensors recording a single-lead ECG and an acquisition module for data storage and processing. Head-to-head signal quality was assessed regarding adequate P-QRS-T distinction and was performed by three electrophysiologists blinded to the recording technology. The accuracy of signal coverage was assessed using Bland-Altman analysis. Fifteen individuals underwent simultaneous 24-h recording. Signal quality and accuracy of the OMgaments was equivalent to Holter-monitoring (84% vs. 93% electrophysiologists rating, p = 0.06). Signal coverage of R-R intervals showed a very close overlay between the OMsignal system and Holter signals, mean difference in heart rate of 2 ± 5 bpm. The noise level of OMgarments was comparable to Holter recording. OMgarments provide high signal quality for adequate rhythm analysis, representing a promising novel technology for long-term non-invasive ECG monitoring.

When is Device-Detected Atrial Fibrillation Actionable?

Device-detected atrial high-rate episodes (AHREs) are frequently encountered in patients with no history of atrial fibrillation (AF) and represent a challenge for clinicians because patients with device-only documented AF have not been included in clinical trials of anticoagulants and other AF therapies. For patients with known history of AF, wireless continuous rhythm monitoring and rapidly acting oral anticoagulants offer the possibility of tailored anticoagulation in response to AHREs, with studies ongoing to evaluate the safety of this approach. This article provides an overview of current evidence on device-detected AHREs and evolving areas of investigation.

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

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.