Precordial electrode placement for optimal ECG monitoring: Implications for ambulatory monitor devices and event recorders

Strategic reprogramming of implantable cardiac monitors reduces the false-positive remote alert burden in a nurse-led service

AIMS

Implantable cardiac monitors (ICMs) can generate false-positive (FP) alerts. Although these devices have an extended programmability, there are no recommendations on their optimization to reduce not-relevant activations.We tested a strategic programming optimization guide based on the type of FP and investigated the safety and feasibility of the nurse-led insertion of ICMs with a long-sensing vector.

METHODS AND RESULTS

Consecutive patients implanted by trained nurses with long-sensing vector ICM were enrolled in a 1-month observational stage (Phase A). Patients who had ≥10 FP episodes underwent ICM reprogramming based on the predefined guide and were followed for an additional month (Phase B). A total of 78 patients had successful ICM insertion by nurses with a mean R wave amplitude of 0.96 ± 0.43 mV and an 86% P wave visibility. Only one patient reported a significant device-related issue, and nurse-delivered ICM was generally well accepted by the patients. During Phase A, 11 patients (14%) generated most of FP (3,627/3,849; 94%) and underwent ICM reprogramming. In the following month (Phase B), five patients (45%) were free from FP and six (55%) transmitted 57 FP alerts (98% reduction compared with Phase A). The median number of FP per patient was significantly reduced after reprogramming [195 (interquartile range, 50-311) vs. one (0-10), P = 0.0002].

CONCLUSION

A strategic reprogramming of ICM in those patients with a high FP alert burden reduces the volume of erroneous activations with potential benefits for the remote monitoring service. No concerns were raised regarding nurse-led insertion of ICMs with a long-sensing vector.

Detection of Ischemic ST-Segment Changes Using a Novel Handheld ECG Device in a Porcine Model

Background

Portable, smartphone-sized electrocardiography (ECG) has the potential to reduce time to treatment for patients suffering acute cardiac ischemia, thereby lowering the morbidity and mortality. In the UMC Utrecht, a portable, smartphone-sized, multi-lead precordial ECG recording device (miniECG 1.0, UMC Utrecht) was developed.

Objectives

The purpose of this study was to investigate the ability of the miniECG to capture ischemic ECG changes in a porcine coronary occlusion model.

Methods

In 8 animals, antero-septal myocardial infarction was induced by 75-minute occlusion of the left anterior descending artery, after the first or second diagonal. MiniECG and 12-lead ECG recordings were acquired simultaneously before, during and after coronary artery occlusion and ST-segment deviation was evaluated.

Results

During the complete occlusion and reperfusion period, miniECG showed large ST-segment deviation in comparison to 12-lead ECG. MiniECG ST-segment deviation was observed within 1 minute for most animals. The miniECG was positive for ischemia (ie, ST-segment deviation ≥1 mm) for 99.7% (Q1-Q3: 99.6%-99.9%) of the occlusion time, while the 12-lead was only positive for 79.8% (Q1-Q3: 81.1%-98.7%) of the time (P = 0.018). ST-segment deviation reached maxima of 10.5 mm [95% CI: 6.5-14.5 mm] vs 5.0 mm [95% CI: 2.0-8.0 mm] for the miniECG vs 12-lead ECG, respectively.

Conclusions

MiniECG ST-segment deviation was observed early and was of large magnitude during 75 minutes of porcine transmural antero-septal infarction. The miniECG was positive for ischemia for the complete occlusion period. These findings demonstrate the potential of the miniECG in the detection of cardiac ischemia. Although clinical research is required, data suggests that the miniECG is a promising tool for the detection of cardiac ischemia.

CatBoost-based improved detection of P-wave changes in sinus rhythm and tachycardia conditions: a lead selection study

Examining P-wave morphological changes in Electrocardiogram (ECG) is essential for characterizing atrial arrhythmias. However, standard 12-lead ECGsuffer from diagnostic redundancy due to low signal-to-noise ratio of P-waves. To address this issue, various optimal leads have been proposed for improved atrial activity recording, but the right selection among these leads is crucial for enhancing diagnostic efficacy. This study proposes an automated lead selection technique using the CatBoost machine learning (ML) model to improve the detection of P-wave changes among optimal bipolar leads under different heart rates. ECGs were obtained from healthy participants with a mean age of 25 ± 3.81 years (34% women), including 114 in sinus rhythm (SR) and 38 in sinus tachycardia (ST). The recordings were made using a newly designed atrial lead system (ALS), standard limb lead (SLL), modified limb lead (MLL), modified Lewis lead (LLM) and P-lead. P-wave features and Atrioventricular (AV) ratio were extracted for statistical analysis and ML classification. The optimum ML model was chosen to identify the best-performing optimal lead, which was selected based on the SLL metrics among different ML classifiers. CatBoost was found to outperform the other ML models in SLL-II with the highest accuracy and sensitivity of 0.82 and 0.90, respectively. The CatBoost model, amid other optimal leads, gave the best results for AL-I and AL-II (0.86 and 0.83 in accuracy and 0.91 and 0.93 in sensitivity). The developed CatBoost model selected AL-I and AL-II as the top two best-performing optimal leads for the enhanced acquisition of P-wave changes, which may be useful for diagnosing atrial arrhythmias.

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.

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.

Factors affecting signal quality in implantable cardiac monitors with long sensing vector

PURPOSE

Electrical artefacts are frequent in implantable cardiac monitors (ICMs). We analyzed the subcutaneous electrogram (sECG) provided by an ICM with a long sensing vector and factors potentially affecting its quality.

METHODS

Consecutive ICM recipients underwent a follow-up where demographics, body mass index (BMI), implant location, and surface ECG were collected. The sECG was then analyzed in terms of R-wave amplitude and P-wave visibility.

RESULTS

A total of 84 patients (43% female, median age 68 [58-76] years) were enrolled at 3 sites. ICMs were positioned with intermediate inclination (n = 44, 52%), parallel (n = 35, 43%), or perpendicular (n = 5, 6%) to the sternum. The median R-wave amplitude was 1.10 (0.72-1.48) mV with P waves readily visible in 69.2% (95% confidence interval, CI: 57.8%-79.2%), partially visible in 23.1% [95% CI: 14.3%-34.0%], and never visible in 7.7% [95% CI: 2.9%-16.0%] of patients. Men had higher R-wave amplitudes compared to women (1.40 [0.96-1.80] mV vs 1.00 [0.60-1.20] mV, P = .001), while obese people tended to have lower values (0.80 [0.62-1.28] mV vs 1.10 [0.90-1.50] mV, P = .074). The P-wave visibility reached 86.2% [95% CI: 68.3%-96.1%] in patients with high-voltage P waves (≥0.2 mV) at surface ECG. The sECG quality was not affected by implant site.

CONCLUSION

In ordinary clinical practice, ICMs with long sensing vector provided median R-wave amplitude above 1 mV and reliable P-wave visibility of nearly 70%, regardless of the position of the device. Women and obese patients showed lower but still very good signal quality.

A pandemic response to home delivery for ambulatory ECG monitoring: Development and validation

In response to the COVID-19 pandemic, a protocol was designed for mail-out devices and educational materials created to teach patients how to install a device for 2 weeks of continuous ambulatory ECG monitoring. We compared data collection from two sequential patient populations; one who received standard device application in the same clinic in the months before the pandemic response, and another, who received their device by mail for self-installation. Patients received a single phone call when the device was mailed and were able to contact the manufacturer as needed for support. A total of 47 devices were assessed from each group. Each group was similar in age (70 vs 65 years), and clinical indication for monitoring. Noise signal magnitude (22.34 vs 26.28%), symptom based manual activation (10 vs 8 events) and APB/recorded hour burden measurements (37.05 vs 23.36%) were similar in both groups (all comparisons were statistically non-significant). Both groups had a similar mean of hours recorded (240.37 vs. 245.05 h). Zero patient kits were lost, and all reports were delivered. Overall, it was found that a mail-delivered home-based recording platform can be reliably used to acquire clinical data with similar data quality and patient compliance as a conventional in-clinic model for long term ambulatory ECG monitoring.

Electrode placement in electrocardiography smart garments: A review

Wearable Electrocardiography (ECG) sensing textiles have been widely used due to their high flexibility, comfort, reusability and the possibility to be used for home-based and real-time measurements. Textile electrodes are dry and non-adhesive, therefor unlike conventional gel electrodes, they don't cause skin irritation and are more user-friendly especially for long-term and continuous monitoring outside the hospital. However, the challenge with textile electrodes is that the quality and reliability of recorded ECG signals by smart garments are more sensitive to different factors such as electrode placement, skin humidity, user activities and contact pressure. This review will particularly focus on the research findings regarding the influence of electrode placement on the quality of biosignal sensing, and will introduce the methods used by researchers to measure the optimal positions of the electrodes in wearable ECG garments. The review will help the designers to take into account different parameters, which affect the data quality, reliability and comfort, when selecting the electrode placement in a wearable ECG garment.

A low-power and miniaturized electrocardiograph data collection system with smart textile electrodes for monitoring of cardiac function

With the increasing aging population as well as health concerns, chronic heart disease has become the focus of public attention. A comfortable, low-powered, and wearable electrocardiogram (ECG) system for continuously monitoring the elderly's ECG signals over several hours is important for preventing cardiovascular diseases. Traditional ECG monitoring apparatus is often inconvenient to carry, has many electrodes to attach to the chest, and has a high-power consumption. There is also a challenge to design an electrocardiograph that satisfies requirements such as comfort, confinement, and compactness. Based on these considerations, this study presents a biosensor acquisition system for wearable, ubiquitous healthcare applications using three textile electrodes and a recording circuit specialized for ECG monitoring. In addition, several methods were adopted to reduce the power consumption of the device. The proposed system is composed of three parts: (1) an ECG analog front end (AFE), (2) digital signal processing and micro-control circuits, and (3) system software. Digital filter methods were used to eliminate the baseline wander, skin contact noise, and other interfering signals. A comparative study was conducted using this system to observe its performance with two commercial Holter monitors. The experimental results demonstrated that the total power consumption of this proposed system in a full round of ECG acquisition was only 29.74 mW. In addition, this low-power system performed well and stably measured the heart rate with an accuracy of 98.55 %. It can also contain a real-time dynamic display with organic light-emitting diodes (OLED) and wirelessly transmit information via a Bluetooth 4.0 module.