Electrocardiogram Monitoring Research Articles

A Compression and Encryption Based Heart Disease Diagnosis with Deep Learning through ECG Signals

Electrocardiogram (ECG) monitoring models are commonly employed for diagnosing heart diseases. Since ECG signals are normally acquired for a longer time duration with high resolution, there is a need to compress the ECG signals for transmission and storage. So, a novel compression technique is essential in transmitting the signals to the telemedicine center to monitor and analyses the data. In addition, the protection of ECG signals poses a challenging issue, which encryption techniques can resolve. The existing Encryption-Then-Compression (ETC) models for multimedia data fail to properly maintain the trade- off between compression performance and signal quality. In this view, this study presents a new ETC with a diagnosis model for ECG data, called the ETC-ECG model. The proposed model involves four major processes, namely, pre-processing, encryption, compression, and classification. Once the ECG data of the patient are gathered, Discrete Wavelet Transform (DWT) with a Thresholding mechanism is used for noise removal. In addition, the chaotic map-based encryption technique is applied to encrypt the data. Moreover, the Burrows-Wheeler Transform (BWT) approach is employed for the compression of the encrypted data. Finally, a Deep Neural Network (DNN) is applied to the decrypted data to diagnose heart disease. The detailed experimental analysis takes place to ensure the effective performance of the presented model to assure data security, compression, and classification performance for ECG data

Safety of outpatient commencement of sotalol

Inpatient monitoring is recommended for sotalol initiation. The purpose of this study was to assess the safety of outpatient sotalol commencement. This is a multicenter, retrospective, observational study of patients initiated on sotalol in an outpatient setting. Serial electrocardiogram monitoring at day 3, day 7, 1 month, and subsequently as clinically indicated was performed. Corrected QT (QTc) interval and clinical events were evaluated. Between 2008 and 2023, 880 consecutive patients who were commenced on sotalol were evaluated. Indications were atrial fibrillation/flutter in 87.3% (n = 768), ventricular arrhythmias in 9.9% (n = 87), and other arrhythmias in 2.8% (n = 25). The daily dosage at initiation was 131.0 ± 53.2 mg/d. The QTc interval increased from baseline (431 ± 32 ms) to 444 ± 37 ms (day 3) and 440 ± 33 ms (day 7) after sotalol initiation (P < .001). Within the first week, QTc prolongation led to the discontinuation of sotalol in 4 and dose reduction in 1. No ventricular arrhythmia, syncope, or death was observed during the first week. Dose reduction due to asymptomatic bradycardia occurred in 3 and discontinuation due to dyspnea in 3 within the first week. Overall, 1.1% developed QTc prolongation (>500 ms/>25% from baseline); 4 within 3 days, 1 within 1 week, 4 within 60 days, and 1 after >3 years. Discontinuation of sotalol due to other adverse effects occurred in 41 patients within the first month of therapy. Sotalol initiation in an outpatient setting with protocolized follow-up is safe, with no recorded sotalol-related mortality, ventricular arrhythmias, or syncope. There was a low incidence of significant QTc prolongation necessitating discontinuation within the first month of treatment. Importantly, we observed a small incidence of late QT prolongation, highlighting the need for vigilant outpatient surveillance of individuals on sotalol.

Examining the Prevalence of Left Atrial Appendage Thrombus in a Cohort of Acute Stroke Patients with an Extended Computed Tomography Angiographic Protocol

Introduction: Current guidelines recommend transthoracic echocardiography (TTE) for routine screening of cardiac emboli; however, the visualization of the left atrial appendage (LAA) where the thrombi are commonly found is poor. Transesophageal echocardiography (TEE) would provide better detectability of LAA thrombus, but it is a time-consuming and semi-invasive method. Extending non-gated carotid computed tomography angiography (CTA) examination to the LAA could reliably detect thrombi and could also aid treatment and secondary prevention of stroke. Methods: We extended the CTA scan range of acute stroke patients 4 cm below the carina to include the left atrium and appendage. During the review, we evaluated LAA thrombi based on contrast relations. We then used gradient boosting to identify the most important predictors of LAA thrombi from a variety of different clinical parameters. Results: We examined 240 acute stroke patients' extended CTA scans. We detected LAA thrombi in eleven cases (4.58%), eight of them had atrial fibrillation. 23.75% of all patients (57 cases) had recently discovered or previously known atrial fibrillation. Windsack morphology was the most commonly associated morphology with filling defects on CTA. According to the gradient-boosting analysis, LAA morphology showed the most predictive value for thrombi. Conclusion: Our extended CTA scans reliably detected LAA thrombi even in cases where TTE did not and showed that 2 patients’ LAA thrombus would have been untreated based on electrocardiogram monitoring and TTE. We also showed that the benefits of CTA outweigh the disadvantages arising from the slight amount of excess radiation.

Cardiac Safety of Ozanimod Use, a Novel Sphingosine-1-Phosphate Receptor Ligand, in COVID-19 Patients Requiring Oxygen: Secondary Analysis of the COZI Randomized Clinical Trial

BackgroundOzanimod is a novel immune modulator that could be useful in viral pulmonary infections by reducing lung inflammation. It is an S1P receptor ligand known to induce bradycardia and more serious adverse cardiac effects, such as atrioventricular block and QT interval prolongation. We present a substudy of the COVID-19 Ozanimod Intervention (COZI) trial in which ozanimod was administered in acute pulmonary infection patients, to assess cardiac safety. MethodsIn this pilot randomized open-label trial, COVID-19 patients requiring oxygen support were randomized into 2 groups: standard-of-care + ozanimod (OZA) vs standard-of-care alone (SOC). All patients were monitored with a 14-day electrocardiogram monitor (CardioSTAT, Icentia, Quebec, QC) during their hospitalization. We evaluated the cardiac effects of ozanimod on heart rate (HR), PR interval length, and QT interval duration. ResultsA total of 42 patients were analyzed: 23 in the SOC group and 19 in the OZA group. Mean hourly HR over the first 10 days of treatment decreased in the OZA group, compared with that in the SOC group (P < 0.0001). The maximum decrease in HR occurred on day 3. The maximum decrease in HR occurred on day 3, without a significant difference between groups: 49 beats per minute (interquartile range, 42-59) in the OZA group, and 54 beats per minute (48–60) in the SOC group, P = 0.45. No high-degree atrioventricular block was recorded. QT and PR interval median values were within the normal range in both groups, without a significant difference. ConclusionsThe maximal reduction in HR occurred 3 days after the onset of ozanimod treatment in patients hospitalized for COVID-19, but it did not remain significant over the 10-day treatment period. No relevant cardiac adverse event was observed.

Prognostic relevance of ventricular arrhythmias in surgical patients with gastrointestinal tumors.

Individuals diagnosed with gastrointestinal tumors are at an increased risk of developing cardiovascular diseases. Among which, ventricular arrhythmia is a prevalent clinical concern. This suggests that ventricular arrhythmias may have predictive value in the prognosis of patients with gastrointestinal tumors. To explore the prognostic value of ventricular arrhythmias in patients with gastrointestinal tumors receiving surgery. We retrospectively analyzed data from 130 patients undergoing gastrointestinal tumor resection. These patients were evaluated by a 24-h ambulatory electrocardiogram (ECG) at the Sixth Affiliated Hospital of Sun Yat-sen University from January 2018 to June 2020. Additionally, 41 general healthy age-matched and sex-matched controls were included. Patients were categorized into survival and non-survival groups. The primary endpoint was all-cause mortality, and secondary endpoints included major adverse cardiovascular events (MACEs). Colorectal tumors comprised 90% of cases. Preoperative ambulatory ECG monitoring revealed that among the 130 patients with gastrointestinal tumors, 100 (76.92%) exhibited varying degrees of premature ventricular contractions (PVCs). Ten patients (7.69%) manifested non-sustained ventricular tachycardia (NSVT). The patients with gastrointestinal tumors exhibited higher PVCs compared to the healthy controls on both conventional ECG [27 (21.3) vs 1 (2.5), P = 0.012] and 24-h ambulatory ECG [14 (1.0, 405) vs 1 (0, 6.5), P < 0.001]. Non-survivors had a higher PVC count than survivors [150.50 (7.25, 1690.50) vs 9 (0, 229.25), P = 0.020]. During the follow-up period, 24 patients died and 11 patients experienced MACEs. Univariate analysis linked PVC > 35/24 h to all-cause mortality, and NSVT was associated with MACE. However, neither PVC burden nor NSVT independently predicted outcomes according to multivariate analysis. Patients with gastrointestinal tumors exhibited elevated PVCs. PVCs > 35/24 h and NSVT detected by 24-h ambulatory ECG were prognostically significant but were not found to be independent predictors.

Dynamic risk stratification of worsening heart failure using a deep learning-enabled implanted ambulatory single-lead electrocardiogram.

Implantable loop recorders (ILRs) provide continuous single-lead ambulatory electrocardiogram (aECG) monitoring. Whether these aECGs could be used to identify worsening heart failure (HF) is unknown. We linked ILR aECG from Medtronic device database to the left ventricular ejection fraction (LVEF) measurements in Optum® de-identified electronic health record dataset. We trained an artificial intelligence (AI) algorithm [aECG-convolutional neural network (CNN)] on a dataset of 35 741 aECGs from 2247 patients to identify LVEF ≤ 40% and assessed its performance using the area under the receiver operating characteristic curve. Ambulatory electrocardiogram-CNN was then used to identify patients with increasing risk of HF hospitalization in a real-world cohort of 909 patients with prior HF diagnosis. This dataset provided 12 467 follow-up monthly evaluations, with 201 HF hospitalizations. For every month, time-series features from these predictions were used to categorize patients into high- and low-risk groups and predict HF hospitalization in the next month. The risk of HF hospitalization in the next 30 days was significantly higher in the cohort that aECG-CNN identified as high risk [hazard ratio (HR) 1.89; 95% confidence interval (CI) 1.28-2.79; P = 0.001] compared with low risk, even after adjusting patient demographics (HR 1.88; 95% CI 1.27-2.79 P = 0.002). An AI algorithm trained to detect LVEF ≤40% using ILR aECGs can also readily identify patients at increased risk of HF hospitalizations by monitoring changes in the probability of HF over 30 days.

Interpretation of electrocardiograms and results of daily ECG Holter monitoring in patients with an implanted cardiac contractility modulator

Cardiac contractility modulation (CCM) is a method of non-drug treatment of chronic heart failure (CHF) in patients with no indications for resynchronization therapy. Now, a detailed study of this method and its capabilities is ongoing, and the indications for its use are expanding. As with any other implantable device, it is important to be able to monitor the operation of the CCM, identify its dysfunction and promptly refer patients to specialized institutions. Assessment of the function of CCM- therapy can be carrying out by recording a standard 12‑channel electrocardiogram (ECG), as well as 24‑hour Holter ECG monitoring (HM-ECG). The mechanism of action of CCM-therapy is fundamentally different from that of other implantable devices. Knowledge of the features of the manifestation of CCM-therapy during instrumental studies is necessary for their correct interpretation.

Bioinspired Robust Gas-Permeable On-Skin Electronics: Armor-Designed Nanoporous Flash Graphene Assembly Enhancing Mechanical Resilience.

Soft on-skin electrodes play an important role in wearable technologies, requiring attributes such as wearing comfort, high conductivity, and gas permeability. However, conventional fabrication methods often compromise simplicity, cost-effectiveness, or mechanical resilience. In this study, a mechanically robust and gas-permeable on-skin electrode is presented that incorporates Flash Graphene (FG) integrated with a bioinspired armor design. FG, synthesized through Flash Joule Heating process, offers a small-sized and turbostratic arrangement that is ideal for the assembly of a conductive network with nanopore structures. Screen-printing is used to embed the FG assembly into the framework of polypropylene melt-blown nonwoven fabrics (PPMF), forming a soft on-skin electrode with low sheet resistance (125.2 ± 4.7 Ω/□) and high gas permeability (≈10.08mg cm⁻2 h⁻¹). The "armor" framework ensures enduring mechanical stability through adhesion, washability, and 10,000 cycles of mechanical contact friction tests. Demonstrating capabilities in electrocardiogram (ECG) and electromyogram (EMG) monitoring, along with serving as a self-powered triboelectric sensor, the FG/PPMF electrode holds promise for scalable, high-performance flexible sensing applications, thereby enriching the landscape of integrated wearable technologies.

Revolutionizing Heart Monitoring with Oximetry

Innovative medical gadgets are now critically needed to monitor and analyze the situation, especially in light of the COVID-19 pandemic. In light of this, a portable, affordable, IOT-based heart rate and SpO2/level sensor device with effective performance has been developed. In order to publish data to a software web page and display data on the OLED, the suggested system has an integrated LED with basic internet access. Its mobility, user-friendliness, and distinctive method of sending collected data are its key qualities. data online, enabling it to perform better than the solutions that are currently on offer in a number of ways. The project is designed in such a way that the analogue quantities which are to be recorded continuously are taken and converted into corresponding digital values using a six-channel ADC. Here we consider temperature and monitor the heart rate. The processed data from ADC is sent to the microcontroller. With the help of a six-channel ADC, the project's architecture transforms the analogue numbers that must be continuously recorded into equivalent digital values. Here, we keep an eye on the heart rate and take the temperature into account. The microcontroller receives the data from the ADC that has been processed. The microcontroller is designed to continuously monitor the status of the sensors. To transfer sensor data to the server web page in the form of a database, the microcontroller and the Wifi Module will be interfaced using serial connection. Monitoring physiological data, such as electrocardiogram (ECG) signals, offers a new avenue for ease of control and prevention in modern healthcare. Consequently, a new era of proactive, intelligent healthcare would emerge—especially considering the major barrier of scarce medical resources. It was shown how to use a mobile ECG monitoring service hosted in the cloud. With the use of a pulse oximeter and a wireless transmission method like WI-FI, these may identify ECG signals and display them on a screen. IOT based on ECG monitoring has been the subject of various works.

Recent Progress in the Development of Flexible Wearable Electrodes for Electrocardiogram Monitoring During Exercise

Electrocardiogram (ECG) monitoring has recently been an important indicator of cardiac health diagnosis. In the past, ECG could be measured under limited conditions in hospitals with 12‐lead electrode systems. Recently, portable and wearable devices have offered continuous, real‐time monitoring of ECG signals in real life. However, developing wearable ECG sensors that provide low‐motion artifacts and high‐quality signals during exercise conditions is still challenging. Herein, this review reports a systematic summary of the key characteristics, properties, and requirements of flexible wearable ECG devices for the early diagnosis of heart dysfunction in dynamic motions, including exercise. In addition, the recent progress in controlling sensor adhesion and novel materials for designing dry electrodes are discussed to improve ECG signal quality in exercise. Finally, various aspects of electrode developmental challenges and limitations are reviewed, and research directions for future studies are discussed.

Remote electrocardiogram monitoring in cancer patients for detecting cardiotoxicity. Case report

Cardiotoxicity is the direct adverse effect of anticancer agents on the function or structure of the heart, occurring both during treatment and many years later. The manifestations of cardiotoxicity can be very different: heart failure, coronary heart disease, cardiomyopathy, myocarditis, pericarditis, and arrhythmias, including atrial fibrillation (AF). The incidence of AF in the cancer patient population during therapy is 20–30%. Current options of remote electrocardiogram monitoring ensure the timely detection and treatment of AF in cancer patients, including the administration of anticoagulants. The article presents a clinical case of a 59-year-old patient with squamous cell carcinoma of the lower third of the esophagus after the first course of the TPF polychemotherapy regimen (docetaxel, cisplatin, 5-fluorouracil) with AF detected using a single-channel electrocardiogram monitor in a smartphone case.

New-onset atrial fibrillation detected by ambulatory ECG monitoring after transcatheter aortic valve implantation.

Little is known about the occurrence of subclinical new-onset atrial fibrillation (NOAF) after transcatheter aortic valve implantation (TAVI). We aimed to evaluate the incidence, predictors, and clinical impact of subclinical NOAF after TAVI. This was a multicentre study, including patients with aortic stenosis (AS) and no previous atrial fibrillation undergoing TAVI, with continuous ambulatory electrocardiogram (AECG) monitoring after TAVI. A total of 700 patients (79±8 years, 49% female, Society of Thoracic Surgeons score 2.9% [1.9-4.0]) undergoing transarterial TAVI were included (85% balloon-expandable valves). AECG was started 1 (0-1) day after TAVI (monitoring time: 14<span class="eij_ref" contenteditable="false" data-id="26797">12</span><span class="eij_ref" contenteditable="false" data-id="18749">13</span><span class="eij_ref" contenteditable="false" data-id="26798">14</span> days). NOAF was detected in 49 patients (7%), with a median duration of 185 (43-421) minutes (atrial fibrillation burden of 0.7% [0.3-2.8]). Anticoagulation was started in 25 NOAF patients (51%). No differences were found in baseline or procedural characteristics, except for a higher AS severity in the NOAF group (peak gradient: no NOAF: 71.9±23.5 mmHg vs NOAF: 85.2±23.8 mmHg; p=0.024; mean gradient: no NOAF: 44.4±14.7 mmHg vs NOAF: 53.8±16.8 mmHg; p=0.004). In the multivariable analysis, the baseline mean transaortic gradient was associated with a higher risk of NOAF after TAVI (odds ratio 1.04, 95% confidence interval: 1.01-1.06 for each mmHg; p=0.006). There were no differences between groups in all-cause mortality (no NOAF: 4.7% vs NOAF: 0%; p=0.122), stroke (no NOAF: 1.4% vs NOAF: 2.0%; p=0.723), or bleeding (no NOAF: 1.9% vs NOAF: 4.1%; p=0.288) from the 30-day to 1-year follow-up. NOAF detected with AECG occurred in 7% of TAVI recipients and was associated with a higher AS severity. NOAF detection determined the start of anticoagulation therapy in about half of the patients, and it was not associated with an increased risk of clinical events at 1-year follow-up.

Comparison of electrocardiogram (ECG) signals between a wearable ambulatory ECG device and a standard 12-lead ECG monitor

Comparison of electrocardiogram (ECG) signals between a wearable ambulatory ECG device and a standard 12-lead ECG monitor

Smartphone-based 12-lead electrocardiogram monitoring in an elderly patient with multimorbidity: A case report of comprehensive cardiac assessment using the Spandan device

ABSTRACT The advent of mobile health (mHealth) technologies, particularly smartphone-based 12-lead electrocardiogram (ECG) devices, has revolutionized cardiac care. This case report highlights the utility of the Spandan ECG device in managing an 84-year-old female patient with a complex medical history of hypertension (HTN), left ventricular hypertrophy, hypothyroidism, osteoarthritis, dyslipidemia, and obstructive sleep apnea. The patient, diagnosed with systemic HTN in 1992 and hypothyroidism in 2002, experienced a decline in mobility due to knee pain and was later diagnosed with bilateral osteoarthritis. Over the years, she developed additional comorbidities including hyperuricemia and dyslipidemia. On several occasions, fluctuating blood pressure and cardiac symptoms led to multiple hospital visits. Comprehensive diagnostic evaluations revealed significant cardiac conditions including right bundle branch block, sinus bradycardia, atrial fibrillation, and diastolic dysfunction. The use of the Spandan 12-lead ECG device facilitated the early detection of these abnormalities, enabling timely interventions. This case underscores the value of smartphone-based ECG devices in providing continuous cardiac monitoring and early diagnosis, particularly for elderly patients with multiple comorbidities. The Spandan device’s portability and ease of use allowed for effective point-of-care diagnostics, leading to proactive management and improved patient outcomes. The ability to perform ECGs at home and during medical consultations ensured that the critical changes in the patient’s cardiac status were promptly identified and addressed. The integration of the Spandan smartphone-based 12-lead ECG device into the patient’s care regimen proved instrumental in managing her complex cardiac conditions. This case highlights the potential of mHealth ECG technologies to enhance point-of-care diagnostics and promote patient-centered care, particularly for elderly individuals with multiple comorbidities. The widespread adoption of such technologies could significantly improve cardiovascular health outcomes and quality of life for patients with similar profiles.

Portable ECG Machine with Future Prediction

Abstract: Approximately thirty percent of people live in poverty in rural areas. The difficulty of limited access to nursing and diagnostic services stems from the outdated healthcare infrastructure. As a result, when heart failure strikes, people frequently neglect to get help and make use of the resources that are accessible. A study suggests a smart electrocardiogram (ECG) monitoring system for heart patients based on the Internet of Things to address these problems. The ECG sensing network (data gathering), IoT cloud (data transmission), result analysis (data prediction), and monetization are the various components that make up the system.

Skin Electrodes Based on TPU Fiber Scaffolds with Conductive Nanocomposites with Stretchability, Breathability, and Washability.

In the context of an aging population and escalating work pressures, cardiovascular diseases pose increasing health risks. Electrocardiogram (ECG) monitoring presents a preventive tool, but conventional devices often compromise comfort. This study proposes an approach using Ag NW/TPU composites for flexible and breathable epidermal electronics. In this new structure, TPU fibers are used to support Ag NWs/TPU nanocomposites. The TPU fiber-reinforced Ag NW/TPU (TFRAT) nanocomposites exhibit excellent conductivity, stretchability, and electromechanical durability. The composite ensures high steam permeability, maintaining stable electrical performance after washing cycles. Employing this technology, a flexible ECG detection system is developed, augmented with a convolutional neural network (CNN) for automated signal analysis. The experimental results demonstrate the system's reliability in capturing physiological signals. Additionally, a CNN model trained on ECG data achieves over 99% accuracy in diagnosing arrhythmias. This study presents TFRAT as a promising solution for wearable electronics, offering both comfort and functionality in long-term epidermal applications, with implications for healthcare and beyond.

Ventricular bigeminy associated with myocardial ischemia in a dog with a colonic torsion: a case report

BackgroundVentricular bigeminy due to myocardial ischemia has been reported in humans as well as in canine patients with obstructive gastrointestinal diseases. This is the first case report of ventricular bigeminy in a dog with a colonic torsion that resolved after fluid resuscitation and restoration of myocardial perfusion.Case presentationAn 11-year-old, male neutered mixed breed dog presented with a one day history of vomiting, tenesmus, and lethargy. Physical examination identified an irregular heart rhythm and intermittent pulse deficits. A ventricular arrhythmia represented by ventricular premature complexes (VPCs) organized in bigeminy, was appreciated on a 3-lead electrocardiogram (ECG) with a single lead (II) view. Abdominal radiographs confirmed a colonic torsion. Prior to anesthetic induction, ventricular bigeminy was non responsive to fentanyl or lidocaine. The patient was anesthetized and intravascular volume deficit was identified by dampened plethysmographic wave amplitude (plethysomographic variability), audible softening of the Doppler sound, and more pronounced pulse deficits. Fluid resuscitation was achieved with a combination of intravenous crystalloid and colloid fluid therapy comprising 7.2% hypertonic saline and 6% hetastarch. The patient’s cardiac rhythm converted to normal sinus after fluid resuscitation. The colonic torsion was surgically corrected. The patient recovered well from anesthesia and was ultimately discharged from the hospital 5 days later.ConclusionsThe present case report highlights that myocardial ischemia can lead to ventricular arrythmias, such as ventricular bigeminy. This is the first documented case of ventricular bigeminy in the canine patient with a colonic torsion. Assessment of patient volume status and appropriate fluid resuscitation along with continuous electrocardiogram (ECG) monitoring are vital to patient stability under general anesthesia.

Skin sympathetic nerve activity and ST-segment depression in women

BackgroundST depression on exercise electrocardiogram (ECG) and ambulatory ECG monitoring may occur without myocardial ischemia. The mechanisms of non-ischemic ST depression remain poorly understood. ObjectiveTo test the hypothesis that the magnitudes of skin sympathetic nerve activity (SKNA) correlate negatively with the ST segment height (ST height) in ambulatory participants. MethodsWe used neuECG to measure ambulatory ST height and average SKNA (aSKNA) in 19 healthy women, 6 women with a history of Takotsubo Syndrome (TTS), and 4 women with ischemia and no obstructive coronary arteries (INOCA). ResultsBaseline average SKNA (aSKNA) was similar between healthy women, TTS, and INOCA (1.098±0.291 μV, 0.980± 0.061 μV, and 0.919 ± 0.0397 μV, respectively, p=0.22). The healthy women had only asymptomatic upsloping ST depression. All participants had a significant (p<0.05) negative correlation between ST height and aSKNA. Ischemic episodes (n=15) were identified in 2 TTS and 4 INOCA participants. The ischemic ST depression was associated with increased heart rate and elevated aSKNA compared to baseline. An analysis of SKNA burst patterns at similar heart rates revealed that SKNA total burst area was significantly higher during ischemic episodes than non-ischemic episodes (0.301±0.380 μV.s and 0.165±0.205 μV.s, p=0.023) in both the TTS and INOCA participants. ConclusionsAsymptomatic ST depression in ambulatory women is associated with elevated SKNA. Heightened aSKNA is also noted during ischemic ST depression in women with TTS and INOCA. These findings suggest that ST segment depression is a physiological response to heightened sympathetic tone but may be aggravated by myocardial ischemia.

The role for ambulatory electrocardiogram monitoring in the diagnosis and prognostication of Brugada syndrome: a sub-study of the Rare Arrhythmia Syndrome Evaluation (RASE) Brugada study.

Brugada syndrome (BrS) diagnosis and risk stratification rely on the presence of a spontaneous type 1 (spT1) electrocardiogram (ECG) pattern; however, its spontaneous fluctuations may lead to misdiagnosis and risk underestimation. This study aims to assess the role for repeat high precordial lead (HPL) resting and ambulatory ECG monitoring in identifying a spT1, and evaluate its prognostic role. HPL resting and ambulatory monitoring ECGs of BrS subjects were reviewed retrospectively, and the presence of a spT1 associated with ventricular dysrhythmias and sudden cardiac death (SCD). Three-hundred and fifty-eight subjects (77 with spT1 pattern at presentation, Group 1, and 281 without, Group 2) were included. In total, 1651 resting HPL resting and 621 ambulatory monitoring ECGs were available for review, or adequately described. Over a median follow-up of 72 months (interquartile range - IQR - 75), 42/77 (55%) subjects in Group 1 showed a spT1 in at least one ECG. In Group 2, 36/281 subjects (13%) had a newly detected spT1 (1.9 per 100 person-year) and 23 on an HPL ambulatory recording (8%). Seven previously asymptomatic subjects, five of whom had a spT1 (four at presentation and one at follow-up), experienced arrhythmic events; survival analysis indicated that a spT1, either at presentation or during lifetime, was associated with events. Univariate models showed that a spT1 was consistently associated with increased risk [spT1 at presentation: hazard ratio (HR) 6.3, 95% confidence interval (CI) 1.4-28, P = 0.016; spT1 at follow-up: HR 3.1, 95% CI 1.3-7.2, P = 0.008]. Repeated ECG evaluation and HPL ambulatory monitoring are vital in identifying transient spT1 Brugada pattern and its associated risk.

On‐Skin Paintable Water‐Resistant Biohydrogel for Wearable Bioelectronics

AbstractTo achieve accurate monitoring of bioelectrical signals, it is essential to use customizable bioelectrodes that can self‐adapt to the skin's surface topography. Ion‐conducting hydrogel has received significant attention in this field due to its softness, adhesion, and skin‐like mechanical properties. However, these bioelectrodes currently suffer from degradation of adhesion, electrical conductivity, and skin‐compliance when exposed to aqueous environments. This significantly limits the application of bioelectrodes. Herein, a customizable biohydrogel that can be applied on skin or fabric by solvent volatilization for liquid ink‐gel film conversion is reported. The biohydrogel's distinct characteristic of transitioning between a liquid and hydrogel phase establishes superb conformal contact and dynamic compliance with the epidermis. This effectively eliminates motion artifacts and results in lower contact impedance and noise in both static and dynamic states when compared to existing bioelectrodes. The biohydrogel is applied to the cotton fabric to create electrocardiogram (ECG) monitoring garments. These garments enable the acquisition of ECG signals with high accuracy in aqueous environment for over 72 h. Besides, the biohydrogel‐based garments outperform the commercial gel electrodes by 83.5% in signal‐to‐noise ratio. Additionally, the cotton/biohydrogel electrode facilitates multi‐channel, high‐fidelity recording of ECG signals, enabling high‐performance capture and classification of ECG waveforms across multiple channels.