Electrocardiogram Research Articles

Prediction of reduced left ventricular ejection fraction using atrial fibrillation or flutter electrocardiograms: A machine-learning study.

Although the evaluation of left ventricular ejection fraction (LVEF) in patients with atrial fibrillation (AF) or atrial flutter (AFL) is crucial for appropriate medical management, the prediction of reduced LVEF (<50%) with AF/AFL electrocardiograms (ECGs) lacks evidence. This study aimed to investigate deep-learning approaches to predict reduced LVEF (<50%) in patients with AF/AFL ECGs and easily obtainable clinical information. Patients with 12-lead ECGs of AF/AFL and echocardiography were divided into those with LVEF <50% and ≥50%. A convolutional neural networks-based model customized to the study (AFibEFNet) and other deep-learning models were investigated. Electrocardiogram signals, ECG features, and clinical features (demographic information, comorbidities, blood cell counts, and blood test results) were collected for training. A hold-out test dataset was constructed using a different recruitment period. Five-fold cross-validation and calibration plots were used to evaluate performance. A total of 15,683 patients were analyzed (mean age, 70.0 ± 11.7 years; 61.2% men), with 82.2% having LVEF ≥50% and 17.8% having LVEF < 50%. Among the learning models, the AFibEFNet outperformed other models regarding area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC), and F1-score. Using ECG signals alone, the AFibEFNet model predicted reduced LVEF with AUROC of 0.798 (95% confidence interval [CI], 0.767-0.829) and AUPRC of 0.508 (95% CI, 0.434-0.564). For the AFibEFNet model, additional training with ECG and clinical features significantly improved AUROC (0.816 vs. 0.798, p = 0.04) and AUPRC (0.547 vs. 0.508, p < 0.001). The AFibEFNet model primarily focused on the R-wave, QRS onset and offset, and T-wave in ECG signals. Among the patients with AF/AFL, machine learning may predict reduced LVEF with 12-lead ECGs of AF/AFL.

Research on spatial resolution in cardiac source imaging for multiple measurement modes using a realistic multi-tissue human model

Magnetocardiography (MCG) and electrocardiography (ECG) are noninvasive techniques that reflect cardiac electrical activity. Combined MCG and ECG (MECG) integrates both measurements, and due to technological advancements, vector MCG (vMCG) is now possible. Although all four modes—MCG, ECG, MECG, and vMCG—are used in cardiac source imaging, their spatial resolutions have not been systematically studied. This study evaluates these modes using a resolution matrix based on a realistic multi-tissue human model, analyzing their dependence on source direction, location, and signal-to-noise ratio. Results show that MECG and vMCG significantly reduce dependence on these factors, with vMCG offering superior spatial resolution. However, its advantage lessens as SNR decreases. Our findings suggest that MECG and vMCG enhance spatial resolution in cardiac source imaging, making them promising options for future research.

Noninvasive prediction of coronary artery disease severity: Comparative analysis of electrocardiographic findings and risk factors with SYNTAX and Gensini score.

Coronary artery disease (CAD) remains a significant global health burden, characterized by the narrowing or blockage of coronary arteries. Treatment decisions are often guided by angiography-based scoring systems, such as the Synergy Between Percutaneous Coronary Intervention with Taxus and Cardiac Surgery (SYNTAX) and Gensini scores, although these require invasive procedures. This study explores the potential of electrocardiography (ECG) as a noninvasive diagnostic tool for predicting CAD severity, alongside traditional risk factors. This retrospective cross-sectional study was conducted on 348 CAD patients who underwent coronary angiography. Demographic data, ECG findings, SYNTAX, and Gensini scores were collected. The association between ECG findings and demographic information with the severity of coronary artery stenosis, as assessed by SYNTAX and Gensini scores, was investigated using SPSS software, version 23. Significant associations were observed between CAD severity and risk factors such as male gender, diabetes mellitus (DM), and smoking. Additionally, certain ECG indicators, including Q waves and ST depression (STD), showed significant correlations with CAD severity, particularly according to the Gensini score. This study underscores the utility of ECG and clinical factors in identifying severe CAD, offering cost-effective diagnostic alternatives to angiography. Integrating various parameters into a single score is crucial in clinical practice, providing a stronger diagnostic and prognostic tool without increasing costs. Further comprehensive studies are warranted to refine risk prediction models and improve CAD management strategies.

Measuring anxiety level on phobia using electrodermal activity, electrocardiogram and respiratory signals

People with spider phobia experience excessive anxiety reactions when exposed to spiders that will interfere with daily life. Diagnosing and measuring anxiety levels in patients with spider phobia is a complex challenge. Conventional diagnosis requires psychological evaluations and clinical interviews that take time and often result in a high degree of subjectivity. Therefore, there is a need for a more objective and efficient approach to measuring anxiety levels in patients. This study performs anxiety level classification based on electrodermal activity, electrocardiogram (ECG) and respiratory signals using the dataset of Arachnophobia subjects. Each raw data is preprocessed using 24 types of features. Feature performance is processed using the recursive feature elimination method. Data processing was performed in 3 anxiety levels (high, medium, low) and two anxiety levels (high, low) with the support vector machine method and hold-out validation method (7:3). The performance of the model is evaluated by showing the accuracy, precision, recall and F1 score values. The polynomial kernel can perform optimal classification and obtain 100% accuracy in 2 classes and three classes with 100% precision, recall, and F1 score values. This result shows excellent potential in measuring anxiety levels that correlate with mental health issues.

Electrocardiogram features detection using stationary wavelet transform

The main objective of this paper is to provide a novel stationary wavelet transform (SWT) based method for electrocardiogram (ECG) feature detection. The proposed technique uses the detail coefficients of the ECG signal decomposition by SWT and the selection of the appropriate coefficient to detect a specific wave of the signal. Indeed, the temporal and frequency analysis of these coefficients allowed us to choose detail coefficient of level 2 (Cd2) to detect the R peaks. In contrast, the coefficient of level 3 (Cd3) is determined to extract the Q, S, P, and T waves from the ECG. The proposed method was tested on recordings from the apnea and Massachusetts Institute of Technology–Beth Israel hospital (MIT-BIH) databases. The performances obtained are excellent. Indeed, the technique presents a sensitivity of 99.83%, a predictivity of 99.72%, and an error rate of 0.44%. A further important advantage of the method is its ability to detect different waves even in the presence of baseline wander (BLW) of the ECG signal. This property makes it possible to bypass the filtering operation of BLW.

Association between anti-seizure medications and cardiac arrhythmias in patients undergoing ambulatory electroencephalographic and electrocardiographic monitoring.

Background Anti-seizure medications (ASMs) are commonly prescribed in epilepsy. However some have been associated with adverse cardiac outcomes including cardiac arrhythmias. Methods We conducted an observational study evaluating patients aged ≥16 years undergoing ambulatory video - electroencephalographic (EEG) - electrocardiographic (ECG) monitoring (AVEEM) between 2020 and 2023 in Australia. Data collected included baseline demographics, type, number and dose of ASMs and cardiac arrhythmias during monitoring. ASMs were not withdrawn while monitored. Average QT interval was calculated and corrected for heart rate (QTc). Logistic regression was used to evaluate association between demographic variables, ASMs and cardiac arrhythmias. Results 3695 patients underwent AVEEM (median age 40 years [interquartile range 26-57], female 64 %). Median AVEEM duration was 6.8 days. 51 % of patients were taking ≥1 ASMs. About 28 % (1029/3695) patients had a cardiac arrhythmia; the most frequent was non-sustained SVT (19 %; 695/3695). On multivariable analysis, carbamazepine (OR 0.72, 95 %CI 0.53-0.98, p = 0.03), lamotrigine (OR 0.57, 95 %CI 0.44-0.73, p<0.001) and lacosamide (OR 0.63, 95 %CI 0.43-0.92, p = 0.02) were associated with fewer cardiac arrhythmias. Their association with cardiac arrhythmias was not dose-dependent. No commonly-prescribed ASMs were associated with increased risk of cardiac arrhythmias. There was no significant association between use of ASMs and dynamic QTc interval change. Conclusions Certain ASMs, namely carbamazepine, lamotrigine and lacosamide, were associated with fewer cardiac arrhythmias and this association was not dose-dependent. No other ASM was associated with cardiac arrhythmias. Further large clinical prospective studies are needed to confirm these findings and to clarify the mechanism for any potential antiarrhythmic properties of ASMs.

HSPICE simulation and analysis of current reused operational transconductance amplifiers for biomedical applications

The proposed work focuses on the design of a current-reused biomedical amplifier; it is a microwatt-level electrocardiogram (ECG) analog circuit design that addresses low power consumption and noise efficiency. As implantable devices require unobtrusiveness and longevity, the current reuse technique in this circuit effectively enhances power and noise efficiencies. Using 90 nm technology enables efficient circuit implementation, yielding promising simulation results. At 100 Hz, the noise performance reaches 62.095 nV/√Hz, while the power consumption is only 8.3797 µW. These advancements are pivotal for next-generation implantable devices, ensuring reliable operation and reducing frequent battery replacements, improving patient convenience. Moreover, the high noise efficiency ensures that ECG signals are captured with high fidelity, crucial for accurate monitoring and diagnosis. This research addresses the challenges in implantable ECG analog circuit design and sets a benchmark for future developments. The techniques employed can be adapted for other bio signal monitoring devices, broadening the impact on healthcare technology. Ultimately, this advancement contributes to more efficient, reliable, and long-lasting medical devices, enhancing patient monitoring and healthcare on a broader scale.

A Multicenter Evaluation of the Impact of Therapies on Deep Learning-based Electrocardiographic Hypertrophic Cardiomyopathy Markers

Artificial intelligence-enhanced electrocardiography (AI-ECG) can identify hypertrophic cardiomyopathy (HCM) on 12-lead ECGs and offers a novel way to monitor treatment response. Although the surgical or percutaneous reduction of the interventricular septum (SRT) represented initial HCM therapies, mavacamten offers an oral alternative. We aimed to assess the use of AI-ECG as a strategy to evaluate biologic responses to SRT and mavacamten. We applied an AI-ECG model for HCM detection to electrocardiography images from patients who underwent SRT across 3 sites: Yale New Haven Health System (YNHHS), Cleveland Clinic Foundation (CCF), and Atlantic Health System (AHS) and to electrocardiography images from patients receiving mavacamten at YNHHS. A total of 70 patients underwent SRT at YNHHS, 100 at CCF, and 145 at AHS. At YNHHS, there was no significant change in the AI-ECG HCM score before versus after SRT (before SRT: median 0.55 [interquartile range 0.24 to 0.77] vs after SRT: 0.59 [0.40 to 0.75]). The AI-ECG HCM scores also did not improve after SRT at CCF (0.61 [0.32 to 0.79] vs 0.69 [0.52 to 0.79]) and AHS (0.52 [0.35 to 0.69] vs 0.61 [0.49 to 0.70]). Of the 36 YNHHS patients on mavacamten therapy, the median AI-ECG score before starting mavacamten was 0.41 (0.22 to 0.77), which decreased significantly to 0.28 (0.11 to 0.50, p <0.001 by Wilcoxon signed-rank test) at the end of a median follow-up period of 237 days. In conclusion, we observed a lack of improvement in AI-based HCM score with SRT, in contrast to a significant decrease with mavacamten. Our approach suggests the potential role of AI-ECG for serial point-of-care monitoring of pathophysiologic improvement after medical therapy in HCM using ECG images.

A multicenter retrospective study of early cardiac toxicity in operable breast cancer patients receiving concurrent dual or mono anti-HER2 therapy with postoperative radiation therapy.

This study aims to assess whether dual anti-HER2 therapy with trastuzumab and pertuzumab increases early cardiac toxicity compared to trastuzumab alone in breast cancer (BC) patients receiving postoperative radiation therapy (RT). Consecutive operable BC patients receiving postoperative RT and trastuzumab with or without pertuzumab between January 2017 and September 2020at seven tertiary hospitals in China were retrospectively reviewed. Cardiac examinations included echocardiography, electrocardiogram (ECG), NT-proBNP, and cTnI at baseline before RT and during the follow-up. The cardiac event is any new-onset symptomatic heart disease or abnormality in the cardiac examination after RT. In total, 681 patients were enrolled in the analysis, of whom 567 were treated with trastuzumab-alone and 124 patients received dual anti-HER2 therapy. The median follow-up was 11 months. Multivariate analysis showed that left-sided breast cancer (HR 2.38; 95%CI 1.65-3.44, p<0.001) and IMN RT (HR 1.47; 95% CI 1.01-2.15, P-value=0.047) are independent risk factors for ECG abnormalities. Age >50 years is an independent risk factor for developing LVDD (HR 5.16; 95%CI 1.17-22.73, P-value=0.030). Dosimetric analysis showed that patients who developed subclinical cardiac events had increased mean heart dose (412.0±249.6 vs. 347.2±242.6cGy, P-value=0.010). Among right-sided patients or patients receiving anthracycline-based chemotherapy, the dual-targeted cohort had a higher risk of developing ECG abnormalities compared to the trastuzumab-only cohort. Compared with trastuzumab-only, dual anti-HER2 therapy does not increase early cardiac toxicity in combination with postoperative RT in BC patients. Cardiac radiation exposure remains the primary risk factor for early toxicity.

A versatile, highly stretchable, and anti-freezing alginate/polyacrylamide/polyaniline multi-network hydrogel for flexible strain sensors and supercapacitors.

Conductive hydrogels have great potential as electrolyte materials for flexible strain sensors and supercapacitors. However, it remains a challenge to develop multifunctional hydrogels with excellent frost resistance, toughness, ionic conductivity, and electrochemical properties using simple methods. Herein, a "chemical-physical-ionic" cross-linked sodium alginate/polyacrylamide/polyaniline (SA/PAM/Ca2+/PANI) multi-network hydrogel was developed by in situ polymerization of aniline monomer within a Ca2+-crosslinked SA/PAM hydrogel network. The SA/PAM/Ca2+/PANI hydrogel shows excellent mechanical properties, (tensile strength of 0.577MPa at a strain of 1991%), high toughness (5.52 KJ·m-3), and high ionic conductivity (16.51S·m-1 at 25°C and 11.08S·m-1 at -20°C). The SA/PAM/Ca2+/PANI hydrogel-based strain sensor exhibited high sensitivity (gauge factor of 3.82 at 60-500% strain), an extensive detection range (0-2000%), and excellent frost resistance. The strain sensor can accurately monitor various human motions, as well as electrocardiograph (ECG) signals during both rest and exercise. The supercapacitor assembled with the SA/PAM/Ca2+/PANI hydrogel electrolyte exhibited a high surface capacitance (177.19 mF·cm-2 at 2mA·cm-2), maximum energy density (21.93Wh·kg-1), and high power density (3089W·kg-1). Moreover, it maintained satisfactory electrochemical stability with 77.8% capacitance retention after 4000cycles. Therefore, the versatile SA/PAM/Ca2+/PANI hydrogel shows promising potential for applications in flexible wearable electronic devices.

ECGEFNet: A two-branch deep learning model for calculating left ventricular ejection fraction using electrocardiogram.

Left ventricular systolic dysfunction (LVSD) and its severity are correlated with the prognosis of cardiovascular diseases. Early detection and monitoring of LVSD are of utmost importance. Left ventricular ejection fraction (LVEF) is an essential indicator for evaluating left ventricular function in clinical practice, the current echocardiography-based evaluation method is not avaliable in primary care and difficult to achieve real-time monitoring capabilities for cardiac dysfunction. We propose a two-branch deep learning model (ECGEFNet) for calculating LVEF using electrocardiogram (ECG), which holds the potential to serve as a primary medical screening tool and facilitate long-term dynamic monitoring of cardiac functional impairments. It integrates original numerical signal and waveform plots derived from the signals in an innovative manner, enabling joint calculation of LVEF by incorporating diverse information encompassing temporal, spatial and phase aspects. To address the inadequate information interaction between the two branches and the lack of efficiency in feature fusion, we propose the fusion attention mechanism (FAT) and the two-branch feature fusion module (BFF) to guide the learning, alignment and fusion of features from both branches. We assemble a large internal dataset and perform experimental validation on it. The accuracy of cardiac dysfunction screening is 92.3%, the mean absolute error (MAE) in LVEF calculation is 4.57%. The proposed model performs well and outperforms existing basic models, and is of great significance for real-time monitoring of the degree of cardiac dysfunction.

Prevalence and Prognostic Impact of ST Segment Elevation in Lead aVR Among Patients with Cardiac Arrest.

In acute coronary syndrome, ST-segment elevation in lead aVR (STE-aVR) indicates global myocardial ischemia, often related to multivessel or severe left main disease, and correlates with increased mortality. The prevalence and prognostic significance of STE-aVR in cardiac arrest (CA) patients is unknown. We identified patients (≥18 years) with CA between 2011 to 2022 who achieved return of spontaneous circulation (ROSC). The first electrocardiogram (ECG) post-ROSC was assessed for STE-aVR, defined as ≥1 mm ST-segment elevation at the J point, measured by two trained assessors. Multivariable logistic regression was used to analyze the association between STE-aVR and outcomes (in-hospital mortality and poor neurologic outcome), adjusted for patient and arrest characteristics. Including 443 CA patients, the median (IQR) age was 61 years (50-72 years), with 60.5% (n=268) male, 65.7% (n=291) presenting with out-of-hospital cardiac arrest (OHCA) and 29.8% (n=132) with shockable rhythms. STE-aVR was observed in 18.3% (n=81) of patients. Those with STE-aVR were more likely to present with OHCA and less likely to have a shockable rhythm (both, P<0.05). STE-aVR was associated with higher in-hospital mortality (86.4% vs 65.8%, P<0.001) and poor neurologic outcomes (90.1% vs 72.9%, P=0.001). After multivariable adjustment, STE-aVR remained associated with higher in-hospital mortality (odds ratio [OR] 2.23; 95% confidence interval [CI]: 1.02-4.84, P=0.04), but not a poor neurologic outcome (OR 2.12; 95% CI: 0.90-4.98, P=0.09). STE-aVR was present in 1 in 5 CA survivors and was independently associated with higher in-hospital mortality.

Beaware of Intracardiac Potentials Induced by Intravascular Lithotripsy.

Intravascular lithotripsy (IVL), that generates shockwaves through spark gap discharge between emitters, has been increasingly used to treat severely calcified coronary artery lesions. However, there is a question as to whether IVL has no electrical effects on endocardial tissues or cardiac implantable devices (CIEDs). The aim of this study was to investigate the effects of IVL-induced intracardiac potentials on cardiac electrophysiology and CIEDs. Specifically, we examined how spark gap discharge of IVL influence myocardial electrical activity and the sensing function of CIEDs. We conducted a preliminary in vitro experiment using an IVL and a pacemaker placed in a saline-filled container, where we observed that the pacemaker did indeed detect the discharge of IVL, leading to pacing inhibition. Then, 13 patients undergoing PCI with IVL were investigated with real-time monitoring of in vivo intracardiac electrogram (EGM) synchronized with body surface ECG, with an external temporary pacing lead placed in the right ventricle. Similar to the above experiment, we found that IVL pulses were indeed detected on the EGM and sensed by the temporary pacemaker. Of the 287 IVL pulses outside the range of absolute refractory period, 59 (20.6%) captured the ventricle, while the remaining 228 (79.4%) did not elicit any electrical myocardial activity. Our observations indicate concerns about the use of IVL: the risk of inducing fatal arrhythmia and the occurrence of cardiac arrest or bradycardia in the CIED-dependent patients. IVL users should be aware of the potential risk of such events.

Inappropriate Shocks in Brugada Syndrome Patients With a Subcutaneous Implantable Cardioverter Defibrillator.

This study aimed to compare inappropriate shock (IAS) rates between subcutaneous implantable cardioverter-defibrillator (S-ICD) and transvenous ICD (TV-ICD) in Brugada syndrome (BrS) patients and identify risk factors for IAS in S-ICD use. We enrolled consecutive patients with BrS who underwent ICD implantation between 2013 and 2023. Data on clinical characteristics, S-ICD screening test data, and IAS occurrence were retrospectively analyzed. In total, 74 patients (40 with S-ICDs and 34 with TV-ICD) were enrolled in the study. During a median follow-up of 4.6 years, IAS occurred in nine S-ICD and three TV-ICD patients, exhibiting a non-statistically significant trend (log-rank p = 0.103) toward a higher incidence in the S-ICD group. The incidence of IAS related to non-atrial tachyarrhythmia (non-AT) causes was significantly higher in the S-ICD group than in the TV-ICD group (log-rank p = 0.014). Fewer electrocardiography (ECG) sensing vectors passing the screening test at both the baseline and exercise test (hazard ratio [HR] 0.31, 95% confidence interval [CI] 0.09-0.85; p = 0.21) and detection of ATs (HR 5.25, 95% CI 1.15-24.05; p = -0.048) were associated with IAS in patients with S-ICD. No significant difference was observed in the overall incidence of IAS between the S-ICD and TV-ICD groups; however, IAS due to non-AT causes occurred more frequently in the S-ICD group. Fewer ECG sensing vectors passing screening were significantly correlated with the IAS when exercise test results were considered. Therefore, ECG screening, including exercise testing, is preferable for S-ICD candidates.

Outcomes of electrical injuries in the emergency department: epidemiology, severity predictors, and chronic sequelae.

Electrical injuries (EIs) represent a significant clinical challenge due to their complex pathophysiology and variable presentation, ranging from minor burns to severe internal organ damage. Despite their prevalence in both; domestic and occupational settings, there remains a rareness of systematic guidelines and comprehensive literature to aid clinicians in effectively managing these injuries. Understanding these factors is crucial for developing protocols that can mitigate the risk of delayed complications, such as cardiac arrhythmias, in patients who initially appear stable. This study aims to elucidate the epidemiology, clinical outcomes, and predictors of severe presentation in EIs, providing insights to improve patient assessment and management strategies. A retrospective study was conducted over 4 years. Data were collected from standardized medical records. The group of patients with severe complications included those who presented a life-threatening cardiac, respiratory, neurological, or biological impairment or died within the first 48 h of the EI. We enrolled 118 cases of electrical injury (EI). Ages ranged from 4 to 82 years, with 31.3% under 15. EI incidence peaked in summer, with 63.5% being home accidents. High-voltage injuries occurred in 13.6%. The most common ED complaints were burns in children (59.5%) and trauma in adults (48.1%). ECG abnormalities correlated with tetany (p = 0.016), and palpitations (p = 0.014). Complications included cardiac arrest (n = 8), rhabdomyolysis (n = 23), and acute renal injury (n = 9). Severe EI was linked to respiratory distress and creatine kinase levels higher than ≥ 253 UI/l. A normal ECG within 1 h post-injury was correlated to a low risk of severe EI. At 2-year follow-up, 43.9% of survivors reported aesthetic sequelae, 25.3% had psychological disorders, and 7% of adults could not return to their previous occupations. EIs are frequent, with diverse clinical presentations requiring multidisciplinary care. Awareness of potential delayed complications is essential, and prevention is crucial.

Angiotensin 1-7 Attenuates the Development of Ischemia-Reperfusion-Induced Arrhythmia in Rats: Electrophysiology, Molecular, and Immunohistochemical Study.

Arrhythmia is a common and serious global health problem, contributing to cardiovascular morbidity and mortality. The cardiac muscle is susceptible to ischemia-reperfusion (I/R) injury, which can lead to fatal arrhythmias during open-heart surgery. We investigated the potential prophylactic effect of angiotensin 1-7 (Ang 1-7) using an invivo rat model of I/R injury and examined the underlying mechanisms. Rats were treated with Ang 1-7 (1 mg/kg, IP) 30 min before the surgical procedures. Twenty-four rats were equally divided into four groups: sham control, sham-treated with Ang 1-7, I/R injury group, and I/R injury group treated with Ang 1-7. Invivo I/R injury was induced by clamping the left coronary artery for 30 min, followed by 1 hour of reperfusion. The I/R group showed abnormal electrophysiological changes and arrhythmic episodes during electrocardiography (ECG) recording, increased oxidative stress, downregulation of peroxisome proliferator-activated receptor gamma (PPAR-γ), and upregulation of C-X-C motif chemokine ligand 16 (CXCL16) expression in cardiac tissue, which increased cardiac NF-kB expression and IL-17 levels. Moreover, I/R injury caused significant histological disruption and increased cyclooxygenase 2 (COX-2) and heat shock protein 90 (HSP90) immunoreactions, correlating with the extent of cardiac damage. However, preoperative Ang 1-7 administration significantly improved the electrophysiological, biochemical, and histopathological changes induced by I/R injury. This study demonstrated that Ang 1-7 exerted protective anti-arrhythmic, anti-inflammatory, and pro-healing effects by upregulating PPAR-γ and downregulating CXCL16, IL-17, and NF-kB pathways, suggesting it is a promising cardioprotective agent for preventing arrhythmias induced by I/R injury.

Determining the QRS axis: visual estimation is equal to calculation.

The QRS axis of the electrocardiogram (ECG) is often considered in clinical practice, but its determination is frequently limited to arough estimation, such as "normal", with left or right deviation, and superior or inferior in the case of premature ventricular complexes (PVCs). However, amore exact determination of the QRS axis may be warranted in certain scenarios, such as to determine the origin of PVCs more precisely, and is attainable by visual estimation using the hexaxial reference system. The aim of this study was to determine how well such an estimation of the QRS axis would correlate with the axis calculated by formulas. APVC database from 2012-2020 was used to extract 12-lead ECGs of patients with outflow tract PVCs and analyze the QRS axes of regularly conducted beats as well as PVCs. QRS axes were determined visually by two physicians with the help of the hexaxial reference system to an accuracy of10° on the one hand, and were calculated using three previously described formulas based on QRS voltages on the other. Atotal of 216 QRS complexes from 108 patients were analyzed (108 regularly conducted beats and 108 PVCs). Estimated QRS axes of regularly conducted beats and PVCs were 39 ± 40° and 88 ± 15°, respectively. Calculated QRS axes of regularly conducted beats according to the three formulas were 37 ± 40°, 36 ± 40° and 35 ± 38°, respectively. Calculated QRS axes of PVCs according to the three formulas were 87 ± 15°, 87 ± 14° and 86 ± 16°, respectively. Correlation coefficients showed strong correlations between the estimated and the three calculated values for regularly conducted beats (0.98, 0.97 and 0.98) and PVCs (0.94, 0.94 and 0.94). Asophisticated visual estimation of the QRS axis correlates well with voltage-based calculations and can therefore be considered sufficient for most purposes.

ELECTROCARDIOGRAPHY FINDINGS IN BLUNT CHEST TRAUMA AT TERTIARY CARE HOSPITAL PESHAWAR

Introduction: Blunt chest trauma is a significant cause of morbidity and mortality, often leading to a range of cardiac complications detectable through electrocardiogram (ECG) abnormalities. Objectives: The primary objective of this research was to identify the early onset of myocardial damage in patients with acute blunt chest injuries using ECG. The secondary objective is being to compare the ECG changes between paediatric and adult trauma patients. Methodology: This cross-sectional study was conducted in the Emergency department (ED) and patients admitted with acute blunt chest trauma were included in the current study. A total of 281 patients were included based on the following inclusion criteria: patients of all ages with blunt chest trauma. Exclusion criteria included preexisting cardiac and neurological conditions, penetrating chest injuries, pregnant women and incomplete medical records. Demographic and clinical data were collected, and a standard 12-lead ECG was performed and analyzed for abnormalities. Statistical analysis was done using SPSS version 26, where chi square test was applied to identify factors that may be associated with ECG abnormalities and assess age-related differences in ECG findings. Results: ECG findings in patients with blunt chest trauma, recorded in 30.9% of the total sample. Sinus arrhythmia's, particularly sinus tachycardia were the most common findings in both adults (6.2%) and pediatrics (8.1%). In adult’s sinus tachycardia was followed by ST segment changes and atrial fibrillation. In pediatrics, sinus tachycardia was accompanied by PVCs and supraventricluar tachycardia. Conclusion: Sinus arrhythmias were the most common findings in both group, followed by ST segment changes and atrial fibrillation in adults while in pediatrics, followed by PVCs and SVT.

Application of Ear-EEG and Other Wearable Systems in Sleep Assessment

Nowadays, about one-third of adults have the symptoms of insomnia. To assess these issues, one of the traditional methods used is polysomnography (PSG). However, it is expensive and not widely accessible, highlighting the urgent need for advancements in wearable technology to provide a more practical alternative for continuous sleep monitoring at home. This paper aims to explore various sleep assessment methods, including electrocardiography (ECG), photoplethysmography (PPG), and actigraphy, which measure heart activity, pulse wave, and muscle movement, respectively. By evaluating these methods, the paper analyses their advantages and challenges, particularly focusing on their accuracy in sleep stage classification and comfort levels. At the same time, this study compares Ear-EEG systems with other methods to assess their effectiveness in sleep monitoring. The future development directions for Ear-EEG in sleep monitoring are also discussed, encompassing aspects such as age variability, design improvements, and integrating advanced algorithms. Future advancements in at-home sleep assessments are expected to treat sleep disorders more efficiently and conveniently through early detection of disorders and improved user-friendliness compared to PSG.

Effects of transcutaneous auricular vagus nerve stimulation (taVNS) on motor planning: a multimodal signal study.

Motor planning plays a pivotal role in daily life. Transcutaneous auricular vagus nerve stimulation (taVNS) has been demonstrated to enhance decision-making efficiency, illustrating its potential use in cognitive modulation. However, current research primarily focuses on behavioral and single-modal electrophysiological signal, such as electroencephalography (EEG) and electrocardiography (ECG). To investigate the effect of taVNS on motor planning, a total of 21 subjects were recruited for this study and were divided into two groups: active group (n = 10) and sham group (n = 11). Each subject was required to be involved in a single-blind, sham-controlled, between-subject end-state comfort (ESC) experiment. The study compared behavioral indicators and electrophysiological features before and following taVNS. The results indicated a notable reduction in reaction time and an appreciable increase in the proportion of end-state comfort among the participants following taVNS, accompanied by notable alterations in motor-related cortical potential (MRCP) amplitude, low-frequency power of HRV (LF), and cortico-cardiac coherence, particularly in the parietal and occipital regions. These findings show that taVNS may impact the brain and heart, potentially enhancing their interaction, and improve participants' ability of motor planning.