Electrocardiographic predictors of cardiovascular events in patients at high cardiovascular risk: a multicenter study

Background There are limited data on the prevalence of electrocardiographic (ECG) abnormalities, and their value for predicting a major adverse cardiovascular event (MACE) in patients at high cardiovascular risk. This study aimed to determine the prevalence of ECG abnormalities in patients at high risk for cardiovascular events, and to identify ECG abnormalities that significantly predict MACE. Methods Patients aged ≥ 45 years with established atherosclerotic disease (EAD) were consecutively enrolled from the outpatient clinics of the six participating hospitals during April 2011 to March 2014. The following data were collected: demographic data, cardiovascular risk factors, history of cardiovascular event, physical examination, ECG and medications. ECG was analyzed using Minnesota Code criteria. MACE included cardiovascular death, non-fatal myocardial infarction, and hospitalization due to unstable angina or heart failure. Results A total of 2009 patients were included, 1048 patients (52.2%) had established EAD, and 961 patients (47.8%) had multiple risk factors (MRF). ECG abnormalities included atrial fibrillation (6.7%), premature ventricular contraction (5.4%), pathological Q-wave (Q/QS)(21.3%), T-wave inversion (20.0%), intraventricular ventricular conduction delay (IVCD)(7.3%), left ventricular hypertrophy (LVH)(12.2%), and AV block (12.5%). MACE occurred in 88 patients (4.4%). Independent predictors of MACE were chronic kidney disease, EAD, and the presence of atrial fibrillation, Q/QS, IVCD or LVH by ECG. Conclusions A high prevalence of ECG abnormalities was found. The prevalence of ECG abnormalities was high even among those with risk factors without documented cardiovascular disease.

Arterial hypertension and electrocardiographic diagnosis of left ventricular hypertension in the group of geriatric patients with coronary heart disease living in the far north

As a result of research, high prevalence of arterial hypertension has been identified in the group of patients with coronary heart disease aged 60 and older. Most often, occurring form of arterial hypertension among geriatric patients is isolated systolic arterial hypertension (ISAH). The comparison of two ethnic groups of the population has showed higher levels of systolic and diastolic blood pressure (SBP and DBP) in the group of patients of non-indigenous nationality, rather than Yakut patients. Correlation was recorded in the group of non-indigenous patients as they age. Significant increase in the level of SBP was identified in the group of senile and long-livers than in the elderly. Detection of ECG signs of LVH showed the lowest specificity of Cornell voltage criterion comparing to Sokolow-Lyon criterion with its more often occurrence. ECG-signs of left ventricle hypertrophy are significantly more often established by Sokolow-Lyon criterion for men, Cornell voltage—for women. Correlation has been found between the presence of LVH and combination of Cornell voltage criterion with both Gubner-Ungerleider and Sokolow-Lyon criteria.

Validity of electrocardiographic criteria for increased left ventricular mass in young patients in the general population

AIMTo investigate validity of electrocardiographic(ECG)criteria for left ventricular hypertrophy(LVH)in young adults.METHODS Retrospectively,echocardiograms showing LVH and concomitant electrocardiograms were collected in patients 18 to 39 years old.A control group of patients without LVH was collected.Using echocardiogram as the gold standard,electrocardiograms were analyzed using common voltage criteria.RESULTS Study included 100 subjects(52%male,mean age=28±6.8 years,96%Hispanic or African-American)with 50%LVH prevalence.Sensitivity and specificity for SokolowLyon criteria were 24%(95%CI:13.5%-38.4%)and 88%(95%CI:74.9%-95%).For Cornell criteria,sensitivity was 32%(95%CI:19.9%-46.8%)and specificity 98%(95%CI:87.9%-99.8%).For R in a VL criteria,sensitivity was 12%(95%CI:4.9%-25%)and specificity 100%(95%CI:91.1%-100%).CONCLUSION In young adults common ECG voltage criteria have low sensitivities and high specificities similar to other age groups.Low sensitivities preclude these ECG criteria from serving as effective screening tests.

Electrocardiographic Safety of Daily Hydroxychloroquine 400 mg Plus Azithromycin 250 mg as an Ambulatory Treatment for COVID-19 Patients in Cameroon

Objective: To determine the early electrocardiographic changes in a cohort of ambulatory cameroonian COVID-19 patients treated with hydroxychlo- roquine and Azithromycin. Design: Prospective study. Setting: Treatment centres of the city of Yaounde, Cameroon, from May 7th to 24th 2020. Participants: We enrolled 51 consecutive confirmed COVID-19 on RT-PCR who having mild forms of COVID-19 and treated by hydroxychloroquine 200 mg twice daily during seven #days plus Azithromycin 500 mg the first day and 250 mg the remaining 4 days as per national standard. Main Outcomes Measures: The primary end-point was the change in QTc interval between day 0 (D0), day 3 (D3) and day 7 (D7). Secondary endpoints were changes in all other cardiac electrical conductivity patterns and the occurrence of clinical arrhythmic events during the course of treatment. Results: The population (29 men and 22 women) was aged 39 ± 11 years (range 17 to 61 years). Mean Tisdale score was 3.35 ± 0.48. No significant change from baseline (D0) of QTc was observed at D7 (429 ± 27 ms at D0 versus 396 ± 26 ms at D7;p = 0.27). A reduction of heart rate was observed between the D0 and D7 (75 ± 13 bpm versus 70 ± 13 bpm, p = 0.02) with increased QRS duration between D0 and D7 (95 ± 10 ms versus 102 ± 17 ms, p = 0.004). No symptomatic arrhythmic events occurred during the treatment course. Conclusions: No life-threatening modification of the QT interval was observed in non-severe COVID-19 patients treated ambulatory with hydroxychloroquine and azithromycin. Studies are needed in critical-ill and older patients.

Electrocardiographic Manifestations of Endocrine and Metabolic Disorders

Endocrine dysfunction has an adverse impact on the cardiovascular system that may be due to an endocrine abnormality that leads to electrocardiogram (EKG) changes. The EKG changes due to endocrine disorder can be reversible and irreversible and treating underlying disease can reverse EKG changes in some cases. In this article, we review the electrocardiogram manifestations of various endocrine disorders.

The electrocardiographic changes in acute brain injury patients

Background Electrocardiographic （ECG） changes occurring during the course of acute brain injury （ABI） have been described frequently, but their significances remain uncertain. The present study was designed to investigate the relation of ECG abnormalities to outcome in the patients with ABI. Methods We performed a retrospective, observational study on the ABI patients admitted to the Department of Neurosurgery of the Beijing Tiantan Hospital between December 2005 and December 2007. All the patients accepted 12-lead electrocardiographic examination within 24 hours after injury, then divided into three groups according to the Glasgow coma score （GCS）. In-hospital mortality and one-month outcome assessed by the Glasgow outcome score （GOS） were investigated. Results Of 335 ABI patients （mean ages 32.4 years）, 246 patients （73.4%） had abnormal ECGs. The most common abnormality was ST-T changes （41.5%）, followed by sinus tachycardia （23.6%）. ECG changes had a significant association with the severity and outcome. Logistic regression analysis showed the presence of ST-T changes （OR 2.587, 95%C/1.009 to 6.629, P=0.048） and QT dispersion prolongation （OR 4.656, 95%C/1.956 to 11.082, P=0.001） significantly associated with short outcomes. Conclusions ABI can lead to myocardial damage and ECG changes had a significant association with the severity. ST-T changes and QT dispersion prolongation were the independent prognosis factors for the negative outcome of ABI patients.

Ventricular repolarization markers for predicting malignant arrhythmias in clinical practice

Malignant cardiac arrhythmias which result in sudden cardiac death may be present in individuals apparently healthy or be associated with other medical conditions. The way to predict their appearance represents a challenge for the medical community due to the tragic outcomes in most cases. In the last two decades some ventricular repolarization(VR) markers have been found to be useful to predict malignant cardiac arrhythmias in several clinical conditions. The corrected QT, QT dispersion, Tpeak-Tend, Tpeak-Tend dispersion and Tp-e/QT have been studied and implemented in clinical practice for this purpose. These markers are obtained from 12 lead surface electrocardiogram. In this review we discuss how these markers have demonstrated to be effective to predict malignant arrhythmias in medical conditions such as long and short QT syndromes, Brugada syndrome, early repolarization syndrome, acute myocardial ischemia, heart failure, hypertension, diabetes mellitus, obesity and highly trained athletes. Also the main pathophysiological mechanisms that explain the arrhythmogenic predisposition in these diseases and the basis for the VR markers are discussed. However, the same results have not been found in all conditions. Further studies are needed to reach a global consensus in order to incorporate these VR parameters in risk stratification of these patients.

Rationale and Design of the Randomized Controlled Trial of Intensive Versus Usual ECG Screening for Atrial Fibrillation in Elderly Chinese by an Automated ECG System in Community Health Centers in Shanghai(AF-CATCH)

Objective:The randomized controlled trial(ClinicalTrials.gov identifier NCT02990741)will investigate whether more frequent electrocardiographic(ECG)recordings and analyses with an automated ECG system would improve detection of atrial fibrillation compared with a single annual ECG screen in elderly Chinese in community health centers.Design:Men and women(≥65 years)will be randomized into intensive(n=3500)and usual(n=3500)screening groups,and within the intensive screening group into intensive screening(n=2625)and more intensive screening(n=875)subgroups.ECG recordings will be performed with an automated ECG analysis system(AliveCor heart monitor)at 1 year in the usual screening group,at 3,6,9,and 12 months in the intensive screening subgroup,and at 1,2,3,and 4 weeks and 3,6,9,and 12 months in the more intensive screening subgroup.The primary outcome is the detection rate of atrial fibrillation between the usual screening group and the intensive screening group.Sample size estimation was based on a projected detection rate of atrial fibrillation of 2.0% by a single ECG recording at 12 months,an improvement of 50% with more frequent ECG recordings,α=0.05,power of 80%,and a one-sided test.Conclusions:The trial will provide evidence on the clinical effectiveness of more frequent ECG recordings by a handheld automated analysis system in the detection of atrial fibrillation.

A cellular automaton model for the ventricular myocardium considering the layer structure

A cellular automaton model for the ventricular myocardium considering the layer structure has been established. The three types of cells in this model differ principally in the repolarization characteristics. For the normal travelling waves in this model, the computer simulation results show the R, S, and T waves and they are qualitatively in agreement with the standard electrocardiograph. Phenomena such as the potential decline of point J and segment ST and the rise of the potential line after the T wave appear when the ischemia occurs in the endocardium. The spiral wave has also been simulated, and the corresponding potential has a lower amplitude, higher frequency, and wider R wave, which accords with the distinguishing feature of the clinical electrocardiograph. Mechanisms underlying the above phenomena are analyzed briefly.

APPLICATION OF FRACTAL THEORY IN TRANSIENT CHAOTIC SIGNAL DETECTION

According to the definition of correlation dimension in fractal theory, this paper presented a method to determine and assess noise part in detected transient signal. Such work is essential to decrease the noise part in the detected signal. It is proved that heart period signal (HPS) is one typical sort of transient chaotic signal. Through experiment and simulation, the analysis of chaotic HPS in the detected signal was done. In the end, we deepen the researches on attractor dimension of HPS for persons who are different in age.

Remote electrocardiograph monitoring using a novel adhesive strip sensor: A pilot study

The increase in health care costs is not sustainable and has heightened the need for innovative low cost effective strategies for delivering patient care. Remote monitoring holds great promise for preventing or shortening duration of hospitalization even while improving quality of care. We therefore conducted a proof of concept study to examine the quality of electrocardiograph (ECG) recordings obtained remotely and to test its potential utility in detecting harmful rhythms such as atrial fibrillation. We tested a novel adhesive strip ECG monitor and assessed the ECG quality in ambulatory individuals. 2630 ECG strips were analyzed and classified as: Sinus, atrial fibrillation (AF), indeterminate, or other. Four readers independently rated ECG quality: 0: Noise; 1: QRS complexes seen, but P-wave indeterminate; 2: QRS complexes seen, P-waves seen but poor quality; and 3: Clean QRS complexes and P-waves. The combined average rating was: Noise 12%; R-R, no P-wave 10%; R-R, no PR interval 18%; and R-R with PR interval 60% (if Sinus). If minimum diagnostic quality was a score of 1, 88% of strips were diagnostic. There was moderate to high agreement regarding quality (weighted Kappa statistic values; 0.58 to 0.76) and high level of agreement regarding ECG diagnosis (ICC = 0.93). A highly variable RR interval (HRV ≥ 7) predicted AF (AUC = 0.87). The monitor acquires and transmits diagnostic high quality ECG data and permits characterization of AF.

Characterization of alternating current impedance properties of biomedical electrodes

To study the alternating current （AC） impedance properties of Ag/AgC1 electrocardiograph （ECG） electrodes, the electrode pair was gel-to-gel connected, and then the electrical potential was recorded after a safe stimulating current passes through the electrode pair, so the AC impedance data of ECG electrodes were obtained. Varying the frequency and value of stimulating current, the detailed comparison and analysis of AC impedance properties of the electrodes were performed, and the stability was further characterized by using the continuous measurement within 24 h. The experimental results show that the AC impedance values of electrodes decreased, and then slightly increased with the increase of frequency of stimulating current. The minimum AC impedance value was obtained when the frequency was changed to 10 kHz. When the stimulating current increased, the AC impedance values of electrodes showed a slight decrease, but did not change significantly. Besides, the continuous measurement results show that the impedance value presented a significant increase in the initial 30 min, and then was stabilized in the following measuring process.

Deep Learning Convolutional Neural Network for ECG Signal Classification Aggregated Using IoT

Much attention has been given to the Internet of Things (IoT) by citizens, industries, governments, and universities for applications like smart buildings, environmental monitoring, health care and so on. With IoT, networkconnectivity is facilitated between smart devices from anyplace and anytime.IoT-based health monitoring systems are gaining popularity and acceptance forcontinuous monitoring and detect health abnormalities from the data collected.Electrocardiographic (ECG) signals are widely used for heart diseases detection.A novel method has been proposed in this work for ECG monitoring using IoTtechniques. In this work, a two-stage approach is employed. In the first stage, arouting protocol based on Dynamic Source Routing (DSR) and Routing byEnergy and Link quality (REL) for IoT healthcare platform is proposed for effi-cient data collection, and in the second stage, classification of ECG for Arrhythmia. Furthermore, this work has evaluated Support Vector Machine (SVM),Artificial Neural Network (ANN), and Convolution Neural Networks (CNNs)-based approach for ECG signals classification. Deep-ECG will use a deep CNNto extract critical features and then compare through evaluation of simple and fastdistance functions in order to obtain an efficient classification of heart abnormalities. For the identification of abnormal data, this work has proposed techniquesfor the classification of ECG data, which has been obtained from mobile watchusers. For experimental verification of the proposed methods, the Beth Israel Hospital (MIT/BIH) Arrhythmia and Massachusetts Institute of Technology (MIT)Database was used for evaluation. Results confirm the presented method’s superior performance with regards to the accuracy of classification. The CNN achievedan accuracy of 91.92% and has a higher accuracy of 4.98% for the SVM and2.68% for the ANN.

Deep learning-based approaches for myocardial infarction detection:A comprehensive review recent advances and emerging challenges

Myocardial infarction(MI)is a severe heart disease requiring immediate and accurate detection for effective treatment.Deep learning(DL)algorithms have recently shown promise in enhancing MI diagnostic accuracy from electrocardiography(ECG)and echocardiogram(ECHO).This review presents a comprehensive literature overview focusing on recent innovative research on DL algorithms in ECG and ECHO analysis for MI identification.We examined relevant studies employing DL models,analyzing datasets,model architectures,preprocessing approaches,and performance measures.The findings reveal that DL-based algorithms substantially improve MI detection in terms of accuracy,sensitivity,specificity,and overall diagnostic performance.This is crucial for quicker,more reliable diagnoses and reducing the risk of complications.DL-based ECG and ECHO analyses emerge as pivotal tools for early and efficient MI identification.This review contributes to understanding the latest DL advancements in ECG and ECHO analysis for MI diagnosis,offering important directions for future research.

Clinical study of 39 Chinese patients with arrhythmogenic right ventricular dysplasia/cardiomyopathy

Background There are few studies on the clinical profile of Chinese patients with arrhythmogenic right ventricular dysplasia/cardiomyopathy （ARVD/C）. The purpose of this study was to describe the clinical characteristics of ARVD/C patients from China, particularly to define the features of electrocardiograph and treatment outcomes. Methods Thirty-nine patients hospitalized in Fu Wai Cardiovascular Hospital from 1998 to 2006 were included. The data were obtained from the medical archive and the follow-up records. Results Of these patients 33 were male and 6 female （age at the first presentation was （34.9 ± 9.8） years）. The most common symptoms were palpitation （62%） and syncope （44%）. Right precordial QRSd 〉 110 ms was detected in 69% of the patients, epsilon wave in 59%, and a ratio of QRSd in V1＋V2＋V3/V4＋V5＋V6 ≥ 1.2 in 82%. The most frequent features of electrocardiogram in patients without right bundle-branch block were T-wave inversions and S-wave upstroke in V1-V3 〉55 ms （96% and 90% of 28 patients, respectively）. Radiofrequency catheter ablation （RFCA） for ventricular tachycardia （VT） was successful in 15 （68%） of 22 patients. The recurrence rate of VT was 46% （7/15） during the follow-up of （16.7 ± 11.2） months. Seven patients had cardioverter/defibrillator （ICD） implanted plus drug therapy and 17 patients took antiarrhythmic drugs alone. During the follow-up of （35.6 ± 19.0） months, all patients with ICD implanted received at least one appropriate ICD shock. One patient died of ventricular fibrillation suddenly and one patient underwent heart transplantation for progressive biventricular heart failure during the drug therapy alone. Conclusions This study demonstrated the clinical and ECG features of the 39 ARVD/C Chinese patients. ICD provided life-saving protection by effectively terminating malignant arrhythmias, and the high recurrence of VT was the major problem of RFCA therapy.

Research on ECG classification based on transfer learning

Concerning current deep learning-based electrocardiograph(ECG) classification methods, there exists domain discrepancy between the data distributions of the training set and the test set in the inter-patient paradigm. To reduce the negative effect of domain discrepancy on the classification accuracy of ECG signals, this paper incorporates transfer learning into the ECG classification, which aims at applying the knowledge learned from the training set to the test set. Specifically, this paper first develops a deep domain adaptation network(DAN) for ECG classification based on the convolutional neural network(CNN). Then, the network is pre-trained with training set data obtained from the famous Massachusetts Institute of Technology-Beth Israel Hospital(MIT-BIH) ECG arrhythmia database. On this basis, by minimizing the multi-kernel maximum mean discrepancy(MK-MMD) between the data distributions of the training set and the test set, the pre-trained network is adjusted to learn transferable feature representations. Finally, with the low-density separation of unlabeled target data, the feature representations are more transferable. The extensive experimental results show that the proposed domain adaptation method has reached a 7.58% improvement in overall classification accuracy on the test set, and achieves competitive performance with other state-of-the-arts.

Soft,stretchable,wireless intelligent three-lead electrocardiograph monitors with feedback functions for warning of potential heart attack

Cardiovascular diseases(CVDs)are fatal chronic diseases,where electrocardiography(ECG)monitoring could be a prominent solution for early diagnosis.In spite of available commercialized,multilead ECG devices,bulky formats,discontinuous monitoring,and no safety alarm system significantly limit their practical applications.Herein,we present a soft,and stretchable,three-lead ECG device allowing continuous monitoring and wireless transmission of ECG signals.A newly developed organohydrogel patch with a strong adhesive ability(~9.9 kPa)and higher conductivity(~6.5 kΩ)is applied for high-quality ECG signals collection.With a long operation duration(6.5 h)and wireless transmission distance(20.9 m),it could fulfill most of the daily applications.Machine learning algorithms and the graphical user interface are used for real-time ECG monitoring and cardiac abnormalities diagnosis.The vibratory flexible actuator,which is triggered by cardiac abnormalities that need immediate medical treatment,is also integrated as a warning system for the user.As a newly reported stretchable multi-lead ECG device for long-term ECG signal monitoring,there is a high potential for improving users'life quality with the high-risk population of CVDs.

Newly detected atrial fibrillation is associated with cortex-involved ischemic stroke

Background: Both cortical and cortical-subcortical (cortex-involved) lesions are typically associated with embolic stroke, of which atrial fibrillation (AF) is the common cause. The aim of this study was to find out the associations between cortex-involved stroke, vascular risk factors, and the subtypes (discovery time and duration) of AF. Methods: This was an imaging study of the China Atrial Fibrillation Screening in Acute Ischemic Stroke Patients (CRIST) trial. Between October 2013 and June 2015, 1511 acute ischemic stroke or transient ischemic attack (TIA) patients within 7 days after stroke onset at 20 Chinese hospitals were enrolled in this prospective, multicenter cohort, cross-sectional study. The final analysis of this sub-study included 243 patients with AF with required magnetic resonance imaging (MRI) sequences. AF was diagnosed by 6-day Holter monitoring and classified by duration of 24 h. Two stroke specialists blinded to the clinical information reviewed MRI (diffusion-weighted MRI). The third stroke specialists, also blinded to the clinical information, assessed the conflicts. Adjusted large artery atherosclerosis as confounding factor, the associations between cortex-involved lesions, vascular risk factors, and the subtype of AF were evaluated by univariate and multivariate regression analyses. Results: Of 243 acute ischemic stroke patients with AF, 190 were known AF and 53 were newly detected AF. There were 28 patients with AF persistent >24 h and 25 persistent ≤24 h in newly detected AF. Patients with newly detected AF were likely to have a fewer history of stroke or TIA (16.98% vs. 36.31%, P = 0.008) and lower fasting blood glucose (5.91 ± 1.83 mmol/L vs. 6.75 ± 3.83 mmol/L, P = 0.030) than patients with known AF. Among these 243 patients, 102 (41.98%) patients were with cortex-involved lesions. Cortex-involved lesions were significantly related to newly detected AF persistent >24 h (odds ratio [OR]: 4.517, 95% confidence interval [CI]: 1.490–13.696, P = 0.008), proteinuria (OR: 3.431, 95% CI: 1.530–7.692, P = 0.021), and glycosylated hemoglobin (OR: 0.632, 95% CI: 0.464–0.861, P = 0.004). Conclusions: Compared to previously known AF, newly detected AF persistent >24 h was associated with cortex-involved ischemic stroke.

Improved modified moving average analysis of T-wave alternans using least squares-based curve fitting method

T-wave alternans （TWA） in surface electrocardiograph （ECG） signal is considered a marker of abnormal ventricular function which may be associated with ventricular tachy- cardia. Several methods have been developed in recent years to evaluate the important feature. One such method is known as modified moving average （MMA） analysis, which performs well for different levels of TWA, but it is sensitive to the noise in T-waves. In this paper we propose an improved MMA algorithm, which adds a stage of T-wave curve fitting for the MMA method before intermediate averaging. The curve fitting is performed by means of least square method technique. Our assessment study demon- strates the improved performance.

The Improvement of ECG Parameter Estimation Obtained by Up-sampling 500 Hz Data

Nowadays, numerous commercial electrocardiographs(ECG) have500 Hz output sampling rate, i.e., 2 ms corresponding sampling interval. Medical workers who have no background of signal processing may worry about whether such low 500 Hz output sampling rate data could support high-precision estimation of electrocardiogram parameters by being up-sampled. With intention to clarify the problem to the medical workers, this paper takes some simulating experiment to illustrate it.The experiment chose the RR interval and R peak amplitude as representative parameters to be estimated. The obtained results were as follows: for RR interval parameter,its estimation error can be lowered to below 0.3 ms by up-sampling; for R peak amplitude, its estimation error can be reduced to below 2.0 μV by up-sampling. It is believed that other ECG parameter estimation can also be improved similarly by up-sampling 500 Hz data.