Computer analysis of electrocardiograms(ECGs)was introduced more than 50 years ago,with the aim to improve efficiency and clinical workflow.[1,2]However,inaccuracies have been documented in the literature.[3,4]Researc...Computer analysis of electrocardiograms(ECGs)was introduced more than 50 years ago,with the aim to improve efficiency and clinical workflow.[1,2]However,inaccuracies have been documented in the literature.[3,4]Research indicates that emergency department(ED)clinician interruptions occur every 4-10 min,which is significantly more common than in other specialties.[5]This increases the cognitive load and error rates and impacts patient care and clinical effi ciency.[1,2,5]De-prioritization protocols have been introduced in certain centers in the United Kingdom(UK),removing the need for clinician ECG interpretation where ECGs have been interpreted as normal by the machine.展开更多
With the rapid advancement and widespread adoption of new artificial intelligence(AI)technologies,personalized medicine and more accurate diagnosis using medical imaging are now possible.Among its many applications,AI...With the rapid advancement and widespread adoption of new artificial intelligence(AI)technologies,personalized medicine and more accurate diagnosis using medical imaging are now possible.Among its many applications,AI has shown remarkable potential in the analysis of electrocardiograms(ECGs),which provide essential insights into the electrical activity of the heart and allowing early detection of ischemic heart disease(IHD).Notably,single-lead ECG(SLECG)analysis has emerged as a key focus in recent research due to its potential for widespread and efficient screening.This editorial focuses on the latest research progress of AI-enabled SLECG utilized in the diagnosis of IHD.展开更多
Objective:To investigate the effect of 12-lead electrocardiogram and 24-hour dynamic electrocardiogram in detecting pacemaker dysfunction and changes in cardiac function indexes in patients with pacemaker implantation...Objective:To investigate the effect of 12-lead electrocardiogram and 24-hour dynamic electrocardiogram in detecting pacemaker dysfunction and changes in cardiac function indexes in patients with pacemaker implantation.Methods:A total of 136 patients with pacemaker implantation in the First Clinical Medical College of Three Gorges University,Institute of Cardiovascular Disease of Three Gorges University and Yicang Central People’s Hospital from January 2023 to December 2024 were selected as the research objects.All patients received 12-lead electrocardiogram and 24-hour holter 3–14 days after implantation.Results:The overall detection rate of various types of pacemaker dysfunction by Holter was significantly higher than that by conventional ECG(27.21%vs.5.15%,χ^(2)=24.402,P<0.001).The overall arrhythmia detection rate of Holter was significantly higher than that of conventional electrocardiogram(57.35%vs.10.29%,χ^(2)=67.277,P<0.001).The time domain indexes of heart rate variability obtained by 24-hour continuous monitoring of Holter were significantly improved compared with those of conventional electrocardiogram(P<0.05).Conclusions:Compared with 12-lead electrocardiogram,24-hour holter monitoring can more accurately detect pacemaker dysfunction and arrhythmia in patients with pacemaker implantation,and provide more comprehensive data of heart rate variability,which is helpful for clinicians to better evaluate the cardiac function of patients and adjust treatment plans.展开更多
BACKGROUND Arm-implanted totally implantable venous access devices(peripherally inserted central catheter port)have become an important vascular access for colorectal cancer chemotherapy,but traditional anatomical lan...BACKGROUND Arm-implanted totally implantable venous access devices(peripherally inserted central catheter port)have become an important vascular access for colorectal cancer chemotherapy,but traditional anatomical landmark positioning techniques have issues with inaccurate positioning and high complication rates.AIM To evaluate the clinical value of image pre-measurement combined with intracavitary electrocardiogram(IC-ECG)positioning technology in arm port implantation for colorectal cancer patients.METHODS A retrospective analysis was conducted on 216 colorectal cancer patients who received arm port implantation in our hospital from January 2024 to December 2024.Patients were divided into an experimental group(image pre-measurement combined with IC-ECG positioning technology,n=103)and a control group(traditional anatomical landmark positioning technique,n=113).Technical success rate,operation time,catheter tip position accuracy,number of intraoperative catheter adjustments,X-ray exposure time,and postoperative complication rates were compared between the two groups.RESULTS The experimental group demonstrated superior outcomes compared to the control group across all key measures.Technical success rate was higher(98.4%vs 92.7%,P<0.05)with significantly reduced operation time(23.6±5.2 minutes vs 31.5±7.8 minutes,P<0.01).Catheter tip positioning accuracy improved substantially(97.6%vs 85.4%,P=0.002)while X-ray exposure time decreased by 71.8%(5.3±2.1 seconds vs 18.7±4.5 seconds,P<0.001).Threemonth complication rates were markedly lower in the experimental group(4.1%vs 14.6%,P=0.008),including significant reductions in catheter-related thrombosis(0.8%vs 4.9%),displacement(1.6%vs 5.7%),and occlusion(1.6%vs 4.1%).Multivariate analysis identified traditional technique as the strongest risk factor(odds ratio=4.27,P<0.001),while the combined IC-ECG approach was protective(odds ratio=0.34 for displacement,P=0.018).Long-term outcomes favored the experimental group with higher chemotherapy completion rates(97.1%vs 88.5%,P=0.014)and longer catheter dwelling time(189.5±45.3 days vs 162.7±53.8 days,P<0.001).CONCLUSION Image pre-measurement combined with intracavitary electrocardiogram positioning technology in arm port implantation for colorectal cancer patients can significantly improve catheter tip positioning accuracy,reduce operation time and X-ray exposure.展开更多
Myocardial infarction(MI)is one of the leading causes of death globally among cardiovascular diseases,necessitating modern and accurate diagnostics for cardiac patient conditions.Among the available functional diagnos...Myocardial infarction(MI)is one of the leading causes of death globally among cardiovascular diseases,necessitating modern and accurate diagnostics for cardiac patient conditions.Among the available functional diagnostic methods,electrocardiography(ECG)is particularly well-known for its ability to detect MI.However,confirming its accuracy—particularly in identifying the localization of myocardial damage—often presents challenges in practice.This study,therefore,proposes a new approach based on machine learning models for the analysis of 12-lead ECG data to accurately identify the localization of MI.In particular,the learning vector quantization(LVQ)algorithm was applied,considering the contribution of each ECG lead in the 12-channel system,which obtained an accuracy of 87%in localizing damaged myocardium.The developed model was tested on verified data from the PTB database,including 445 ECG recordings from both healthy individuals and MI-diagnosed patients.The results demonstrated that the 12-lead ECG system allows for a comprehensive understanding of cardiac activities in myocardial infarction patients,serving as an essential tool for the diagnosis of myocardial conditions and localizing their damage.A comprehensive comparison was performed,including CNN,SVM,and Logistic Regression,to evaluate the proposed LVQ model.The results demonstrate that the LVQ model achieves competitive performance in diagnostic tasks while maintaining computational efficiency,making it suitable for resource-constrained environments.This study also applies a carefully designed data pre-processing flow,including class balancing and noise removal,which improves the reliability and reproducibility of the results.These aspects highlight the potential application of the LVQ model in cardiac diagnostics,opening up prospects for its use along with more complex neural network architectures.展开更多
Cardiovascular diseases(CVDs)continue to present a leading cause ofmortalityworldwide,emphasizing the importance of early and accurate prediction.Electrocardiogram(ECG)signals,central to cardiac monitoring,have increa...Cardiovascular diseases(CVDs)continue to present a leading cause ofmortalityworldwide,emphasizing the importance of early and accurate prediction.Electrocardiogram(ECG)signals,central to cardiac monitoring,have increasingly been integratedwithDeep Learning(DL)for real-time prediction of CVDs.However,DL models are prone to performance degradation due to concept drift and to catastrophic forgetting.To address this issue,we propose a realtime CVDs prediction approach,referred to as ADWIN-GFR that combines Convolutional Neural Network(CNN)layers,for spatial feature extraction,with Gated Recurrent Units(GRU),for temporal modeling,alongside adaptive drift detection and mitigation mechanisms.The proposed approach integratesAdaptiveWindowing(ADWIN)for realtime concept drift detection,a fine-tuning strategy based on Generative Features Replay(GFR)to preserve previously acquired knowledge,and a dynamic replay buffer ensuring variance,diversity,and data distribution coverage.Extensive experiments conducted on the MIT-BIH arrhythmia dataset demonstrate that ADWIN-GFR outperforms standard fine-tuning techniques,achieving an average post-drift accuracy of 95.4%,amacro F1-score of 93.9%,and a remarkably low forgetting score of 0.9%.It also exhibits an average drift detection delay of 12 steps and achieves an adaptation gain of 17.2%.These findings underscore the potential of ADWIN-GFR for deployment in real-world cardiac monitoring systems,including wearable ECG devices and hospital-based patient monitoring platforms.展开更多
Cardiovascular diseases are the world’s leading cause of death;therefore cardiac health of the human heart has been a fascinating topic for decades.The electrocardiogram(ECG)signal is a comprehensive non-invasive met...Cardiovascular diseases are the world’s leading cause of death;therefore cardiac health of the human heart has been a fascinating topic for decades.The electrocardiogram(ECG)signal is a comprehensive non-invasive method for determining cardiac health.Various health practitioners use the ECG signal to ascertain critical information about the human heart.In this article,swarm intelligence approaches are used in the biomedical signal processing sector to enhance adaptive hybrid filters and empirical wavelet transforms(EWTs).At first,the white Gaussian noise is added to the input ECG signal and then applied to the EWT.The ECG signals are denoised by the proposed adaptive hybrid filter.The honey badge optimization(HBO)algorithm is utilized to optimize the EWT window function and adaptive hybrid filter weight parameters.The proposed approach is simulated by MATLAB 2018a using the MIT-BIH dataset with white Gaussian,electromyogram and electrode motion artifact noises.A comparison of the HBO approach with recursive least square-based adaptive filter,multichannel least means square,and discrete wavelet transform methods has been done in order to show the efficiency of the proposed adaptive hybrid filter.The experimental results show that the HBO approach supported by EWT and adaptive hybrid filter can be employed efficiently for cardiovascular signal denoising.展开更多
Electrocardiograms (ECG) of Eremias multiocellata were studied at 5-35℃ in body temperature. Electrocardiogram wave intervals (R-R,P-R,QRS,T-P,and R-T) shortened while heart rate increased with the increasing of bod...Electrocardiograms (ECG) of Eremias multiocellata were studied at 5-35℃ in body temperature. Electrocardiogram wave intervals (R-R,P-R,QRS,T-P,and R-T) shortened while heart rate increased with the increasing of body temperature. The average heart rate was 14.6/min at 5℃,whereas it was 201/min at 35℃. The duration of wave intervals of ECG and the heart rate were related significantly to the body temperature (P<0.001). Among the components of a cardiac cycle the cardiac rest period (TP intervals) and the atria-ventricular conduction time (PR interval) were affected mostly by body temperature. In the other hand the ventricular depolarization and repolarization (QRS and R-T intervals) were relatively less affected by the body temperature. The increasing of heart rate with body temperature was mainly caused by the shortening of ECG wave intervals,and the T-P interval (the cardiac rest period) was shortened more noticeably than other intervals.展开更多
Hydrogen sulfide （H2S） is the third gaseous signaling molecule discovered in recent years, and plays an important physiological role in the cardivascular system. To explore the effects of different doses of exogenou...Hydrogen sulfide （H2S） is the third gaseous signaling molecule discovered in recent years, and plays an important physiological role in the cardivascular system. To explore the effects of different doses of exogenous H2S on the electrocardiogram （ECG） of rats generally anesthetized by zoletil, different doses of NariS solution were used for the intervention of intraperitoneal injection 20 rain before the zoletil anesthesia. The ECGs of rats from each treatment group during the time range of 10^th-50^th min were determined under general anesthesia, and then were compared with those from the control group. The results showed that exogenous H2S could significantly reduce the Q-T interval time limit, thus played a role in slowing tachycardia or arrhythmia and other anomalies, thereby protecting the heart. S-T segment and T segment evaluation values were significantly reduced, which might be associated with bradycardia.展开更多
Objective: Myocardial infarction (MI) is the main cause of heart failure, but the relationship between the extent of MI and cardiac function has not been clearly determined. The present study was undertaken to investi...Objective: Myocardial infarction (MI) is the main cause of heart failure, but the relationship between the extent of MI and cardiac function has not been clearly determined. The present study was undertaken to investigate early changes in the electrocardiogram associated with infarct size and cardiac function after MI. Methods: MI was induced by ligating the left anterior descending coronary artery in rats. Electrocardiograms, echocardiographs and hemodynamic parameters were assessed and myocardial infarct size was measured from mid-transverse sections stained with Masson抯 trichrome. Results: The sum of pathological Q wave amplitudes was strongly correlated with myocardial infarct size (r = 0.920, P < 0.0001), left ventricular ejection fraction (r = -0.868, P < 0.0001) and left ventricular end diastolic pressure (r = 0.835, P < 0.0004). Furthermore, there was close relationship between MI size and cardiac function as assessed by left ventricular ejection fraction (r = -0.913, P < 0.0001) and left ventricular end diastolic pressure (r = 0.893, P < 0.0001). Conclusion: The sum of pathological Q wave amplitudes after MI can be used to estimate the extent of MI as well as cardiac function.展开更多
Objective To describe the clinical characteristics of idiopathic ventricular fibrillation （IVF） with fragmented QRS complex （f-QRS） and J wave in resting electrocardiogram. Methods We reviewed data from 21 case su...Objective To describe the clinical characteristics of idiopathic ventricular fibrillation （IVF） with fragmented QRS complex （f-QRS） and J wave in resting electrocardiogram. Methods We reviewed data from 21 case subjects in our hospital who were resuscitated after cardiac arrest due to IVF and assessed the prevalence of f-QRS and J wave in resting electrocardiogram （ECG）. All the case subjects were classified among three groups based on the electrocardiographic morphology： group I, both f-QRS and J wave were observed （n = 6）, group II, only J wave was observed （n = 9）, group III, neither f-QRS nor J wave was observed （n = 6）. Population characteristics, history of syncope or sudden cardiac arrest, incidence of ventricular fibrillation （VF）, and circumstance of VF were evaluated among the three groups. Results The incidence of index events （syncope, survived cardiac arrest and VF episodes recorded in implantable cardioverter defibrillator （ICD） or pacemakers） was 13.4 ~ 5.6 per-year in group I, 10.8 ~ 3.9 per-year in group II, and 9.8 -4- 4.2 per-year in group HI. There were significant differences in incidences among the three groups, the most frequent index events were observed in group I. The hazard ratio for incidence was 3.2 （95%CI, 1.1-7.9; P = 0.01）. The history and circumstance of the index events were different among the groups. In group I, all the index events occurred during sleep in early morning. In group II, four subjects suffered VF during strenuous physical activities or agitation state, two during sleep in early morning, three in usual activity. In group III, one subject suffered VF during sleep in early morning, one in agitation state, four in usual activity. Conclusions This study suggests that the IVF patients with the combined appearance of f-QRS and J wave in the resting ECG suffer an increased risk of VF, this subgroup of IVF patients has a unique clinical feature.展开更多
The electrocardiogram （ECG） has broad applications in clinical diagnosis and prognosis of cardiovascular disease. Many researchers have contributed to its progressive development. To commemorate those pioneers, and ...The electrocardiogram （ECG） has broad applications in clinical diagnosis and prognosis of cardiovascular disease. Many researchers have contributed to its progressive development. To commemorate those pioneers, and to better study and promote the use of ECG, we reviewed and present here a systematic introduction about the history, hotspots, and trends of ECG. In the historical part, information including the invention, improvement, and extensive applications of ECG, such as in long QT syndrome （LQTS）, angina, and myocardial infarction （MI）, are chronologi- cally presented. New technologies and applications from the 1990s are also introduced. In the second part, we use the bibliometric analysis me- thod to analyze the hotspots in the field of ECG-related research. By using total citations and year-specific total citations as our main criteria, four key hotspots in ECG-related research were identified from 11 articles, including atrial fibrillation, LQTS, angina and MI, and heart rate variability. Recent studies in those four areas are also reported. In the final part, we discuss the future trends concerning ECG-related research. The authors believe that improvement of the ECG instrumentation, big data mining for ECG, and the accuracy of diagnosis and application will be areas of continuous concern.展开更多
Brugada phenocopies(BrP) are clinical entities that are etiologically distinct from true congenital Brugada syndrome. BrP are characterized by type 1 or type 2 Brugada electrocardiogram(ECG) patterns in precordial lea...Brugada phenocopies(BrP) are clinical entities that are etiologically distinct from true congenital Brugada syndrome. BrP are characterized by type 1 or type 2 Brugada electrocardiogram(ECG) patterns in precordial leads V1-V3. However, BrP are elicited by various un-derlying clinical conditions such as myocardial ischemia, pulmonary embolism, electrolyte abnormalities, or poor ECG filters. Upon resolution of the inciting underlying pathological condition, the BrP ECG subsequently nor-malizes. To date, reports have documented BrP in the context of singular clinical events. More recently, recur-rent BrP has been demonstrated in the context of re-current hypokalemia. This demonstrates clinical repro-ducibility, thereby advancing the concept of this new ECG phenomenon. The key to further understanding the pathophysiological mechanisms behind BrP requires experimental model validation in which these phenom-ena are reproduced under strictly controlled environ-mental conditions. The development of these validation models will help us determine whether BrP are tran-sient alterations of sodium channels that are not repro-ducible with a sodium channel provocative test or al-ternatively, a malfunction of other ion channels. In this editorial, we discuss the conceptual emergence of BrP as a new ECG phenomenon, review the progress made to date and identify opportunities for further investiga-tion. In addition, we also encourage investigators that are currently reporting on these cases to use the term BrP in order to facilitate literature searches and to help establish this emerging concept.展开更多
In order to study supply chain of the telecom value-added service,a multi-leaders and multi-followers Stackelberg game model with multiple telecom operators and multiple service providers whose income is composed of i...In order to study supply chain of the telecom value-added service,a multi-leaders and multi-followers Stackelberg game model with multiple telecom operators and multiple service providers whose income is composed of information fee division and advertisement was constructed.Then a demonstration was simulated,and the results were compared with the situation of service providers' income only from information fee division.The simulated and compared results indicate that,the enterprises in the supply chain have the nature of pursuing the maximum profits in capital markets;meanwhile,first-mover advantages and some enterprise can get more profits with the information asymmetry.展开更多
Aslanger’s sign,also known as the arterial pulse tapping artifact or electromechanical association artifact,is an electrocardiographic artifact caused by arterial pulsation at the site where the limb leads of the sta...Aslanger’s sign,also known as the arterial pulse tapping artifact or electromechanical association artifact,is an electrocardiographic artifact caused by arterial pulsation at the site where the limb leads of the standard 12-lead electrocardiogram near the radial or posterior tibial arteries are positioned,particularly in hyperdynamic states.[1–8]It occurs in every cardiac cycle with a constant coupling interval between the QRS complex and artifact.This synchronization with the underlying heart rhythm makes it less likely to be recognized as an artifact compared to unsynchronized artifacts,such as those caused by limb movement and inadequate contact between the electrode and skin.[1,2,7,8]Almost all reported cases of Aslanger’s sign exhibit an unusual waveform morphology in all 12 leads except one of the standard 12-lead electrocardiogram.This sign is often confused with an electrocardiographic finding commonly observed during acute coronary events.展开更多
Early detection of sudden cardiac death may be used for surviving the life of cardiac patients. In this paper we have investigated an algorithm to detect and predict sudden cardiac death, by processing of heart rate v...Early detection of sudden cardiac death may be used for surviving the life of cardiac patients. In this paper we have investigated an algorithm to detect and predict sudden cardiac death, by processing of heart rate variability signal through the classical and time-frequency methods. At first, one minute of ECG signals, just before the cardiac death event are extracted and used to compute heart rate variability (HRV) signal. Five features in time domain and four features in frequency domain are extracted from the HRV signal and used as classical linear features. Then the Wigner Ville transform is applied to the HRV signal, and 11 extra features in the time-frequency (TF) domain are obtained. In order to improve the performance of classification, the principal component analysis (PCA) is applied to the obtained features vector. Finally a neural network classifier is applied to the reduced features. The obtained results show that the TF method can classify normal and SCD subjects, more efficiently than the classical methods. A MIT-BIH ECG database was used to evaluate the proposed method. The proposed method was implemented using MLP classifier and had 74.36% and 99.16% correct detection rate (accuracy) for classical features and TF method, respectively. Also, the accuracy of the KNN classifier were 73.87% and 96.04%.展开更多
Respiratory monitoring is increasingly used in clinical and healthcare practices to diagnose chronic cardio-pulmonary functional diseases during various routine activities.Wearable medical devices have realized the po...Respiratory monitoring is increasingly used in clinical and healthcare practices to diagnose chronic cardio-pulmonary functional diseases during various routine activities.Wearable medical devices have realized the possibilities of ubiquitous respiratory monitoring,however,relatively little attention is paid to accuracy and reliability.In previous study,a wearable respiration biofeedback system was designed.In this work,three kinds of signals were mixed to extract respiratory rate,i.e.,respiration inductive plethysmography(RIP),3D-acceleration and ECG.In-situ experiments with twelve subjects indicate that the method significantly improves the accuracy and reliability over a dynamic range of respiration rate.It is possible to derive respiration rate from three signals within mean absolute percentage error 4.37%of a reference gold standard.Similarly studies derive respiratory rate from single-lead ECG within mean absolute percentage error 17%of a reference gold standard.展开更多
Holter usually monitors electrocardiogram(ECG)signals for more than 24 hours to capture short-lived cardiac abnormalities.In view of the large amount of Holter data and the fact that the normal part accounts for the m...Holter usually monitors electrocardiogram(ECG)signals for more than 24 hours to capture short-lived cardiac abnormalities.In view of the large amount of Holter data and the fact that the normal part accounts for the majority,it is reasonable to design an algorithm that can automatically eliminate normal data segments as much as possible without missing any abnormal data segments,and then take the left segments to the doctors or the computer programs for further diagnosis.In this paper,we propose a preliminary abnormal segment screening method for Holter data.Based on long short-term memory(LSTM)networks,the prediction model is established and trained with the normal data of a monitored object.Then,on the basis of kernel density estimation,we learn the distribution law of prediction errors after applying the trained LSTM model to the regular data.Based on these,the preliminary abnormal ECG segment screening analysis is carried out without R wave detection.Experiments on the MIT-BIH arrhythmia database show that,under the condition of ensuring that no abnormal point is missed,53.89% of normal segments can be effectively obviated.This work can greatly reduce the workload of subsequent further processing.展开更多
AIM To investigate the impact of coronary artery disease in a cohort of patients resuscitated from cardiac arrest with non-diagnostic electrocardiogram.METHODS From March 2004 to February 2016, 203 consecutive patient...AIM To investigate the impact of coronary artery disease in a cohort of patients resuscitated from cardiac arrest with non-diagnostic electrocardiogram.METHODS From March 2004 to February 2016, 203 consecutive patients resuscitated from in or out-of-hospital sudden cardiac arrest and non-diagnostic post-resuscitation electrocardiogram(defined as ST segment elevation or pre-sumably new left bundle branch block) whounderwent invasive coronary angiogram during hospitalization were included. For purpose of analysis and comparison, patients were classified in two groups: Initial shockable rhythm(ventricular tachycardia or ventricular fibrillation; n = 148, 72.9%) and initial non-shockable rhythm(n = 55, 27.1%). Baseline characteristics, coronary angiogram findings including Syntax Score and long-term survival rates were compared. RESULTS Sudden cardiac arrest was witnessed in 95.2% of cases, 66.7% were out-of-hospital patients and 72.4% were male. There were no significant differences in baseline characteristics between groups except for higher mean age(68.1 years vs 61 years, P = 0.001) in the nonshockable rhythm group. Overall 5-year mortality of the resuscitated patients was 37.4%. Patients with non-shockable rhythms had higher mortality(60% vs 29.1%, P < 0.001) and a worst neurological status at hospital discharge based on cerebral performance category score(CPC 1-2: 32.7% vs 53.4%, P = 0.02). Although there were no significant differences in global burden of coronary artery disease defined by Syntax Score(mean Syntax Score: 10.2 vs 10.3, P = 0.96) there was a trend towards a higher incidence of acute coronary lesions in patients with shockable rhythm(29.7% vs 16.4%, P = 0.054). There was also a higher need for ad-hoc percutaneous coronary intervention in this group(21.9% vs 9.1%, P = 0.03). CONCLUSION Initial shockable group of patients had a trend towards higher incidence of acute coronary lesions and higher need of ad-hoc percutaneous intervention vs nonshockable group.展开更多
Hyperkalemia is defined as serum potassium level of more than 5 mmol/L. Prompt identification of hyper-kalemia and appropriate management are critical, since severe hyperkalemia can lead to lethal cardiac dysrhythmias...Hyperkalemia is defined as serum potassium level of more than 5 mmol/L. Prompt identification of hyper-kalemia and appropriate management are critical, since severe hyperkalemia can lead to lethal cardiac dysrhythmias. There is a wide range of electrocardiogram (EKG) changes associated with hyperkalemia. The sequence of EKG changes has been previously described with limited information to correlate the level of potassium to a particular change in the EKG. This study aims to describe a correlation between the level of potassium and EKG changes in the presence or absence of certain diagnoses, to determine which EKG finding in the context of level of hyperkalemia, should be considered life-threatening and prompt emergency intervention. If a relationship between serum levels of potassium and EKG changes is significant, clinicians may be able to better monitor and treat hyperkalemic patients. This paper reviews the literature on hyperkalemia, potassium homeostasis and EKG changes attributed to elevated potassium.展开更多
文摘Computer analysis of electrocardiograms(ECGs)was introduced more than 50 years ago,with the aim to improve efficiency and clinical workflow.[1,2]However,inaccuracies have been documented in the literature.[3,4]Research indicates that emergency department(ED)clinician interruptions occur every 4-10 min,which is significantly more common than in other specialties.[5]This increases the cognitive load and error rates and impacts patient care and clinical effi ciency.[1,2,5]De-prioritization protocols have been introduced in certain centers in the United Kingdom(UK),removing the need for clinician ECG interpretation where ECGs have been interpreted as normal by the machine.
基金Supported by National Natural Science Foundation of China,No.82170327 and No.82370332Tianjin Key Medical Discipline(Specialty)Construction Project,No.TJYXZDXK-029A.
文摘With the rapid advancement and widespread adoption of new artificial intelligence(AI)technologies,personalized medicine and more accurate diagnosis using medical imaging are now possible.Among its many applications,AI has shown remarkable potential in the analysis of electrocardiograms(ECGs),which provide essential insights into the electrical activity of the heart and allowing early detection of ischemic heart disease(IHD).Notably,single-lead ECG(SLECG)analysis has emerged as a key focus in recent research due to its potential for widespread and efficient screening.This editorial focuses on the latest research progress of AI-enabled SLECG utilized in the diagnosis of IHD.
文摘Objective:To investigate the effect of 12-lead electrocardiogram and 24-hour dynamic electrocardiogram in detecting pacemaker dysfunction and changes in cardiac function indexes in patients with pacemaker implantation.Methods:A total of 136 patients with pacemaker implantation in the First Clinical Medical College of Three Gorges University,Institute of Cardiovascular Disease of Three Gorges University and Yicang Central People’s Hospital from January 2023 to December 2024 were selected as the research objects.All patients received 12-lead electrocardiogram and 24-hour holter 3–14 days after implantation.Results:The overall detection rate of various types of pacemaker dysfunction by Holter was significantly higher than that by conventional ECG(27.21%vs.5.15%,χ^(2)=24.402,P<0.001).The overall arrhythmia detection rate of Holter was significantly higher than that of conventional electrocardiogram(57.35%vs.10.29%,χ^(2)=67.277,P<0.001).The time domain indexes of heart rate variability obtained by 24-hour continuous monitoring of Holter were significantly improved compared with those of conventional electrocardiogram(P<0.05).Conclusions:Compared with 12-lead electrocardiogram,24-hour holter monitoring can more accurately detect pacemaker dysfunction and arrhythmia in patients with pacemaker implantation,and provide more comprehensive data of heart rate variability,which is helpful for clinicians to better evaluate the cardiac function of patients and adjust treatment plans.
基金Supported by the Affiliated Hospital of Xuzhou Medical University,No.2024ZH04Xuzhou Municipal Science and Technology Bureau,No.KC23282.
文摘BACKGROUND Arm-implanted totally implantable venous access devices(peripherally inserted central catheter port)have become an important vascular access for colorectal cancer chemotherapy,but traditional anatomical landmark positioning techniques have issues with inaccurate positioning and high complication rates.AIM To evaluate the clinical value of image pre-measurement combined with intracavitary electrocardiogram(IC-ECG)positioning technology in arm port implantation for colorectal cancer patients.METHODS A retrospective analysis was conducted on 216 colorectal cancer patients who received arm port implantation in our hospital from January 2024 to December 2024.Patients were divided into an experimental group(image pre-measurement combined with IC-ECG positioning technology,n=103)and a control group(traditional anatomical landmark positioning technique,n=113).Technical success rate,operation time,catheter tip position accuracy,number of intraoperative catheter adjustments,X-ray exposure time,and postoperative complication rates were compared between the two groups.RESULTS The experimental group demonstrated superior outcomes compared to the control group across all key measures.Technical success rate was higher(98.4%vs 92.7%,P<0.05)with significantly reduced operation time(23.6±5.2 minutes vs 31.5±7.8 minutes,P<0.01).Catheter tip positioning accuracy improved substantially(97.6%vs 85.4%,P=0.002)while X-ray exposure time decreased by 71.8%(5.3±2.1 seconds vs 18.7±4.5 seconds,P<0.001).Threemonth complication rates were markedly lower in the experimental group(4.1%vs 14.6%,P=0.008),including significant reductions in catheter-related thrombosis(0.8%vs 4.9%),displacement(1.6%vs 5.7%),and occlusion(1.6%vs 4.1%).Multivariate analysis identified traditional technique as the strongest risk factor(odds ratio=4.27,P<0.001),while the combined IC-ECG approach was protective(odds ratio=0.34 for displacement,P=0.018).Long-term outcomes favored the experimental group with higher chemotherapy completion rates(97.1%vs 88.5%,P=0.014)and longer catheter dwelling time(189.5±45.3 days vs 162.7±53.8 days,P<0.001).CONCLUSION Image pre-measurement combined with intracavitary electrocardiogram positioning technology in arm port implantation for colorectal cancer patients can significantly improve catheter tip positioning accuracy,reduce operation time and X-ray exposure.
基金funded by the Ministry of Science and Higher Education of the Republic of Kazakhstan,grant numbers AP14969403 and AP23485820.
文摘Myocardial infarction(MI)is one of the leading causes of death globally among cardiovascular diseases,necessitating modern and accurate diagnostics for cardiac patient conditions.Among the available functional diagnostic methods,electrocardiography(ECG)is particularly well-known for its ability to detect MI.However,confirming its accuracy—particularly in identifying the localization of myocardial damage—often presents challenges in practice.This study,therefore,proposes a new approach based on machine learning models for the analysis of 12-lead ECG data to accurately identify the localization of MI.In particular,the learning vector quantization(LVQ)algorithm was applied,considering the contribution of each ECG lead in the 12-channel system,which obtained an accuracy of 87%in localizing damaged myocardium.The developed model was tested on verified data from the PTB database,including 445 ECG recordings from both healthy individuals and MI-diagnosed patients.The results demonstrated that the 12-lead ECG system allows for a comprehensive understanding of cardiac activities in myocardial infarction patients,serving as an essential tool for the diagnosis of myocardial conditions and localizing their damage.A comprehensive comparison was performed,including CNN,SVM,and Logistic Regression,to evaluate the proposed LVQ model.The results demonstrate that the LVQ model achieves competitive performance in diagnostic tasks while maintaining computational efficiency,making it suitable for resource-constrained environments.This study also applies a carefully designed data pre-processing flow,including class balancing and noise removal,which improves the reliability and reproducibility of the results.These aspects highlight the potential application of the LVQ model in cardiac diagnostics,opening up prospects for its use along with more complex neural network architectures.
基金supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R196)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Cardiovascular diseases(CVDs)continue to present a leading cause ofmortalityworldwide,emphasizing the importance of early and accurate prediction.Electrocardiogram(ECG)signals,central to cardiac monitoring,have increasingly been integratedwithDeep Learning(DL)for real-time prediction of CVDs.However,DL models are prone to performance degradation due to concept drift and to catastrophic forgetting.To address this issue,we propose a realtime CVDs prediction approach,referred to as ADWIN-GFR that combines Convolutional Neural Network(CNN)layers,for spatial feature extraction,with Gated Recurrent Units(GRU),for temporal modeling,alongside adaptive drift detection and mitigation mechanisms.The proposed approach integratesAdaptiveWindowing(ADWIN)for realtime concept drift detection,a fine-tuning strategy based on Generative Features Replay(GFR)to preserve previously acquired knowledge,and a dynamic replay buffer ensuring variance,diversity,and data distribution coverage.Extensive experiments conducted on the MIT-BIH arrhythmia dataset demonstrate that ADWIN-GFR outperforms standard fine-tuning techniques,achieving an average post-drift accuracy of 95.4%,amacro F1-score of 93.9%,and a remarkably low forgetting score of 0.9%.It also exhibits an average drift detection delay of 12 steps and achieves an adaptation gain of 17.2%.These findings underscore the potential of ADWIN-GFR for deployment in real-world cardiac monitoring systems,including wearable ECG devices and hospital-based patient monitoring platforms.
文摘Cardiovascular diseases are the world’s leading cause of death;therefore cardiac health of the human heart has been a fascinating topic for decades.The electrocardiogram(ECG)signal is a comprehensive non-invasive method for determining cardiac health.Various health practitioners use the ECG signal to ascertain critical information about the human heart.In this article,swarm intelligence approaches are used in the biomedical signal processing sector to enhance adaptive hybrid filters and empirical wavelet transforms(EWTs).At first,the white Gaussian noise is added to the input ECG signal and then applied to the EWT.The ECG signals are denoised by the proposed adaptive hybrid filter.The honey badge optimization(HBO)algorithm is utilized to optimize the EWT window function and adaptive hybrid filter weight parameters.The proposed approach is simulated by MATLAB 2018a using the MIT-BIH dataset with white Gaussian,electromyogram and electrode motion artifact noises.A comparison of the HBO approach with recursive least square-based adaptive filter,multichannel least means square,and discrete wavelet transform methods has been done in order to show the efficiency of the proposed adaptive hybrid filter.The experimental results show that the HBO approach supported by EWT and adaptive hybrid filter can be employed efficiently for cardiovascular signal denoising.
文摘Electrocardiograms (ECG) of Eremias multiocellata were studied at 5-35℃ in body temperature. Electrocardiogram wave intervals (R-R,P-R,QRS,T-P,and R-T) shortened while heart rate increased with the increasing of body temperature. The average heart rate was 14.6/min at 5℃,whereas it was 201/min at 35℃. The duration of wave intervals of ECG and the heart rate were related significantly to the body temperature (P<0.001). Among the components of a cardiac cycle the cardiac rest period (TP intervals) and the atria-ventricular conduction time (PR interval) were affected mostly by body temperature. In the other hand the ventricular depolarization and repolarization (QRS and R-T intervals) were relatively less affected by the body temperature. The increasing of heart rate with body temperature was mainly caused by the shortening of ECG wave intervals,and the T-P interval (the cardiac rest period) was shortened more noticeably than other intervals.
文摘Hydrogen sulfide （H2S） is the third gaseous signaling molecule discovered in recent years, and plays an important physiological role in the cardivascular system. To explore the effects of different doses of exogenous H2S on the electrocardiogram （ECG） of rats generally anesthetized by zoletil, different doses of NariS solution were used for the intervention of intraperitoneal injection 20 rain before the zoletil anesthesia. The ECGs of rats from each treatment group during the time range of 10^th-50^th min were determined under general anesthesia, and then were compared with those from the control group. The results showed that exogenous H2S could significantly reduce the Q-T interval time limit, thus played a role in slowing tachycardia or arrhythmia and other anomalies, thereby protecting the heart. S-T segment and T segment evaluation values were significantly reduced, which might be associated with bradycardia.
文摘Objective: Myocardial infarction (MI) is the main cause of heart failure, but the relationship between the extent of MI and cardiac function has not been clearly determined. The present study was undertaken to investigate early changes in the electrocardiogram associated with infarct size and cardiac function after MI. Methods: MI was induced by ligating the left anterior descending coronary artery in rats. Electrocardiograms, echocardiographs and hemodynamic parameters were assessed and myocardial infarct size was measured from mid-transverse sections stained with Masson抯 trichrome. Results: The sum of pathological Q wave amplitudes was strongly correlated with myocardial infarct size (r = 0.920, P < 0.0001), left ventricular ejection fraction (r = -0.868, P < 0.0001) and left ventricular end diastolic pressure (r = 0.835, P < 0.0004). Furthermore, there was close relationship between MI size and cardiac function as assessed by left ventricular ejection fraction (r = -0.913, P < 0.0001) and left ventricular end diastolic pressure (r = 0.893, P < 0.0001). Conclusion: The sum of pathological Q wave amplitudes after MI can be used to estimate the extent of MI as well as cardiac function.
文摘Objective To describe the clinical characteristics of idiopathic ventricular fibrillation （IVF） with fragmented QRS complex （f-QRS） and J wave in resting electrocardiogram. Methods We reviewed data from 21 case subjects in our hospital who were resuscitated after cardiac arrest due to IVF and assessed the prevalence of f-QRS and J wave in resting electrocardiogram （ECG）. All the case subjects were classified among three groups based on the electrocardiographic morphology： group I, both f-QRS and J wave were observed （n = 6）, group II, only J wave was observed （n = 9）, group III, neither f-QRS nor J wave was observed （n = 6）. Population characteristics, history of syncope or sudden cardiac arrest, incidence of ventricular fibrillation （VF）, and circumstance of VF were evaluated among the three groups. Results The incidence of index events （syncope, survived cardiac arrest and VF episodes recorded in implantable cardioverter defibrillator （ICD） or pacemakers） was 13.4 ~ 5.6 per-year in group I, 10.8 ~ 3.9 per-year in group II, and 9.8 -4- 4.2 per-year in group HI. There were significant differences in incidences among the three groups, the most frequent index events were observed in group I. The hazard ratio for incidence was 3.2 （95%CI, 1.1-7.9; P = 0.01）. The history and circumstance of the index events were different among the groups. In group I, all the index events occurred during sleep in early morning. In group II, four subjects suffered VF during strenuous physical activities or agitation state, two during sleep in early morning, three in usual activity. In group III, one subject suffered VF during sleep in early morning, one in agitation state, four in usual activity. Conclusions This study suggests that the IVF patients with the combined appearance of f-QRS and J wave in the resting ECG suffer an increased risk of VF, this subgroup of IVF patients has a unique clinical feature.
基金This research was supported in part by National Natural Science Foundation of China，supported by Research Funds of China Space Medical Engineering，supported by State Key Laboratory of Space Medicine Fundamentals and Applications, China Astronaut Research and Training Centre
文摘The electrocardiogram （ECG） has broad applications in clinical diagnosis and prognosis of cardiovascular disease. Many researchers have contributed to its progressive development. To commemorate those pioneers, and to better study and promote the use of ECG, we reviewed and present here a systematic introduction about the history, hotspots, and trends of ECG. In the historical part, information including the invention, improvement, and extensive applications of ECG, such as in long QT syndrome （LQTS）, angina, and myocardial infarction （MI）, are chronologi- cally presented. New technologies and applications from the 1990s are also introduced. In the second part, we use the bibliometric analysis me- thod to analyze the hotspots in the field of ECG-related research. By using total citations and year-specific total citations as our main criteria, four key hotspots in ECG-related research were identified from 11 articles, including atrial fibrillation, LQTS, angina and MI, and heart rate variability. Recent studies in those four areas are also reported. In the final part, we discuss the future trends concerning ECG-related research. The authors believe that improvement of the ECG instrumentation, big data mining for ECG, and the accuracy of diagnosis and application will be areas of continuous concern.
文摘Brugada phenocopies(BrP) are clinical entities that are etiologically distinct from true congenital Brugada syndrome. BrP are characterized by type 1 or type 2 Brugada electrocardiogram(ECG) patterns in precordial leads V1-V3. However, BrP are elicited by various un-derlying clinical conditions such as myocardial ischemia, pulmonary embolism, electrolyte abnormalities, or poor ECG filters. Upon resolution of the inciting underlying pathological condition, the BrP ECG subsequently nor-malizes. To date, reports have documented BrP in the context of singular clinical events. More recently, recur-rent BrP has been demonstrated in the context of re-current hypokalemia. This demonstrates clinical repro-ducibility, thereby advancing the concept of this new ECG phenomenon. The key to further understanding the pathophysiological mechanisms behind BrP requires experimental model validation in which these phenom-ena are reproduced under strictly controlled environ-mental conditions. The development of these validation models will help us determine whether BrP are tran-sient alterations of sodium channels that are not repro-ducible with a sodium channel provocative test or al-ternatively, a malfunction of other ion channels. In this editorial, we discuss the conceptual emergence of BrP as a new ECG phenomenon, review the progress made to date and identify opportunities for further investiga-tion. In addition, we also encourage investigators that are currently reporting on these cases to use the term BrP in order to facilitate literature searches and to help establish this emerging concept.
基金supported by Research Start Fund of Northwest A&F University and Youth Fund of Communication University of China under Grant No.XNG1035partly performed in the project"On-line Multi-attribute Procurement Auction Mechanism Design and Multi-agent System Implementation"supported by National Natural Science Foundation of China under Grant No.71001009
文摘In order to study supply chain of the telecom value-added service,a multi-leaders and multi-followers Stackelberg game model with multiple telecom operators and multiple service providers whose income is composed of information fee division and advertisement was constructed.Then a demonstration was simulated,and the results were compared with the situation of service providers' income only from information fee division.The simulated and compared results indicate that,the enterprises in the supply chain have the nature of pursuing the maximum profits in capital markets;meanwhile,first-mover advantages and some enterprise can get more profits with the information asymmetry.
文摘Aslanger’s sign,also known as the arterial pulse tapping artifact or electromechanical association artifact,is an electrocardiographic artifact caused by arterial pulsation at the site where the limb leads of the standard 12-lead electrocardiogram near the radial or posterior tibial arteries are positioned,particularly in hyperdynamic states.[1–8]It occurs in every cardiac cycle with a constant coupling interval between the QRS complex and artifact.This synchronization with the underlying heart rhythm makes it less likely to be recognized as an artifact compared to unsynchronized artifacts,such as those caused by limb movement and inadequate contact between the electrode and skin.[1,2,7,8]Almost all reported cases of Aslanger’s sign exhibit an unusual waveform morphology in all 12 leads except one of the standard 12-lead electrocardiogram.This sign is often confused with an electrocardiographic finding commonly observed during acute coronary events.
文摘Early detection of sudden cardiac death may be used for surviving the life of cardiac patients. In this paper we have investigated an algorithm to detect and predict sudden cardiac death, by processing of heart rate variability signal through the classical and time-frequency methods. At first, one minute of ECG signals, just before the cardiac death event are extracted and used to compute heart rate variability (HRV) signal. Five features in time domain and four features in frequency domain are extracted from the HRV signal and used as classical linear features. Then the Wigner Ville transform is applied to the HRV signal, and 11 extra features in the time-frequency (TF) domain are obtained. In order to improve the performance of classification, the principal component analysis (PCA) is applied to the obtained features vector. Finally a neural network classifier is applied to the reduced features. The obtained results show that the TF method can classify normal and SCD subjects, more efficiently than the classical methods. A MIT-BIH ECG database was used to evaluate the proposed method. The proposed method was implemented using MLP classifier and had 74.36% and 99.16% correct detection rate (accuracy) for classical features and TF method, respectively. Also, the accuracy of the KNN classifier were 73.87% and 96.04%.
基金Project(2012M510207)supported by the China Postdoctoral Science FoundationProjects(60932001,61072031)supported by the National Natural Science Foundation of China+2 种基金Project(2012AA02A604)supported by the National High Technology Research and Development Program of ChinaProject(2013ZX03005013)supported by the Next Generation Communication Technology Major Project of National Science and Technology,ChinaProject supported by the"One-hundred Talent"and the"Low-cost Healthcare"Programs of Chinese Academy of Sciences
文摘Respiratory monitoring is increasingly used in clinical and healthcare practices to diagnose chronic cardio-pulmonary functional diseases during various routine activities.Wearable medical devices have realized the possibilities of ubiquitous respiratory monitoring,however,relatively little attention is paid to accuracy and reliability.In previous study,a wearable respiration biofeedback system was designed.In this work,three kinds of signals were mixed to extract respiratory rate,i.e.,respiration inductive plethysmography(RIP),3D-acceleration and ECG.In-situ experiments with twelve subjects indicate that the method significantly improves the accuracy and reliability over a dynamic range of respiration rate.It is possible to derive respiration rate from three signals within mean absolute percentage error 4.37%of a reference gold standard.Similarly studies derive respiratory rate from single-lead ECG within mean absolute percentage error 17%of a reference gold standard.
文摘Holter usually monitors electrocardiogram(ECG)signals for more than 24 hours to capture short-lived cardiac abnormalities.In view of the large amount of Holter data and the fact that the normal part accounts for the majority,it is reasonable to design an algorithm that can automatically eliminate normal data segments as much as possible without missing any abnormal data segments,and then take the left segments to the doctors or the computer programs for further diagnosis.In this paper,we propose a preliminary abnormal segment screening method for Holter data.Based on long short-term memory(LSTM)networks,the prediction model is established and trained with the normal data of a monitored object.Then,on the basis of kernel density estimation,we learn the distribution law of prediction errors after applying the trained LSTM model to the regular data.Based on these,the preliminary abnormal ECG segment screening analysis is carried out without R wave detection.Experiments on the MIT-BIH arrhythmia database show that,under the condition of ensuring that no abnormal point is missed,53.89% of normal segments can be effectively obviated.This work can greatly reduce the workload of subsequent further processing.
文摘AIM To investigate the impact of coronary artery disease in a cohort of patients resuscitated from cardiac arrest with non-diagnostic electrocardiogram.METHODS From March 2004 to February 2016, 203 consecutive patients resuscitated from in or out-of-hospital sudden cardiac arrest and non-diagnostic post-resuscitation electrocardiogram(defined as ST segment elevation or pre-sumably new left bundle branch block) whounderwent invasive coronary angiogram during hospitalization were included. For purpose of analysis and comparison, patients were classified in two groups: Initial shockable rhythm(ventricular tachycardia or ventricular fibrillation; n = 148, 72.9%) and initial non-shockable rhythm(n = 55, 27.1%). Baseline characteristics, coronary angiogram findings including Syntax Score and long-term survival rates were compared. RESULTS Sudden cardiac arrest was witnessed in 95.2% of cases, 66.7% were out-of-hospital patients and 72.4% were male. There were no significant differences in baseline characteristics between groups except for higher mean age(68.1 years vs 61 years, P = 0.001) in the nonshockable rhythm group. Overall 5-year mortality of the resuscitated patients was 37.4%. Patients with non-shockable rhythms had higher mortality(60% vs 29.1%, P < 0.001) and a worst neurological status at hospital discharge based on cerebral performance category score(CPC 1-2: 32.7% vs 53.4%, P = 0.02). Although there were no significant differences in global burden of coronary artery disease defined by Syntax Score(mean Syntax Score: 10.2 vs 10.3, P = 0.96) there was a trend towards a higher incidence of acute coronary lesions in patients with shockable rhythm(29.7% vs 16.4%, P = 0.054). There was also a higher need for ad-hoc percutaneous coronary intervention in this group(21.9% vs 9.1%, P = 0.03). CONCLUSION Initial shockable group of patients had a trend towards higher incidence of acute coronary lesions and higher need of ad-hoc percutaneous intervention vs nonshockable group.
文摘Hyperkalemia is defined as serum potassium level of more than 5 mmol/L. Prompt identification of hyper-kalemia and appropriate management are critical, since severe hyperkalemia can lead to lethal cardiac dysrhythmias. There is a wide range of electrocardiogram (EKG) changes associated with hyperkalemia. The sequence of EKG changes has been previously described with limited information to correlate the level of potassium to a particular change in the EKG. This study aims to describe a correlation between the level of potassium and EKG changes in the presence or absence of certain diagnoses, to determine which EKG finding in the context of level of hyperkalemia, should be considered life-threatening and prompt emergency intervention. If a relationship between serum levels of potassium and EKG changes is significant, clinicians may be able to better monitor and treat hyperkalemic patients. This paper reviews the literature on hyperkalemia, potassium homeostasis and EKG changes attributed to elevated potassium.
