Journal of electrocardiology最新文献

MrSeNet: Electrocardiogram signal denoising based on multi-resolution residual attention network.

IF 1.3 4区医学

Journal of electrocardiology Pub Date : 2024-12-27 DOI: 10.1016/j.jelectrocard.2024.153858

Zhen Wang, Hanshuang Xie, Yamin Liu, Huaiyu Zhu, Hongpo Zhang, Zongmin Wang, Yun Pan

{"title":"MrSeNet: Electrocardiogram signal denoising based on multi-resolution residual attention network.","authors":"Zhen Wang, Hanshuang Xie, Yamin Liu, Huaiyu Zhu, Hongpo Zhang, Zongmin Wang, Yun Pan","doi":"10.1016/j.jelectrocard.2024.153858","DOIUrl":"https://doi.org/10.1016/j.jelectrocard.2024.153858","url":null,"abstract":"Electrocardiography (ECG) is a widely used, non-invasive, and cost-effective diagnostic method that plays a crucial role in the early detection and management of cardiac conditions. However, the ECG signal is easily disrupted by various noise signals in the real world, leading to a decrease in signal quality and potentially compromising accurate clinical interpretation. With the goal of reducing noise in ECG signals, this research proposes an end-to-end multi-resolution deep learning network with attention mechanism, namely the MrSeNet to perform effective denoising of ECG data. Our MrSeNet fuses features at different scales for effective denoising with the squeeze-and-excitation module to enhance the features of the ECG signal channel. CPSC2018 database and the MIT-BIH database were used to verify the validity of the model by adding different intensity noises based on NSTDB. Using Pearson correlation coefficient, signal-to-noise ratio, and root mean square error performance evaluation model, the experimental results show that MrSeNet performs better than the traditional method, the model can achieve a good denoising effect to different degrees of noise signal data, and has a good future application prospect.","PeriodicalId":15606,"journal":{"name":"Journal of electrocardiology","volume":"89 ","pages":"153858"},"PeriodicalIF":1.3,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142915048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Case report: Improved detection of electrocardiographic abnormalities using precordial bipolar leads. 病例报告：使用心前区双极导联改进心电图异常的检测。

IF 1.3 4区医学

Journal of electrocardiology Pub Date : 2024-12-26 DOI: 10.1016/j.jelectrocard.2024.153856

Mario J Mc Loughlin

引用次数: 0

The role of telemetry monitoring: From diagnosing arrhythmia to predictive models of patient instability.

IF 1.3 4区医学

Journal of electrocardiology Pub Date : 2024-12-25 DOI: 10.1016/j.jelectrocard.2024.153861

Ran Xiao

{"title":"The role of telemetry monitoring: From diagnosing arrhythmia to predictive models of patient instability.","authors":"Ran Xiao","doi":"10.1016/j.jelectrocard.2024.153861","DOIUrl":"https://doi.org/10.1016/j.jelectrocard.2024.153861","url":null,"abstract":"Over the past sixty years, telemetry monitoring has become integral to hospital care, offering critical insights into patient health by tracking key indicators like heart rate, respiratory rate, blood pressure, and oxygen saturation. Its primary application, continuous electrocardiographic (ECG) monitoring, is essential in diverse settings such as emergency departments, step-down units, general wards, and intensive care units for the early detection of cardiac rhythms signaling acute clinical deterioration. Recent advancements in data analytics and machine learning have expanded telemetry's role from observation to prognostication, enabling predictive models that forecast inhospital events indicative of patient instability. This short communication reviews the current applications and benefits of telemetry monitoring, including its vital role in identifying arrhythmias and predicting conditions like sepsis and cardiac arrest, while also addressing challenges such as alarm fatigue and the economic impact on health systems. It further explores opportunities for developing algorithms to enhance the practical use of telemetry data in clinical settings.","PeriodicalId":15606,"journal":{"name":"Journal of electrocardiology","volume":"89 ","pages":"153861"},"PeriodicalIF":1.3,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142909666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

12 lead surface ECGs as a surrogate of atrial electrical remodeling - a deep learning based approach.

IF 1.3 4区医学

Journal of electrocardiology Pub Date : 2024-12-25 DOI: 10.1016/j.jelectrocard.2024.153862

Ishan Vatsaraj, Yazan Mohsen, Lukas Grüne, Lucas Steffens, Shane Loeffler, Marc Horlitz, Florian Stöckigt, Natalia Trayanova

{"title":"12 lead surface ECGs as a surrogate of atrial electrical remodeling - a deep learning based approach.","authors":"Ishan Vatsaraj, Yazan Mohsen, Lukas Grüne, Lucas Steffens, Shane Loeffler, Marc Horlitz, Florian Stöckigt, Natalia Trayanova","doi":"10.1016/j.jelectrocard.2024.153862","DOIUrl":"https://doi.org/10.1016/j.jelectrocard.2024.153862","url":null,"abstract":"Background and purpose: Atrial fibrillation (AF), a common arrhythmia, is linked with atrial electrical and structural changes, notably low voltage areas (LVAs) which are associated with poor ablation outcomes and increased thromboembolic risk. This study aims to evaluate the efficacy of a deep learning model applied to 12‑lead ECGs for non-invasively predicting the presence of LVAs, potentially guiding pre-ablation strategies and improving patient outcomes.Methods: A retrospective analysis was conducted on 204 AF patients, who underwent catheter ablation. Pre-procedural sinus rhythm ECGs and electroanatomical maps (EAM) were utilized alongside demographic data to train a deep learning model combining Long Short-Term Memory networks and Convolutional Neural Networks with a cross-attention layer. Model performance was evaluated using a 5-fold cross-validation strategy.Results: The model effectively identified the presence of LVA on the examined atrial walls, achieving accuracies of 78 % for both the anterior and posterior walls, and 82 % for the LA roof. Moreover, it accurately predicted the global left atrial (LA) average voltage <0.7 mV, with an accuracy of 88 %.Conclusion: The study showcases the potential of deep learning applied to 12‑lead ECGs to effectively predict regional LVAs and global LA voltage in AF patients non-invasively. This model offers a promising tool for the pre-ablation assessment of atrial substrate, facilitating personalized therapeutic strategies and potentially enhancing ablation success rates.","PeriodicalId":15606,"journal":{"name":"Journal of electrocardiology","volume":"89 ","pages":"153862"},"PeriodicalIF":1.3,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142915045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identifying early left atrial dysfunction in COPD patients using ECG morphology-voltage-P wave duration score.

IF 1.3 4区医学

Journal of electrocardiology Pub Date : 2024-12-19 DOI: 10.1016/j.jelectrocard.2024.153854

Uğur Küçük, Pınar Mutlu, Arzu Mirici, Uğur Özpınar, Selin Beyza Özpınar

{"title":"Identifying early left atrial dysfunction in COPD patients using ECG morphology-voltage-P wave duration score.","authors":"Uğur Küçük, Pınar Mutlu, Arzu Mirici, Uğur Özpınar, Selin Beyza Özpınar","doi":"10.1016/j.jelectrocard.2024.153854","DOIUrl":"https://doi.org/10.1016/j.jelectrocard.2024.153854","url":null,"abstract":"Background: Chronic Obstructive Pulmonary Disease (COPD) is associated with left atrial (LA) dyfunction, which may contribute to adverse cardiovascular outcomes. This study investigates the predictive value of lately identified morphology-voltage-P wave duration electrocardiography (MVP ECG) score for detecting early LA dysfunction in COPD patients.Methods: In this cross-sectional study, 101 COPD patients were enrolled. All patients underwent speckle tracking echocardiography and were classified into two groups based on their LA functions.Results: Our findings demonstrate significant variations in Peak Atrial Longitudinal Strain (PALS) values among COPD patients, with a mean PALS of 28.74 ± 1.81 % for the group with normal LA function and 18.44 ± 1.87 % for the group with abnormal LA function (p < 0.001). Despite similar LA diameters across groups, these variations indicate subclinical LA pathogenesis. ROC curve analysis indicated that an MVP ECG score greater than 2.5 predicted abnormal LA function with a sensitivity of 65 % and a specificity of 91 % (area under the curve [AUC]: 0.873; p < 0.001), suggesting its utility in identifying atrial damage and remodeling.Conclusions: The MVP ECG score shows promise as a tool for early detection of atrial remodeling in COPD patients.","PeriodicalId":15606,"journal":{"name":"Journal of electrocardiology","volume":"88 ","pages":"153854"},"PeriodicalIF":1.3,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142894713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mortality in Modena.

IF 1.3 4区医学

Journal of electrocardiology Pub Date : 2024-12-18 DOI: 10.1016/j.jelectrocard.2024.153852

Mario Jorge Mc Loughlin

引用次数: 0

Case presentation of acute ischemia induced ST-depression masking Brugada syndrome ECG pattern in a relatively young patient.

IF 1.3 4区医学

Journal of electrocardiology Pub Date : 2024-12-15 DOI: 10.1016/j.jelectrocard.2024.153853

Kristina Torngren, Aleksei Savelev, Erik Ljungström, Pyotr G Platonov

引用次数: 0

In the face of confounders: Atrial fibrillation detection - Practitioners vs. ChatGPT.

IF 1.3 4区医学

Journal of electrocardiology Pub Date : 2024-12-07 DOI: 10.1016/j.jelectrocard.2024.153851

Yuval Avidan, Vsevolod Tabachnikov, Orel Ben Court, Razi Khoury, Amir Aker

{"title":"In the face of confounders: Atrial fibrillation detection - Practitioners vs. ChatGPT.","authors":"Yuval Avidan, Vsevolod Tabachnikov, Orel Ben Court, Razi Khoury, Amir Aker","doi":"10.1016/j.jelectrocard.2024.153851","DOIUrl":"https://doi.org/10.1016/j.jelectrocard.2024.153851","url":null,"abstract":"Introduction: Atrial fibrillation (AF) is the most common arrhythmia in clinical practice, yet interpretation concerns among healthcare providers persist. Confounding factors contribute to false-positive and false-negative AF diagnoses, leading to potential omissions. Artificial intelligence advancements show promise in electrocardiogram (ECG) interpretation. We sought to examine the diagnostic accuracy of ChatGPT-4omni (GPT-4o), equipped with image evaluation capabilities, in interpreting ECGs with confounding factors and compare its performance to that of physicians.Methods: Twenty ECG cases, divided into Group A (10 cases of AF or atrial flutter) and Group B (10 cases of sinus or another atrial rhythm), were crafted into multiple-choice questions. Total of 100 practitioners (25 from each: emergency medicine, internal medicine, primary care, and cardiology) were tasked to identify the underlying rhythm. Next, GPT-4o was prompted in five separate sessions.Results: GPT-4o performed inadequately, averaging 3 (±2) in Group A questions and 5.40 (±1.34) in Group B questions. Upon examining the accuracy of the total ECG questions, no significant difference was found between GPT-4o, internists, and primary care physicians (p = 0.952 and = 0.852, respectively). Cardiologists outperformed other medical disciplines and GPT-4o (p < 0.001), while emergency physicians followed in accuracy, though comparison to GPT-4o only indicated a trend (p = 0.068).Conclusion: GPT-4o demonstrated suboptimal accuracy with significant under- and over-recognition of AF in ECGs with confounding factors. Despite its potential as a supportive tool for ECG interpretation, its performance did not surpass that of medical practitioners, underscoring the continued importance of human expertise in complex diagnostics.","PeriodicalId":15606,"journal":{"name":"Journal of electrocardiology","volume":"88 ","pages":"153851"},"PeriodicalIF":1.3,"publicationDate":"2024-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142818416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Triple pacing spikes on QRST: What is the mechanism?

IF 1.3 4区医学

Journal of electrocardiology Pub Date : 2024-12-07 DOI: 10.1016/j.jelectrocard.2024.153849

Sudipta Mondal, N Sharath, Jyothi Vijay, Narayanan Namboodiri

引用次数: 0

Immediate changes in depolarization and repolarization after left bundle branch area pacing and atrioventricular nodal ablation.

IF 1.3 4区医学

Journal of electrocardiology Pub Date : 2024-11-30 DOI: 10.1016/j.jelectrocard.2024.153847

Mert Doğan, Uğur Canpolat, Cem Çöteli, Hikmet Yorgun, Kudret Aytemir

{"title":"Immediate changes in depolarization and repolarization after left bundle branch area pacing and atrioventricular nodal ablation.","authors":"Mert Doğan, Uğur Canpolat, Cem Çöteli, Hikmet Yorgun, Kudret Aytemir","doi":"10.1016/j.jelectrocard.2024.153847","DOIUrl":"https://doi.org/10.1016/j.jelectrocard.2024.153847","url":null,"abstract":"Background: Malignant arrhythmia due to ventricular depolarization and repolarization alterations after atrioventricular node (AVN) ablation is a known clinical entity. Here, we aimed to demonstrate the ventricular depolarization and repolarization changes in patients who underwent left bundle branch area pacing (LBBaP) and AVN ablation.Methods: This is a single-center, retrospective preliminary study (n = 10). All patients underwent single-chamber pacemaker implantation with LBBaP before the AVN ablation procedure. Electrocardiographic (ECG) parameters [QRS duration (QRSd), QTc (Fridericia formula), Tp-e, and JT interval] were measured and analyzed before and after the procedure.Results: The mean age of the study population was 67.1 ± 8.88 years, and 70 % of the patients were female. 60 % of the patients had AF, and 40 % of them had atrial tachycardia during the procedures. Eight patients had undergone more than two catheter ablations before the procedure. The QT interval (263.47 ± 26.79 vs. 416.14 ± 36.31 msec) and QRSd (93.3 ± 7.3 vs. 122.32 ± 21.16 msec) were prolonged when the patient's ECG parameters were analyzed. Still, the Tp-Te interval (75.57 ± 18.62 vs. 80.93 ± 17.35 msec) did not change, and the QTc (Fridericia formula) interval (425 ± 29.82 vs. 461.70 ± 35.33 msec) did not show a significant difference.Conclusion: Malignant arrhythmia may occur due to ventricular depolarization and repolarization changes after the AVN ablation procedure. This study showed no significant change in Tp-e and QTc durations previously defined for malignant arrhythmia development. At the same time, JT time, which indicates ventricular repolarization duration, did not show a significant difference. LBBaP is more physiological and safer for patients planning to undergo AVN ablation.","PeriodicalId":15606,"journal":{"name":"Journal of electrocardiology","volume":"88 ","pages":"153847"},"PeriodicalIF":1.3,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142780387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0