[Diagnostic and intervention value of implantable cardiac monitor in patients over 60 years of age with unexplained syncope].

Objective: To investigate the value of implantable cardiac monitor (ICM) in the diagnosis and treatment of patients over 60 years old with unexplained syncope. Methods: This was a multi-center, prospective cohort study. Between June 2018 and April 2021, patients over the age of 60 with unexplained syncope at Beijing Hospital, Fuwai Hospital, Beijing Anzhen Hospital and Puren Hospital were enrolled. Patients were divided into 2 groups based on their decision to receive ICM implantation (implantation group and conventional follow-up group). The endpoint was the recurrence of syncope and cardiogenic syncope as determined by positive cardiac arrhythmia events recorded at the ICM or diagnosed during routine follow-up. Kaplan-Meier survival analysis was used to compare the differences of cumulative diagnostic rate between the 2 groups. A multivariate Cox regression analysis was performed to determine independent predictors of diagnosis of cardiogenic syncope in patients with unexplained syncope. Results: A total of 198 patients with unexplained syncope, aged (72.9±8.25) years, were followed for 558.0 (296.0,877.0) d, including 98 males (49.5%). There were 100 (50.5%) patients in the implantation group and 98 (49.5%) in the conventional follow-up group. Compared with conventional follow-up group, patients in the implantation group were older, more likely to have comorbidities, had a higher proportion of first degree atrioventricular block indicated by baseline electrocardiogram, and had a lower body mass index (all P<0.05). During the follow-up period, positive cardiac arrhythmia events were recorded in 58 (58.0%) patients in the ICM group. The diagnosis rate (42.0% (42/100) vs. 4.1% (4/98), P<0.001) and the intervention rate (37.0% (37/100) vs. 2.0% (2/98), P<0.001) of cardiogenic syncope in the implantation group were higher than those in the conventional follow-up group (all P<0.001). Kaplan-Meier survival analysis showed that the cumulative diagnostic rate of cardiogenic syncope was significantly higher in the implantation group than in the traditional follow-up group (HR=11.66, 95%CI 6.49-20.98, log-rank P<0.001). Multivariate analysis indicated that ICM implantation, previous atrial fibrillation, diabetes mellitus or first degree atrioventricular block in baseline electrocardiogram were independent predictors for cardiogenic syncope (all P<0.05). Conclusions: ICM implantation improves the diagnosis and intervention rates in patients with unexplained syncope, and increases diagnostic efficiency in patients with unexplained syncope.

RETRACTED: PO-04-037 ARTIFICIAL INTELLIGENCE FOR ANALYSIS OF MOBILE CARDIAC TELEMETRY.

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/policies/article-withdrawal). This abstract has been retracted at the request of the Authors; please see Elsevier Policy on Article Withdrawal (http://www.elsevier.com/locate/withdrawalpolicy). The abstract was withdrawn after being accepted for presentation at Heart Rhythm, the annual meeting of the Heart Rhythm Society, because there was substantial content development after it had been submitted, both in terms of more in-depth analyses and quantitative changes due to final adjudication of events. The Authors intended to withdraw the abstract from publication as well but omitted to do so. The Authors apologize for the inconvenience caused by this oversight.

The Association Between Late Gadolinium Enhancement by Cardiac Magnetic Resonance and Ventricular Arrhythmia in Patients With Mitral Valve Prolapse: A Systematic Review and Meta-Analysis.

INTRODUCTION: Malignant ventricular arrhythmia (VA) and sudden cardiac death (SCD) have been reported in patients with mitral valve prolapse (MVP); however, effective risk stratification methods are still lacking. Myocardial fibrosis is thought to play an important role in the development of VA; however, observational studies have produced contradictory findings regarding the relationship between VA and late gadolinium enhancement (LGE) in MVP patients. The aim of this meta-analysis and systematic review of observational studies was to investigate the association between left ventricular LGE and VA in patients with MVP. METHODS: We searched the PubMed, Embase, and Web of Science databases from 1993 to 2023 to identify case-control, cross-sectional, and cohort studies that compared the incidence of VA in patients with MVP who had left ventricular LGE and those without left ventricular LGE. RESULTS: A total of 1464 subjects with MVP from 12 observational studies met the eligibility criteria. Among them, VA episodes were reported in 221 individuals (15.1%). Meta-analysis demonstrated that the presence of left ventricular LGE was significantly associated with an increased risk of VA (pooled risk ratio 2.96, 95% CI: 2.26-3.88, p for heterogeneity = 0.07, I2 = 40%). However, a meta-regression analysis of the prevalence of mitral regurgitation (MR) showed that the severity of MR did not significantly affect the association between the occurrence of LGE and VA (p = 0.079). CONCLUSION: The detection of LGE could be helpful for stratifying the risk of VA in patients with MVP.

Association between obstructive sleep apnea and arrhythmia and heart rate variability among hypertensive patients.

BACKGROUND: The relationship between obstructive sleep apnea (OSA) and the occurrence of arrhythmias and heart rate variability (HRV) in hypertensive patients is not elucidated. Our study investigates the association between OSA, arrhythmias, and HRV in hypertensive patients. METHODS: We conducted a cross-sectional analysis involving hypertensive patients divided based on their apnea-hypopnea index (AHI) into two groups: the AHI ≤ 15 and the AHI > 15. All participants underwent polysomnography (PSG), 24-hour dynamic electrocardiography (DCG), cardiac Doppler ultrasound, and other relevant evaluations. RESULTS: The AHI > 15 group showed a significantly higher prevalence of frequent atrial premature beats and atrial tachycardia (P = 0.030 and P = 0.035, respectively) than the AHI ≤ 15 group. Time-domain analysis indicated that the standard deviation of normal-to-normal R-R intervals (SDNN) and the standard deviation of every 5-minute normal-to-normal R-R intervals (SDANN) were significantly higher in the AHI > 15 group (P = 0.020 and P = 0.033, respectively). Frequency domain analysis revealed that the low-frequency (LF), high-frequency (HF) components, and the LF/HF ratio were also significantly elevated in the AHI > 15 group (P < 0.001, P = 0.031, and P = 0.028, respectively). Furthermore, left atrial diameter (LAD) was significantly larger in the AHI > 15 group (P < 0.001). Both univariate and multivariable linear regression analyses confirmed a significant association between PSG-derived independent variables and the dependent HRV parameters SDNN, LF, and LF/HF ratio (F = 8.929, P < 0.001; F = 14.832, P < 0.001; F = 5.917, P = 0.016, respectively). CONCLUSIONS: Hypertensive patients with AHI > 15 are at an increased risk for atrial arrhythmias and left atrial dilation, with HRV significantly correlating with OSA severity.

State-of-the-art pulsed field ablation for cardiac arrhythmias: ongoing evolution and future perspective.

Pulsed field ablation (PFA) is an innovative approach in the field of cardiac electrophysiology aimed at treating cardiac arrhythmias. Unlike traditional catheter ablation energies, which use radiofrequency or cryothermal energy to create lesions in the heart, PFA utilizes pulsed electric fields to induce irreversible electroporation, leading to targeted tissue destruction. This state-of-the-art review summarizes biophysical principles and clinical applications of PFA, highlighting its potential advantages over conventional ablation methods. Clinical data of contemporary PFA devices are discussed, which combine predictable procedural outcomes and a reduced risk of thermal collateral damage. Overall, these technological developments have propelled the rapid evolution of contemporary PFA catheters, with future advancements potentially impacting patient care.

Incidence and Types of Cardiac Arrhythmias in the Peri-Ictal Period in Patients Having a Generalized Convulsive Seizure.

BACKGROUND AND OBJECTIVES: Generalized convulsive seizures (GCSs) are the main risk factor of sudden unexpected death in epilepsy (SUDEP), which is likely due to peri-ictal cardiorespiratory dysfunction. The incidence of GCS-induced cardiac arrhythmias, their relationship to seizure severity markers, and their role in SUDEP physiopathology are unknown. The aim of this study was to analyze the incidence of seizure-induced cardiac arrhythmias, their association with electroclinical features and seizure severity biomarkers, as well as their specific occurrences in SUDEP cases. METHODS: This is an observational, prospective, multicenter study of patients with epilepsy aged 18 years and older with recorded GCS during inpatient video-EEG monitoring for epilepsy evaluation. Exclusion criteria were status epilepticus and an obscured video recording. We analyzed semiologic and cardiorespiratory features through video-EEG (VEEG), electrocardiogram, thoracoabdominal bands, and pulse oximetry. We investigated the presence of bradycardia, asystole, supraventricular tachyarrhythmias (SVTs), premature atrial beats, premature ventricular beats, nonsustained ventricular tachycardia (NSVT), atrial fibrillation (Afib), ventricular fibrillation (VF), atrioventricular block (AVB), exaggerated sinus arrhythmia (ESA), and exaggerated sinus arrhythmia with bradycardia (ESAWB). A board-certified cardiac electrophysiologist diagnosed and classified the arrhythmia types. Bradycardia, asystole, SVT, NSVT, Afib, VF, AVB, and ESAWB were classified as arrhythmias of interest because these were of SUDEP pathophysiology value. The main outcome was the occurrence of seizure-induced arrhythmias of interest during inpatient VEEG monitoring. Moreover, yearly follow-up was conducted to identify SUDEP cases. Binary logistic generalized estimating equations were used to determine clinical-demographic and peri-ictal variables that were predictive of the presence of seizure-induced arrhythmias of interest. The z-score test for 2 population proportions was used to test whether the proportion of seizures and patients with postconvulsive ESAWB or bradycardia differed between SUDEP cases and survivors. RESULTS: This study includes data from 249 patients (mean age 37.2 ± 23.5 years, 55% female) who had 455 seizures. The most common arrhythmia was ESA, with an incidence of 137 of 382 seizures (35.9%) (106/224 patients [47.3%]). There were 50 of 352 seizure-induced arrhythmias of interest (14.2%) in 41 of 204 patients (20.1%). ESAWB was the commonest in 22 of 394 seizures (5.6%) (18/225 patients [8%]), followed by SVT in 18 of 397 seizures (4.5%) (17/228 patients [7.5%]). During follow-up (48.36 ± 31.34 months), 8 SUDEPs occurred. Seizure-induced bradycardia (3.8% vs 12.5%, z = -16.66, p < 0.01) and ESAWB (6.6% vs 25%; z = -3.03, p < 0.01) were over-represented in patients who later died of SUDEP. There was no association between arrhythmias of interest and seizure severity biomarkers (p > 0.05). DISCUSSION: Markers of seizure severity are not related to seizure-induced arrhythmias of interest, suggesting that other factors such as occult cardiac abnormalities may be relevant for their occurrence. Seizure-induced ESAWB and bradycardia were more frequent in SUDEP cases, although this observation was based on a very limited number of SUDEP patients. Further case-control studies are needed to evaluate the yield of arrhythmias of interest along with respiratory changes as potential SUDEP biomarkers.

Arrhythmia classification based on multi-feature multi-path parallel deep convolutional neural networks and improved focal loss.

Early diagnosis of abnormal electrocardiogram (ECG) signals can provide useful information for the prevention and detection of arrhythmia diseases. Due to the similarities in Normal beat (N) and Supraventricular Premature Beat (S) categories and imbalance of ECG categories, arrhythmia classification cannot achieve satisfactory classification results under the inter-patient assessment paradigm. In this paper, a multi-path parallel deep convolutional neural network was proposed for arrhythmia classification. Furthermore, a global average RR interval was introduced to address the issue of similarities between N vs. S categories, and a weighted loss function was developed to solve the imbalance problem using the dynamically adjusted weights based on the proportion of each class in the input batch. The MIT-BIH arrhythmia dataset was used to validate the classification performances of the proposed method. Experimental results under the intra-patient evaluation paradigm and inter-patient evaluation paradigm showed that the proposed method could achieve better classification results than other methods. Among them, the accuracy, average sensitivity, average precision, and average specificity under the intra-patient paradigm were 98.73%, 94.89%, 89.38%, and 98.24%, respectively. The accuracy, average sensitivity, average precision, and average specificity under the inter-patient paradigm were 91.22%, 89.91%, 68.23%, and 95.23%, respectively.

AttBiLFNet: A novel hybrid network for accurate and efficient arrhythmia detection in imbalanced ECG signals.

Within the domain of cardiovascular diseases, arrhythmia is one of the leading anomalies causing sudden deaths. These anomalies, including arrhythmia, are detectable through the electrocardiogram, a pivotal component in the analysis of heart diseases. However, conventional methods like electrocardiography encounter challenges such as subjective analysis and limited monitoring duration. In this work, a novel hybrid model, AttBiLFNet, was proposed for precise arrhythmia detection in ECG signals, including imbalanced class distributions. AttBiLFNet integrates a Bidirectional Long Short-Term Memory (BiLSTM) network with a convolutional neural network (CNN) and incorporates an attention mechanism using the focal loss function. This architecture is capable of autonomously extracting features by harnessing BiLSTM's bidirectional information flow, which proves advantageous in capturing long-range dependencies. The attention mechanism enhances the model's focus on pertinent segments of the input sequence, which is particularly beneficial in class imbalance classification scenarios where minority class samples tend to be overshadowed. The focal loss function effectively addresses the impact of class imbalance, thereby improving overall classification performance. The proposed AttBiLFNet model achieved 99.55% accuracy and 98.52% precision. Moreover, performance metrics such as MF1, K score, and sensitivity were calculated, and the model was compared with various methods in the literature. Empirical evidence showed that AttBiLFNet outperformed other methods in terms of both accuracy and computational efficiency. The introduced model serves as a reliable tool for the timely identification of arrhythmias.

Deep learning based ECG segmentation for delineation of diverse arrhythmias.

Accurate delineation of key waveforms in an ECG is a critical step in extracting relevant features to support the diagnosis and treatment of heart conditions. Although deep learning based methods using segmentation models to locate P, QRS, and T waves have shown promising results, their ability to handle arrhythmias has not been studied in any detail. In this paper we investigate the effect of arrhythmias on delineation quality and develop strategies to improve performance in such cases. We introduce a U-Net-like segmentation model for ECG delineation with a particular focus on diverse arrhythmias. This is followed by a post-processing algorithm which removes noise and automatically determines the boundaries of P, QRS, and T waves. Our model has been trained on a diverse dataset and evaluated against the LUDB and QTDB datasets to show strong performance, with F1-scores exceeding 99% for QRS and T waves, and over 97% for P waves in the LUDB dataset. Furthermore, we assess various models across a wide array of arrhythmias and observe that models with a strong performance on standard benchmarks may still perform poorly on arrhythmias that are underrepresented in these benchmarks, such as tachycardias. We propose solutions to address this discrepancy.

Clinical Presentation and Therapy of Arrhythmias.

The electrocardiogram (ECG) is one of the cornerstones of diagnostic investigations in pediatric or adult cardiology. The standard ECG includes 12 leads; there are 6 leads that are derived from electrodes from the arms and legs (Einthoven and Goldberger leads) and 6 precordial leads (Wilson leads).

Predictors and 5-Year Clinical Outcomes of Pacemaker After TAVR: Analysis From the PARTNER 2 SAPIEN 3 Registries.

BACKGROUND: Conduction disturbances requiring a permanent pacemaker (PPM) are a frequent complication of transcatheter aortic valve replacement (TAVR) with few reports of rates, predictors, and long-term clinical outcomes following implantation of the third-generation, balloon-expandable SAPIEN 3 (S3) transcatheter heart valve (THV). OBJECTIVES: The aim of this study was to investigate the rates, predictors, and long-term clinical outcomes of PPM implantation following TAVR with the S3 THV. METHODS: The current study included 857 patients in the PARTNER 2 S3 registries with intermediate and high surgical risk without prior PPM, and investigated predictors and 5-year clinical outcomes of new PPM implanted within 30 days of TAVR. RESULTS: Among 857 patients, 107 patients (12.5%) received a new PPM within 30 days after TAVR. By multivariable analysis, predictors of PPM included increased age, pre-existing right bundle branch block, larger THV size, greater THV oversizing, moderate or severe annulus calcification, and implantation depth >6 mm. At 5 years (median follow-up 1,682.0 days [min 2.0 days, max 2,283.0 days]), new PPM was not associated with increased rates of all-cause mortality (Adj HR: 1.20; 95% CI: 0.85-1.70; P = 0.30) or repeat hospitalization (Adj HR: 1.22; 95% CI: 0.67-2.21; P = 0.52). Patients with new PPM had a decline in left ventricular ejection fraction at 1 year that persisted at 5 years (55.1 ± 2.55 vs 60.4 ± 0.65; P = 0.02). CONCLUSIONS: PPM was required in 12.5% of patients without prior PPM who underwent TAVR with a SAPIEN 3 valve in the PARTNER 2 S3 registries and was not associated with worse clinical outcomes, including mortality, at 5 years. Modifiable factors that may reduce the PPM rate include bioprosthetic valve oversizing, prosthesis size, and implantation depth.

Observational study protocol for an arrhythmia notification feature.

INTRODUCTION: Screening for atrial fibrillation (AF) in the general population may help identify individuals at risk, enabling further assessment of risk factors and institution of appropriate treatment. Algorithms deployed on wearable technologies such as smartwatches and fitness bands may be trained to screen for such arrhythmias. However, their performance needs to be assessed for safety and accuracy prior to wide-scale implementation. METHODS AND ANALYSIS: This study will assess the ability of the WHOOP strap to detect AF using its WHOOP Arrhythmia Notification Feature (WARN) algorithm in an enriched cohort with a 2:1 distribution of previously diagnosed AF (persistent and paroxysmal) and healthy controls. Recruited participants will collect data for 7 days with the WHOOP wrist-strap and BioTel ePatch (electrocardiography gold-standard). Primary outcome will be participant level sensitivity and specificity of the WARN algorithm in detecting AF in analysable windows compared with the ECG gold-standard. Similar analyses will be performed on an available epoch-level basis as well as comparison of these findings in important subgroups. ETHICS AND DISSEMINATION: The study was approved by the ethics board at the study site. Participants will be enrolled after signing an online informed consent document. Updates will be shared via clinicaltrials.gov. The data obtained from the conclusion of this study will be presented in national and international conferences with publication in clinical research journals. TRIAL REGISTRATION NUMBER: NCT05809362.

ECG autoencoder based on low-rank attention.

The prevalence of cardiovascular disease (CVD) has surged in recent years, making it the foremost cause of mortality among humans. The Electrocardiogram (ECG), being one of the pivotal diagnostic tools for cardiovascular diseases, is increasingly gaining prominence in the field of machine learning. However, prevailing neural network models frequently disregard the spatial dimension features inherent in ECG signals. In this paper, we propose an ECG autoencoder network architecture incorporating low-rank attention (LRA-autoencoder). It is designed to capture potential spatial features of ECG signals by interpreting the signals from a spatial perspective and extracting correlations between different signal points. Additionally, the low-rank attention block (LRA-block) obtains spatial features of electrocardiogram signals through singular value decomposition, and then assigns these spatial features as weights to the electrocardiogram signals, thereby enhancing the differentiation of features among different categories. Finally, we utilize the ResNet-18 network classifier to assess the performance of the LRA-autoencoder on both the MIT-BIH Arrhythmia and PhysioNet Challenge 2017 datasets. The experimental results reveal that the proposed method demonstrates superior classification performance. The mean accuracy on the MIT-BIH Arrhythmia dataset is as high as 0.997, and the mean accuracy and F 1 -score on the PhysioNet Challenge 2017 dataset are 0.850 and 0.843.

Empagliflozin's role in reducing ventricular repolarization heterogeneity: insights into cardiovascular mortality decline from the EMPATHY-HEART trial.

BACKGROUND: The incidence of myocardial infarction (MI) and sudden cardiac death (SCD) is significantly higher in individuals with Type 2 Diabetes Mellitus (T2DM) than in the general population. Strategies for the prevention of fatal arrhythmias are often insufficient, highlighting the need for additional non-invasive diagnostic tools. The T-wave heterogeneity (TWH) index measures variations in ventricular repolarization and has emerged as a promising predictor for severe ventricular arrhythmias. Although the EMPA-REG trial reported reduced cardiovascular mortality with empagliflozin, the underlying mechanisms remain unclear. This study investigates the potential of empagliflozin in mitigating cardiac electrical instability in patients with T2DM and coronary heart disease (CHD) by examining changes in TWH. METHODS: Participants were adult outpatients with T2DM and CHD who exhibited TWH > 80 µV at baseline. They received a 25 mg daily dose of empagliflozin and were evaluated clinically including electrocardiogram (ECG) measurements at baseline and after 4 weeks. TWH was computed from leads V4, V5, and V6 using a validated technique. The primary study outcome was a significant (p < 0.05) change in TWH following empagliflozin administration. RESULTS: An initial review of 6,000 medical records pinpointed 800 patients for TWH evaluation. Of these, 412 exhibited TWH above 80 µV, with 97 completing clinical assessments and 90 meeting the criteria for high cardiovascular risk enrollment. Empagliflozin adherence exceeded 80%, resulting in notable reductions in blood pressure without affecting heart rate. Side effects were generally mild, with 13.3% experiencing Level 1 hypoglycemia, alongside infrequent urinary and genital infections. The treatment consistently reduced mean TWH from 116 to 103 µV (p = 0.01). CONCLUSIONS: The EMPATHY-HEART trial preliminarily suggests that empagliflozin decreases heterogeneity in ventricular repolarization among patients with T2DM and CHD. This reduction in TWH may provide insight into the mechanism behind the decreased cardiovascular mortality observed in previous trials, potentially offering a therapeutic pathway to mitigate the risk of severe arrhythmias in this population. TRIAL REGISTRATION: NCT: 04117763.

A Clinical Diagnostic Test for Calcium Release Deficiency Syndrome.

Importance: Sudden death and cardiac arrest frequently occur without explanation, even after a thorough clinical evaluation. Calcium release deficiency syndrome (CRDS), a life-threatening genetic arrhythmia syndrome, is undetectable with standard testing and leads to unexplained cardiac arrest. Objective: To explore the cardiac repolarization response on an electrocardiogram after brief tachycardia and a pause as a clinical diagnostic test for CRDS. Design, Setting, and Participants: An international, multicenter, case-control study including individual cases of CRDS, 3 patient control groups (individuals with suspected supraventricular tachycardia; survivors of unexplained cardiac arrest [UCA]; and individuals with genotype-positive catecholaminergic polymorphic ventricular tachycardia [CPVT]), and genetic mouse models (CRDS, wild type, and CPVT were used to define the cellular mechanism) conducted at 10 centers in 7 countries. Patient tracings were recorded between June 2005 and December 2023, and the analyses were performed from April 2023 to December 2023. Intervention: Brief tachycardia and a subsequent pause (either spontaneous or mediated through cardiac pacing). Main Outcomes and Measures: Change in QT interval and change in T-wave amplitude (defined as the difference between their absolute values on the postpause sinus beat and the last beat prior to tachycardia). Results: Among 10 case patients with CRDS, 45 control patients with suspected supraventricular tachycardia, 10 control patients who experienced UCA, and 3 control patients with genotype-positive CPVT, the median change in T-wave amplitude on the postpause sinus beat (after brief ventricular tachycardia at ≥150 beats/min) was higher in patients with CRDS (P < .001). The smallest change in T-wave amplitude was 0.250 mV for a CRDS case patient compared with the largest change in T-wave amplitude of 0.160 mV for a control patient, indicating 100% discrimination. Although the median change in QT interval was longer in CRDS cases (P = .002), an overlap between the cases and controls was present. The genetic mouse models recapitulated the findings observed in humans and suggested the repolarization response was secondary to a pathologically large systolic release of calcium from the sarcoplasmic reticulum. Conclusions and Relevance: There is a unique repolarization response on an electrocardiogram after provocation with brief tachycardia and a subsequent pause in CRDS cases and mouse models, which is absent from the controls. If these findings are confirmed in larger studies, this easy to perform maneuver may serve as an effective clinical diagnostic test for CRDS and become an important part of the evaluation of cardiac arrest.