Selection of candidates for cardiac resynchronization therapy and implantation management: an Italian survey promoted by the Italian Association of Arrhythmology and Cardiac Pacing.

BACKGROUND: Cardiac resynchronization therapy (CRT) represents an effective heart failure treatment, associated with reduction in mortality and heart failure hospitalizations. This Italian survey aimed to address relevant CRT issues. METHODS: An online survey was administered to AIAC members. RESULTS: One hundred and five electrophysiologists participated, with a median of 40 (23-70) CRT implantations/year (33% in high-volume centres). Forty-five percent of respondents (especially working in high-volume centres) reported an increase in CRT implantations in the last 2 years, in 16% a decrease, and in 38% CRT remained stable. Seventy-five percent of respondents implanted CRT only in patients with European Heart Rhythm Association (EHRA) class I indications. All operators collected ECG and echocardiography before implantation. Eighty-five percent of respondents selected coronary sinus target vein empirically, whereas 10% used mechanical and/or electrical delay techniques. Physicians working in high-volume centres reported a lower failure rate compared with others (16 vs. 34%; P = 0.03). If the coronary sinus lead could not be positioned in the target branch, 80% placed it in another vein, whereas 16% opted for a surgical approach or for conduction system pacing (CSP). Eighty percent accomplished CRT optimization in all patients, 17% only in nonresponders. Regarding anticoagulation, high agreement with EHRA guidelines emerged. CONCLUSION: CRT represents a valid therapeutic option in heart failure treatment. Nowadays, CRT implantations remain stable and are mainly performed in patients with class I indications. ECG remains the preferred tool for patient selection, whereas imaging is increasingly used to determine the left pacing target area. In most patients, the left ventricular lead can be successfully positioned in the target vein, but in some cases, the result can be unsatisfactory; however, the decision to explore alternative resynchronization approaches is rarely pursued.

MDDBranchNet: A Deep Learning Model for Detecting Major Depressive Disorder Using ECG Signal.

Major depressive disorder (MDD) is a chronic mental illness which affects people's well-being and is often detected at a later stage of depression with a likelihood of suicidal ideation. Early detection of MDD is thus necessary to reduce the impact, however, it requires monitoring vitals in daily living conditions. EEG is generally multi-channel and due to difficulty in signal acquisition, it is unsuitable for home-based monitoring, whereas, wearable sensors can collect single-channel ECG. Classical machine-learning based MDD detection studies commonly use various heart rate variability features. Feature generation, which requires domain knowledge, is often challenging, and requires computation power, often unsuitable for real time processing, MDDBranchNet is a proposed parallel-branch deep learning model for MDD binary classification from a single channel ECG which uses additional ECG-derived signals such as R-R signal and degree distribution time series of horizontal visibility graph. The use of derived branches was able to increase the model's accuracy by around 7%. An optimal 20-second overlapped segmentation of ECG recording was found to be beneficial with a 70% prediction threshold for maximum MDD detection with a minimum false positive rate. The proposed model evaluated MDD prediction from signal excerpts, irrespective of location (first, middle or last one-third of the recording), instead of considering the entire ECG signal with minimal performance variation stressing the idea that MDD phenomena are likely to manifest uniformly throughout the recording.

Pulmonary embolism in patients with chronic coronary syndrome masquerading as acute coronary syndrome: a case report and literature review.

BACKGROUND: Pulmonary embolisms (PEs) exhibit clinical features similar to those of acute coronary syndrome (ACS), including electrocardiographic abnormalities and elevated troponin levels, which frequently lead to misdiagnoses in emergency situations. CASE PRESENTATION: Here, we report a case of PE coinciding with chronic coronary syndrome in which the patient's condition was obscured by symptoms mimicking ACS. A 68-year-old female with syncope presented to the hospital. Upon admission, she was found to have elevated troponin levels and an electrocardiogram showing ST-segment changes across multiple leads, which initially led to a diagnosis of ACS. Emergency coronary arteriography revealed occlusion of the posterior branches of the left ventricle of the right coronary artery, but based on the complexity of the intervention, the occlusion was considered chronic rather than acute. On the 3rd day after admission, the patient experienced recurrent chest tightness and shortness of breath, which was confirmed as acute PE by emergency computed tomography pulmonary angiography. Following standardized anticoagulation treatment, the patient improved and was subsequently discharged. CONCLUSIONS: This case report highlights the importance of recognizing the nonspecific features of PE. Clinicians should be vigilant when identifying other clinical features that are difficult to explain accompanying the expected disease, and it is necessary to carefully identify the causes to prevent missed diagnoses or misdiagnoses.

An Intramyocardial Mass Mimicking ST-Segment Elevation Myocardial Infarct at Presentation.

ST-segment elevation on the electrocardiogram typically indicates acute myocardial infarction but can mimic ST-segment elevation myocardial infarction in various conditions. We present a case of a patient with an intramyocardial mass and anterior ST-segment elevation without significant myocardial biomarker elevation. Multimodality imaging was crucial in revealing cardiac metastasis as the attributable cause.

Electrocardiographic abnormalities and NT-proBNP levels at long-term follow-up of patients with dyspnea after pulmonary embolism.

OBJECTIVES: Electrocardiogram (ECG) and measurement of plasma brain natriuretic peptides (BNP) are established markers of right ventricular dysfunction (RVD) in the setting of acute pulmonary embolism (PE) but their value at long-term follow-up is largely unknown. The purpose of this prospective study was to determine the prevalence of ECG abnormalities, describe levels of N-terminal proBNP (NT-proBNP), and establish their association with dyspnea at long-term follow-up after PE. DESIGN: All Swedish patients diagnosed with acute PE in 2005 (n = 5793) were identified through the Swedish National Patient Registry. Surviving patients in 2007 (n = 3510) were invited to participate. Of these, 2105 subjects responded to a questionnaire about dyspnea and comorbidities. Subjects with dyspnea or risk factors for development of chronic thromboembolic pulmonary hypertension were included in the study in a secondary step, which involved collection of blood samples and ECG registration. RESULTS: Altogether 49.3% had a completely normal ECG. The remaining participants had a variety of abnormalities, 7.2% had atrial fibrillation/flutter (AF). ECG with any sign of RVD was found in 7.2% of subjects. Right bundle branch block was the most common RVD sign with a prevalence of 6.4%. An abnormal ECG was associated with dyspnea. AF was associated with dyspnea, whereas ECG signs of RVD were not. 61.2% of subjects had NT-proBNP levels above clinical cut-off (>125 ng/L). The degree of dyspnea did not associate independently with NT-proBNP levels. CONCLUSIONS: We conclude that the value of ECG and NT-proBNP in long term follow-up after PE lies mostly in differential diagnostics.

Artificial Intelligence-Based Electrocardiographic Biomarker for Outcome Prediction in Patients With Acute Heart Failure: Prospective Cohort Study.

BACKGROUND: Although several biomarkers exist for patients with heart failure (HF), their use in routine clinical practice is often constrained by high costs and limited availability. OBJECTIVE: We examined the utility of an artificial intelligence (AI) algorithm that analyzes printed electrocardiograms (ECGs) for outcome prediction in patients with acute HF. METHODS: We retrospectively analyzed prospectively collected data of patients with acute HF at two tertiary centers in Korea. Baseline ECGs were analyzed using a deep-learning system called Quantitative ECG (QCG), which was trained to detect several urgent clinical conditions, including shock, cardiac arrest, and reduced left ventricular ejection fraction (LVEF). RESULTS: Among the 1254 patients enrolled, in-hospital cardiac death occurred in 53 (4.2%) patients, and the QCG score for critical events (QCG-Critical) was significantly higher in these patients than in survivors (mean 0.57, SD 0.23 vs mean 0.29, SD 0.20; P<.001). The QCG-Critical score was an independent predictor of in-hospital cardiac death after adjustment for age, sex, comorbidities, HF etiology/type, atrial fibrillation, and QRS widening (adjusted odds ratio [OR] 1.68, 95% CI 1.47-1.92 per 0.1 increase; P<.001), and remained a significant predictor after additional adjustments for echocardiographic LVEF and N-terminal prohormone of brain natriuretic peptide level (adjusted OR 1.59, 95% CI 1.36-1.87 per 0.1 increase; P<.001). During long-term follow-up, patients with higher QCG-Critical scores (>0.5) had higher mortality rates than those with low QCG-Critical scores (<0.25) (adjusted hazard ratio 2.69, 95% CI 2.14-3.38; P<.001). CONCLUSIONS: Predicting outcomes in patients with acute HF using the QCG-Critical score is feasible, indicating that this AI-based ECG score may be a novel biomarker for these patients. TRIAL REGISTRATION: ClinicalTrials.gov NCT01389843; https://clinicaltrials.gov/study/NCT01389843.

Screening Sportsmen and Sportswomen Over Age 35: The Relevance of an Exercise Electrocardiogram. Data From the SEEPRED Study.

INTRODUCTION: The importance of exercise electrocardiogram (ECG) is still controversial in the prevention of cardiovascular events among sportsmen and sportswomen. The aim of this study was to assess the relevance of exercise ECG as a screening tool to prevent cardiovascular events when any cardiovascular disease (CVD) risk factors are present. METHODS: The study included leisure time asymptomatic sportsmen and sportswomen over age 35 evaluated from 2011 to 2016 at the University Hospital of Saint-Etienne (France). Major adverse cardiovascular events (MACE) and atrial fibrillation were collected at 3 years. RESULTS: Of the cohort of 2457 sportsmen and sportswomen (mean age 50.2 ± 9.4 years), 50 (2%) had a high-risk SCORE2. A total of 256 exercise ECGs (10%) were defined as positive, most of them due to silent myocardial ischemia (SMI) (n = 196; 8%). These 196 SMI cases led to 33 coronary angiograms (1%), which revealed 23 significant coronary stenoses requiring revascularization. In multivariate logistic regression analysis, having at least two CVD risk factors was independently associated with (1) positive exercise ECG (OR = 1.80 [95% CI: 1.29-2.52], p = 0.0006), with (2) suspected SMI (OR = 2.57 [95% CI: 1.10-6.02], p = 0.0304), with (3) confirmed SMI (OR = 8.20 [95% CI: 3.46-19.46], p < 0.0001) and with (4) cardiovascular events (MACE or atrial fibrillation) (OR = 6.95 [95% CI: 3.49-13.81], p < 0.0001) at 3 years (median). CONCLUSIONS: The study supports the European recommendations for the use of exercise ECG in evaluation of asymptomatic leisure time sportsmen over age 35. Having at least two CVD risk factors was the best predictor for presence of coronary artery stenosis that may increase the risk for adverse events. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT06024863.

Alpha tACS on Parieto-Occipital Cortex Mitigates Motion Sickness Based on Multiple Physiological Observation.

Approximately one third of the population is prone to motion sickness (MS), which is associated with the dysfunction in the integration of sensory inputs. Transcranial alternating current stimulation (tACS) has been widely used to modulate neurological functions by affecting neural oscillation. However, it has not been applied in the treatment of motion sickness. This study aims to investigate changes in brain oscillations during exposure to MS stimuli and to further explore the potential impact of tACS with the corresponding frequency and site on MS symptoms. A total of 19 subjects were recruited to be exposed to Coriolis stimuli to complete an inducing session. After that, they were randomly assigned to tACS stimulation group or sham stimulation group to complete a stimulation session. Electroencephalography (EEG), electrocardiogram, and galvanic skin response were recorded during the experiment. All the subjects suffering from obvious MS symptoms after inducing session were observed that alpha power of four channels of parieto-occipital lobe significantly decreased (P7: t =3.589, p <0.001; P8: t =2.667, p <0.05; O1: t =3.556, p <0.001; O2: t =2.667, p <0.05). Based on this, tACS group received the tACS stimulation at 10Hz from Oz to CPz. Compared to sham group, tACS stimulation significantly improved behavioral performance and entrained the alpha oscillation in individuals whose alpha power decrease during the inducing session. The findings show that parieto-occipital alpha oscillation plays a critical role in the integration of sensory inputs, and alpha tACS on parieto-occipital can become a potential method to mitigate MS symptoms.

Impact of baseline ECG characteristics on changes in cardiac biomarkers and echocardiographic metrices after acute myocardial infarction treated with Empagliflozin.

The EMMY trial was a multicentre, investigator-initiated, placebo-controlled, double-blind trial, which enrolled 476 patients immediately following AMI and the first study demonstrating a significant reduction in NT-proBNP-levels as well as significant improvements in cardiac structure and function in patients after acute myocardial infarction treated with empagliflozin vs. placebo. However, hardly any data are available investigating the prognostic role of baseline electrocardiogram metrics in SGLT2-inhibitor-treated patients. This post-hoc analysis investigated the association of baseline ECG metrics collected in one centre of the trial (181 patients) with changes in structural and functional cardiac parameters as well as cardiac biomarkers in response to Empagliflozin treatment. A total of 181 patients (146 men; mean age 58 ± 14 years) were included. Median PQ-interval was 156 (IQR 144-174) milliseconds (ms), QRS width 92 (84-98) ms, QTc interval 453 (428-478) ms, Q-wave duration 45 (40-60) ms, Q-wave amplitude 0.40 (0.30-0.70) millivolt (mV), and heart rate was 71 (64-85) bpm. For functional cardiac parameters (LVEF and E/e') of the entire cohort, a greater decrease of E/e' from baseline to week 26 was observed in shorter QRS width (P = 0.005).Structural cardiac endpoints were only found to have a significant positive correlation between LVEDD and Q wave duration (P = 0.037). Higher heart rate was significantly correlated with better response in LVEF (P = 0.001), E/e' (P = 0.021), and NT-proBNP (P = 0.005). Empagliflozin-treatment showed no interaction with the results. Baseline ECG characteristics post AMI are neither predictive for beneficial NTproBNP effects of Empagliflozin post AMI, nor for functional or structural changes within 26 weeks post AMI.

Certain investigation on hybrid neural network method for classification of ECG signal with the suitable a FIR filter.

The Electrocardiogram (ECG) records are crucial for predicting heart diseases and evaluating patient's health conditions. ECG signals provide essential peak values that reflect reliable health information. Analyzing ECG signals is a fundamental technique for computerized prediction with advancements in Very Large-Scale Integration (VLSI) technology and significantly impacts in biomedical signal processing. VLSI advancements focus on high-speed circuit functionality while minimizing power consumption and area occupancy. In ECG signal denoising, digital filters like Infinite Impulse Response (IIR) and Finite Impulse Response (FIR) are commonly used. The FIR filters are preferred for their higher-order performance and stability over IIR filters, especially in real-time applications. The Modified FIR (MFIR) blocks were reconstructed using the optimized adder-multiplier block for better noise reduction performance. The MIT-BIT database is used as reference where the noises are filtered by the MFIR based on Optimized Kogge Stone Adder (OKSA). Features are extracted and analyzed using Discrete wavelet transform (DWT) and Cross Correlation (CC). At this modern era, Hybrid methods of Machine Learning (HMLM) methods are preferred because of their combined performance which is better than non-fused methods. The accuracy of the Hybrid Neural Network (HNN) model reached 92.3%, surpassing other models such as Generalized Sequential Neural Networks (GSNN), Artificial Neural Networks (ANN), Support Vector Machine with linear kernel (SVM linear), and Support Vector Machine with Radial Basis Function kernel (SVM RBF) by margins of 3.3%, 5.3%, 23.3%, and 24.3%, respectively. While the precision of the HNN is 91.1%, it was slightly lower than GSNN and ANN but higher than both SVM linear and SVM -RBF. The HNN with various features are incorporated to improve the ECG classification. The accuracy of the HNN is switched to 95.99% when the DWT and CC are combined. Also, it improvises other parameters such as precision 93.88%, recall is 0.94, F1 score is 0.88, Kappa is 0.89, kurtosis is 1.54, skewness is 1.52 and error rate 0.076. These parameters are higher than recently developed models whose algorithms and methods accuracy is more than 90%.

Prolonged ventricular repolarization associated with mild cognitive impairment and white matter hyperintensities: a cross-sectional study.

Prolonged ventricular repolarization has been associated with cardiovascular disease. We sought to investigate the association of prolonged ventricular repolarization with mild cognitive impairment (MCI) and the potential underlying neuropathological mechanisms in older adults. This cross-sectional study included 4328 dementia-free participants (age ≥ 65 years; 56.8% female) in the baseline examination of the Multidomain INterventions to delay dementia and Disability in rural China; of these, 989 undertook structural brain magnetic resonance imaging (MRI) scans. QT, QTc, JT, JTc, and QRS intervals were derived from 12-lead electrocardiograph. MCI, amnestic MCI (aMCI), and non-amnestic MCI (naMCI) were defined following the Petersen's criteria. Volumes of gray matter (GM), white matter, cerebrospinal fluid, total white matter hyperintensities (WMH), periventricular WMH (PWMH), and deep WMH (DWMH) were automatically estimated. Data were analyzed using logistic and general linear regression models. Prolonged QT, QTc, JT, and JTc intervals were significantly associated with an increased likelihood of MCI and aMCI, but not naMCI (p < 0.05). In the MRI subsample, QT, QTc, JT, and JTc intervals were significantly associated with larger total WMH and PWMH volumes (p < 0.05), but not with DWMH volume. Statistical interactions were detected, such that prolonged QT and JT intervals were significantly associated with reduced GM volume only among participants with coronary heart disease or without APOE ε4 allele (p < 0.05). Prolonged ventricular repolarization is associated with MCI and cerebral microvascular lesions in a general population of older adults. This underlies the importance of cognitive assessments and brain MRI examination among older adults with prolonged QT interval.

Pharmacotherapy and cardiovascular challenges: a case report of olverembatinib-induced myocardial infarction with non-obstructive coronary arteries.

The anticancer drug of tyrosine kinase-inhibitors (TKIs) has significantly improved the prognosis of patients with specific leukemia but has also increased the risk of organ adverse reactions. Herein, we present a case of a patient diagnosed with myeloproliferative neoplasms who experienced recurrent chest pain after receiving treatment with Olverembatinib. Electrocardiography and coronary angiography confirmed the diagnosis of myocardial infarction with non-obstructive coronary arteries. This case serves as a reminder for clinicians to pay more attention and actively prevent the cardiac adverse reactions of TKIs when using such medications.

Combined Stellate Ganglion Blockade and Epidural Thoracic Anesthesia for the Management of Ventricular Storm: A Case Report.

ABSTRACT: The term "ventricular storm (VS)" is defined as the occurrence of two or more separate episodes of ventricular tachycardia or fibrillation (VT/VF) or three or more appropriate discharges of an implantable cardioverter defibrillator for VT/VF during a 24-h period. A patient in his early 40s was observed in the emergency department of our hospital and was admitted to the cardiac intensive care unit due to multiple episodes of VT. This led to the need for deep sedation with orotracheal intubation and mechanical ventilation. Intravenous lidocaine treatment was started; however, the patient had a recurrence of the episodes of VT. We decided to combine stellate ganglion block with epidural thoracic anesthesia. After the sympathetic block, there was no recurrence of the arrhythmic episodes. The patient was then transferred for ablation treatment. We demonstrated the efficacy of both techniques in managing a patient with multiple episodes of ventricular storm.

A novel approach to terminate roof-dependent atrial flutter with epicardial conduction through septopulmonary bundle.

Atrial flutter, a prevalent cardiac arrhythmia, is primarily characterized by reentrant circuits in the right atrium. However, atypical forms of atrial flutter present distinct challenges in terms of diagnosis and treatment. In this study, we examine three noteworthy clinical cases of atypical atrial flutter, which offer compelling evidence indicating the implication of the lesser-known Septopulmonary Bundle (SPB). This inference is based on the identification of distinct electrocardiographic patterns observed in these patients and their favorable response to catheter ablation, which is a standard treatment for atrial flutter. Remarkably, in each case, targeted ablation at the anterior portion of the left atrial roof effectively terminated the arrhythmia, thus providing further support for the hypothesis of SPB involvement. These insightful observations shed light on the potential significance of the SPB in the etiology of atypical atrial flutter and introduce a promising therapeutic target. We anticipate that this paper will stimulate further exploration into the role of the SPB in atrial flutter and pave the way for the development of targeted ablation strategies.

Exploratory analysis of predictors of ventricular aneurysm in a cohort of 291 patients with acute myocardial infarction.

OBJECTIVE: In this study, we explored the determinants of ventricular aneurysm development following acute myocardial infarction (AMI), thereby prompting timely interventions to enhance patient prognosis. METHODS: In this retrospective cohort analysis, we evaluated 297 AMI patients admitted to the First People's Hospital of Changzhou. The study was structured as follows. Comprehensive baseline data collection included hematological evaluations, ECG, echocardiography, and coronary angiography upon admission. Within 3 months post-AMI, cardiac ultrasounds were administered to detect ventricular aneurysm development. Univariate and multivariate logistic regression analysis were employed to pinpoint the determinants of ventricular aneurysm formation. Subsequently, a predictive model was formulated for ventricular aneurysm post-AMI. Moreover, the diagnostic efficacy of this model was appraised using the ROC curves. RESULTS: In our analysis of 291 AMI patients, spanning an age range of 32-91 years, 247 were male (84.9%). At the conclusion of a 3-month observational period, the cohort bifurcated into two subsets: 278 patients without ventricular aneurysm and 13 with evident ventricular aneurysm. Distinguishing features of the ventricular aneurysm subgroup were markedly higher values for age, B-type natriuretic peptide(BNP), Left atrium(LA), Left ventricular end-diastolic dimension (LEVDD), left ventricular end systolic diameter (LVEWD), E-wave velocity (E), Left atrial volume (LAV), E/A ratio (E/A), E/e ratio (E/e), ECG with elevated adjacent four leads(4 ST-Elevation), and anterior wall myocardial infarction(AWMI) compared to their counterparts (p < 0.05). Among the singular predictive factors, total cholesterol (TC) emerged as the most significant predictor for ventricular aneurysm development, exhibiting an AUC of 0.704. However, upon crafting a multifactorial model that incorporated gender, TC, an elevated ST-segment in adjacent four leads, and anterior wall infarction, its diagnostic capability: notably surpassed that of the standalone TC, yielding an AUC of 0.883 (z = -9.405, p = 0.000) as opposed to 0.704. Multivariate predictive model included gender, total cholesterol, ST elevation in 4 adjacent leads, anterior myocardial infarction, the multivariate predictive model showed better diagnostic efficacy than single factor index TC (AUC: 0. 883 vs. 0.704,z =-9.405, p = 0.000), it also improved predictive power for correctly reclassifying ventricular aneurysm occurrence in patients with AMI, NRI = 28.42% (95% CI: 6.29-50.55%; p = 0.012). Decision curve analysis showed that the use of combination model had a positive net benefit. CONCLUSION: Lipid combined with ECG model after myocardial infarction could be used to predict the formation of ventricular aneurysm and aimed to optimize and adjust treatment strategies.