Active clinical trials for "Death, Sudden, Cardiac"

Single-channel electrocardiograms (lead I of 12-lead surface ECG; 30 seconds) will be collected from subjects/patients at 11 clinical centers in Germany to train an Artificial Intelligence in the automatic diagnosis of regular and irregular heart rhythms. Heart rhythms of interest are normal sinus rhythm (SR), atrial fibrillation (AF), atrial premature beats (APBs), ventricular premature beats (VPBs), and nonsustained ventricular tachycardia (VT). Per diagnosis, 20,000 ECGs are required, for a total of 100,000 ECGs to be obtained from approximately 10,000 subjects/patients.

Sudden cardiac death is a tragic event that strikes all age groups and is unfortunately increasing in prevalence. Because it is difficult to predict those at highest risk, this study is designed to test the hypothesis that new imaging techniques (magnetic resonance imaging [MRI] and computed tomography [CT]) are useful for identifying factors which put people at high risk for sudden death.

Cardiac arrest causes the heart to stop functioning to maintain circulation that provides oxygen to the brain. The global incidence of cardiac arrest is 50 to 60 per 100,000 people per year. The incidence of cardiac arrest in Indonesia in 2016 was 350,000 cases, in which 12% were successfully resuscitated, compared to the global success rate of 24.8%. Cardiac arrest events urgently require CPR action that is useful to save lives in an emergency. The application of Code Blue aims to reduce the mortality rate and increase the rate of return of spontaneous circulation. The Code Blue team itself includes a set of teams who are trained in the handling of cardiorespiratory arrest.

There is some limited evidence that reduced size of electrical complexes/traces of the heart on the electrocardiogram (ECG) may be associated with scarring in the heart muscle, which may predispose to serious life-threatening electrical abnormalities and sudden cardiac death (SCD). There is no current guidance on how young individuals and athletes with reduced ECG traces should be managed. Therefore, correct interpretation of this ECG finding is crucial for identifying athletes with disease and at risk of SCD. Some athletes experience SCD despite normal standard cardiac tests. The investigators, therefore, propose to study young healthy individuals and young athletes using cardiovascular MRI, cardiopulmonary exercise testing, 24 hour ECG monitoring and genetic analysis to determine the significance of reduced ECG traces and possibly revise current international sports recommendations.

The CMR/CT WG of the Italian pediatric cardiology society set up a multi-center observational clinical database of repaired-TOF evaluated. This registry will enroll prospectively patients evaluated by CMR for clinical indication in most of the CHD Italian centers. Data collection will include surgical history, clinical data, imaging data, and also adverse cardiac events for a period of 6 years.

Fibrotic tissue is known to be the substrate for the appearance of scar-related reentrant ventricular arrhythmias (VA) in chronic ischemic cardiomyopathy (ICM). Late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) has proven to be a useful technique in the non-invasive characterization of the scarred tissue and the underlying arrhythmogenic substrate. Previous studies identified the presence of significant scarring (> 5% of the left ventricular -LV- mass) is an independent predictor of adverse outcome (all-cause mortality or appropriate ICD discharge for ventricular tachycardia or fibrillation) in patients being considered for implantable cardioverter-defibrillator (ICD) placement. Parallelly, the presence of heterogeneous tissue channels, which correlate with voltage channels after endocardial voltage mapping of the scar, can be more frequently observed in patients suffering from sustained monomorphic ventricular tachycardias (SMVT) than in matched controls for age, sex, infarct location, and left ventricular ejection fraction (LVEF). However, the lack of solid evidence and randomized trials make LVEF still the main decision parameter when assessing suitability for ICD implantation in primary prevention of sudden cardiac death (SCD). In a recent, case-control study, we identified the border zone channel (BZC) mass as the only independent predictor for VT occurrence, after matching for age, sex, LVEF and total scar mass. This BZC mass can be automatically calculated using a commercially available, post-processing imaging platform named ADAS 3D LV (ADAS3D Medical, Barcelona, Spain), with FDA 510(k) Clearance and European Community Mark approval. Thus, CMR-derived BZC mass might be used as an automatically reproducible criterium to reclassify those patients with chronic ICM at highest risk for developing VA/SCD in a relatively short period of approx. 2 years. In the present cohort study, we sought to evaluate the usefulness of the BZC mass measurement to predict the occurrence of VT events in a prospective, multicenter, unselected series of consecutive chronic ischemic patients without previous arrhythmia evidence, irrespectively of their LVEF.

Active surveillance study using real-world data collected in the ASSURE Patient Registry. Outcome measures are based on analysis of ASSURE Registry data including data recorded by the WCD then annotated by clinical experts in electrophysiology.

Sudden cardiac death (SCD) poses a significant health care challenge with high annual incidence and low survival rates. Implantable cardioverter defibrillators (ICDs) prevent SCD in patients with poor heart function. However, the critical survival benefit afforded by the devices is accompanied by short and long-term complications and a high economic burden. Moreover, in using current practice guidelines of reduced heart function, specifically left ventricular ejection fraction (LVEF)≤35%, as the main determining factor for patient selection, only a minority of patients actually benefit from ICD therapy (<25% in 5 years). There is an essential need for more robust diagnostic approaches to SCD risk stratification. This project examines the hypothesis that structural abnormalities of the heart itself, above and beyond global LV dysfunction, are important predictors of SCD risk since they indicate the presence of the abnormal tissue substrate required for the abnormal electrical circuits and heart rhythms that actually lead to SCD. Information about the heart's structure will be obtained from cardiac magnetic resonance imaging and used in combination with a number of other clinical risk factors to see if certain characteristics can better predict patients at risk for SCD.

Patients with diabetes have an increased risk of sudden cardiac death compared to the general population. Severe hypoglycemia is associated with an increased risk of cardiovascular (CV) disease (CVD) and events, including cardiac arrhythmias and sudden cardiac death; likewise, increased glycemic variability is associated with macrovascular complications and increased mortality. The physiological mechanisms linking hypoglycemia and glycemic variability to CVD and CV events remain unclear. Myocardial work and mechanical dyssynchrony will be measured by speckle tracking echocardiography during euglycemia, hypoglycemia and hyperglycemia in individuals with type 1 diabetes, type 2 diabetes, and without diabetes. Echocardiographic images from three experimental clamp studies - Hypo-Heart 1 (sub-study 1), Hypo-Heart 2 (sub-study 2) and Rapid-Heart - will be included in this study.

The Medtronic InSync III Marquis Cardiac Resynchronization Therapy Defibrillator (CRT-D)-System (implantable cardioverter-defibrillator with biventricular stimulation for cardiac resynchronization) is equipped with the "Conducted-Atrial Fibrillation (AF)-Response-Algorithm (CAFR)". This algorithm is designed to maximize biventricular stimulation and thus the amount of cardiac resynchronization when atrial fibrillation occurs. The goal of the study is the evaluation of the effect of the CAFR in CRT-patients suffering from atrial fibrillation by quantification of the increase of biventricular pacing during atrial fibrillation caused by CAFR as well as the influence of the CAFR on the ventricular heart rate.