View clinical trials related to Death, Sudden, Cardiac.
Filter by:Ventricular tachycardia (VT) is a leading cause of death and suffering in the Veteran population. Currently, ablation procedures are performed to destroy the diseased tissue that causes this problem. This study will test to see if a new non-invasive targeting tool can help guide doctors during the procedure and improve the outcomes of the ablation procedure. Once this study is completed, the investigators will know whether this tool could help increase the efficacy, safety and accuracy of ablation therapy of fatal heart rhythms.
Aim This was a population-based retrospective cohort study of OHCA. This study intends to retrospectively analyze the data of pre-hospital emergency system in Guangzhou for 10 years, explore the incidence trend of OHCA in Guangzhou for 10 years; Through further analysis, we try to explore the time distribution characteristics of OHCA in order to understand the epidemiological characteristics and rules of OHCA in super large cities in southern China. Methods The pre-hospital traffic data in the main urban area of Guangzhou Emergency Medical Command Center database from 2011 to 2020 were collected. The cases diagnosed as "cardiac arrest" and "sudden death" were screened, and the cases with non-cardiac causes in the diagnosis were deleted. The crude incidence rate and age-standardized incidence rate of OHCA were calculated. Joinpoint software was used to calculate the changing nodes in the OHCA incidence trend, and the AnnualPercent Change (APC) and Average AnnualPercent Change (Average AnnualPercent Change, APC) of OHCA incidence were calculated. AAPC). The OHCA data were grouped according to the six main urban areas, and the crude incidence rate, ASIR and changing trend of the six main urban areas were calculated. The data of OHCA were grouped by age, and the crude incidence rate, ASIR and changing trend of each age group were calculated. The data information was divided into groups according to 24 hours a day, 7 days a week, and four seasons. The number of OHCA cases in different time periods was statistically described. The data were imported into SPSS 26.0 for analysis, and Mann-Kendall test was used to evaluate the statistical significance of the time trend. Time rhythm variability was tested for mean distribution using chi-square goodness of fit test.
Some of the patients affected by Out-of-hospital cardiac arrest (OHCA) with ventricular fibrillation (VF)/ventricular tachycardia (VT) do not respond to initial defibrillation. The survival decreases with number of defibrillations required to terminate VF/VT. In 2022, one prospective cluster randomized trial showed increased survival among (OHCA) patients in refractory VF using Double Sequential Defibrillation (DSD). To evaluate feasibility and safety this randomized pilot trial will compare the effect of double defibrillation strategy initiated as soon as possible after the first defibrillation with continued resuscitation using standard defibrillation, in patients with Out of Hospital Cardiac arrest (OHCA). The results from this pilot trial will form the basis for design of a larger multicenter survival study.
The goal of this observational study is to identify potential indicators for pre-warning of sudden cardiac death (SCD), including clinical biochemistry markers, electrocardiogram, echocardiography, MRI and CT imaging values, genetic markers and so on, and further construct a series of multi-parameter assessments of SCD early screening.
Sudden cardiac death (SCD) is the final result of cardiac arrest (CA) , defined as an abrupt and unexpected loss of cardiovascular function resulting in circulatory collapse and death. Up to 50% of cardiac deaths in Europe are due to CA. The estimated mortality of CA is approximately 90%, and significant functional and/or cognitive disabilities often persist among those who survive. The advent of the implantable cardioverter-defibrillator (ICD) has revolutionized the prevention of SCD in high-risk patients with reduced left ventricular ejection fraction (LVEF<35%). However, the algorithm recommended by current guidelines based on LVEF, considered the only parameter to identify high-risk patients, cannot stratify the population and the spectrum of risk with high accuracy. Although the risk of CA is higher among patients with LVEF<35% and NYHA class>1, because of the enormity of the population size at risk (i.e., with organic heart disease and LVEF>35%), most SCD does occur in patients with LVEF>35%. Additionally, the majority of pts who receive the ICD for primary prevention of SCD will not benefit from the device (in the Sudden Cardiac Death in Heart Failure Trial published in 2005, the rate of appropriate ICD therapy was 21% at five years), and/or will experience some side effects of it. In the Israeli registry of patients who underwent ICD (n= 1729) or cardiac resynchronization therapy (n= 1326), the 12-year cumulative incidence of adverse events was 20% for inappropriate shock, 6% for device-related infection, and 17% for lead failure. Moreover, recent improvements in drug treatment for HF and myocardial revascularization have further reduced the incidence of SCD in pts with low LVEF. Finally, pts with advanced HF are unlikely to benefit from ICD therapy because of the high rates of non-arrhythmic deaths. Therefore, improved risk stratification approaches to guide the selection of pts for ICD implantation are needed, and only a multiparametric approach may aim to personalize the risk prediction of SCD across the broad spectrum of the phenotypes of HF patients. The RESPECT project has been designed to personalize the risk of SCD by integrating and interpreting information highly multidisciplinary: clinical and bio-humoral, genetics and electrocardiography, conventional and advanced cardiac imaging, and data science. The investigators hypothesized that machine learning models capable of dealing with non-linearities and complex interactions among predictors, including genetic, clinical, electrocardiographic, bio-humoral, echocardiographic, cardiac magnetic resonance (CMR), and nuclear cardiology data, would have superior accuracy in predicting the occurrence of SCD compared with the currently recommended metrics of NYHA class and LVEF by two-dimensional echocardiography and that the personalized risk prediction of SCD will translate in more cost-effective use of ICDs. In addition, the investigators will use the multiparametric predictive models to develop a cloud-computing app that will allow clinicians to predict the risk of occurrence of SCD based on specific covariate profiles of individual patients.
The Multitude is a registry of patients who receive commercially available CIEDs that remotely communicate through the LATITUDE monitoring system and transfer data to a central database. The registry is designed to constitute a shared environment for the collection, management, analysis and reporting of clinical and diagnostic data, adopted by a network of European scientifically-motivated physicians who use rhythm management diagnostic and therapeutic solutions from Boston Scientific in their clinical practice. The Multitude study will facilitate the sharing of scientific proposals within a large network of researchers, and it will allow researchers to record the experience with medical devices throughout the device and patient lifecycle.
Implantable cardioverter-defibrillators (ICD) are currently recommended for the primary prevention of sudden cardiac death (SCD) in patients with a remote (>6 weeks) myocardial infarction (MI) and a low (≤35%) left ventricular ejection fraction (LVEF). Ventricular tachycardia (VT) and/or ventricular fibrillation (VF), which are responsible for most SCDs, result from the presence of surviving myocytes embedded within fibrotic MI-scar. The presence of these surviving myocytes, as well as their specific arrhythmic characteristics, is not captured by LVEF. Hence, the use of LVEF as a unique risk-stratifier of SCD results in a low proportion (17 to 31%) of appropriate ICD device therapy at 2 years. Consequently, most patients with a prophylactic ICD do not present VT/VF requiring ICD therapy prior to their first-ICD battery depletion. Thus, many patients are exposed to ICD complications, such as inappropriate shocks, without deriving any health benefit. Therefore, the current implantation strategy of prophylactic ICDs, based on LVEF only, needs to be improved in post-MI patients.
The overall goal of this project is to design, develop, and pilot test an emergency healthcare drone delivery system suitable for rural communities that can deliver AEDs to out-of-hospital cardiac arrest (OHCA) locations more rapidly than can be achieved with current first responder and EMS systems. The goal is to determine whether this method of AED delivery can be achieved rapidly enough to justify a future clinical trial directly testing its ability to improve OHCA survival.
Anomalous aortic origin of a coronary artery (AAOCA) is a group of rare congenital heart defects with various clinical presentations. The lifetime-risk of an individual living with AAOCA is unknown, and data from multicentre registries are urgently needed to adapt current recommendations and guide optimal patient management. The European Registry for AAOCA (EURO-AAOCA) aims to assess differences with regard to AAOCA management between centres.
WILLEM is a multi-center, prospective and retrospective cohort study. The study will assess the performance of a cloud-based and AI-powered ECG analysis platform, named Willem™, developed to detect arrhythmias and other abnormal cardiac patterns. The main questions it aims to answer are: 1. A new AI-powered ECG analysis platform can automatice the classification and prediction of cardiac arrhythmic episodes at a cardiologist level. 2. This AI-powered ECG analysis can delay or even avoid harmful therapies and severe cardiac adverse events such as sudden death. The prerequisites for inclusion of patients will be the availability of at least one ECG record in raw data, along with patient clinical data and evolution data after more than 1-year follow-up. Cardiac electrical signals from multiple medical devices will be collected by cardiology experts after obtaining the informed consent. Every cardiac electrical signal from every subject will be reviewed by a board-certified cardiologist to label the arrhythmias and patterns recorded in those tracings. In order to obtain tracings of relevant information, >95% of the subjects enrolled will have rhythm disorders or abnormal ECG's patterns at the time of enrollment.