View clinical trials related to Structural Heart Abnormality.
Filter by:The HEART-AI (Harnessing ECG Artificial Intelligence for Rapid Treatment and Accurate Interpretation) is an open-label, single-center, randomized controlled trial, that aims to deploy a platform called DeepECG at point-of-care for AI-analysis of 12-lead ECGs. The platform will be tested among healthcare professionals (medical students, residents, doctors, nurse practitioners) who read 12-lead ECGs. In the intervention group, the platform will display the ECHONeXT structural heart disease (SHD) scores in randomized patients to help doctors prioritize TTEs (Supplemental Table 2, Figure 1). Also, this platform will display the DeepECG-AI interpretation which detects problems such as ischemic conditions, arrhythmias or chamber enlargements and acts an improved alternative to commercially available ECG interpretation systems such as MUSE (Supplemental Table 1). The performance for both of these models is presented in supplemental appendix (Supplemental Table 1, Supplemental Table 2, Supplemental Figure 1). Our primary objective is to assess the impact of displaying the ECHONeXT interpretation on 12-lead ECGs, specifically focusing on the detection rates of Structural Heart Disease (SHD) on TTE among newly referred patients at MHI and on the delay between the time of the first ECG opened in the platform and the TTE evaluation among newly referred patients at MHI at high or intermediate risk of SHD, by comparing patients in the intervention (ECHONeXT prediction of SHD displayed and recommendation on the priority to assign to the TTE) arm and patients in the control (ECHONeXT prediction and recommendation hidden) arm. The main secondary objective is to evaluate the proportion of ECGs where the users agree with the DeepECG diagnosis, across all ECGs accessed by the user of the platform. By integrating an AI-analysis platform at the point of care and evaluating its impact on ECG interpretation accuracy and prioritization of incremental tests, the HEART-AI study aims to provide valuable insights into the potential of AI in improving cardiac care and patient outcomes.
The purpose of this prospective cohort study is to determine the parameters of cardiac magnetic imaging to identify structural heart disease using use transthoracic echocardiography or cardiac magnetic resonance as reference standard.
The goal of this registry-based observational study is to establish a comprehensive management plan, which focus on medical therapy, cardiac rehabilitation and active post-market surveillance of medical devices, in patients with cardiovascular diseases (CVD). Patients with CVD mainly refers to four groups of patients：1) post-percutaneous coronary intervention (post-PCI) patients; 2) patients with heart failure (HF); 3) patients with cardiometabolic diseases (CMD); 4) patients with structural heart disease (SHD), and the detailed definition of each group can be found in "Eligibility" section. The main questions this study aims to answer are: - the effectiveness of exercise-based cardiac rehabilitation in improving cardiac function, reducing CVD recurrence and mortality, and promoting quality of life for patients with CVD; - the feasibility of registry-based active post-market surveillance of high-risk medical devices used in cardiovascular surgeries, such as PCI, heart valve replacement, and cardiac resynchronization therapy (CRT); - the utilization of multiomics datasets to identify and dissect cardiovascular heterogeneity in both healthy and diseased populations and to guide precision medicine in patients with CVD; - the analysis and evaluation of the prescription patterns and drug response in patients with CVD.
Ventricular tachycardia (VT) is an abnormal rhythm arising from the bottom chambers (ventricles) of the heart. The hearts of most patients who develop VT have been previously damaged by a myocardial infarction (heart attack) or other heart muscle diseases (cardiomyopathies). The damage produces scar or fatty deposits that conduct electrical impulses slowly allowing VT to occur. Recurrent episodes of VT can compromise heart function and increase mortality. VT is prevented by special drugs but these are not always effective and can have many side effects. Most patients with VT will also have a specialised device called an implantable defibrillator (ICD) implanted. The ICD treats VT by either stimulating the heart rapidly or delivering a shock to it. ICDs are very effective but the shocks are painful and have a big impact on quality of life. If VT occurs despite optimal drug treatment, patients undergo an invasive procedure called catheter ablation. Here, wires are passed into the heart from the blood vessels in the leg and the damaged heart muscle causing the VT is identified whilst the heart is in VT. An electrical current is passed down the wire making its tip heat up allowing discrete burns (ablation) to be placed inside the heart. The ablated heart muscle doesn't conduct electricity which stops the VT and prevents it recurring. Some patients are so frail that ablation cannot be performed safely. A recent clinical trial has shown that VT can be treated in such patients using radiotherapy, which is usually used to treat tumours with high energy radiation. This approach is non-invasive, painless and requires no sedation or anaesthesia. This study will test whether VT can be successfully treated using stereotactic ablative radiotherapy. This can deliver high dose radiotherapy very precisely, whilst minimising the risk of damage to healthy tissues.
Cardiovascular diseases represent the most common cause of death worldwide. Percutaneous approaches with intravascular catheters are pivotal, since they allow to treat patients with high perioperative risks. However, catheter-based treatments require steep learning curves and are characterized by poor ergonomics and exposure to damaging radiation. ARTERY will offer a radiation-free approach based on shared-autonomy robotic catheters, with increased user engagement and easy interaction. Intraprocedural three-dimensional echocardiography as well as computed tomography images obtained during usual clinical practice will provide artificial intelligence algorithms that will turn catheter navigation to a simple task. Optical and electromagnetic sensing techniques will ensure a superior view upon the cardiovascular anatomy and will guide the autonomous catheter upon the interventionist supervision, who will be able to take over control at any instant.
The SALMANTICOR study will obtain data on the prevalence and incidence of structural heart disease in a population setting. A cross-section survey of randomly selected residents of Salamanca (Spain) will be performed. A total of approximately 2400 individuals, stratifies by place of residence (rural and urban) and by age and sex will be studied. The variables to analyzed will be obtained from the clinical history, different surveys including social status, Mediterranean diet, functional capacity, electrocardiogram, echocardiogram and biochemical and genetic analysis. Surviving participants are expected to return for a 5 and 10-year follow-up visit.