View clinical trials related to Aortic Valve Stenosis.
Filter by:The goal of this study is to increase shared decision making for patients considering treatment for severe aortic stenosis. The main questions it aims to answer are: - Do patient decision aids and clinician skills training course improve the quality of decisions, and do they work well for different patient populations? - Are heart clinics able to reach the majority of patients with decision aids before their specialist visit and do the majority of clinicians complete the training course? All participating sites will start in the usual care group and then will be randomly assigned a time to switch to the intervention group. Participants will complete surveys before and after their specialist visit. Researchers will compare data from patients seen during usual care with data from those seen after the interventions are implemented to see if there are improvements in the quality of decisions.
Background: Artificial Intelligence (AI) in cardiac imaging has previously been shown to provide highly reproducible and accurate results, outperforming clinical experts. Cardiac magnetic resonance (CMR) imaging represents the gold standard for assessment of myocardial structure and function. However, measurements of more sensitive markers of early left (LV) and right ventricular (RV) function, such as global longitudinal shortening (GLS), mitral annular plane systolic excursion (MAPSE), and tricuspid annular plane systolic excursion (TAPSE), are frequently not performed due to the lack of automated analysis. Objectives: The investigators aim to evaluate whether AI-based measurements of ventricular structure and function convey important prognostic information in patients with severe aortic stenosis (AS) beyond LV and RV ejection fraction (EF) and represent early markers of adverse cardiac remodeling. Materials & Methods: This large-scale international, multi-center, observational study will recruit ~1500 patients with severe AS scheduled for aortic valve replacement (AVR). Patients are invited to undergo CMR imaging prior to AVR and at 12-months post-AVR. An AI-based algorithm, developed in the UK, will be used for fully automated assessment of parameters of cardiac structure (end-diastolic volume, end-systolic volume, LV mass, maximum wall thickness) and function (EF, GLS, MAPSE, TAPSE). Application of the AI-model allows to capture these parameters for large patient cohorts within seconds (as opposed to the current practice of time-consuming manual post-processing). Association of AI-based CMR parameters with clinical outcomes post-AVR will be analyzed. The composite of all-cause mortality and heart failure hospitalization will serve as the primary endpoint. Trajectories of AI-based parameters from pre- to post-AVR will be assessed as a secondary endpoint. Future Outlook: In severe AS, a novel AI-based algorithm allows immediate and precise measurements of ventricular structure and function on CMR imaging. Our goal is to identify early markers of cardiac dysfunction indicating adverse prognosis post-AVR. This has guideline-forming potential as the optimal timepoint for AVR in patients with AS is currently a matter of debate.
This is a pilot randomised control study assessing the feasibility and effectiveness of a perioperative multi-component intervention aimed at reducing adverse hospital events and improving functional outcomes in patients with acute decompensated aortic stenosis undergoing urgent transcatheter aortic valve implantation compared to standard care. The intervention will consist of physical rehabilitation, delirium prevention, nutritional supplementation and anaemia correction (where indicated). The primary objective is to determine the feasibility and safety of delivering this intervention Secondary objectives include investigating the impact on adverse hospital events such as hospital-acquired disability and post-TAVI delirium, and on health-related quality of life and functional recovery following TAVI.
This multi-center, prospective, cluster-randomized controlled trial will evaluate Mpirik automated notifications as an intervention to support identification and evaluation of patients possibly indicated for Aortic Valve Replacement (AVR). This study will evaluate the impact of Mpirik automated notifications on: (1) AVR utilization (including time to AVR); and (2) multidisciplinary heart team clinic evaluation (including time to evaluation) for patients with definitive or possible severe AS on echocardiogram. These endpoints will also be examined within and between assigned groups according to race, ethnicity, sex, and geography. The primary question that will be answered: Do automated alerts sent to clinical providers decrease under-treatment of severe aortic stenosis? The study will compare the rate of clinical follow-up and aortic valve surgery in a control group (no alerts sent) to a treatment group (alerts sent to an appropriate care provider).
The goal of this clinical trial is to learn about the safety and performance of the F2 device for cerebral embolic protection in participants with symptomatic aortic stenosis undergoing a Transcatheter Aortic Valve replacement procedure.
This study will investigate changes right ventricular function and functional recovery metrics after transcatheter aortic valve implantation
Calcific aortic stenosis (CAS) is a disease characterized by progressive calcification of the aortic valve, obstructing the passage of blood from the left ventricle into the general circulation. It is the most frequent cause of valve disease in the elderly. To date, no means of preventing the disease has been discovered, and the only treatment available is valve replacement during cardiac surgery, or percutaneous implantation of a valve prosthesis when the narrowing becomes severe and causes symptoms. The intestinal flora or microbiota, the reservoir of all the microorganisms in the gut, is implicated in numerous diseases, particularly of the intestine. But to date, no study has established a link between CAS and microbiota. The intestinal microbiota acts through molecules produced by itself or the host and passing into the bloodstream. In the pathophysiology of CAS, the valve leaflets are breached and do not heal. These molecules can enter and have beneficial or deleterious effects, in particular promoting calcification of aortic valve cells. Concrete objectives: Improve understanding of calcific aortic stenosis in humans Study the composition of intestinal flora in patients with aortic stenosis and compare it with healthy subjects Study the molecules in the intestinal flora likely to be involved in the development of aortic stenosis in humans.
ATTR-cardiac amyloidosis (CA) is present in 4% to 16% of elderly patients with severe calcific aortic stenosis (AS). The reasons for this association are not fully known. It is hypothesized that an amyloidotic infiltration of the aortic valve acts as a trigger for the development of endothelial damage and subsequent calcification. Elderly patients undergoing TAVI will be evaluated for the presence of ATTR-CA in Jordan.
The purpose is to evaluate the safety, effectiveness and performance of Venus-Vitae Transcatheter Heart Valve System in patients with severe aortic stenosis.
Study is aimed to demonstrate that the self-expandable Allegra TAVI system provides lower mean gradient assessed by TTE compared to balloon-expandable valve systems in a female patient population with symptomatic severe aortic stenosis