View clinical trials related to Aortic Valve Stenosis.
Filter by:There are procedure related risk factors for permanent pacemaker implantation (PPI) that can be identified and assessed in a prospective cohort of 300 patients at high risk for PPI Prospective, multicenter, European registry in patients at high risk for PPI undergoing TAVI with the Edwards SAPIEN 3 valve. Additional assessment of calcification using a CT data core lab. Statistical analysis of the dataset obtained with respect to the objectives of the registry.
Study the consequences on heart muscle of the stenosis aortic valve before and after the replacement procedure, the repercussion on heart. Study the impact on the heart of "sick" valve can affect on "well-being" and prognosis in the year following the surgery.
This study is to analyse if the size of the valve can be determined with a preoperative CT scan of the heart in order to prepare the valve preoperatively to save time.
To compare changes in Left Ventricular Mass (LVM) depending on each blood pressure regulation between the intensive care group and the usual care group for patients with hypertension accompanied by aortic valve disease and evaluate an influence of blood pressure regulation on improvement of left ventricular hypertrophy and its safety
The aim of this study is to test the diagnostic added value of Volume Challenge (VC) to low-dose dobutamine stress echocardiography (LDDSE) in patients with a low-flow, low-gradient aortic stenosis (LFLGAS). This study will assess if LDDSE plus VC allows to increase the proportion of patients in whom a true severe AS can be differentiated from a pseudo severe AS.
Background: Computer aided auscultation in the differentiation of pathologic (AHA class I) from no- or innocent murmurs (AHA class III) via artificial intelligence algorithms could be a useful tool to assist healthcare providers in identifying pathological heart murmurs and may avoid unnecessary referrals to medical specialists. Objective: Assess the quality of the artificial intelligence (AI) algorithm that autonomously detects and classifies heart murmurs as either pathologic (AHA class I) or as no- or innocent (AHA class III). Hypothesis: The algorithm used in this study is able to analyze and identify pathologic heart murmurs (AHA class I) in an adult population with valve defects with a similar sensitivity compared to medical specialist. Methods: Each patient is auscultated and diagnosed independently by a medical specialist by means of standard auscultation. Auscultation findings are verified via gold-standard echocardiogram diagnosis. For each patient, a phonocardiogram (PCG) - a digital recording of the heart sounds - is acquired. The recordings are later analyzed using the AI algorithm. The algorithm results are compared to the findings of the medical professionals as well as to the echocardiogram findings.
The aim of this collaborative analysis is to evaluate stroke rates and mortality in patients undergoing TAVI with the self-expandable MCV prosthesis compared to the balloon-expandable ES valve. In the absence of large randomized controlled trials, we will conduct a large collaborative patient-pooled meta-analysis on 30-day stroke and mortality in patients undergoing primary transfemoral TAVI with either MCV or ES valve.
Prospective, multicenter registry in patients undergoing commercially available balloon expandable valve implantation. The registry will consist of 3 phases: Prospective determination of baseline Status Quo (3 months): Documentation of treatment pathways and endpoints of "routine" patients without educational program Dedicated reflection and training (1 day): One training session after the observational period to reflect on treatment pathways, exchange between valve coordinators involved, and develop improvements. Implementation of tailored changes (2 months): Implementation of the changes developed in the training. Determination of the effect (3 months): Coordinator measures optimization changes and determines effects.
Feasibility Trial on the ACURATE TA™ transapical implantation in patients presenting severe symptomatic aortic stenosis to collect human feasibility data pertaining to the safety and performance of the device.
There are patient related risk factors for PPI that can be identified and assessed in retrospective pooling of 1000+ TAVI patient datasets. Retrospective pooling of 6 datasets already available at participating centres (4 sites in Germany, 1 in Zwolle / The Netherlands, 1 in Linköping / Sweden). Additional assessment of calcifications using a CT data core lab. Statistical analysis of the obtained dataset with respect to the objectives of the registry.