View clinical trials related to Heart Murmurs.
Filter by:The Eko Artificial Intelligence (AI) has primarily been evaluated in the primary care setting. The digital stethoscope records a phonocardiogram of heart sounds of the patient and uses machine learning artificial intelligence to identify if there are abnormalities present (Eko Health, 2023). The Eko SENSORA will be tested in the emergency department. Chest pain, fatigue, shortness of breath and syncope are all symptoms that could indicate a cardiac dysfunction. The hypothesis is that this device will allow us increased ability to detect valvular heart disease that is clinically significant.
This observational study aims to assess the performance of the software called ausculto™. ausculto™ is a collection of computer algorithms that intend to analyse heart sounds recorded from the built-in microphone of a smartphone for abnormal sounds. Participants will have their heart sounds recorded during their regular clinic appointment after consenting to participate in this study. Researchers will manually annotate the recorded heart sounds to create a database for use in future training and testing of artificial intelligence (AI) intended for medical uses.
Heart failure (HF) is a condition in which the heart cannot pump blood adequately. It is increasingly common, consumes 4% of the UK National Health Service (NHS) budget and is deadlier than most cancers. Early diagnosis and treatment of HF improves quality of life and survival. Unacceptably, 80% of patients have their HF diagnosed only when very unwell, requiring an emergency hospital admission, with worse survival and higher treatment costs to the NHS. This is largely because General Practitioners (GPs) have no easy-to-use tools to check for suspected HF, with patients having to rely on a long and rarely completed diagnostic pathway involving blood tests and hospital assessment. The investigators have previously demonstrated that an artificial intelligence-enabled stethoscope (AI-stethoscope) can detect HF in 15 seconds with 92% accuracy (regardless of age, gender or ethnicity) - even before patients develop symptoms. While the GP uses the stethoscope, it records the heart sounds and electrical activity, and uses inbuilt artificial intelligence to detect HF. The goal of this clinical trial is to determine the clinical and cost-effectiveness of providing primary care teams with the AI-stethoscope for the detection of heart failure. The main questions it aims to answer are if provision of the AI-stethoscope: 1. Increases overall detection of heart failure 2. Reduces the proportion of patients being diagnosed with heart failure following an emergency hospital admission 3. Reduces healthcare system costs 200 primary care practices across North West London and North Wales, UK, will be recruited to a cluster randomised controlled trial, meaning half of the primary care practices will be randomly assigned to have AI-stethoscopes for use in direct clinical care, and half will not. Researchers will compare clinical and cost outcomes between the groups.
The purpose of this research is to prospectively test and validate the utility of Eko artificial intelligence (AI) plus Eko Murmur Analysis Software (EMAS) murmur characterization in algorithm in a real world, point-of-care setting.
The purpose of this research is to evaluate the impact of Eko AI plus EMAS (Eko Murmur Analysis Software) on a clinician's referral decision in a real-world primary care setting. There is an additional objective of understanding patient outcomes when patients are referred for cardiology follow-up and/or echocardiogram.
The current study concerns Cardiags Trimod, a new non-invasive medical device for cardiac examinations. The evaluation of its effectiveness is done relative to specific standard devices.
The principal objective of the study is to determine if patient-empowered, real-time and home- based patient monitoring of vital parameters can lead to: - Reduction in admission rates and improved clinical management of chronically ill patients - Reduction in use of medications - Reported quality of life A minimum of 100 patients will be recruited, monitored and observed over 6 months from home with the Coala Heart Monitor. The study population will be representative of rural, high-risk, Medicare (65+ of age) subjects with chronic conditions and will be recruited by the Perry Community Hospital in Linden, TN.
The Eko CORE and DUO stethoscopes are FDA-approved electronic devices that have the capacity to record heart sounds. The study seeks to expand murmur detection to include VHD classification through the development of novel ML algorithms that are able to distinguish between systolic vs. diastolic vs. continuous murmurs, as well as classify VHD type and severity, using 4-point auscultation with Eko CORE and DUO electronic stethoscopes to record heart sounds.
The Eko CORE and DUO stethoscopes are FDA approved electronic devices which have the capacity to record heart sounds. This study will utilize these devices to see if they can differentiate between pathologic and innocent heart murmurs in children.
The combination of fever and auscultation of a heart murmur suggests the diagnosis of endocarditis. However, fever itself increases cardiac output and could therefore modify heart sounds. The aim of the FeMur study is to measure the modification of heart sounds during fever. Heart sounds of 15 hospitalized febrile patients with a heart murmur will be recorded using an electronic stethoscope before and after resolution of fever. The records will be analyzed using a computerized application in order to quantify the intensity of heart murmurs.