Clinical Research Directory

EKO SENSORA: Detecting Clinically Significant Murmurs

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.

Validate the Efficacy and the Safety of the Keikku Electronic Stethoscope for Its Indication and Intended Purpose, Under the Intended Conditions of Use.

This study is testing a digital stethoscope called the Keikku electronic stethoscope. Doctors use stethoscopes to listen to the heart, and this new device records heart sounds using a smartphone app. The purpose of the study is to check how well this new device works and whether it is safe to use. The study will include 149 participants of all ages (from birth to 99 years), who are undergoing routine (non-urgent) heart checks. After giving consent, each participant will have their heart sounds listened to twice: once with the Keikku electronic stethoscope and once with a regular stethoscope. Two different doctors will do the listening, and they won't share information with each other. The doctors will record whether they hear a heart murmur and how clear the sounds were. The study will compare the findings from the new device to those from the regular stethoscope. Researchers will also check for any device problems or side effects. The study takes place at a single site in Peru and will take about one day for each participant. The goal is to find out if the Keikku electronic stethoscope is accurate and safe for doctors to use in real medical settings.

Can a Smartphone Listen to Your Heart? A Performance Study on Detecting Abnormalities in Your Heart Sounds

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.

Triple Cardiovascular Disease Detection With an Artificial Intelligence-enabled Stethoscope

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.