Detection of Heart Conditions Using Artificial Intelligence
- Conditions
- Left Ventricular DysfunctionHeart Failure
- Registration Number
- NCT04933890
- Lead Sponsor
- Eko Devices, Inc.
- Brief Summary
The purpose of this study is to evaluate how Eko AI performs in the real world, front-line setting where the availability of sophisticated, expensive diagnostic tools is limited, and where there is a premium on detecting VHD early in its course.
- Detailed Description
Echocardiography is the state of the art for diagnosing VHD. However, without an effective pre-screening tool, many echocardiograms ("echos") are being ordered unnecessarily. A recent study found that greater than 66% of all echos performed in the United States do not alter clinical management, while an additional 4% may be deemed inappropriate altogether.
Because of this, echos now make up a disproportionately large segment of healthcare expenditure. Each year, 1 in 5 Medicare enrollees receives an echo at a total cost of $1.2 billion, or 11% of total Medicare spending on imaging services. This is compounded by the fact that an estimated 35 million Americans live in medically underserved areas, where patients must travel an average of 56 miles to see a specialist and receive an echo. This does not encourage compliance, and only adds to cost, lost working hours, and inconvenience.
There is therefore a growing, unmet need for better VHD screening tools. Tools that will consistently, reliably, quickly, and cheaply identify VHD when it is early and asymptomatic, when patients can be managed early and appropriately, and when they are at the lowest risk from an intervention. Such a tool will have a positive impact on the cost of care, patient and provider experience, and healthcare outcomes.
The FDA-cleared Eko CORE and Eko DUO electronic stethoscopes offer clinicians a familiar and inexpensive tool that is widely accepted by patients and providers, while at the same time offer sensors and artificial intelligence technology that can improve screening and detection of medical conditions such as VHD. Both the CORE and the DUO feature sound amplification during auscultation - the CORE also offers active noise cancellation - which improves the ability of the clinician to detect nuanced changes in heart sounds.
Recruitment & Eligibility
- Status
- COMPLETED
- Sex
- All
- Target Recruitment
- 68
- English-speaking adults who are 18 years and older
- Able and willing to provide informed consent
- Complete a clinical echocardiogram within 7 days before or after study procedures
- Unwilling or unable to provide informed consent
- Patients who are hospitalized
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Single-lead ECG based algorithm development Within two minutes of device use Evaluate performance of single-lead ECG based algorithm to identify individuals with reduced ejection fraction.
Single-lead ECG based algorithm Performance Within two minutes of device use To demonstrate that Eko's murmur detection algorithm outperforms front-line healthcare providers in detecting heart murmurs in real-world use. Collecting data in a point-of-care setting will demonstrate how accurately the algorithm detects murmurs in comparison to an unassisted clinical examination. Algorithm output and clinical determination will be confirmed by echocardiographic ground truth, with the results being blinded until the end of the study
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (1)
Parker Jewish Institute of Health Care and Rehabilitation
🇺🇸New Hyde Park, New York, United States