Clinical Trial

Detecting Valvular Disease with Phono and Electrocardiogram

Study Description

Phono- and Electrocardiogram Assisted Detection of Valvular Disease

The diagnosis of valvular heart disease (VHD), or its absence, invariably requires cardiac imaging. A familiar and inexpensive tool to assist in the diagnosis or exclusion of significant VHD could both expedite access to life-saving therapies and reduce the need for costly testing. The FDA-approved Eko Duo device consists of a digital stethoscope and a single-lead electrocardiogram (ECG), which wirelessly pairs with the Eko Mobile application to allow for simultaneous recording and visualization of phono- and electrocardiograms. These features uniquely situate this device to accumulate large sets of auscultatory data on patients both with and without VHD. In this study, the investigators seek to develop an automated system to identify VHD by phono- and electrocardiogram. Specifically, the investigators will attempt to develop machine learning algorithms to learn the phonocardiograms of patients with clinically important aortic stenosis (AS) or mitral regurgitation (MR), and then task the algorithms to identify subjects with clinically important VHD, as identified by a gold standard, from naA?ve phonocardiograms. The investigators anticipate that the study has the potential to revolutionize the diagnosis of VHD by providing a more accurate substitute to traditional auscultation.

Location

Locations Selected Location

Methods

No pharmaceutical medication involved No pharmaceutical medication involved
Patients and healthy individuals accepted Patients and healthy individuals accepted

Diagnostic Test - AS Algorithm 1

Machine learning algorithm, generated from ECG and PCG recordings, distinguishing moderate-to-severe or greater aortic stenosis from controls having structurally normal hearts with no greater than mild valvular heart disease at any location.

Diagnostic Test - AS Algorithm 2

Machine learning algorithm, generated from ECG and PCG recordings, distinguishing moderate-to-severe or greater aortic stenosis from controls having any findings other than moderate-to-severe or greater aortic stenosis.

Diagnostic Test - MR Algorithm 1

Machine learning algorithm, generated from ECG and PCG recordings, distinguishing moderate-to-severe or greater mitral regurgitation from controls having structurally normal hearts with no greater than mild valvular heart disease at any location.

Diagnostic Test - MR Algorithm 2

Machine learning algorithm, generated from ECG and PCG recordings, distinguishing moderate-to-severe or greater mitral regurgitation from controls having any findings other than moderate-to-severe or greater mitral regurgitation.

Additional Information

Official Study Title

Phono- and Electrocardiogram Assisted Detection of Valvular Disease

Clinical Trial ID

NCT03458806

ParticipAid ID

5eVwOa