- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT05010655
Low Ejection Fraction in Single Lead ECG
Detection of Reduced Left Ventricular Ejection Fraction and Atrial Arrhythmias With Single Lead ECG Using Artificial Intelligence
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
Heart failure with reduced left ventricular ejection fraction (EF) is a relatively common cardiac pathology with major clinical implications. People with reduced left ventricular EF are at increased risk for sudden death, ventricular and atrial arrhythmias, and acute hemodynamic decompensation due to heart failure. There are proven medical interventions that prevent sudden cardiac death and complications in people with decreased left ventricular EF. Unfortunately, some people with decreased left ventricular EF are asymptomatic, or have non-specific symptoms like dyspnea, and would not receive those interventions in a timely manner. Currently, there are no effective ways to screen for asymptomatic decreased left ventricular EF in the population, because detection of low EF requires the use of echocardiography. There is a significant need to identify novel technologies that can help to detect people with decreased left ventricular EF in a simple, effective, and reliable manner.
Eko Devices features a cloud-based platform of point-of-care cardiac screening devices and machine learning algorithms that enables more effective detection and management of cardiovascular disease. In this study, we will use the Eko DUO device to collect single-lead ECG data.
The Eko DUO is an FDA-cleared and CE-marked electronic stethoscope that allows audio recording of heart sound to produce a phonocardiogram (PCG) as well as recording a single-lead electrocardiogram (ECG). The DUO features 60x audio amplification, ambient noise reduction, a 4000Hz sample rate, and 4 audio filters. The ECG component is made up of 2 stainless steel electrodes, 0.01Hz high-pass filter, selectable 50/60Hz mains filter, and a 500Hz sample rate. The de-identified auscultatory DUO recordings transmit wirelessly via Bluetooth to the secure, HIPAA-compliant Eko application on a smartphone or tablet, which allows the user to playback heart sound recordings, annotate notes on recorded audio, and save recordings. This data is synced in real-time to a secure, HIPAA-compliant, cloud-based Amazon Web Services (AWS) database server managed by Eko Devices.
It has been previously demonstrated that artificial intelligence processing information from a 12-lead ECG can help to identify people with decreased left ventricular EF1. Using paired 12-lead ECG and echocardiogram data, including the left ventricular ejection fraction, from 44,959 patients at the Mayo Clinic, a convolutional neural was trained to identify patients with low ejection fraction. When tested on an independent set of 52,870 patients, the model showed an Area Under the Curve ("AUC") of 0.93 and an accuracy of 86%. We have also developed a single-lead version of the same algorithm, which will be more easily accessible in a clinical setting since it can be used with a single-lead ECG device like the Eko DUO device. We propose to validate performance of this new model using the current study.
Study Type
Enrollment (Actual)
Contacts and Locations
Study Locations
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Illinois
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O'Fallon, Illinois, United States, 62269
- Prairie Cardiovascular Consultants
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Springfield, Illinois, United States, 62701
- Prairie Cardiovascular Consultants
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- 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
Exclusion Criteria:
- Unwilling or unable to provide informed consent
- Patients who are hospitalized
Study Plan
How is the study designed?
Design Details
- Observational Models: Cohort
- Time Perspectives: Cross-Sectional
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Single-lead ECG based algorithm development
Time Frame: Within two minutes of device use
|
Evaluate performance of single-lead ECG based algorithm to identify individuals with reduced ejection fraction.
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Within two minutes of device use
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Collaborators and Investigators
Sponsor
Investigators
- Principal Investigator: Scott Marrus, MD, Prairie Cardiovascular
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Actual)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Estimate)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
- 2021.6
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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