Ignite Creation Date:
2024-05-06 @ 2:43 PM
Last Modification Date:
2024-10-26 @ 1:35 PM
Study NCT ID:
NCT04400435
Status:
COMPLETED
Last Update Posted:
2022-12-09
First Post:
2020-05-19
Brief Title:
Detection of Heart Conditions With Single Lead ECG Using Artificial Intelligence
Sponsor:
Eko Devices Inc
Organization:
Eko Devices Inc
Study Overview
Official Title:
Detection of Reduced Left Ventricular Ejection Fraction and Atrial Arrhythmias With Single Lead ECG Using Artificial Intelligence
Status:
COMPLETED
Status Verified Date:
2022-12
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
DAVID1
Brief Summary:
The purpose of this research is to prospectively test and validate the single-lead Low EF algorithm in outpatients in order to test the performance of a single-lead ECG based algorithm to identify people with decreased left ventricular EF
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 001Hz high-pass filter selectable 5060Hz 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 44959 patients at the Mayo Clinic a convolutional neural was trained to identify patients with low ejection fraction When tested on an independent set of 52870 patients the model showed an Area Under the Curve AUC of 093 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
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 001Hz high-pass filter selectable 5060Hz 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 44959 patients at the Mayo Clinic a convolutional neural was trained to identify patients with low ejection fraction When tested on an independent set of 52870 patients the model showed an Area Under the Curve AUC of 093 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 Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None