Use of Eko CORE and Eko CORE 500 electronic stethoscope
DeviceAuscultation of heart sounds using electronic stethoscopes
NCT Number: NCT05459545
The purpose of this research is to prospectively test and validate the utility of Eko artificial intelligence (AI) plus Eko Murmur Analysis Software (EMAS) murmur characterization in algorithm in a real world, point-of-care setting.
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Notify Me65 year and older
All sexes
Observational
Pentucket Medical Associates, Haverhill, Massachusetts, United States
Eko has developed a platform to aid in screening for cardiac conditions using a digital stethoscope and machine-learning algorithms to detect the presence or absence of heart conditions such as heart murmurs and atrial fibrillation.
In November 2019, the US Food and Drug Administration (FDA) granted Eko a 510(k) clearance for the marketing of "Eko AI", a set of machine learning algorithms that includes atrial fibrillation (AF) and heart murmur detection. The detection of heart murmurs may aid in detecting occult and dangerous valvular heart disease (VHD). Other Eko AI outputs include bradycardia, tachycardia, noisy signal, QRS duration, and unclassified data. Eko AI has accuracy comparable to physician judgment (atrial fibrillation sensitivity of 98.9% and specificity of 96.9%, murmur sensitivity of 87.6% and specificity of 87.8%). Both AF and VHD can cause significant morbidity and mortality when missed or diagnosed late.
Eko has further developed the murmur detection function of Eko AI to now not only identify whether a murmur is present, but also to inform the clinician of its timing during the cardiac cycle (systole vs diastole), and whether it is innocent or structural. We are calling this product the Eko Murmur Analysis Software (EMAS) and submitted a premarket notification to FDA in December 2021.
This study sets out to understand the utility of the Eko AI plus EMAS murmur characterization algorithm in real world use. Collecting data in a point-of-care setting will demonstrate how accurately the algorithm characterizes murmurs in comparison to an AI-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 patient visit.
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Auscultation of heart sounds using electronic stethoscopes
Time frame: 02/20/2022 - 05/20/2024
Sensitivity and specificity of Eko's murmur detection algorithm relative to ground truth. Ground truth is defined as echocardiography-confirmed clinically-significant (graded "mild-to-moderate" or greater severity) VHD that is associated with a murmur, as confirmed by an expert panel.
Time frame: 02/20/2022 - 05/20/2024
Sensitivity and specificity of Eko's murmur detection algorithm relative to ground truth and PCP auscultation ground truth. Ground truth is defined as echocardiography-confirmed clinically-significant (graded "mild-to-moderate" or greater severity) VHD that is associated with a murmur, as confirmed by an expert panel.
Time frame: 02/20/2022 - 05/20/2024
Positive and negative predictive values of Eko's algorithms for detecting new clinically significant valvular heart disease
Time frame: 02/20/2022 - 05/20/2024
Positive and negative predictive values of a PCP's outpatient visit for detecting new clinically significant valvular heart disease
Time frame: 02/20/2022 - 05/20/2024
Sensitivity and specificity of Eko's murmur detection algorithm relative to echocardiographic ground truth.
Time frame: 02/20/2022 - 05/20/2024
Performance of the machine algorithm vs. the physician
Time frame: 02/20/2022 - 05/20/2024
Number of cardiac tests and consultations ordered
Eko Devices, Inc.
Industry
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View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
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