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Completed

NCT Number: NCT05459545

Real-World Evaluation of Eko Algorithms in a Point of Care Setting

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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Key information

Age range

65 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Pentucket Medical Associates, Haverhill, Massachusetts, United States

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About this study

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.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Patient consents to participation
  • Willing to have heart sounds recorded with an electronic stethoscope
  • Willing to undergo echocardiography
  • Willing to undergo a 12-lead electrocardiogram
  • Adults aged 65 years and older
  • History of at least one of the following: hypertension, BMI ≥ 30, diabetes mellitus, hyperlipidemia, atrial fibrillation, myocardial infarction, stroke/TIA, previous coronary surgery, or previous coronary angiography
  • No prior diagnosis of valve disease or heart murmur

Exclusion criteria

  • Patient is unwilling or unable to give written informed consent
  • Patients experiencing a known or suspected acute cardiac event
  • Under the age of 65 years old
  • Prior diagnosis of valve disease or heart murmurs

Treatment and study plan

Use of Eko CORE and Eko CORE 500 electronic stethoscope

Device

Auscultation of heart sounds using electronic stethoscopes

Primary outcomes

  1. Sensitivity and Specificity of Eko's AI relative to ground truth

    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.

  2. Sensitivity and Specificity of Eko's AI relative to PCP auscultation and ground truth

    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.

  3. Positive and negative predictive values for AI detecting new VHD

    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

  4. Positive and negative predictive values for PCP detecting new VHD

    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

Secondary outcomes

  1. Sensitivity and Specificity of Eko's AI relative to echocardiographic ground truth.

    Time frame: 02/20/2022 - 05/20/2024

    Sensitivity and specificity of Eko's murmur detection algorithm relative to echocardiographic ground truth.

  2. Performance of the machine algorithm vs. the physician

    Time frame: 02/20/2022 - 05/20/2024

    Performance of the machine algorithm vs. the physician

  3. Number of cardiac tests and consultations ordered

    Time frame: 02/20/2022 - 05/20/2024

    Number of cardiac tests and consultations ordered

Sponsors and collaborators

Lead sponsor

Eko Devices, Inc.

Industry

Registry information

Important dates

Study start
2022
Primary completion
2023
Study completion
2023
First posted
Jul 15, 2022
Registry last updated
Nov 25, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

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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