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Improvement of an Algorithm to Detect Structural Heart Murmurs in Adult Patients Using Electronic Stethoscopes

Improvement of an Algorithm to Detect Structural Heart Murmurs in Adult Patients Using Electronic Stethoscopes

Status
Withdrawn
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT07202104
Enrollment
0
Registered
2025-10-01
Start date
2026-06-29
Completion date
2026-06-29
Last updated
2026-07-15

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Structural Heart Disease

Keywords

structural heart disease, structural murmur

Brief summary

The main objective of this study is to evaluate a machine learning model's ability to detect murmurs indicative of structural heart disease ("structural murmur") by analyzing phonocardiogram waveforms-and simultaneous electrocardiogram waveforms when available-in multiple auscultatory positions per subject. Diagnosis of structural murmur will be confirmed by gold-standard echocardiography and reviewed by an expert panel of cardiologists.

Interventions

Use of the Eko CORE 500 digital stethoscope and 3M Littmann CORE Digital Stethoscope to auscultate and record cardiac phonocardiogram and (when available) electrocardiogram waveforms, as well as heart sounds.

Sponsors

Eko Devices, Inc.
Lead SponsorINDUSTRY

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

* 18+ years old * Patient or patient's legal healthcare proxy consents to participation * Documented history of SHD * Undergoing (or has undergone, within 30 days) a complete echocardiogram * Willing to have heart recordings done with two different electronic stethoscopes

Exclusion criteria

* Patient or proxy is unwilling/unable to give written informed consent * Unable to complete a complete echocardiogram, or none recent completed within the last 30 days * No documented history of SHD * Experiencing a known or suspected acute cardiac event * Mechanical ventricular support (such as ECMO, LVAD, RVAD, BiVAD, Impella, intra-aortic balloon pumps, TAH, VentrAssist, DuraHeart, HVAD, EVAHEART LVAS, HeartMate, Jarvik 2000) * Unwilling or unable to follow or complete study procedures

Design outcomes

Primary

MeasureTime frameDescription
Primary outcome6 monthsEvaluate a machine learning model's ability to detect murmurs indicative of structural heart disease ("structural murmur") by analyzing phonocardiogram waveforms-and simultaneous electrocardiogram waveforms when available-in multiple auscultatory positions per subject. Diagnosis of structural murmur will be confirmed by gold-standard echocardiography and review by an expert panel of cardiologists.

Countries

United States

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Jul 16, 2026