Clinical trial Recruiting at 1 site Observational Ages 18 and up

Screening for pulmonary hypertension with the Eko CORE 500 digital stethoscope

Official title: Deep Learning for Algorithmic Detection of Pulmonary Hypertension Using a Combined Digital Stethoscope and Three-lead Electrocardiogram

Run by Eko Devices, Inc. · NCT07136623 · Data updated 2026-11-12

This project will test whether synchronized heart-sound and three-lead ECG recordings from the Eko CORE 500 can help detect pulmonary hypertension in adults undergoing a clinical echocardiogram or right-heart catheterization.

Quick facts

Study typeObservational
Ages18 Years and up
SexAll
Enrollment1513 (estimated)
SponsorEko Devices, Inc.
Industry-sponsored
Locations2 sites (Los Angeles, California and 1 other locations)
StatusRecruiting
StartedAugust 1, 2025
Main results expectedMay 31, 2027
Study endsMay 31, 2027
Registry record updatedAugust 24, 2026
Trial IDNCT07136623 on ClinicalTrials.gov

Is this trial a fit for you?

Likely a good fit

Adults aged 18 or older who can consent and are scheduled for a clinically indicated transthoracic echocardiogram or right-heart catheterization within ±7 days are ideal candidates.

Probably not a fit

Patients who are currently hospitalized, unable to provide informed consent, or who have a limited/non-diagnostic echocardiogram are unlikely to benefit from participation.

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This prospective, observational, multi-center project collects synchronized phonocardiogram (PCG) and three-lead ECG recordings using the FDA-cleared Eko CORE 500 from adults referred for clinically indicated transthoracic echocardiography (TTE) or right-heart catheterization (RHC). Trained staff obtain at least four 15-second recordings from standard aortic, pulmonic, tricuspid, and mitral auscultation sites during a single ~20-minute visit, and clinical TTE/RHC results within ±7 days provide reference labels. De-identified clinical data and, when available, clinical 12-lead ECGs may be abstracted for comparison. The primary goal is to develop and validate a software algorithm to detect pulmonary hypertension and, where possible, stratify its severity, with secondary analyses of diagnostic performance and subgroup generalizability.

Why it matters

Potential benefit: If successful, the approach could offer a quick, noninvasive screening tool to flag patients who may have pulmonary hypertension and need confirmatory testing.

How similar studies have gone: Acoustic and AI-based analyses have shown promise for detecting other cardiac conditions, but using synchronized PCG plus three-lead ECG specifically to screen for pulmonary hypertension is relatively novel and not yet widely validated.

Who can join: the full rules

Show full inclusion / exclusion criteria
Inclusion Criteria:

Age ≥ 18 years.

Able and willing to provide informed consent.

Clinically indicated transthoracic echocardiogram (TTE) or right heart catheterization (RHC) scheduled/performed within ±7 days of the study recording visit.

Exclusion Criteria:

Unwilling or unable to provide informed consent.

Currently hospitalized at the time of study procedures.

If enrolled via TTE path: limited (non-diagnostic) echocardiogram.

Where it's running

  • University of California Los Angeles
    Los Angeles, California, United States
    Recruiting
  • Duke University
    Durham, North Carolina, United States
    Suspended

Study contacts

How to take part

  1. Review the eligibility criteria above with your treating physician.
  2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
  3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.
Browse more
Last reviewed 2026-11-14 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.