Hypertension, PulmonaryPH ELEFT 2-0NCT07087613
Deep Learning Detection of Pulmonary Hypertension and Low Ejection Fraction Via Digital Stethoscope and 3-Lead ECG
An observational study of Hypertension, Pulmonary and Heart Failure With Reduced Ejection Fraction, run by Eko Devices, Inc. at 4 sites in United States.
Trial summary
This is a prospective, observational study evaluating whether heart sounds (phonocardiograms) and three-lead electrocardiograms (ECGs) recorded using the Eko CORE 500 digital stethoscope can help detect pulmonary hypertension (PH) and low left ventricular ejection fraction (EF ≤ 40%). Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Hypertension, Pulmonary, Heart Failure With Reduced Ejection Fraction
- What is being tested?
- Eko CORE 500 Digital Stethoscope
- Type of treatment
- Medical device
- How many people
- 3,850 participants
- Where
- 4 sitesUnited States
- Study dates
- 15 Jun 2025to 31 May 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Adult, Older adult
Study population: This study will enroll adult patients (18 years and older) who are undergoing clinically indicated transthoracic echocardiography or right heart catheterization. Participants must be able and willing to provide informed consent and must complete a clinical echocardiogram or right heart catheterization within 7 days before or after the study procedures. Patients who are hospitalized, unable or unwilling to provide informed consent, or who are undergoing a limited echocardiogram will be excluded.
Who may be able to join
- Adults aged 18 years and older
- Able and willing to provide informed consent
- Completed a clinical echocardiogram or right heart catheterization within 7 days before or after study procedures
Who cannot join
- Unwilling or unable to provide informed consent
- Patients who are hospitalized
- Patients undergoing echocardiography with a limited echocardiogram (does not apply to patients undergoing right heart catheterization)
Trial locations and contacts
4 sites in 1 country. Contact the study team or a site near you to ask about taking part.
United States4 sites, 4 recruiting
- Recruiting
Sentara Norfolk General Hospital
Norfolk, Virginia, 23501
KIMBERLY MACIAS, MS, 757-388-5625, KXMACIAS@sentara.com
Raymond Benza, MD
- Recruiting
Prairie Cardiovascular
O'Fallon, Illinois, 62269
Lauren McNeil, 217.492.9115, lmcneil@prairieresearch.com
Scott Marrus, MD
- Recruiting
Prairie Education & Research Cooperative
Springfield, Illinois, 62769
Lauren McNeil, 217.492.9115, lmcneil@prairieresearch.com
Scott Marrus, MD
- Recruiting
St Johns Hospital, Springfield
Springfield, Illinois, 62769
Lauren McNeil, 217.492.9115, lmcneil@prairieresearch.com
Scott Marrus, MD
About this study
Official title: Deep Learning for Detection of Pulmonary Hypertension and Reduced Left Ventricular Ejection Fraction Using a Combined Digital Stethoscope and Three-lead Electrocardiogram
This is a prospective, observational study evaluating whether heart sounds (phonocardiograms) and three-lead electrocardiograms (ECGs) recorded using the Eko CORE 500 digital stethoscope can help detect pulmonary hypertension (PH) and low left ventricular ejection fraction (EF ≤ 40%). PH is a condition characterized by high blood pressure in the pulmonary arteries, which can lead to heart failure and carries significant risks if undiagnosed. Low EF, which indicates reduced pumping ability of the heart, is also associated with increased risk of severe cardiac events but can remain undetected because patients often have no symptoms or only nonspecific symptoms.
In this study, adults undergoing clinically indicated echocardiograms or right heart catheterization at outpatient sites will be invited to participate. Participants will complete a single study session lasting about 20 minutes, during which heart sounds and a three-lead ECG will be collected using the Eko CORE 500 device. If participants have had a clinical 12-lead ECG within 30 days of their echocardiogram or right heart catheterization, those data may also be used for analysis. A clinically indicated echocardiogram or right heart catheterization (RHC) performed within seven days before or after the Eko CORE 500 recording will serve as the reference standard to confirm the presence or absence of PH and low EF.
Up to 3,850 participants may be enrolled across multiple sites to ensure that approximately 3,500 complete the study. The data collected will be used to develop and validate artificial intelligence (AI) algorithms that aim to detect PH and identify low EF, potentially enabling earlier and simpler screening for these conditions in clinical practice.
Read the detailed description
Pulmonary hypertension (PH) and low left ventricular ejection fraction (EF) are significant cardiovascular conditions associated with increased morbidity and mortality but often remain underdiagnosed due to the need for specialized imaging such as echocardiography or invasive right heart catheterization. Early detection tools could enable timely intervention and improved patient outcomes.
This prospective, observational study aims to determine whether acoustic heart sounds (phonocardiograms, PCG) and three-lead electrocardiograms (ECG) recorded with the Eko CORE 500 digital stethoscope can identify patients with PH or low EF (defined as EF ≤ 40%) when compared with echocardiographic or right heart catheterization findings as the reference standard. The study will enroll adult patients undergoing clinically indicated transthoracic echocardiography or right heart catheterization at outpatient sites.
Participants will complete a single study visit, lasting approximately 20 minutes, during which heart sounds and three-lead ECG signals will be recorded at four standard auscultation sites (aortic, pulmonic, tricuspid, and mitral) while seated. Each recording lasts approximately 15 seconds. If a participant has undergone a 12-lead ECG within 30 days of their echocardiogram or right heart catheterization, de-identified ECG data will also be included for comparison purposes. Poor-quality recordings will be repeated once before moving to the next auscultation site. No results from the CORE 500 device or developed algorithms will be shared with participants or entered into the medical record.
De-identified demographic data collected will include age, race/ethnicity, and sex. Clinical data will include past medical history, relevant laboratory results (such as BNP or NT-proBNP), electrocardiographic findings, and echocardiographic measurements including tricuspid regurgitant jet velocity, pulmonary artery pressures, chamber size, and left ventricular ejection fraction.
Data will be analyzed by Eko Health, Inc. using machine learning techniques, including transformer-based models implemented in Python with PyTorch. Models will initially be pre-trained on unlabeled data and then fine-tuned on labeled data, optimizing performance using the Adam optimizer and binary cross-entropy loss. Algorithm performance will be evaluated based on sensitivity, specificity, area under the receiver operating characteristic curve (AUC), and other diagnostic metrics. Confidence intervals for sensitivity and specificity will be calculated to assess the statistical reliability of results.
Sample size calculations account for the estimated prevalence of each condition. For PH, an anticipated prevalence of 25-30% and target algorithm sensitivity and specificity exceeding 0.7 drive a required enrollment of approximately 2,400 participants to achieve statistical confidence. For low EF, assuming a prevalence of 10%, a minimum of 2,000 participants is required to adequately power analyses for sensitivity and specificity above 0.7.
The primary endpoint of this study is to evaluate sensitivity and specificity for the PH and low EF detection algorithms, respectively. The secondary endpoint is to measure algorithm accuracy, area under the ROC curve, negative predictive value, and positive predictive value for detecting low EF.
The study plans to enroll up to 3,850 participants across multiple sites to ensure sufficient evaluable data from approximately 3,500 participants. The intended outcome is to develop and validate AI-based tools that may facilitate non-invasive, point-of-care screening for PH and low EF using the Eko CORE 500 digital stethoscope, potentially reducing the burden of undiagnosed cardiovascular disease.
- Being tested
- Eko CORE 500 Digital Stethoscope
- Medical subject headings
- Hypertension, Pulmonary
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Eko CORE 500 Digital StethoscopeDevice
The FDA-cleared Eko CORE 500 digital stethoscope is used to collect phonocardiogram (PCG) and three-lead ECG recordings from participants. This observational study uses these recordings to develop and validate artificial intelligence algorithms to detect pulmonary hypertension and low left ventricular ejection fraction. No modifications to the device or device functionality are being tested.
| Study group | Role | What they receive |
|---|---|---|
| All Participants | Adults aged 18 years and older undergoing clinically indicated transthoracic echocardiography or right heart catheterization in an outpatient setting. Participants will have phonocardiogram (PCG) and 3-lead ECG recordings collected using the Eko CORE 500 digital stethoscope. Data will be used to develop and validate artificial intelligence algorithms to detect pulmonary hypertension and low left ventricular ejection fraction. Receives: Device: Eko CORE 500 Digital Stethoscope |
What is being measured
The primary outcome is the main question the study is designed to answer.
Sensitivity and specificity of the deep-learning algorithm for detecting pulmonary hypertension (PH)
The primary outcome is the diagnostic performance of the algorithm developed from Eko CORE 500 recordings to detect pulmonary hypertension, as confirmed by clinical echocardiography or right heart catheterization. Sensitivity and specificity will be calculated by comparing algorithm predictions to the echocardiogram or right heart catheterization gold standard.
Measured: Up to 24 months
Secondary outcomes (1)
Algorithm Diagnostic Performance for Detection of Low Ejection Fraction
To evaluate the diagnostic accuracy of the Eko algorithm in detecting low ejection fraction (EF), measured by area under the receiver operating characteristic (ROC) curve (AUC), positive predictive value (PPV), and negative predictive value (NPV).
Measured: Through study completion, 2 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted28 Jul 2025
- Study start15 Jun 2025
- Primary completion31 May 2027 (estimated)
- Study completion31 May 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (11)Papers the sponsor has linked to this study.
- Other trials for Hypertension, PulmonaryStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 3,850 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Eko Devices, Inc.
- Sponsor type
- Industry (pharma, biotech, devices)
- Responsible party
- Sponsor
- Investigators
- Rose McDonough, MD, Study director, Senior Manager, Medical Affairs
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07087613
- Sponsor's protocol ID
- 2025.2
- Acronym
- PH ELEFT 2-0
- Status last verified
- Jun 2026
- First submitted
- 11 Jul 2025
- Last updated
- 18 Jun 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Authorized study personnel will be responsible for collecting clinical research data and maintaining a Master File that links Key-Coded IDs to participant identifiers. The Master File and signed informed consent forms will be securely stored with access limited to study personnel and will not be shared with the sponsor. De-identified data, including Eko recordings and demographic/clinical data from the EHR, will be entered under a Key-Coded ID and shared electronically with the sponsor via secure, password-protected systems. No personal identifiers will be stored or exported in any shared data files.
Publications
Frost A, Badesch D, Gibbs JSR, Gopalan D, Khanna D, Manes A, Oudiz R, Satoh T, Torres F, Torbicki A. Diagnosis of pulmonary hypertension. Eur Respir J. 2019 Jan 24;53(1):1801904. doi: 10.1183/13993003.01904-2018. Print 2019 Jan.
PubMed 30545972Maron BA, Hess E, Maddox TM, Opotowsky AR, Tedford RJ, Lahm T, Joynt KE, Kass DJ, Stephens T, Stanislawski MA, Swenson ER, Goldstein RH, Leopold JA, Zamanian RT, Elwing JM, Plomondon ME, Grunwald GK, Baron AE, Rumsfeld JS, Choudhary G. Association of Borderline Pulmonary Hypertension With Mortality and Hospitalization in a Large Patient Cohort: Insights From the Veterans Affairs Clinical Assessment, Reporting, and Tracking Program. Circulation. 2016 Mar 29;133(13):1240-8. doi: 10.1161/CIRCULATIONAHA.115.020207. Epub 2016 Feb 12.
PubMed 26873944Assad TR, Maron BA, Robbins IM, Xu M, Huang S, Harrell FE, Farber-Eger EH, Wells QS, Choudhary G, Hemnes AR, Brittain EL. Prognostic Effect and Longitudinal Hemodynamic Assessment of Borderline Pulmonary Hypertension. JAMA Cardiol. 2017 Dec 1;2(12):1361-1368. doi: 10.1001/jamacardio.2017.3882.
PubMed 29071338Strange G, Stewart S, Celermajer DS, Prior D, Scalia GM, Marwick TH, Gabbay E, Ilton M, Joseph M, Codde J, Playford D; NEDA Contributing Sites. Threshold of Pulmonary Hypertension Associated With Increased Mortality. J Am Coll Cardiol. 2019 Jun 4;73(21):2660-2672. doi: 10.1016/j.jacc.2019.03.482.
PubMed 31146810Choudhary G, Jankowich M, Wu WC. Elevated pulmonary artery systolic pressure predicts heart failure admissions in African Americans: Jackson Heart Study. Circ Heart Fail. 2014 Jul;7(4):558-64. doi: 10.1161/CIRCHEARTFAILURE.114.001366. Epub 2014 Jun 5.
PubMed 24902739Maron BA, Choudhary G, Khan UA, Jankowich MD, McChesney H, Ferrazzani SJ, Gaddam S, Sharma S, Opotowsky AR, Bhatt DL, Rocco TP, Aragam JR. Clinical profile and underdiagnosis of pulmonary hypertension in US veteran patients. Circ Heart Fail. 2013 Sep 1;6(5):906-12. doi: 10.1161/CIRCHEARTFAILURE.112.000091. Epub 2013 Jun 27.
PubMed 23811965Attia ZI, Kapa S, Lopez-Jimenez F, McKie PM, Ladewig DJ, Satam G, Pellikka PA, Enriquez-Sarano M, Noseworthy PA, Munger TM, Asirvatham SJ, Scott CG, Carter RE, Friedman PA. Screening for cardiac contractile dysfunction using an artificial intelligence-enabled electrocardiogram. Nat Med. 2019 Jan;25(1):70-74. doi: 10.1038/s41591-018-0240-2. Epub 2019 Jan 7.
PubMed 30617318Guo L, Khobragade N, Kieu S, Ilyas S, Nicely PN, Asiedu EK, Lima FV, Currie C, Lastowski E, Choudhary G. Development and Evaluation of a Deep Learning-Based Pulmonary Hypertension Screening Algorithm Using a Digital Stethoscope. J Am Heart Assoc. 2025 Feb 4;14(3):e036882. doi: 10.1161/JAHA.124.036882. Epub 2025 Feb 3.
PubMed 39895552Colman R, Whittingham H, Tomlinson G, Granton J. Utility of the physical examination in detecting pulmonary hypertension. A mixed methods study. PLoS One. 2014 Oct 24;9(10):e108499. doi: 10.1371/journal.pone.0108499. eCollection 2014.
PubMed 25343585Guo L, Pressman GS, Kieu SN, Marrus SB, Mathew G, Prince J, Lastowski E, McDonough RV, Currie C, Tiwari U, Maidens JN, Al-Sudani H, Friend E, Padmanabhan D, Kumar P, Kersh E, Venkatraman S, Qamruddin S. Automated Detection of Reduced Ejection Fraction Using an ECG-Enabled Digital Stethoscope: A Large Cohort Validation. JACC Adv. 2025 Mar;4(3):101619. doi: 10.1016/j.jacadv.2025.101619. Epub 2025 Feb 20.
PubMed 39983614Marcus GM, Vessey J, Jordan MV, Huddleston M, McKeown B, Gerber IL, Foster E, Chatterjee K, McCulloch CE, Michaels AD. Relationship between accurate auscultation of a clinically useful third heart sound and level of experience. Arch Intern Med. 2006 Mar 27;166(6):617-22. doi: 10.1001/archinte.166.6.617.
PubMed 16567599
Study at a glance
From the registry record, last updated by the sponsor on 18 Jun 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Deep Learning for Detection of Pulmonary Hypertension and Reduced Left Ventricular Ejection Fraction Using a Combined Digital Stethoscope and Three-lead Electrocardiogram
- ClinicalTrials.gov ID
- NCT07087613
- Acronym / sponsor ID
- PH ELEFT 2-0 / 2025.2
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 3,850 participants (estimated)
- Lead sponsor
- Eko Devices, Inc.Industry (pharma, biotech, devices)
- Study start
- 15 Jun 2025 (actual)
- Primary completion
- 31 May 2027 (estimated)
- Study completion
- 31 May 2027 (estimated)
- First posted
- 28 Jul 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This is a prospective, observational study evaluating whether heart sounds (phonocardiograms) and three-lead electrocardiograms (ECGs) recorded using the Eko CORE 500 digital stethoscope can help detect pulmonary hypertension (PH) and low left ventricular ejection fraction (EF ≤ 40%). PH is a condition characterized by high blood pressure in the pulmonary arteries, which can lead to heart failure and carries significant risks if undiagnosed. Low EF, which indicates reduced pumping ability of the heart, is also associated with increased risk of severe cardiac events but can remain undetected because patients often have no symptoms or only nonspecific symptoms.
In this study, adults undergoing clinically indicated echocardiograms or right heart catheterization at outpatient sites will be invited to participate. Participants will complete a single study session lasting about 20 minutes, during which heart sounds and a three-lead ECG will be collected using the Eko CORE 500 device. If participants have had a clinical 12-lead ECG within 30 days of their echocardiogram or right heart catheterization, those data may also be used for analysis. A clinically indicated echocardiogram or right heart catheterization (RHC) performed within seven days before or after the Eko CORE 500 recording will serve as the reference standard to confirm the presence or absence of PH and low EF.
Up to 3,850 participants may be enrolled across multiple sites to ensure that approximately 3,500 complete the study. The data collected will be used to develop and validate artificial intelligence (AI) algorithms that aim to detect PH and identify low EF, potentially enabling earlier and simpler screening for these conditions in clinical practice.
Detailed description
Pulmonary hypertension (PH) and low left ventricular ejection fraction (EF) are significant cardiovascular conditions associated with increased morbidity and mortality but often remain underdiagnosed due to the need for specialized imaging such as echocardiography or invasive right heart catheterization. Early detection tools could enable timely intervention and improved patient outcomes.
This prospective, observational study aims to determine whether acoustic heart sounds (phonocardiograms, PCG) and three-lead electrocardiograms (ECG) recorded with the Eko CORE 500 digital stethoscope can identify patients with PH or low EF (defined as EF ≤ 40%) when compared with echocardiographic or right heart catheterization findings as the reference standard. The study will enroll adult patients undergoing clinically indicated transthoracic echocardiography or right heart catheterization at outpatient sites.
Participants will complete a single study visit, lasting approximately 20 minutes, during which heart sounds and three-lead ECG signals will be recorded at four standard auscultation sites (aortic, pulmonic, tricuspid, and mitral) while seated. Each recording lasts approximately 15 seconds. If a participant has undergone a 12-lead ECG within 30 days of their echocardiogram or right heart catheterization, de-identified ECG data will also be included for comparison purposes. Poor-quality recordings will be repeated once before moving to the next auscultation site. No results from the CORE 500 device or developed algorithms will be shared with participants or entered into the medical record.
De-identified demographic data collected will include age, race/ethnicity, and sex. Clinical data will include past medical history, relevant laboratory results (such as BNP or NT-proBNP), electrocardiographic findings, and echocardiographic measurements including tricuspid regurgitant jet velocity, pulmonary artery pressures, chamber size, and left ventricular ejection fraction.
Data will be analyzed by Eko Health, Inc. using machine learning techniques, including transformer-based models implemented in Python with PyTorch. Models will initially be pre-trained on unlabeled data and then fine-tuned on labeled data, optimizing performance using the Adam optimizer and binary cross-entropy loss. Algorithm performance will be evaluated based on sensitivity, specificity, area under the receiver operating characteristic curve (AUC), and other diagnostic metrics. Confidence intervals for sensitivity and specificity will be calculated to assess the statistical reliability of results.
Sample size calculations account for the estimated prevalence of each condition. For PH, an anticipated prevalence of 25-30% and target algorithm sensitivity and specificity exceeding 0.7 drive a required enrollment of approximately 2,400 participants to achieve statistical confidence. For low EF, assuming a prevalence of 10%, a minimum of 2,000 participants is required to adequately power analyses for sensitivity and specificity above 0.7.
The primary endpoint of this study is to evaluate sensitivity and specificity for the PH and low EF detection algorithms, respectively. The secondary endpoint is to measure algorithm accuracy, area under the ROC curve, negative predictive value, and positive predictive value for detecting low EF.
The study plans to enroll up to 3,850 participants across multiple sites to ensure sufficient evaluable data from approximately 3,500 participants. The intended outcome is to develop and validate AI-based tools that may facilitate non-invasive, point-of-care screening for PH and low EF using the Eko CORE 500 digital stethoscope, potentially reducing the burden of undiagnosed cardiovascular disease.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| All Participants | – | Device: Eko CORE 500 Digital StethoscopeAdults aged 18 years and older undergoing clinically indicated transthoracic echocardiography or right heart catheterization in an outpatient setting. Participants will have phonocardiogram (PCG) and 3-lead ECG recordings collected using the Eko CORE 500 digital stethoscope. Data will be used to develop and validate artificial intelligence algorithms to detect pulmonary hypertension and low left ventricular ejection fraction. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- This study will enroll adult patients (18 years and older) who are undergoing clinically indicated transthoracic echocardiography or right heart catheterization. Participants must be able and willing to provide informed consent and must complete a clinical echocardiogram or right heart catheterization within 7 days before or after the study procedures. Patients who are hospitalized, unable or unwilling to provide informed consent, or who are undergoing a limited echocardiogram will be excluded.
Key inclusion criteria (3 listed)
- Adults aged 18 years and older
- Able and willing to provide informed consent
- Completed a clinical echocardiogram or right heart catheterization within 7 days before or after study procedures
Key exclusion criteria (3 listed)
- Unwilling or unable to provide informed consent
- Patients who are hospitalized
- Patients undergoing echocardiography with a limited echocardiogram (does not apply to patients undergoing right heart catheterization)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Eko CORE 500 Digital StethoscopeThe FDA-cleared Eko CORE 500 digital stethoscope is used to collect phonocardiogram (PCG) and three-lead ECG recordings from participants. This observational study uses these recordings to develop and validate artificial intelligence algorithms to detect pulmonary hypertension and low left ventricular ejection fraction. No modifications to the device or device functionality are being tested. | Device | All Participants |
Primary outcome
Sensitivity and specificity of the deep-learning algorithm for detecting pulmonary hypertension (PH)
Time frame: Up to 24 months
The primary outcome is the diagnostic performance of the algorithm developed from Eko CORE 500 recordings to detect pulmonary hypertension, as confirmed by clinical echocardiography or right heart catheterization. Sensitivity and specificity will be calculated by comparing algorithm predictions to the echocardiogram or right heart catheterization gold standard.
1 secondary outcome
Algorithm Diagnostic Performance for Detection of Low Ejection Fraction
Time frame: Through study completion, 2 years
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 18 Jun 2026.
- Background: PubMed 30545972Frost A, Badesch D, Gibbs JSR, Gopalan D, Khanna D, Manes A, Oudiz R, Satoh T, Torres F, Torbicki A. Diagnosis of pulmonary hypertension. Eur Respir J. 2019 Jan 24;53(1):1801904. doi: 10.1183/13993003.01904-2018. Print 2019 Jan.
- Background: PubMed 26873944Maron BA, Hess E, Maddox TM, Opotowsky AR, Tedford RJ, Lahm T, Joynt KE, Kass DJ, Stephens T, Stanislawski MA, Swenson ER, Goldstein RH, Leopold JA, Zamanian RT, Elwing JM, Plomondon ME, Grunwald GK, Baron AE, Rumsfeld JS, Choudhary G. Association of Borderline Pulmonary Hypertension With Mortality and Hospitalization in a Large Patient Cohort: Insights From the Veterans Affairs Clinical Assessment, Reporting, and Tracking Program. Circulation. 2016 Mar 29;133(13):1240-8. doi: 10.1161/CIRCULATIONAHA.115.020207. Epub 2016 Feb 12.
- Background: PubMed 29071338Assad TR, Maron BA, Robbins IM, Xu M, Huang S, Harrell FE, Farber-Eger EH, Wells QS, Choudhary G, Hemnes AR, Brittain EL. Prognostic Effect and Longitudinal Hemodynamic Assessment of Borderline Pulmonary Hypertension. JAMA Cardiol. 2017 Dec 1;2(12):1361-1368. doi: 10.1001/jamacardio.2017.3882.
- Background: PubMed 31146810Strange G, Stewart S, Celermajer DS, Prior D, Scalia GM, Marwick TH, Gabbay E, Ilton M, Joseph M, Codde J, Playford D; NEDA Contributing Sites. Threshold of Pulmonary Hypertension Associated With Increased Mortality. J Am Coll Cardiol. 2019 Jun 4;73(21):2660-2672. doi: 10.1016/j.jacc.2019.03.482.
- Background: PubMed 24902739Choudhary G, Jankowich M, Wu WC. Elevated pulmonary artery systolic pressure predicts heart failure admissions in African Americans: Jackson Heart Study. Circ Heart Fail. 2014 Jul;7(4):558-64. doi: 10.1161/CIRCHEARTFAILURE.114.001366. Epub 2014 Jun 5.
- Background: PubMed 23811965Maron BA, Choudhary G, Khan UA, Jankowich MD, McChesney H, Ferrazzani SJ, Gaddam S, Sharma S, Opotowsky AR, Bhatt DL, Rocco TP, Aragam JR. Clinical profile and underdiagnosis of pulmonary hypertension in US veteran patients. Circ Heart Fail. 2013 Sep 1;6(5):906-12. doi: 10.1161/CIRCHEARTFAILURE.112.000091. Epub 2013 Jun 27.
- Background: PubMed 30617318Attia ZI, Kapa S, Lopez-Jimenez F, McKie PM, Ladewig DJ, Satam G, Pellikka PA, Enriquez-Sarano M, Noseworthy PA, Munger TM, Asirvatham SJ, Scott CG, Carter RE, Friedman PA. Screening for cardiac contractile dysfunction using an artificial intelligence-enabled electrocardiogram. Nat Med. 2019 Jan;25(1):70-74. doi: 10.1038/s41591-018-0240-2. Epub 2019 Jan 7.
- Background: PubMed 39895552Guo L, Khobragade N, Kieu S, Ilyas S, Nicely PN, Asiedu EK, Lima FV, Currie C, Lastowski E, Choudhary G. Development and Evaluation of a Deep Learning-Based Pulmonary Hypertension Screening Algorithm Using a Digital Stethoscope. J Am Heart Assoc. 2025 Feb 4;14(3):e036882. doi: 10.1161/JAHA.124.036882. Epub 2025 Feb 3.
- Background: PubMed 25343585Colman R, Whittingham H, Tomlinson G, Granton J. Utility of the physical examination in detecting pulmonary hypertension. A mixed methods study. PLoS One. 2014 Oct 24;9(10):e108499. doi: 10.1371/journal.pone.0108499. eCollection 2014.
- Background: PubMed 39983614Guo L, Pressman GS, Kieu SN, Marrus SB, Mathew G, Prince J, Lastowski E, McDonough RV, Currie C, Tiwari U, Maidens JN, Al-Sudani H, Friend E, Padmanabhan D, Kumar P, Kersh E, Venkatraman S, Qamruddin S. Automated Detection of Reduced Ejection Fraction Using an ECG-Enabled Digital Stethoscope: A Large Cohort Validation. JACC Adv. 2025 Mar;4(3):101619. doi: 10.1016/j.jacadv.2025.101619. Epub 2025 Feb 20.
- Background: PubMed 16567599Marcus GM, Vessey J, Jordan MV, Huddleston M, McKeown B, Gerber IL, Foster E, Chatterjee K, McCulloch CE, Michaels AD. Relationship between accurate auscultation of a clinically useful third heart sound and level of experience. Arch Intern Med. 2006 Mar 27;166(6):617-22. doi: 10.1001/archinte.166.6.617.
- Individual participant dataSharing planned: No. Authorized study personnel will be responsible for collecting clinical research data and maintaining a Master File that links Key-Coded IDs to participant identifiers. The Master File and signed informed consent forms will be securely stored with access limited to study personnel and will not be shared with the sponsor. De-identified data, including Eko recordings and demographic/clinical data from the EHR, will be entered under a Key-Coded ID and shared electronically with the sponsor via secure, password-protected systems. No personal identifiers will be stored or exported in any shared data files.
Related trials for Hypertension, Pulmonary
Not yet recruitingPhase 3
Intraarterial Therapies Plus Tislelizumab Plus Lenvatinib Versus Tislelizumab Plus Gemcitabine-Cisplatin in Unresectable Intrahepatic Cholangiocarcinoma
Intrahepatic Cholangiocarcinoma (Icc)
RecruitingObservational study
Natural History of Noncirrhotic Portal Hypertension
Cystic Fibrosis, Immunologic Deficiency Syndrome
RecruitingPhase 3
Efficacy and Safety Study of Treprostinil Palmitil Inhalation Powder (TPIP) in Participants With Pulmonary Hypertension Associated With Interstitial Lung Disease (PH-ILD)
Pulmonary Hypertension, Interstitial Lung Disease
RecruitingPhase 2
Study of REGN13335 in Adult Participants With Pulmonary Arterial Hypertension (PAH)
Pulmonary Arterial Hypertension (PAH)
Active, not recruitingObservational study
TrEatment Approach in the Multimodal Era Registry
Chronic Thromboembolic Pulmonary Hypertension, CTEPH
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Rose McDonough, MD study director
Senior Manager, Medical Affairs
4 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Hypertension, Pulmonary and Heart Failure With Reduced Ejection Fraction, run by Eko Devices, Inc. at 4 sites in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 18 Jun 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 4 sites in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Nicole Sutter (707-280-7059, colie.sutter@ekohealth.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Sensitivity and specificity of the deep-learning algorithm for detecting pulmonary hypertension (PH) (time frame: Up to 24 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07087613, which also lists 11 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 18 Jun 2026.