Pulmonary HypertensionPULSARNCT07147725
Pulmonary Arterial Hypertension and Associated Cardiovascular Disease Detection Using Artificial Intelligence
An observational study of Pulmonary Hypertension and Cardiovascular Diseases (CVD), run by Imperial College London at 1 site in United Kingdom.
Trial summary
Cardiovascular disease (CVD) is a leading global cause of morbidity and mortality and excessive healthcare expenditures. Pulmonary hypertension (PH) represents an insidious and progressive subset of CVD affecting an estimated 1% of the general population, increasing to up to 10% in the population over the age of 65. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Pulmonary Hypertension, Cardiovascular Diseases (CVD)
- What is being tested?
- AI Stethoscope
- Type of treatment
- Medical device
- How many people
- 1,000 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- 1 Oct 2025to 1 Aug 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
- Healthy volunteers accepted
- Adult, Older adult
Study population: All-comers to echocardiography (n=1,000) will be approached for participation by a member of the research team i.e. identification by virtue of presence in the Imperial College NHS echocardiography department whilst attending routine care, gold-standard investigation.
Who may be able to join
- Age 18 years or above
- Able to give informed consent
- Attending for echocardiography at Imperial College NHS Trust
Who cannot join
- Any chest wound, skin pathology or other feature that would prohibit routine stethoscope examination
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Patrik Bächtiger, MD contact
United Kingdom1 site
Imperial College Healthcare NHS Trust
London
Nicholas S Peters, MD, +44 (0) 207 594 1880, n.peters@imperial.ac.uk
About this study
Cardiovascular disease (CVD) is a leading global cause of morbidity and mortality and excessive healthcare expenditures. Pulmonary hypertension (PH) represents an insidious and progressive subset of CVD affecting an estimated 1% of the general population, increasing to up to 10% in the population over the age of 65. Recent advancements in artificial intelligence (AI) have shown promise in transforming PH diagnosis by enabling the analysis of complex physiological data. Specifically, AI algorithms applied to electrocardiography (ECG) and phonocardiography (PCG) waveforms captured through novel medical devices, such as smart stethoscopes, have demonstrated potential in detecting PH and other cardiovascular conditions with high sensitivity and specificity.
Despite the promising capabilities of AI algorithms, a significant barrier to their clinical implementation is the lack of high-quality, prospectively collected datasets for validation. Many existing AI algorithms have been trained on retrospective data, which may not capture the variability and complexity of real-world clinical scenarios. This limitation raises concerns about the generalisability and reliability of AI predictions across diverse patient populations.
Therefore, there is a critical need for prospective validation studies to assess the performance of AI algorithms in realworld settings, ensuring their accuracy and applicability before widespread clinical deployment. Imperial College London's Health Impact Lab (Hi Lab) and collaborators continue to develop artificial intelligence (AI) algorithms that use cardiac waveforms to predict cardiovascular disease (CVD), including pulmonary hypertension (PH). The performance of these algorithms requires validation on prospectively collected patient data (waveforms) - where the ground truth for the algorithms under investigation is recorded during routine echocardiography as part of clinical care. This study aims to prospectively collect a large dataset of cardiovascular ECG and PCG data, along with corresponding gold-standard echocardiography findings. This dataset will be used to validate AI algorithms for important CVD, such as pulmonary hypertension enhancing their reliability and clinical applicability.
Read the detailed description
This prospective observational cohort and validation study aims to create a patient dataset of point-of-care cardiovascular waveforms for validation of Imperial College London artificial intelligence (AI) algorithms trained for the detection of cardiovascular disease (CVD), using said waveforms as input, with a focus on pulmonary hypertension (PH).
The study will recruit 1,000 unselected patients attending Imperial College Healthcare NHS Trust for routine echocardiography. Each patient will undergo a non-invasive examination using a smart stethoscope that records 3- lead electrocardiogram (ECG) and phonocardiogram (PCG) waveforms, in addition to the standard echocardiography parameters. Baseline demographic data and medical history will also be collected, and a chart review will be performed at 24 months to capture any subsequent morbidity or mortality. The study will validate the AI algorithms by comparing their performance to echocardiography results, the current gold standard for CVD diagnosis. The primary outcome measures will include performance characteristics - sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and F-1 Score of the AI algorithm in detecting CVD.
- Being tested
- AI Stethoscope
- Keywords
- Artificial Intelligence, Algorithms, Digital Health, Cardiology
- Medical subject headings
- Hypertension, Pulmonary, Cardiovascular Diseases
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI StethoscopeDevice
Patients attending routine echocardiography who satisfy the inclusion and exclusion criteria will be approached before their echocardiography appointment to obtain informed consent to participate in the study. On providing informed consent, each patient will receive a non-invasive, external examination with a smart stethoscope that records a 3-lead electrocardiogram (ECG) and phonocardiogram (PCG) waveforms. This examination will require only one study visit (during routine echocardiography) and no additional visits. The stethoscope is a fully CE-marked device.
In addition to echocardiography parameters and smart stethoscope waveforms, baseline demographics, clinical and medication history will be recorded. These data points will be re-examined at 24 months following enrolment (via chart review).
What is being measured
The primary outcome is the main question the study is designed to answer.
Performance characteristics for developed algorithms
Performance characteristics for developed algorithms (external validation). Performance characteristics include area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio, negative likelihood ratio and and F1 Score of the AI algorithm in detecting the condition of interest e.g. PH, compared to echocardiography (ground truth).
Measured: 24 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Aug 2025
- Study start1 Oct 2025 (estimated)
- Primary completion1 Dec 2025 (estimated)
- Study completion1 Aug 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Pulmonary HypertensionStudies of the same condition, open and under way.
- More trials run by Imperial College LondonThe sponsor's other registered studies.
- 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
- 1,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Imperial College London
- Sponsor type
- University, hospital or other
- Collaborators
- Imperial College Healthcare NHS Trust
- Responsible party
- Sponsor
- Investigators
- Nicholas S Peters, MD, Principal investigator, Imperial College London
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07147725
- Sponsor's protocol ID
- 25NW0182
- Acronym
- PULSAR
- Status last verified
- Sep 2025
- First submitted
- 22 Aug 2025
- Last updated
- 23 Sep 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 23 Sep 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Pulmonary Arterial Hypertension and Associated Cardiovascular Disease Detection Using Artificial Intelligence
- ClinicalTrials.gov ID
- NCT07147725
- Acronym / sponsor ID
- PULSAR / 25NW0182
- Keywords
- Artificial Intelligence, Algorithms, Digital Health, Cardiology
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 1,000 participants (estimated)
- Lead sponsor
- Imperial College LondonUniversity, hospital or other
- Collaborators
- Imperial College Healthcare NHS Trust
- Study start
- 1 Oct 2025 (estimated)
- Primary completion
- 1 Dec 2025 (estimated)
- Study completion
- 1 Aug 2027 (estimated)
- First posted
- 29 Aug 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.
Cardiovascular disease (CVD) is a leading global cause of morbidity and mortality and excessive healthcare expenditures. Pulmonary hypertension (PH) represents an insidious and progressive subset of CVD affecting an estimated 1% of the general population, increasing to up to 10% in the population over the age of 65. Recent advancements in artificial intelligence (AI) have shown promise in transforming PH diagnosis by enabling the analysis of complex physiological data. Specifically, AI algorithms applied to electrocardiography (ECG) and phonocardiography (PCG) waveforms captured through novel medical devices, such as smart stethoscopes, have demonstrated potential in detecting PH and other cardiovascular conditions with high sensitivity and specificity.
Despite the promising capabilities of AI algorithms, a significant barrier to their clinical implementation is the lack of high-quality, prospectively collected datasets for validation. Many existing AI algorithms have been trained on retrospective data, which may not capture the variability and complexity of real-world clinical scenarios. This limitation raises concerns about the generalisability and reliability of AI predictions across diverse patient populations.
Therefore, there is a critical need for prospective validation studies to assess the performance of AI algorithms in realworld settings, ensuring their accuracy and applicability before widespread clinical deployment. Imperial College London's Health Impact Lab (Hi Lab) and collaborators continue to develop artificial intelligence (AI) algorithms that use cardiac waveforms to predict cardiovascular disease (CVD), including pulmonary hypertension (PH). The performance of these algorithms requires validation on prospectively collected patient data (waveforms) - where the ground truth for the algorithms under investigation is recorded during routine echocardiography as part of clinical care. This study aims to prospectively collect a large dataset of cardiovascular ECG and PCG data, along with corresponding gold-standard echocardiography findings. This dataset will be used to validate AI algorithms for important CVD, such as pulmonary hypertension enhancing their reliability and clinical applicability.
Detailed description
This prospective observational cohort and validation study aims to create a patient dataset of point-of-care cardiovascular waveforms for validation of Imperial College London artificial intelligence (AI) algorithms trained for the detection of cardiovascular disease (CVD), using said waveforms as input, with a focus on pulmonary hypertension (PH).
The study will recruit 1,000 unselected patients attending Imperial College Healthcare NHS Trust for routine echocardiography. Each patient will undergo a non-invasive examination using a smart stethoscope that records 3- lead electrocardiogram (ECG) and phonocardiogram (PCG) waveforms, in addition to the standard echocardiography parameters. Baseline demographic data and medical history will also be collected, and a chart review will be performed at 24 months to capture any subsequent morbidity or mortality. The study will validate the AI algorithms by comparing their performance to echocardiography results, the current gold standard for CVD diagnosis. The primary outcome measures will include performance characteristics - sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and F-1 Score of the AI algorithm in detecting CVD.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- All-comers to echocardiography (n=1,000) will be approached for participation by a member of the research team i.e. identification by virtue of presence in the Imperial College NHS echocardiography department whilst attending routine care, gold-standard investigation.
Key inclusion criteria (3 listed)
- Age 18 years or above
- Able to give informed consent
- Attending for echocardiography at Imperial College NHS Trust
Key exclusion criteria (1 listed)
- Any chest wound, skin pathology or other feature that would prohibit routine stethoscope examination
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 |
|---|---|---|
| AI StethoscopePatients attending routine echocardiography who satisfy the inclusion and exclusion criteria will be approached before their echocardiography appointment to obtain informed consent to participate in the study. On providing informed consent, each patient will receive a non-invasive, external examination with a smart stethoscope that records a 3-lead electrocardiogram (ECG) and phonocardiogram (PCG) waveforms. This examination will require only one study visit (during routine echocardiography) and no additional visits. The stethoscope is a fully CE-marked device. In addition to echocardiography parameters and smart stethoscope waveforms, baseline demographics, clinical and medication history will be recorded. These data points will be re-examined at 24 months following enrolment (via chart review). | Device | – |
Primary outcome
Performance characteristics for developed algorithms
Time frame: 24 months
Performance characteristics for developed algorithms (external validation). Performance characteristics include area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio, negative likelihood ratio and and F1 Score of the AI algorithm in detecting the condition of interest e.g. PH, compared to echocardiography (ground truth).
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 23 Sep 2025.
- Individual participant dataSharing planned: No
Related trials for Pulmonary Hypertension
Not yet recruitingPhase 2/3
An Open-Label Extension Study to Evaluate Inhaled Treprostinil SMI in Participants With Pulmonary Hypertension Associated With Chronic Obstructive Pulmonary Disease (PH-COPD)
Pulmonary Hypertension Associated With Chronic Obstructive Pulmonary Disease
Not yet recruitingPhase 2
Study of Treprostinil Administered Via Soft Mist Inhaler (SMI) in Participants With Pulmonary Hypertension Associated With Chronic Obstructive Pulmonary Disease (PH-COPD)
Pulmonary Hypertension Associated With Chronic Obstructive Pulmonary Disease
Active, not recruitingPhase 1
A Pilot Study of Microbiota Transplant With Antibiotic Preconditioning and Fiber Supplementation in Pulmonary Arterial Hypertension (GUT RESTORE-PAH)
Pulmonary Arterial Hypertension
RecruitingObservational study
Natural History Study of Biomarkers in Pulmonary Arterial Hypertension
Pulmonary Disease, Pulmonary Hypertension
Active, not recruitingPhase 1
Study of Intravenous ZMA001 in Healthy Subjects
Pulmonary Arterial Hypertension PAH
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.
Patrik Bächtiger, MD contact
Nicholas S Peters, MD principal investigator
Imperial College London
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Pulmonary Hypertension and Cardiovascular Diseases (CVD), run by Imperial College London at 1 site in United Kingdom.
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 1 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: opening soon, as of the sponsor's last update on 23 Sep 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United Kingdom. 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 Saloni Nakhare, MBChB, MSc (Email, s.nakhare@imperial.ac.uk), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Performance characteristics for developed algorithms (time frame: 24 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 23 Sep 2025.