Heart FailureNCT06009718
Artificial Intelligence (AI) Analysis of Synchronized Phonocardiography (PCG) and Electrocardiogram(ECG)
An observational study of Heart Failure, run by Ruijin Hospital at 3 sites in China.
Trial summary
The diagnosis of depressed left ventricular ejection fraction (dLVEF) (EF<50%) depends on golden standard ultrasound cardiography (UCG). A wearable synchronized phonocardiography (PCG) and electrocardiogram (ECG) device can assist in the diagnosis of dLVEF, which can both expedite access to life-saving therapies and… Read more about this study
- Who is it for?
- Ages 18 to 100 years
- Conditions the study is for
- Heart Failure
- How many people
- 3,000 participants
- Where
- 3 sitesChina
- Study dates
- 25 Aug 2023to 1 Jun 2028
- 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 to 100 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: This is one-center cohort study. Patients undergo echocardiogram at Ruijin Hospital.
Who may be able to join
- Attendance at RuiJin hospital for UCG
- Signed dated informed consent
- Commit to follow the research procedures and cooperate in the implementation of the whole process research
- UCG has been completed
- Age ≥ 18
- At least 8 consecutive cycles of sinus rhythm can be recorded
Who cannot join
- Patients with pacemakers
- Complete left bundle branch block or block or QRS wave widening>120ms
- Left chest skin damaged or allergic to patch
- Refusal to participate
Trial locations and contacts
3 sites in 1 country. Contact the study team or a site near you to ask about taking part.
China3 sites, 3 recruiting
- Recruiting
Ruijin Hospital, Shanghai Jiaotong School of Medicine
Shanghai, 200025
Wenli Zhang, MD, +86 021 64370045, 13917615339@163.com
Ruiyan Zhang, MD, PhD
- Recruiting
Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine
Shanghai, 200030
Jingjuan Huang, MD，PhD, +86 021 22200000, hjjxinhua@163.com
Ruogu Li, MD，PhD
- Recruiting
Shanghai East Hospital
Shanghai, 200123
Min Chen, MD, +86 15900727844, 1427926201@qq.com
Min Chen, MD
About this study
Official title: A Deep-learning-based Multi-modal Phonocardiogram(PCG) and Electrocardiogram(ECG) Processing Framework for Screening Depressed Left Ventricular Ejection Fraction (dLVEF) Using a Wearable Cardiac Patch
The diagnosis of depressed left ventricular ejection fraction (dLVEF) (EF<50%) depends on golden standard ultrasound cardiography (UCG). A wearable synchronized phonocardiography (PCG) and electrocardiogram (ECG) device can assist in the diagnosis of dLVEF, which can both expedite access to life-saving therapies and reduce the need for costly testing.
Read the detailed description
The synchronized PCG and ECG is wirelessly paired with the WenXin Mobile application, allowing for simultaneous recording and visualization of PCG and ECG. These features uniquely enable this device to accumulate large sets of acoustic data on patients both with and without heart failure(HF).
This study is a Case-control study. In this study, the investigators seek to develop an artificial intelligence (AI) analysis system to identify dLVEF (EF<50%) by PCG and ECG. All adults (aged ≥18 years) planned for UCG were eligible to participate (inpatients and outpatients). Specifically, the investigators will attempt to develop machine learning algorithms to learn synchronized PCG and ECG of patients with dLVEF. Then we use these algorithms to identify dLVEF subjects. The investigators anticipate to demonstrate the wearable cardiac patch with synchronized PCG and ECG can reliably and accurately diagnose dLVEF in the primary care setting.
- Conditions
- Heart Failure
- Keywords
- Phonocardiography (PCG), Electrocardiogram (ECG), Heart Failure (HF), depressed left ventricular ejection fraction (dLVEF)
- Medical subject headings
- Heart Failure
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Model training group | Compare the results of PCG and ECG with UCG, and conduct model training analysis | |
| Model validation group | Compare the results of PCG and ECG with UCG, and conduct model validation analysis |
What is being measured
The primary outcome is the main question the study is designed to answer.
Determination of Heart Failure Disease
Heart Failure Disease was determined by EMAT （millisecond, ms）calculate from synchronized PCG and ECG signals using an artificial intelligence (AI) guided model.
Measured: one time assessment at baseline (approx. 5 minutes)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Aug 2023
- Study start25 Aug 2023
- Primary completion1 Jun 2027 (estimated)
- Study completion1 Jun 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Heart FailureStudies of the same condition, open and under way.
- More trials run by Ruijin HospitalThe 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
- Case-control
- Time perspective
- Prospective
- Enrolment
- 3,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Ruijin Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, RUIYAN ZHANG, Ruijin Hospital
- Investigators
- Ruiyan Zhang, MD, PhD, Principal investigator, Ruijin Hospital, Shanghai Jiaotong School of MedicineWenli Zhang, MD, Study director, Ruijin Hospital, Shanghai Jiaotong School of MedicineBei Song, MD, Study chair, Ruijin Hospital, Shanghai Jiaotong School of Medicine
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06009718
- Sponsor's protocol ID
- RJH-PEG
- Status last verified
- Jan 2025
- First submitted
- 6 Jul 2023
- Last updated
- 16 Jan 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 16 Jan 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Deep-learning-based Multi-modal Phonocardiogram(PCG) and Electrocardiogram(ECG) Processing Framework for Screening Depressed Left Ventricular Ejection Fraction (dLVEF) Using a Wearable Cardiac Patch
- ClinicalTrials.gov ID
- NCT06009718
- Acronym / sponsor ID
- RJH-PEG
- Conditions
- Heart Failure
- Keywords
- Phonocardiography (PCG), Electrocardiogram (ECG), Heart Failure (HF), depressed left ventricular ejection fraction (dLVEF)
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 3,000 participants (estimated)
- Lead sponsor
- Ruijin HospitalUniversity, hospital or other
- Study start
- 25 Aug 2023 (actual)
- Primary completion
- 1 Jun 2027 (estimated)
- Study completion
- 1 Jun 2028 (estimated)
- First posted
- 24 Aug 2023 (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.
The diagnosis of depressed left ventricular ejection fraction (dLVEF) (EF<50%) depends on golden standard ultrasound cardiography (UCG). A wearable synchronized phonocardiography (PCG) and electrocardiogram (ECG) device can assist in the diagnosis of dLVEF, which can both expedite access to life-saving therapies and reduce the need for costly testing.
Detailed description
The synchronized PCG and ECG is wirelessly paired with the WenXin Mobile application, allowing for simultaneous recording and visualization of PCG and ECG. These features uniquely enable this device to accumulate large sets of acoustic data on patients both with and without heart failure(HF).
This study is a Case-control study. In this study, the investigators seek to develop an artificial intelligence (AI) analysis system to identify dLVEF (EF<50%) by PCG and ECG. All adults (aged ≥18 years) planned for UCG were eligible to participate (inpatients and outpatients). Specifically, the investigators will attempt to develop machine learning algorithms to learn synchronized PCG and ECG of patients with dLVEF. Then we use these algorithms to identify dLVEF subjects. The investigators anticipate to demonstrate the wearable cardiac patch with synchronized PCG and ECG can reliably and accurately diagnose dLVEF in the primary care setting.
Study design
- Observational model
- Case-control
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Model training group | – | –Compare the results of PCG and ECG with UCG, and conduct model training analysis |
| Model validation group | – | –Compare the results of PCG and ECG with UCG, and conduct model validation analysis |
Who may qualify
- Ages
- 18 to 100 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- This is one-center cohort study. Patients undergo echocardiogram at Ruijin Hospital.
Key inclusion criteria (6 listed)
- Attendance at RuiJin hospital for UCG
- Signed dated informed consent
- Commit to follow the research procedures and cooperate in the implementation of the whole process research
- UCG has been completed
- Age ≥ 18
Key exclusion criteria (4 listed)
- Patients with pacemakers
- Complete left bundle branch block or block or QRS wave widening>120ms
- Left chest skin damaged or allergic to patch
- Refusal to participate
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Determination of Heart Failure Disease
Time frame: one time assessment at baseline (approx. 5 minutes)
Heart Failure Disease was determined by EMAT （millisecond, ms）calculate from synchronized PCG and ECG signals using an artificial intelligence (AI) guided model.
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 16 Jan 2025.
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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.
Ruiyan Zhang, MD, PhD principal investigator
Ruijin Hospital, Shanghai Jiaotong School of Medicine
Wenli Zhang, MD study director
Ruijin Hospital, Shanghai Jiaotong School of Medicine
Bei Song, MD study chair
Ruijin Hospital, Shanghai Jiaotong School of Medicine
3 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Heart Failure, run by Ruijin Hospital at 3 sites in China.
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 6 inclusion and 4 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 16 Jan 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 3 sites in China. 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 Wenli Zhang, MD (+86 21 13917615339, zwl11929@rjh.com.cn), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Determination of Heart Failure Disease (time frame: one time assessment at baseline (approx. 5 minutes)). 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 16 Jan 2025.