Artificial Intelligence (AI) Analysis of Synchronized Phonocardiography (PCG) and Electrocardiogram(ECG)
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
1 other identifier
observational
3,000
1 country
3
Brief 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 reduce the need for costly testing.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Aug 2023
Longer than P75 for all trials
3 active sites
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
July 6, 2023
CompletedFirst Posted
Study publicly available on registry
August 24, 2023
CompletedStudy Start
First participant enrolled
August 25, 2023
CompletedPrimary Completion
Last participant's last visit for primary outcome
June 1, 2027
ExpectedStudy Completion
Last participant's last visit for all outcomes
June 1, 2028
January 16, 2025
January 1, 2025
3.8 years
July 6, 2023
January 14, 2025
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
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.
one time assessment at baseline (approx. 5 minutes)
Study Arms (2)
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
Eligibility Criteria
This is one-center cohort study. Patients undergo echocardiogram at Ruijin Hospital.
You may qualify if:
- 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
You may not qualify if:
- 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
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Ruijin Hospitallead
Study Sites (3)
Ruijin Hospital, Shanghai Jiaotong School of Medicine
Shanghai, 200025, China
Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine
Shanghai, 200030, China
Shanghai East Hospital
Shanghai, 200123, China
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Ruiyan Zhang, MD, PhD
Ruijin Hospital, Shanghai Jiaotong School of Medicine
- STUDY DIRECTOR
Wenli Zhang, MD
Ruijin Hospital, Shanghai Jiaotong School of Medicine
- STUDY CHAIR
Bei Song, MD
Ruijin Hospital, Shanghai Jiaotong School of Medicine
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- CASE CONTROL
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Director of Cardiology Department, Chief Physician
Study Record Dates
First Submitted
July 6, 2023
First Posted
August 24, 2023
Study Start
August 25, 2023
Primary Completion (Estimated)
June 1, 2027
Study Completion (Estimated)
June 1, 2028
Last Updated
January 16, 2025
Record last verified: 2025-01