Blinded Randomized Controlled Trial of Artificial Intelligence Guided Detection of Intracardiac Thrombus
NCT ID: NCT06206187
Last Updated: 2024-01-16
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.
NOT_YET_RECRUITING
NA
1500 participants
INTERVENTIONAL
2024-01-05
2025-12-31
Brief Summary
Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.
Related Clinical Trials
Explore similar clinical trials based on study characteristics and research focus.
Safety and Efficacy Study of AI LVEF
NCT05140642
Artificial Intelligence (AI) Analysis of Synchronized Phonocardiography (PCG) and Electrocardiogram(ECG)
NCT06009718
Artificial Intelligence-assisted Diagnosis and Prognostication in Low Ejection Fraction Using Electrocardiograms
NCT05117970
Intra-Cardiac Echocardiography Guided Cardioversion(ICE-CHIP) Study
NCT00281073
Foresight Intracardiac Echocardiography (ICE) System
NCT02514876
Detailed Description
Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.
Conditions
See the medical conditions and disease areas that this research is targeting or investigating.
Study Design
Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.
RANDOMIZED
PARALLEL
DIAGNOSTIC
SINGLE
Study Groups
Review each arm or cohort in the study, along with the interventions and objectives associated with them.
Electrophysiologist judgment
Electrophysiologist judgment of the intracardiac thrombus
Cardiac electrophysiologists use their own experience to determine whether there is intracardiac thrombus
Artificial Intelligence Detection
Automated detection of the intracardiac thrombus through deep learning
A deep learning model will identify the intracardiac thrombus. The AI model will produce an assessment of intracardiac thrombus using video based features.
Interventions
Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.
Automated detection of the intracardiac thrombus through deep learning
A deep learning model will identify the intracardiac thrombus. The AI model will produce an assessment of intracardiac thrombus using video based features.
Electrophysiologist judgment of the intracardiac thrombus
Cardiac electrophysiologists use their own experience to determine whether there is intracardiac thrombus
Eligibility Criteria
Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.
Inclusion Criteria
2. Willing to sign informed consent.
3. Patients diagnosed with atrial fibrillation Paroxysmal AF and Persistent AF according to the latest clinical guidelines
Exclusion Criteria
2. New York Heart Association (NYHA) class III or IV, or last known left ventricular ejection fraction less than 30%
3. Previous surgical or catheter ablation for AF
4. Bradycardia and presence of implanted ICD
5. Uncontrolled hypertension: Systolic blood pressure (SBP) \>180 mmHg or diastolic blood pressure (DBP) \> 110 mmHg
6. Patients with Cardiovascular events including acute myocardial infarction, any PCI, valvular cardiac surgical, or percutaneous procedure within the past 3 months
7. Women of childbearing potential who are, or plan to become, pregnant during the time of the study
8. Have been enrolled in an investigational study evaluating devices or drugs.
18 Years
90 Years
ALL
Yes
Sponsors
Meet the organizations funding or collaborating on the study and learn about their roles.
Johnson & Johnson
INDUSTRY
Shanghai Chest Hospital
OTHER
Responsible Party
Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.
Xu Liu
professor
Locations
Explore where the study is taking place and check the recruitment status at each participating site.
Shanghai Chest Hospital
Shanghai, Shanghai Municipality, China
Countries
Review the countries where the study has at least one active or historical site.
Central Contacts
Reach out to these primary contacts for questions about participation or study logistics.
Facility Contacts
Find local site contact details for specific facilities participating in the trial.
Other Identifiers
Review additional registry numbers or institutional identifiers associated with this trial.
ICE Detector-RCT
Identifier Type: -
Identifier Source: org_study_id
More Related Trials
Additional clinical trials that may be relevant based on similarity analysis.