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Blinded Randomized Controlled Trial of Artificial Intelligence Guided Detection of Intracardiac Thrombus

Not Applicable
Not yet recruiting
Conditions
Atrial Fibrillation
Interventions
Other: Electrophysiologist judgment of the intracardiac thrombus
Other: Automated detection of the intracardiac thrombus through deep learning
Registration Number
NCT06206187
Lead Sponsor
Shanghai Chest Hospital
Brief Summary

To determine whether an integrated AI decision support can save time and improve the accuracy of detection of intracardiac thrombus, the investigators are conducting a blinded, randomized controlled study of AI-guided detection of intracardiac thrombus to electrophysiologist judgment in preliminary readings of echocardiograms.

Detailed Description

Not available

Recruitment & Eligibility

Status
NOT_YET_RECRUITING
Sex
All
Target Recruitment
1500
Inclusion Criteria
  1. Aged 18-80 years.
  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
  1. End-stage disease with a mean life expectancy less than 1 year
  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.

Study & Design

Study Type
INTERVENTIONAL
Study Design
PARALLEL
Arm && Interventions
GroupInterventionDescription
Electrophysiologist judgmentElectrophysiologist judgment of the intracardiac thrombus-
Artificial Intelligence DetectionAutomated detection of the intracardiac thrombus through deep learning-
Primary Outcome Measures
NameTimeMethod
Degree of change from initial (AI vs EP doctor) assessment to final cardiologist assessment10 Minutes
Secondary Outcome Measures
NameTimeMethod
Perioperative adverse event rates10 Minutes

Trial Locations

Locations (1)

Shanghai Chest Hospital

🇨🇳

Shanghai, 上海市, China

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