This is a randomized controlled trial (RCT) to test a novel artificial intelligence (AI)-enabled electrocardiogram (ECG)-based screening tool for improving the diagnosis and management of Atrial Fibrillation.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
SCREENING
Masking
NONE
Enrollment
25,732
Primary care clinicians in the intervention group had access to the report, which displayed whether the AI-ECG result was positive or negative. The system will send a message to corresponding physicians if positive finding.
National Defense Medical Center
Taipei, Taiwan
Proportion of taking AF treatment medications
defined as use of long-term NOAC (apixaban, rivaroxaban, endoxaban, dabigatran).
Time frame: Within 90 days
Proportion of ischemic Stroke
After performing an electrocardiogram, the patient's physical conditions is tracked.
Time frame: Within 90 days
Proportion of cardiologist consultation
Cardiovascular outpatient visit after discovering atrial fibrillation.
Time frame: Within 90 days
Proportion of new-onset AF diagnosis
Atrial fibrillation diagnosis in medical records
Time frame: Within 90 days
Proportion of echocardiogram performed after ECGs
After performing the ECG examination, perform the echocardiography examination.
Time frame: Within 90 days
Proportion of new-onset heart failure
After performing an electrocardiogram, the patient's medical record is tracked.
Time frame: Within 90 days
Proportion of gastrointestinal bleeding
After performing an electrocardiogram, the patient's medical record is tracked.
Time frame: Within 90 days
Proportion of hemorrhagic stroke
After performing an electrocardiogram, the patient's medical record is tracked.
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Time frame: Within 90 days
Proportion of all cause mortality(death)
After performing an electrocardiogram, the patient's survival is tracked.
Time frame: Within 90 days