Prevention of Stroke and Sudden Cardiac Death by Recording of 1-Channel Electrocardiograms (PRICE)

A-Rhythmik

Status: Unknown

Conditions: Ventricular Tachycardia, Nonsustained; Atrial Fibrillation; Ventricular Premature Complexes; Sinus Rhythm; Atrial Premature Complexes

Treatments: Diagnostic Test: Electrocardiogram analysis by Artificial Intelligence

Study type: Observational

Funder types: Other

Identifiers

NCT04637230

20-139

Details and patient eligibility

About

Single-channel electrocardiograms (lead I of 12-lead surface ECG; 30 seconds) will be collected from subjects/patients at 11 clinical centers in Germany to train an Artificial Intelligence in the automatic diagnosis of regular and irregular heart rhythms. Heart rhythms of interest are normal sinus rhythm (SR), atrial fibrillation (AF), atrial premature beats (APBs), ventricular premature beats (VPBs), and nonsustained ventricular tachycardia (VT). Per diagnosis, 20,000 ECGs are required, for a total of 100,000 ECGs to be obtained from approximately 10,000 subjects/patients.

Full description

In phase 1 of a research project titled 'Prevention of stroke and sudden cardiac death by Recording of 1-Channel Electrocardiograms' (PRICE), a total of 100,000 30-sec single-channel ECGs (lead I of 12-lead surface ECG) will be collected from approximately 10,000 subjects/patients at 11 participating clinical centers in Germany. Relevant baseline clinical patient characteristics will also be recorded. The ECGs, diagnosed by an experienced electrophysiologist (diagnostic gold standard), will be fed into an Artificial Intelligence (AI) for the automatic detection of normal sinus rhythm (SR), atrial fibrillation (AF), atrial premature beats (APBs), ventricular premature beats (VPBs), and nonsustained ventricular tachycardia (VT). It is expected that the overall diagnostic accuracy of the AI against an experienced electrophysiologist will be on the order of 95%.

In PRICE phase 2, ECG diagnosis by the AI will be compared with the diagnosis by 3 general cardiologists of the same ECGs. It is expected that the AI will surpass the general cardiologists in terms of diagnostic accuracy.

The final clinical phase of the PRICE project will comprise a randomized controlled community trial of risk patients to establish the superiority in stroke prevention of AI detection of AF on smart-watch ECGs vs. no AF detection.

Enrollment: 10,000 estimated patients

Sex: All

Ages: 18 to 85 years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• Heart rhythm of interest present on ECG

Exclusion criteria

• Patient incapable of or not willing to sign informed consent form

Trial design

10,000 participants in 5 patient groups

Sinus Rhythm

Description:

Subjects/patients in normal sinus rhythm

Treatment:

Diagnostic Test: Electrocardiogram analysis by Artificial Intelligence

Atrial Fibrillation

Description:

Patients with atrial fibrillation

Treatment:

Diagnostic Test: Electrocardiogram analysis by Artificial Intelligence

Atrial Premature Complexes

Description:

Patients with atrial premature complexes in between sinus beats

Treatment:

Diagnostic Test: Electrocardiogram analysis by Artificial Intelligence

Ventricular Premature Complexes

Description:

Patients with ventricular premature complexes in between sinus beats

Treatment:

Diagnostic Test: Electrocardiogram analysis by Artificial Intelligence

Ventricular Tachycardia, Nonsustained

Description:

Patients with episodes of nonsustained ventricular tachycardia in between sinus beats

Treatment:

Diagnostic Test: Electrocardiogram analysis by Artificial Intelligence