NL-OMON56279
Not yet recruiting
Not Applicable
Machine Learning and Artificial Intelligence for Early Detection of Stroke and Atrial Fibrillation - MAESTRIA-AFNET 10
Kompetenznetz Vorhofflimmern e.V./Atrial Fibrillation NETwork (AFNET)0 sites150 target enrollmentTBD
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Not specified
- Sponsor
- Kompetenznetz Vorhofflimmern e.V./Atrial Fibrillation NETwork (AFNET)
- Enrollment
- 150
- Status
- Not yet recruiting
- Last Updated
- 2 years ago
Overview
Brief Summary
No summary available.
Investigators
Eligibility Criteria
Inclusion Criteria
- •1\. Patients with paroxysmal AF (clinically defined as AF episodes less than one
- •patients with persistent AF (clinically defined as AF episodes longer than one
- •or patients with permanent AF (no documented sinus rhythm or possibility to
- •restore sinus rhythm by any means).
- •2\. Patient (or legally acceptable representative if applicable) provides
- •written Informed Consent to participate in the study. The patient has the
- •option to give separate consent to donate extra volume of blood during routine
- •blood collection, that can be used for biomedical research.
- •3\. Patient is at least 18 years of age.
- •4\. Patient must own a Smartphone with Apple iOS Version 14\.5 (or higher) or
Exclusion Criteria
- •1\. Any disease that limits life expectancy to less than 1 year.
- •2\. All persons unable to provide informed consent.
- •3\. All persons exempt from participation in a study or trial by law.
- •4\. Any medical or psychiatric condition which, in the Investigator\*s opinion,
- •would preclude the participant from adhering to the protocol or completing the
- •study per protocol.
Outcomes
Primary Outcomes
Not specified
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