Early Detection of Atrial Fibrillation Using Mobile Technology in Cryptogenic Stroke Patients

Not Applicable

Recruiting

• Conditions: Cryptogenic Stroke; Atrial Fibrillation

• Registration Number: NCT05006105
• Lead Sponsor: Ziekenhuis Oost-Limburg

Brief Summary

The purpose of this study is to demonstrate the added value of mobile health (mHealth) to detect atrial fibrillation (AF) early in the care path of cryptogenic stroke and transient ischemic attack (TIA) patients.

Detailed Description

The use of photoplethysmography (PPG)-based mHealth (with smartphone and smartwatch) is compared to the guideline-recommended insertable loop recorders (ILR) in the detection of AF in cryptogenic stroke or TIA patients.

Study Timeline

• Study Start: 2020-10-12
• Study First Submitted: 2021-07-13
• Study First Submitted QC: 2021-08-06
• Study First Posted: 2021-08-16
• Status Verified: 2022-09
• Last Update Submitted: 2022-09-14
• Last Update Posted: 2022-09-16
• Primary Completion: 2025-02
• Study Completion: 2025-02

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 225

Inclusion Criteria

• Diagnosis of cryptogenic ischemic stroke or TIA
• The patient or its legal representative is willing to sign the informed consent

Exclusion Criteria

• History of AF or atrial flutter
• Life expectancy of less than one year
• Not qualified for ILR insertion
• Indication or contraindication for permanent oral anticoagulants (OAC) at enrolment
• Untreated hyperthyroidism
• Myocardial infarction or coronary bypass grafting less than one month before the stroke onset
• Presence of patent foramen ovale (PFO) and it is or was an indication to start OAC according to the European Stroke Organization guidelines
• Inclusion in another clinical trial that will affect the objectives of this study
• Not able to understand the Dutch language
• Patient or partner not in possession of a smartphone

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: PARALLEL

Primary Outcome Measures

Name	Time	Method
AF detection with mHealth versus ILR - Percentage	After 6 months of having an ILR inserted and using mHealth.	Percentage of patients with AF detected

Secondary Outcome Measures

Name	Time	Method
AF detection with mHealth versus ILR - Duration	Baseline until end of study (after 12 months of having an ILR inserted).	Duration of AF episodes
AF detection with ILR - Percentage	After 12 months of having an ILR inserted.	Percentage of patients with AF detected
AF detection with mHealth versus ILR - Time to first AF detection	Baseline until end of study (after 12 months of having an ILR inserted).	Time to first AF detection
AF detection with mHealth versus ILR - Frequency	Baseline until end of study (after 12 months of having an ILR inserted).	Frequency of AF episodes
User experience and feeling of safety questionnaire	After 6 months of having an ILR inserted and using mHealth.	Questionnaire with a 7 point Likert scale
Correlation between baseline characteristics and AF detection	Baseline until end of study (after 12 months of having an ILR inserted).	Baseline characteristics include comorbidities, results of standard of care in-hospital stroke examinations and scores, relevant in-hospital therapy
Correlation between follow-up characteristics and AF detection	Baseline until end of study (after 12 months of having an ILR inserted).	Follow-up characteristics include changes in therapy, number of relevant readmissions, mortality and healthcare-related costs

Trial Locations

Locations (2)

Ziekenhuist Oost-Limburg; 🇧🇪 Genk, Limburg, Belgium

Jessa Hospital; 🇧🇪 Hasselt, Limburg, Belgium