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CATCH AF - Atrial Fibrillation Detection in Cryptogenic Stroke
Sponsor: Medical University of Graz
Summary
Early detection of atrial fibrillation detected after stroke (AFDAS) is crucial for secondary stroke prevention, as initiating direct oral anticoagulants (DOACs) can reduce atrial fibrillation (AF)-related stroke risk by up to 60%. In cryptogenic stroke (CS), AFDAS likely represents the most frequent underlying etiology, yet paroxysmal and short-duration AF episodes often elude standard monitoring. The Graz AF Risk Score, implemented across all Neurology Departments in Styria, Austria, stratifies patients into tailored monitoring pathways but remains limited by delays in implantable loop recorder (ILR) implantation, patient refusal, and restricted access to early ambulatory ECG monitoring. The study aims to close diagnostic gaps in the current AF detection pathway by implementing a non-invasive, wrist-worn photoplethysmography (PPG) device (i.e., CardioWatch 287-2 \[CW2\]) for early cardiac rhythm monitoring in CS patients. Methods: CATCH-AF is an investigator-initiated, prospective, longitudinal, multi-center, pre-post interventional study including all CS patients admitted to one of five Styrian Neurology Departments. In the pre-intervention phase, AF detection will follow the established Graz AF Risk Score-based algorithm. In the intervention phase, CardioWatch 287-2 screening will replace Holter-ECG screening in moderate-risk patients and will be used for high-risk patients with delayed or declined ILR implantation. Suspected AF episodes will be confirmed by ECG- based assessment at the discretion of the treating cardiologist. The primary endpoint isAFDAS detection at 3 months; secondary endpoints include AFDAS at 12 months, time to AF detection and DOAC initiation, cerebrovascular event recurrence, cardiovascular death, and all-cause mortality at 3 and 12 months. Data will be collected via REDCap and analyzed using descriptive, univariable, and multivariable regression methods, adjusted for confounders with inverse probability of treatment weighting. The investigators hypothesize that CardioWatch 287-2 implementation will increase early AFDAS detection and reduce diagnostic and therapeutic delays, potentially lowering recurrent cerebrovascular events and mortality over 12 months. CATCH-AF represents the first European, population-wide evaluation of a wrist-worn PPG device integrated into an established AF detection pathway for cryptogenic stroke, aiming to improve early diagnosis, treatment initiation and secondary prevention outcomes.
Official title: Continuous Arrhythmia Monitoring to Identify Atrial Fibrillation in Cryptogenic Ischemic Stroke - The CATCH AF Study
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
INTERVENTIONAL
Enrollment
1500
Start Date
2026-10-01
Completion Date
2030-08-31
Last Updated
2026-10-29
Healthy Volunteers
No
Conditions
Interventions
CardioWatch 287-2 Group
* Low Risk (Graz AF Risk Score: 0-1 points, negative predictive value: \>99%): No additional monitoring will be done * Moderate Risk (Graz AF Risk Score: 2-3 points): CardioWatch 287-2 (CW2) will be used in all patients whose stroke etiology remains cryptogenic after the initial work-up instead of Holter-ECG. * High Risk (Graz AF Risk Score: \>= 4 points): An implantable loop recorder implantation will be offered. If there is a delay of more than 7 days before implantation, or if the patient refuses the procedure, a CardioWatch 287-2 (CW2) will be used instead of the Holter-ECG.
Control Group
* Low Risk (Graz AF Risk Score: 0-1 points, negative predictive value: \>99%): No additional monitoring will be done * Moderate Risk (Graz AF Risk Score: 2-3 points): An ambulatory Holter-ECG of at least 24 hours will be used to monitor for covert AF * High Risk (Graz AF Risk Score: \>= 4 points): An implantable loop recorder implantation will be offered. If there is a delay of more than 7 days before implantation, or if the patient refuses the procedure, a Holter-ECG of at least 24 hours will be used instead.
Locations (1)
Medical University of Graz, Department of Neurology
Graz, Styria, Austria