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Actively Recruiting

Phase Not Applicable
Age: 50Years - 89Years
All Genders
ID06542770

Early Detection of Silent Atrial Fibrillation Using Implantable Cardiac Monitors in Patients Aged 50-89 with Cryptogenic Stroke and Atrial Ultrasound Anomalies

Led by Parc de Salut Mar · Updated on 2024-08-07

100

Participants Needed

1

Research Sites

13 weeks

Total Duration

AI-Summary

What this Trial Is About

Cryptogenic stroke CS causes about 30% of stroke unit admissions and often has an unknown cause. Silent paroxysmal atrial fibrillation PAF is believed to underlie many CS cases. This study evaluates the usefulness of implantable cardiac monitors ICM for early detection of silent PAF in patients with CS. The study also explores clinical and ultrasound predictors, such as atrial contraction strain ACS, to identify patients at higher risk who may need closer monitoring. Patients admitted with CS are randomized within 48 hours of admission to either standard care or early ICM implantation before discharge. The ICM devices are implanted subcutaneously in the chest and programmed to detect atrial fibrillation episodes lasting 30 seconds or more. The study also uses cardiac ultrasound to assess atrial features like left atrial volume and strain to classify patients as having atrial cardiomyopathy or not. Standard care includes continuous ECG monitoring for at least 48 hours and follow-up ECGs and Holter monitoring. Participants undergo neurological exams, ECGs, brain imaging, and blood tests during admission and are followed up in outpatient clinics at 3, 6, 12 months, and every 6 months thereafter up to 2 years. Researchers will monitor for atrial fibrillation detection confirmed by ECG or device recordings, assess ultrasound predictors of PAF, and track stroke recurrence. All ICM recordings are reviewed by specialists, and oral anticoagulation is started if atrial fibrillation is detected.

CONDITIONS

Brief Title

Atrial Anomalies Predict Silent Atrial Fibrillation Detected by Implantable Cardiac Monitor in Cryptogenic Stroke

Research Team

E

Ermengol Valles Gras, PhD

A

Ana Beatriz Garcia Duran, MD

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