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Intelligent Monitoring to Predict Atrial Fibrillation

NCT06600620 · Status: SUSPENDED · Type: OBSERVATIONAL · Enrollment: 1200

Last updated 2025-09-15

No results posted yet for this study

Summary

Atrial Fibrillation (AF) is the commonest arrhythmia worldwide, affects 5% of people over the age of 65 and increases the risk of stroke and heart failure. The investigators aim to detect clinical and subclinical episodes of atrial fibrillation lasting \>30 seconds to develop risk prediction models to identify patients at high risk for ischaemic stroke.

Conditions

Interventions

DEVICE

Monitoring patients heart rythms with a wireless patch device

The investigators will collect data in patients at high risk of atrial fibrillation (AF) without a known history of AF to determine clinical predicators of AF. This data will be used to generate virtual digital twins to to predict clinical and subclinical episodes of AF

Sponsors & Collaborators

  • University of Copenhagen

    collaborator OTHER

  • Isansys Lifecare LTD

    collaborator UNKNOWN

  • University of Liverpool

    collaborator OTHER

  • Liverpool John Moores University

    collaborator OTHER

  • Liverpool University Hospitals NHS Foundation Trust

    lead OTHER_GOV

Eligibility

Min Age
50 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-09-23
Primary Completion
2028-07-31
Completion
2028-08-01

Countries

  • United Kingdom

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06600620 on ClinicalTrials.gov