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NCT Number: NCT06988189

Unmasking Concealed Arrhythmia Syndromes

This study seeks to evaluate whether using non-invasive electrocardiograph (ECG) techniques, including long term ECG monitoring with wearable ECGs, can improve the detection of concealed Brugada syndrome.

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Key information

Conditions

Brugada ECG Patterns Arrhythmias, Cardiac Brugada Syndrome Brugada Syndrome (BrS) Cardiac Conduction System Disease Cardiovascular Diseases Congenital, Hereditary, and Neonatal Diseases and Abnormalities Genetic Diseases, Inborn Heart Diseases

Age range

18 year–100 year

Sex eligibility

All sexes

Study type

Observational

Primary location

About this study

Application of long term continuous ECG monitoring via ECG wearables and ambulatory ECG monitors to detect manifestations of Brugada syndrome. This approach will be combined with development of an AI (artificial intelligence) enabled ECG platform to automate Brugada ECG detection and analysis.

The protocol will comprise the following parts:

Study A: Brugada ECG AI development. This will automate the recognition of the type 1 Brugada ECG pattern on 12 lead ECGs.

Study B: Remote arrhythmia diagnostics. A prospective observational study whereby recruited participants will be fitted with a wearable ECG or cardiac monitor to undergo continuous long term ambulatory ECG monitoring. The algorithms developed in study A will be applied to long term ECG data captured in this study.

Study C: Arrhythmic risk stratification using ultra-high-frequency ECG. This exploratory study will look for markers of arrhythmic risk in patients with manifest and concealed arrhythmia syndromes.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Adults willing to take part
  • Able to give consent

Exclusion criteria

  • Unable to give consent
  • Children age < 18 years and adults > 100 years old

Treatment and study plan

12-lead ECG

Diagnostic Test

12-lead ECG from a conventional ECG machine

Continuous long term ambulatory ECG monitoring

Diagnostic Test

Continuous long term ambulatory ECG monitoring using wearable ECG or cardiac monitor

Ultra-high-frequency ECG

Diagnostic Test

Ultra-high-frequency ECG acquired using specific acquisition equipment

Primary outcomes

  1. Sensitivity, specificity, and area under the curve (AUC) of AI algorithm for detection of Brugada type 1 ECG pattern on 12-lead ECGs.

    Time frame: At completion of algorithm validation, approximately 12 months after study start

    Assessment of performance and accuracy of AI ECG detection algorithm for type 1 Brugada ECG.

  2. Detection rate of Brugada ECG pattern using extended-duration multi-electrode ambulatory ECG monitoring (wearable ECG) in patients with concealed Brugada syndrome.

    Time frame: Up to 12 months from enrolment

    AI ECG detection algorithm, developed in Study A, applied to full ECG recording to detect Type 1 Brugada ECG pattern.

  3. Number of cases of Brugada or Long QT Syndrome (LQTS) detected using extended-duration multi-electrode ambulatory ECG monitoring in patients with idiopathic ventricular fibrillation (VF), after application of AI ECG detection algorithms.

    Time frame: Up to 12 months from enrolment

    AI ECG detection algorithms applied to full ECG recording to detect Type 1 Brugada ECG pattern or LQTS unmasking.

Study contacts

Contact information is provided by the study sponsor or research team.

Ahran Arnold, PhD

CONTACT

[email protected]

+442033132243

Keenan Saleh, MBBS

CONTACT

[email protected]

+442033132243

Sponsors and collaborators

Lead sponsor

Imperial College London

Other

Registry information

Acronym: UCAS

Important dates

Study start
2024
Primary completion
2026
Study completion
2026
First posted
May 23, 2025
Registry last updated
May 23, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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