Wearable Devices for Patient Monitoring in Long QT Syndrome

Application of Wearable Devices for Remote QT Interval Monitoring and Symptom Investigation for Patients With Long QT Syndrome

The main research question of this study is whether wearable devices have utility in monitoring patients with Long QT syndrome.

Study Overview

• Status: Recruiting
• Conditions: Long QT Syndrome
• Intervention / Treatment: Device: Wearable device

• Study Type: Observational
• Enrollment (Estimated): 80

Contacts and Locations

Study Locations

• United Kingdom
  • London, United Kingdom
    • Recruiting
    • Barts and London Hospital NHS Trust
    • Contact: William Young; Phone Number: 07872533176; Email: w.young@qmul.ac.uk
    • Contact: William Young

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Patients with a diagnosis of long QT syndrome

Description

Inclusion Criteria:

• Clinical diagnosis of Long QT Syndrome
• Aged 18 years or over
• Phone with iOS version 15 or Android OS 9.0 or higher
• Able and willing to provide informed consent

Exclusion Criteria:

• Unwilling or unable to give consent
• Ventricular pacing at recruitment
• Bundle branch block or pre-excitation at baseline

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Time Frame
1. Determine the accuracy of repeated QT interval measurements using Fitbit-derived ECGs in patients with Long QT syndrome compared with the current standard (12-lead ECG and ambulatory monitors)	From enrollment to 3 months
2. Establish intra-patient QT variability from weekly Fitbit-ECGs and frequency of measurements over 500ms.	From enrollment to 3 months

Secondary Outcome Measures

Outcome Measure	Time Frame
1. Establish the utility of wearable devices for determining symptom aetiology in LQTS.	From enrollment to 3 months
2. Develop pipelines for the analysis of ECG data collected remotely including use of in-house QT automated algorithms for future machine learning applications.	From enrollment to 3 months

Collaborators and Investigators

• Sponsor: Queen Mary University of London
• Investigators: Principal Investigator: William J Young, MBBS, PhD, Queen Mary University of London and St Bartholomew's Hospital

Study record dates

Study Major Dates

• Study Start (Actual): April 1, 2025
• Primary Completion (Estimated): September 4, 2026
• Study Completion (Estimated): September 4, 2026

Study Registration Dates

• First Submitted: March 14, 2025
• First Submitted That Met QC Criteria: March 14, 2025
• First Posted (Actual): March 20, 2025

Study Record Updates

• Last Update Posted (Actual): May 19, 2026
• Last Update Submitted That Met QC Criteria: May 18, 2026
• Last Verified: May 1, 2026

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Cardiac Conduction System Disease; Cardiovascular Diseases; Pathologic Processes; Heart Diseases; Arrhythmias, Cardiac; Congenital Abnormalities; Cardiovascular Abnormalities; Heart Defects, Congenital; Congenital, Hereditary, and Neonatal Diseases and Abnormalities; Pathological Conditions, Signs and Symptoms; Long QT Syndrome; Equipment and Supplies; Electrical Equipment and Supplies; Wearable Electronic Devices
• Other Study ID Numbers: 173178

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No