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Prospective Evaluation of Artificial Intelligence-enhanced Electrocardiography for Detection of Structural Heart Disease
This study aims to improve the early detection of undiagnosed heart disease, which causes serious health issues, hospital admissions, and high healthcare costs. Researchers are exploring how artificial intelligence (AI) can analyse routine heart tests, called electrocardiograms (ECGs), to detect heart problems. These tests can be done using both traditional ECG machines and portable, wearable devices like smartwatches, making it easier for people to monitor their heart health at home. While AI has shown promise using past data, this study will involve the collection of ECG data and subsequent testing of its accuracy in real-world settings to ensure it works well for both doctors and patients. The goal is to see if AI can identify conditions like heart muscle weakness, valve issues, and high lung pressure from the ECG data of patients. The researchers will also compare AI's detections with other blood tests commonly used to diagnose heart disease. The AI models that will be used are being tested for research and validation purposes only. They will not be used for clinical decision-making or providing information to influence diagnosis, treatment, or patient care during the study. The AI outputs are not shared with clinicians and will have no impact on the care pathway. This research will demonstrate if AI-powered ECG analysis - whether from traditional or portable devices - can provide a low-cost, non-invasive way to detect heart disease early and improve health assessments.
Age
18 - 90 years
Sex
ALL
Healthy Volunteers
Yes
Southmead Hospital
Bristol, United Kingdom
Chelsea and Westminster Hospital
London, United Kingdom
Hammersmith Hospital
London, United Kingdom
St Mary's Hospital
London, United Kingdom
West Middlesex University Hospital
London, United Kingdom
Start Date
November 4, 2025
Primary Completion Date
May 3, 2027
Completion Date
August 2, 2027
Last Updated
March 9, 2026
590
ESTIMATED participants
Traditional 12-lead Electrocardiogram
OTHER
Apple Watch Series 4 Single-lead Electrocardiogram
OTHER
Eko Core 500 Digital Stethoscope 3-lead Electrocardiogram
OTHER
AliveCor KardiaMobile Single- and 6-lead Electrocardiogram
OTHER
Phlebotomy for N-terminal pro-B-type natriuretic peptide
OTHER
Lead Sponsor
Imperial College London
Data Source & Attribution
This clinical trial information is sourced from ClinicalTrials.gov, a service of the U.S. National Institutes of Health.
Modifications: This data has been reformatted for display purposes. Eligibility criteria have been parsed into inclusion/exclusion sections. Location data has been geocoded to enable distance-based search. For the authoritative and most current information, please visit ClinicalTrials.gov.
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