NCT07057466

Brief Summary

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.

Trial Health

77
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
590

participants targeted

Target at P75+ for all trials

Timeline
15mo left

Started Nov 2025

Geographic Reach
1 country

5 active sites

Status
recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Progress29%
Nov 2025Aug 2027

First Submitted

Initial submission to the registry

June 26, 2025

Completed
13 days until next milestone

First Posted

Study publicly available on registry

July 9, 2025

Completed
4 months until next milestone

Study Start

First participant enrolled

November 4, 2025

Completed
1.5 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

May 3, 2027

Expected
3 months until next milestone

Study Completion

Last participant's last visit for all outcomes

August 2, 2027

Last Updated

March 9, 2026

Status Verified

March 1, 2026

Enrollment Period

1.5 years

First QC Date

June 26, 2025

Last Update Submit

March 6, 2026

Conditions

Keywords

Artificial IntelligenceMachine LearningWearable DevicesPortable DevicesHeart FailurePulmonary HypertensionValvular Heart DiseaseEchocardiographyElectrocardiography

Outcome Measures

Primary Outcomes (1)

  • AI-ECG model classification performance for detection of structural heart disease (SHD)

    AI-ECG model classification performance for HF, PH, and VHD, will be assessed for all ECG modalities (single-, 3-, 6-, and 12-lead ECGs) using the area under the receiver operating characteristic (AUROC; pre-defined threshold).

    From enrolment to end of patient's study visit (up to 1 hour)

Secondary Outcomes (3)

  • Additional AI-ECG performance metrics for detection of SHD

    From enrolment to end of patient's study visit (up to 1 hour)

  • NT-proBNP performance metrics for detection of SHD

    From enrolment to end of patient's study visit (up to 1 hour)

  • Combined AI-ECG and NT-proBNP performance analysis for detection of SHD

    From enrolment to end of patient's study visit (up to 1 hour)

Study Arms (2)

Echocardiography cohort

This cohort of patients will be attending for inpatient and outpatient transthoracic echocardiograms (TTEs) as part of their routine clinical care, having been referred by clinicians for various standard TTE indications, including investigation of symptoms such as breathlessness due to possible heart failure (HF), and screening for suspected valvular heart disease (VHD) and/or pulmonary hypertension (PH). These patients will have had no prior formal diagnosis of HF, VHD, and/or PH.

Other: Traditional 12-lead ElectrocardiogramOther: Apple Watch Series 4 Single-lead ElectrocardiogramOther: Eko Core 500 Digital Stethoscope 3-lead ElectrocardiogramOther: AliveCor KardiaMobile Single- and 6-lead Electrocardiogram

N-terminal pro B-type natriuretic peptide subgroup

A subgroup of 203 patients, out of the total 590 patiets in the Echocardiography cohort, will be randomised to undergo blood tests and collection of serum N-terminal pro B-type natriuretic peptide (NT-proBNP).

Other: Traditional 12-lead ElectrocardiogramOther: Apple Watch Series 4 Single-lead ElectrocardiogramOther: Eko Core 500 Digital Stethoscope 3-lead ElectrocardiogramOther: AliveCor KardiaMobile Single- and 6-lead ElectrocardiogramOther: Phlebotomy for N-terminal pro-B-type natriuretic peptide

Interventions

A single- or 6-lead ECG recorded using the AliveCor KardiaMobile 6L device which is a portable, non-invasive method for capturing cardiac electrical activity. Operated by the participant or clinician, the device enables rapid rhythm assessment and detection of abnormalities such as atrial fibrillation. The 6-lead configuration offers more comprehensive data than single-lead recordings, supporting enhanced arrhythmia and conduction analysis in both in-clinic and remote settings. For the purposes of this study, single- and 6-lead ECGs will be collected for the application of AI-ECG models for the detection of HF, VHD, and/or PH and will not be used to inform or alter patients' standard NHS care.

Echocardiography cohortN-terminal pro B-type natriuretic peptide subgroup

Single-lead ECG taken using an Apple Watch Series 4 is a non-invasive, participant-initiated recording of cardiac electrical activity through a wearable device. While more limited than a 12-lead ECG, it can capture rhythm abnormalities-such as atrial fibrillation-and offers a convenient method for remote or continuous heart monitoring during the study. For the purposes of this study, single-lead ECGs will be collected for the application of AI-ECG models for the detection of HF, VHD, and/or PH and will not be used to inform or alter patients' standard NHS care.

Echocardiography cohortN-terminal pro B-type natriuretic peptide subgroup

Three-lead ECG recorded using the Eko CORE 500 digital stethoscope is a non-invasive, clinician-operated cardiac assessment tool that captures real-time electrical activity of the heart during auscultation. It provides enhanced diagnostic information compared to single-lead recordings, allowing detection of arrhythmias and signs of structural heart disease at the point of care, supporting integrated clinical and digital assessment. For the purposes of this study, 3-lead ECGs will be collected for the application of AI-ECG models for the detection of HF, VHD, and/or PH and will not be used to inform or alter patients' standard NHS care.

Echocardiography cohortN-terminal pro B-type natriuretic peptide subgroup

12-lead ECG investigation is a standard, non-invasive diagnostic procedure used as an intervention to assess participants' cardiac electrical activity. For the purposes of this study, 12-lead ECGs will be collected for the application of AI-ECG models for the detection of HF, VHD, and/or PH and will not be used to inform or alter patients' standard NHS care.

Echocardiography cohortN-terminal pro B-type natriuretic peptide subgroup

A minimally invasive biomarker assessment used to evaluate cardiac wall stress and function. Elevated levels can indicate the presence or severity of heart failure and other forms of structural heart disease, making it a valuable tool for diagnosis, risk stratification, and monitoring of cardiac status throughout the study period. For the purposes of this study, NT-proBNP will be collected to assess its accuracy at detecting HF, PH, and VHD with comparison with AI-ECG detections. The investigators will also evaluate the accuracy of AI-ECG detections combined with NT-pro-BNP, for detecting HF, VHD, and PH. The investigators will not be using NT-proBNP results to inform or alter patients' standard NHS care.

N-terminal pro B-type natriuretic peptide subgroup

Eligibility Criteria

Age18 Years - 90 Years
Sexall
Healthy VolunteersYes
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

This prospective observational cohort and validation study will recruit 590 unselected patients attending Chelsea and Westminster Hospital NHS Foundation Trust for routine echocardiography as part of their routine clinical care. Patients attending routine echocardiography who satisfy the inclusion and exclusion criteria will be approached before their echocardiography appointment to obtain informed consent to participate in the study.

You may qualify if:

  • Patients aged 18-90 years
  • No prior formal diagnosis of HF (including systolic and diastolic dysfunction), PH, or VHD
  • Ability to provide informed consent

You may not qualify if:

  • Severe arrhythmia or unstable cardiovascular disease
  • Prior formal diagnosis of HF (including systolic and diastolic dysfunction), PH, or VHD
  • Cardiac implantable electronic device in-situ, including a permanent pacemaker or implantable cardioverter defibrillator
  • Involvement in current research or recent involvement in any research prior to recruitment

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (5)

Southmead Hospital

Bristol, United Kingdom

RECRUITING

Chelsea and Westminster Hospital

London, United Kingdom

RECRUITING

Hammersmith Hospital

London, United Kingdom

RECRUITING

St Mary's Hospital

London, United Kingdom

RECRUITING

West Middlesex University Hospital

London, United Kingdom

RECRUITING

Biospecimen

Retention: SAMPLES WITHOUT DNA

Blood samples for NT-proBNP

MeSH Terms

Conditions

Gastroesophageal RefluxDiseaseHypertension, PulmonaryHeart FailureHeart Valve Diseases

Interventions

Phlebotomypro-brain natriuretic peptide (1-76)

Condition Hierarchy (Ancestors)

Esophageal Motility DisordersDeglutition DisordersEsophageal DiseasesGastrointestinal DiseasesDigestive System DiseasesPathologic ProcessesPathological Conditions, Signs and SymptomsLung DiseasesRespiratory Tract DiseasesHypertensionVascular DiseasesCardiovascular DiseasesHeart Diseases

Intervention Hierarchy (Ancestors)

Blood Specimen CollectionSpecimen HandlingClinical Laboratory TechniquesDiagnostic Techniques and ProceduresDiagnosisPuncturesTherapeuticsSurgical Procedures, OperativeInvestigative Techniques

Central Study Contacts

Ahmed YM El-Medany, MBChB, MRCP, MSc, FHEA

CONTACT

Study Design

Study Type
observational
Observational Model
COHORT
Time Perspective
PROSPECTIVE
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

June 26, 2025

First Posted

July 9, 2025

Study Start

November 4, 2025

Primary Completion (Estimated)

May 3, 2027

Study Completion (Estimated)

August 2, 2027

Last Updated

March 9, 2026

Record last verified: 2026-03

Data Sharing

IPD Sharing
Will not share

Locations