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Triple Cardiovascular Disease Detection With an Artificial Intelligence-enabled Stethoscope

Not Applicable
Active, not recruiting
Conditions
Heart Valve Diseases
Heart Failure
Atrial Fibrillation
Heart Murmurs
Heart Failure With Reduced Ejection Fraction
Congestive Heart Failure
Interventions
Device: AI-stethoscope
Registration Number
NCT05987670
Lead Sponsor
Imperial College London
Brief Summary

Heart failure (HF) is a condition in which the heart cannot pump blood adequately. It is increasingly common, consumes 4% of the UK National Health Service (NHS) budget and is deadlier than most cancers. Early diagnosis and treatment of HF improves quality of life and survival. Unacceptably, 80% of patients have their HF diagnosed only when very unwell, requiring an emergency hospital admission, with worse survival and higher treatment costs to the NHS. This is largely because General Practitioners (GPs) have no easy-to-use tools to check for suspected HF, with patients having to rely on a long and rarely completed diagnostic pathway involving blood tests and hospital assessment.

The investigators have previously demonstrated that an artificial intelligence-enabled stethoscope (AI-stethoscope) can detect HF in 15 seconds with 92% accuracy (regardless of age, gender or ethnicity) - even before patients develop symptoms. While the GP uses the stethoscope, it records the heart sounds and electrical activity, and uses inbuilt artificial intelligence to detect HF.

The goal of this clinical trial is to determine the clinical and cost-effectiveness of providing primary care teams with the AI-stethoscope for the detection of heart failure. The main questions it aims to answer are if provision of the AI-stethoscope:

1. Increases overall detection of heart failure

2. Reduces the proportion of patients being diagnosed with heart failure following an emergency hospital admission

3. Reduces healthcare system costs

200 primary care practices across North West London and North Wales, UK, will be recruited to a cluster randomised controlled trial, meaning half of the primary care practices will be randomly assigned to have AI-stethoscopes for use in direct clinical care, and half will not. Researchers will compare clinical and cost outcomes between the groups.

Detailed Description

Triple Cardiovascular Disease Detection with Artificial Intelligence-enabled Stethoscope (TRICORDER) is an open label, cluster randomised controlled trial. The aim is to determine whether use of an artificial intelligence-enabled stethoscope (AI-stethoscope) in UK Primary Care improves community-based detection of heart failure (HF), compared with usual care. 200 primary care practices in North West London (UK) will be randomised to receive the AI-stethoscope (intervention arm) or continue with usual care (control arm). The intervention arm will use the AI-stethoscope in routine clinical practice. Outcomes will be measured using pooled primary and secondary care clinical and cost-data, as well as clinician questionnaires.

Recruitment & Eligibility

Status
ACTIVE_NOT_RECRUITING
Sex
All
Target Recruitment
200
Inclusion Criteria
  • Primary care practices that care for adult patients and have the ability to request natriuretic peptide blood testing
  • Primary care practices within the NIHR North West London Clinical Research Network or Betsi Cadwaladr University Health Board.
Exclusion Criteria
  • Poor WiFi and/or mobile data connectivity within primary care consulting rooms
  • No face-to-face patient consultations

Study & Design

Study Type
INTERVENTIONAL
Study Design
PARALLEL
Arm && Interventions
GroupInterventionDescription
InterventionAI-stethoscopeReceive 3-6 AI-stethoscopes (Eko DUO, Eko Health Inc, CA, USA) including artificial intelligence software for detection of: 1. Reduced left ventricular ejection fraction \<40% 2. Atrial fibrillation 3. Cardiac murmurs
Primary Outcome Measures
NameTimeMethod
Ratio of route to diagnosis of heart failure (co-primary) between emergency and community-based pathways24 months

Difference in ratio of the incidence of coded diagnoses of HF via hospital admission-based versus community-based pathways.

Incidence of heart failure (co-primary)24 months

Difference in incidence of coded new diagnoses of heart failure (HF)

Secondary Outcome Measures
NameTimeMethod
Device therapy24 months

New implantation of cardiac resynchronisation therapy (CRT) and/or implantable cardioverter-defibrillator (ICD)

Cost-consequence (AF)24 months

Cost-consequence analysis (form of health economic evaluation) for diagnosis of atrial fibrillation, stratified by route to diagnosis. Presented in pounds sterling.

Determinants of uptake and utilisation24 months

Determinants of utilisation of AI-stethoscope in primary care (clinician questionnaires)

Incidence of atrial fibrillation24 months

New coded diagnoses of atrial fibrillation (AF)

Incidence of valvular heart disease24 months

New coded diagnoses of valvular heart disease (VHD)

Cost-consequence (HFrEF)24 months

Cost-consequence analysis (form of health economic evaluation) for diagnosis of HFrEF, stratified by route to diagnosis. Presented in pounds sterling.

Proportion of patients prescribed guideline-directed medical therapy24 months

Proportion of patients prescribedguideline-directed medical therapy (HF, AF, VHD)

Cost-consequence (VHD)24 months

Cost-consequence analysis (form of health economic evaluation) for diagnosis of VHD, stratified by route to diagnosis. Presented in pounds sterling.

Patient quality of life24 months

Healthy Days at Home (patient-level analysis)

Health service utilisation24 months

Health service utilisation for diagnostics e.g. rates of request for echocardiography, electrocardiography, primary care appointments. Collected from NHS organisation business intelligence repositories and UK Trusted Research Environments.

Uptake and utilisation24 months

Differential rates of uptake and utilisation of AI-stethoscope in primary care

Trial Locations

Locations (1)

NHS North West London Integrated Care System

🇬🇧

London, United Kingdom

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