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| Name | Class |
|---|---|
| Imperial College Health Partners | UNKNOWN |
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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:
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.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Intervention | Experimental | Receive 3-6 AI-stethoscopes (Eko DUO, Eko Health Inc, CA, USA) including artificial intelligence software for detection of:
|
|
| Control | No Intervention | Usual care |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| AI-stethoscope | Device | Clinicians at practices in the intervention arm will be provided with one session of in-person training in use of the AI-stethoscope within 2 weeks of randomisation, including
|
| Measure | Description | Time Frame |
|---|---|---|
| Incidence of heart failure (co-primary) | Difference in incidence of coded new diagnoses of heart failure (HF) | 24 months |
| Ratio of route to diagnosis of heart failure (co-primary) between emergency and community-based pathways | Difference in ratio of the incidence of coded diagnoses of HF via hospital admission-based versus community-based pathways. | 24 months |
| Measure | Description | Time Frame |
|---|---|---|
| Incidence of atrial fibrillation | New coded diagnoses of atrial fibrillation (AF) | 24 months |
| Incidence of valvular heart disease | New coded diagnoses of valvular heart disease (VHD) |
| Measure | Description | Time Frame |
|---|---|---|
| Sensitivity analysis | Patient-level sensitivity analyses will be performed for patients with abnormal Eko DUO predictions for HF, to identify direct associations between AI-stethoscope predictions and specific diagnostic codes for HF, AF and VHD | 24 months |
Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Nicholas S Peters, MD | Imperial College London | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| NHS North West London Integrated Care System | London | United Kingdom |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 34998740 | Background | Bachtiger P, Petri CF, Scott FE, Ri Park S, Kelshiker MA, Sahemey HK, Dumea B, Alquero R, Padam PS, Hatrick IR, Ali A, Ribeiro M, Cheung WS, Bual N, Rana B, Shun-Shin M, Kramer DB, Fragoyannis A, Keene D, Plymen CM, Peters NS. Point-of-care screening for heart failure with reduced ejection fraction using artificial intelligence during ECG-enabled stethoscope examination in London, UK: a prospective, observational, multicentre study. Lancet Digit Health. 2022 Feb;4(2):e117-e125. doi: 10.1016/S2589-7500(21)00256-9. Epub 2022 Jan 5. | |
| 36921978 |
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Open label cluster randomised controlled trial
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|
|
| 24 months |
| Cost-consequence (AF) | Cost-consequence analysis (form of health economic evaluation) for diagnosis of atrial fibrillation, stratified by route to diagnosis. Presented in pounds sterling. | 24 months |
| Cost-consequence (HFrEF) | Cost-consequence analysis (form of health economic evaluation) for diagnosis of HFrEF, stratified by route to diagnosis. Presented in pounds sterling. | 24 months |
| Cost-consequence (VHD) | Cost-consequence analysis (form of health economic evaluation) for diagnosis of VHD, stratified by route to diagnosis. Presented in pounds sterling. | 24 months |
| Health service utilisation | 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. | 24 months |
| Proportion of patients prescribed guideline-directed medical therapy | Proportion of patients prescribedguideline-directed medical therapy (HF, AF, VHD) | 24 months |
| Device therapy | New implantation of cardiac resynchronisation therapy (CRT) and/or implantable cardioverter-defibrillator (ICD) | 24 months |
| Uptake and utilisation | Differential rates of uptake and utilisation of AI-stethoscope in primary care | 24 months |
| Determinants of uptake and utilisation | Determinants of utilisation of AI-stethoscope in primary care (clinician questionnaires) | 24 months |
| Patient quality of life | Healthy Days at Home (patient-level analysis) | 24 months |
| Background |
| Bachtiger P, Kelshiker MA, Petri CF, Gandhi M, Shah M, Kamalati T, Khan SA, Hooper G, Stephens J, Alrumayh A, Barton C, Kramer DB, Plymen CM, Peters NS. Survival and health economic outcomes in heart failure diagnosed at hospital admission versus community settings: a propensity-matched analysis. BMJ Health Care Inform. 2023 Mar;30(1):e100718. doi: 10.1136/bmjhci-2022-100718. |
| 40398956 | Derived | Kelshiker MA, Bachtiger P, Mansell J, Kramer DB, Nakhare S, Almonte MT, Alrumayh A, Petri CF, Peters A, Costelloe C, Falaschetti E, Barton C, Al-Lamee R, Majeed A, Plymen CM, Peters NS. Triple cardiovascular disease detection with an artificial intelligence-enabled stethoscope (TRICORDER): design and rationale for a decentralised, real-world cluster-randomised controlled trial and implementation study. BMJ Open. 2025 May 21;15(5):e098030. doi: 10.1136/bmjopen-2024-098030. |
| ID | Term |
|---|---|
| D006333 | Heart Failure |
| D006349 | Heart Valve Diseases |
| D001281 | Atrial Fibrillation |
| D006337 | Heart Murmurs |
| ID | Term |
|---|---|
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
| D001145 | Arrhythmias, Cardiac |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D012816 | Signs and Symptoms |
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