Triple Cardiovascular Disease Detection With an Artificial Intelligence-enabled Stethoscope

NCT05987670 | Active Not Recruiting FDA Device

• 1 other identifier: 22HH8045
• Study Type: interventional
• Target: 200
• Locations: 1 country
• Sites: 1

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. 1.Increases overall detection of heart failure
2. 2.Reduces the proportion of patients being diagnosed with heart failure following an emergency hospital admission
3. 3.Reduces healthcare system costs

Conditions

Heart Failure; Heart Valve Diseases; Atrial Fibrillation; Heart Murmurs; Congestive Heart Failure; Heart Failure With Reduced Ejection Fraction

Keywords

cluster randomized controlled trial; artificial intelligence; digital health; cardiology; primary care

Outcome Measures

Primary Outcomes (2)

• 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

Secondary Outcomes (11)

• Incidence of atrial fibrillation

  24 months

• Incidence of valvular heart disease

  24 months

• Cost-consequence (AF)

  24 months

• Cost-consequence (HFrEF)

  24 months

• Cost-consequence (VHD)

  24 months

Other Outcomes (1)

• Sensitivity analysis

  24 months

Study Arms (2)

Intervention

EXPERIMENTAL

Receive 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

Device: AI-stethoscope

Control

NO INTERVENTION

Usual care

Interventions

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 1. Delivery and setup 2. Smartphone app installation and login 3. Pairing of all clinician smartphones with all AI-stethoscopes in the same practice 4. Demo of patient examination The AI-stethoscope will be used within its CE/UKCA-marked intended purpose. The clinical guidelines for use have been agreed by the NHS North West London Integrated Care System and Betsi Cadwaladr University Health Board Cardiovascular Executive Groups. Patients will be examined with the AI-stethoscope in accordance with these guidelines, and/or where stethoscope examination is deemed clinically appropriate. Patients will provide verbal consent for examination with the AI-stethoscope as per any physical examination performed by healthcare professionals for direct care, in accordance with UK law and General Medical Council guidelines.

Also known as: Eko DUO, Eko Core 500, Eko EAS

Intervention

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• 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.

You may not qualify if:

• Poor WiFi and/or mobile data connectivity within primary care consulting rooms
• No face-to-face patient consultations

Sponsors & Collaborators

• Imperial College London: lead
• Imperial College Health Partners: collaborator

Study Sites (1)

NHS North West London Integrated Care System

London, United Kingdom

Location

Related Publications (3)

• 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.

  PMID: 34998740 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.

  PMID: 36921978 BACKGROUND

• 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.

  PMID: 40398956 DERIVED

MeSH Terms

Conditions

Heart Failure; Heart Valve Diseases; Atrial Fibrillation; Heart Murmurs

Condition Hierarchy (Ancestors)

Heart Diseases; Cardiovascular Diseases; Arrhythmias, Cardiac; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Signs and Symptoms

Study Officials

• Nicholas S Peters, MD

  Imperial College London

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Model Details: Open label cluster randomised controlled trial

Study Record Dates

• First Submitted: July 21, 2023
• First Posted: August 14, 2023
• Study Start: October 25, 2023
• Primary Completion: December 23, 2025
• Study Completion: December 23, 2025
• Last Updated: July 11, 2024

Record last verified: 2024-07

Data Sharing

• IPD Sharing: Will not share

Locations

GB (1)