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
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Introduction Early detection of cardiovascular disease in primary care is a public health priority, for which the clinical and cost-effectiveness of an artificial intelligence-enabled stethoscope that detects left ventricular systolic dysfunction, atrial fibrillation and cardiac murmurs is unproven but potentially transformative.
Methods and analysis TRICORDER is a pragmatic, two-arm, multi-centre (decentralised), cluster-randomised controlled trial and implementation study. Up to 200 primary care practices in urban North West London and rural North Wales, UK, will be randomised to usual care or to have artificial intelligence-enabled stethoscopes available for use. Primary care clinicians will use the artificial intelligence-enabled stethoscopes at their own discretion, without patient-level inclusion or exclusion criteria. They will be supported to do so by a clinical guideline developed and approved by the regional health system executive board. Patient and outcome data will be captured from pooled primary and secondary care records, supplemented by qualitative and quantitative clinician surveys. The coprimary endpoints are (i) difference in the coded incidence (detection) of heart failure and (ii) difference in the ratio of coded incidence of heart failure via hospital admission versus community-based diagnostic pathways. Secondary endpoints include difference in the incidence of atrial fibrillation and valvular heart disease, cost-consequence differential, and prescription of guideline-directed medical therapy.
Ethics and dissemination This trial has ethical approval from the UK Health Research Authority (23/LO/0051). Findings from this trial will be disseminated through publication of peer-reviewed manuscripts, presentations at scientific meetings and conferences with local and national stakeholders.
Trial registration number NCT05987670
Methods and analysis TRICORDER is a pragmatic, two-arm, multi-centre (decentralised), cluster-randomised controlled trial and implementation study. Up to 200 primary care practices in urban North West London and rural North Wales, UK, will be randomised to usual care or to have artificial intelligence-enabled stethoscopes available for use. Primary care clinicians will use the artificial intelligence-enabled stethoscopes at their own discretion, without patient-level inclusion or exclusion criteria. They will be supported to do so by a clinical guideline developed and approved by the regional health system executive board. Patient and outcome data will be captured from pooled primary and secondary care records, supplemented by qualitative and quantitative clinician surveys. The coprimary endpoints are (i) difference in the coded incidence (detection) of heart failure and (ii) difference in the ratio of coded incidence of heart failure via hospital admission versus community-based diagnostic pathways. Secondary endpoints include difference in the incidence of atrial fibrillation and valvular heart disease, cost-consequence differential, and prescription of guideline-directed medical therapy.
Ethics and dissemination This trial has ethical approval from the UK Health Research Authority (23/LO/0051). Findings from this trial will be disseminated through publication of peer-reviewed manuscripts, presentations at scientific meetings and conferences with local and national stakeholders.
Trial registration number NCT05987670
Date Issued
2025-05-01
Date Acceptance
2025-03-28
Citation
BMJ Open, 2025, 15 (5)
ISSN
2044-6055
Publisher
BMJ Publishing Group
Journal / Book Title
BMJ Open
Volume
15
Issue
5
Copyright Statement
© Author(s) (or their employer(s)) 2025. Re-use permitted under CC BY. Published by BMJ Group.
License URL
Identifier
10.1136/bmjopen-2024-098030
Publication Status
Published
Article Number
e098030
Date Publish Online
2025-05-21