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Triple cardiovascular disease detection with an artificial intelligence-enabled stethoscope (TRICORDER): design and
Mihir A Kelshiker1,2, Patrik Bächtiger1,2, Josephine Mansell1,2
1National Heart and Lung Institute, Imperial College London, London, England, UK.
Insights
This study investigates an AI-enabled stethoscope for early cardiovascular disease detection in primary care. The TRICORDER trial will assess its impact on heart failure diagnosis rates and pathways.
Area of Science:
- Cardiology
- Primary Care Medicine
- Health Technology Assessment
Background:
- Early detection of cardiovascular disease (CVD) is crucial in primary care.
- Artificial intelligence (AI)-enabled stethoscopes offer potential for transformative CVD diagnostics.
- The clinical and cost-effectiveness of AI stethoscopes for conditions like left ventricular systolic dysfunction, atrial fibrillation, and cardiac murmurs remains unproven.
Purpose of the Study:
- To evaluate the clinical and cost-effectiveness of AI-enabled stethoscopes in primary care.
- To assess the impact of AI stethoscopes on the detection and diagnostic pathways of heart failure.
- To explore the incidence of atrial fibrillation and valvular heart disease with AI stethoscope use.
Main Methods:
- The TRICORDER trial is a pragmatic, multi-centre, cluster-randomised controlled implementation study.
- Up to 200 UK primary care practices will be randomized to usual care or AI-enabled stethoscope availability.
- Data will be collected from electronic health records, supplemented by clinician surveys, with coprimary endpoints on heart failure incidence and diagnostic pathways.
Main Results:
- The study is ongoing; primary results are not yet available.
- The trial aims to determine differences in coded heart failure incidence and diagnostic pathway ratios.
- Secondary endpoints include atrial fibrillation, valvular heart disease incidence, cost-consequence analysis, and guideline-directed medical therapy prescription.
Conclusions:
- The findings will inform the integration of AI stethoscopes into routine primary care.
- This research could establish the value of AI-enabled tools for improving cardiovascular care.
- Successful implementation may lead to earlier and more efficient diagnosis of critical cardiac conditions.
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.
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