TRICORDER

Triple Cardiovascular Disease Detection with an Artificial Intelligence-Enabled Stethoscope (TRICORDER) in the UK: a Cluster-Randomised Controlled Implementation Trial

Patient / Population Intervention / Exposition Comparaison Critère de jugement

In 1,553,175 patients registered at 205 UK primary care practices (701,933 at 96 intervention and 851,242 at 109 control practices), training and implementation of an AI-enabled stethoscope in routine care did not improve detection of newly diagnosed heart failure over 12 months compared with routine care.

N
1 553 175
Schéma
Pragmatic cluster-randomised implementation trial, UK primary care (205 practices)
Critère
Incidence of any newly coded heart-failure diagnosis per 1,000 patient-years (IRR); co-primary: detection stratified by community vs hospital diagnosis
Pertinence
1
RésultatHeart-failure detection IRR 0.94 (95% CI 0.86–1.02) in intention-to-treat analysis, with no difference in community-based or hospital-based diagnoses (P>0.05); intervention practices recorded 12,725 AI-stethoscope examinations across 972 clinical users.
Kelshiker MA, et al. Lancet. 2026;407(10529):704-715. 10.1016/S0140-6736(25)02156-7
Discussion et critique

The largest randomised implementation trial of an AI diagnostic device, and a negative one: despite regulatory-approved algorithms for reduced ejection fraction, AF and valvular disease, practice-level heart-failure detection did not rise in 12 months. Use was the problem — 12,725 examinations across a registered population of over 700,000 — and use itself was independently associated with higher detection of heart failure, AF and VHD, the adoption mechanism EAGLE and Rushlow had exposed. Open-label by necessity; it teaches that implementation, not accuracy, is the rate-limiting step for AI in primary care.