Heart Failure With Reduced Ejection Fraction (HFrEF; Diagnosis)

AI-ECG-SHD is a multicentre prospective observational diagnostic accuracy study evaluating artificial intelligence-enhanced electrocardiography (AI-ECG) for the detection of structural heart disease in adults undergoing clinically indicated transthoracic echocardiography (TTE). Participants undergo standard 12-lead ECG acquisition together with ECG recordings obtained using portable or wearable single-, 3-, and 6-lead devices. Established AI-ECG models will be evaluated for the detection of heart failure, pulmonary hypertension and valvular heart disease using TTE as the clinical reference standard, with performance compared across ECG acquisition modalities within the same prospective cohort. AI-ECG predictions are generated offline and are not provided to treating clinicians or used to alter clinical care. The study will also compare AI-ECG performance with N-terminal pro-B-type natriuretic peptide (NT-proBNP) and evaluate the diagnostic performance of a combined AI-ECG and NT-proBNP approach. The study aims to recruit 590 participants across six NHS hospital sites. A prespecified subgroup of 203 participants will undergo dedicated venous blood sampling for NT-proBNP; eligible same-day NT-proBNP measurements obtained as part of routine clinical care will also be included where available.