Soh, Cheng Hwee

Wright, Leah

Baumann, Angus

Seidel, Bastian

Yu, Christopher

Nolan, Mark

Mylius, Tony

Marwick, Thomas H

2024-08-10

Transthoracic echocardiography (TTE) is essential in the diagnosis of cardiovascular diseases (CVD), including but not limited to heart failure (HF) and heart valve disease (HVD). However, its dependence on expert acquisition means that its accessibility in rural areas may be limited, leading to delayed management decisions and potential missed diagnoses. Artificial intelligence-guided (AI)-TTE offers a solution by permitting non-expert image acquisition. The impact of AI-TTE on the timing of diagnosis and early initiation of cardioprotection is undefined.AGILE-Echo (use of Artificial intelligence-Guided echocardiography to assIst cardiovascuLar patient managEment) is a randomized-controlled trial conducted in 5 rural and remote areas around Australia. Adults with CV risk factors and exercise intolerance, or concerns regarding HVD are randomized into AI-TTE or usual care (UC). AI-TTE participants may have a cardiovascular problem excluded, identified (leading to AI-guided interventions) or unresolved (leading to conventional TTE). UC participants undergo usual management, including referral for standard TTE. The primary endpoint is a composite of HVD or HF diagnosis at 12-months. Subgroup analysis, stratified based on age range and sex, will be conducted. All statistical analyses will be conducted using R.Of the first 157 participants, 78 have been randomized into AI-TTE (median age 68 [IQR 17]) and 79 to UC (median age 65 [IQR 17], P = .034). HVD was the primary concern in 37 participants (23.6%) while 84.7% (n = 133) experienced exercise intolerance. The overall 10-year HF incidence risk was 13.4% and 20.0% (P = .089) for UC and AI-TTE arm respectively. Atrial remodeling, left ventricular remodeling and valvular regurgitation were the most common findings. Thirty-three patients (42.3%) showed no abnormalities.This randomized-controlled trial of AI-TTE will provide proof-of-concept for the role of AI-TTE in identifying pre-symptomatic HF or HVD when access to TTE is limited. Additionally, this could promote the usage of AI-TTE in rural or remote areas, ultimately improving health and quality of life of community dwelling adults with risks, signs or symptoms of cardiac dysfunction.

Imaging Research, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia; Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Victoria, Australia.

Imaging Research, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.

Alice Springs Hospital, The Gap, Northern Territory, Australia.

Ochre Medical Centre, Hobart, Tasmania, Australia.

Walgett Aboriginal Medical Service Limited, Walgett, New South Wales, Australia; Nepean Clinical School, University of Sydney, Sydney, New South Wales, Australia.

Imaging Research, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.

Merredin District Hospital, Western Australian Country Health Service, Wheatbelt, Western Australia, Australia.

Imaging Research, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia; Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Victoria, Australia; Menzies Institute for Medical Research, Hobart, Tasmania, Australia. Electronic address: tom.marwick@baker.edu.au.

Am Heart J . 2024 Aug 10:277:11-19. doi: 10.1016/j.ahj.2024.08.004. Online ahead of print.

1097-6744

https://pubmed.ncbi.nlm.nih.gov/39128659/?otool=iaurydwlib

https://hdl.handle.net/10137/13510

Artificial intelligence

Transthoracic echocardiography

Cardiovascular diseases

Heart failure

Heart valve disease

Remote area

Use of artificial intelligence-guided echocardiography to detect cardiac dysfunction and heart valve disease in rural and remote areas: Rationale and design of the AGILE-echo trial.

Journal Article

Publication