Valvular & structural heart disease
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
Authors' conclusion
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.
Study context
- Population
- Adults with CV risk factors and exercise intolerance, or concerns regarding heart valve disease, in rural and remote Australiafirst participants enrolled
- Participants
- 157 adults
- Comparison
- AI-guided TTE vs usual care
- AI-TTEn = 78
- Usual care (UC)n = 79reference
- Primary endpoint
- Composite of:
- Heart valve disease
- Heart failure (HF) diagnosis
- Follow-up
- 12 months
Methodological details5 rural and remote areas, Australia, Subgroup analysis stratified by age range and sex planned
- 5 rural and remote areas, Australia
- Subgroup analysis stratified by age range and sex planned
Primary result
As reported in the abstract
Baseline characteristics of first 157 participants
Baseline characteristics of first 157 participants
10-year HF incidence risk AI-TTE 20.0% · UC 13.4% · P = 0.089
- AI-TTE vs UC: P = 0.034 — age
- Heart valve disease as primary concern
- 37 (23.6%)
- Exercise intolerance
- 84.7% (n = 133)
- No abnormalities
- 33 (42.3%)
Original publication
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. Am Heart J. Published 10 August 2024. doi:10.
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