AI Echo mobile screening for early signs of heart failure

Diagnosis of sub-clinical heart failure with preserved ejection fraction is challenging and echo services are traditionally limited to tertiary echo centres.  Early signs of heart failure often go undiagnosed until patients are hospitalized for heart failure syndrome.

We want to extend echo diagnostics into the community, especially for the primary care diabetes population, so that we can detect diastolic dysfunction early and intervene early to delay disease progression. In this study, measured diastolic parameters by AI Echo with point of care ultrasound (POCUS) were compared with manual measurements on CART based echo. 

AI Echo with POCUS showed very good diagnostic accuracy in detecting diastolic dysfunction, and matched well with manual echo irrespective of image quality. AI Echo addressed diagnostic challenges of sub-clinical HFpEF, allowing for echo screening at the community level, particularly in the population at high risk of developing heart failure. 

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