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. 2025 Feb;38(2):129-132.
doi: 10.1016/j.echo.2024.10.010. Epub 2024 Oct 30.

Machine Learning to Stratify Risk in Low-Gradient Aortic Stenosis Among Medicare Beneficiaries

Sean W Dooley  1 , Naveena V K Yanamala  2 , Nora Al-Roub  3 , Nicholas Spetko  1 , Madeline A Cassidy  3 , Constance Angell-James  3 , Partho P Sengupta  4 , Jordan B Strom  5
Affiliations

Machine Learning to Stratify Risk in Low-Gradient Aortic Stenosis Among Medicare Beneficiaries

Sean W Dooley et al. J Am Soc Echocardiogr. 2025 Feb.
No abstract available

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Conflict of interest statement

Conflicts of Interest None.

Figures

Figure:
Figure:. Kaplan-Meier Curve Evaluating Time to Death by AI-Risk Category and Receipt of Aortic Valve Replacement Among Individuals with Severe Low-gradient Aortic Stenosis
Displayed is a Kaplan Meier curve demonstrating the proportion of individuals without an event (death; y-axis) according to time in years (x-axis) from the index echocardiogram by machine-learning (ML) designated risk group and receipt of aortic valve replacement (AVR). The red curve indicates individuals determined to be higher-risk by the ML algorithm who received an AVR in follow-up, the green curve indicates individuals determined to be lower-risk who received an AVR, the blue curve indicates individuals at higher-risk who did not receive an AVR, and the orange curve indicates individuals at lower-risk who did not receive an AVR. Numbers in the risk set are provided below at 1-year intervals. The log-rank p-value for comparison across groups was <0.001.
See this image and copyright information in PMC

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