Definition and Validation of Prognostic Phenotypes in Moderate Aortic Stenosis (JIMG February 2025)-Article: Definition and Validation of Prognostic Phenotypes in Moderate Aortic Stenosis

Article: Definition and Validation of Prognostic Phenotypes in Moderate Aortic Stenosis

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This study delved into moderate aortic stenosis (AS), a condition involving the narrowing of the aortic valve, and aimed to identify risk phenotypes using machine learning techniques. Conducted by a team led by Jonathan Sen and published in JACC: Cardiovascular Imaging, researchers sought to delineate groups within those suffering from moderate AS to better guide treatment decisions, particularly regarding aortic valve replacement (AVR), be it surgical or via transcatheter (TAVR).<br /><br />The researchers employed unsupervised clustering algorithms on a cohort of 2,469 patients, identifying four distinct clusters based on demographic, clinical, and echocardiographic data. The clusters were characterized as: low-risk, calcified AV, low-flow AS, and cardiovascular-comorbid. These clusters were externally validated with a separate cohort of 1,358 individuals. The study tracked composite outcomes of cardiac death, heart failure hospitalization, or AV intervention over five years.<br /><br />Notably, outcomes varied significantly across clusters. The cardiovascular-comorbid cluster presented the highest risk, with AVR showing notable benefits in reducing adverse outcomes mainly in those with calcified AVs, but not in other groups like the low-risk or low-flow clusters. While the research underscored the heterogeneity within moderate AS patients, it highlighted that certain phenotypes, particularly those with calcified AV, could significantly benefit from focused interventions.<br /><br />Conclusively, the study emphasizes the importance of a nuanced approach to managing moderate AS, recommending that patient management be tailored not solely based on AS severity but also on a comprehensive clinical phenotype that includes demographic and comorbid profiles. Further research could explore more comprehensive treatment strategies adapted to these distinct phenotypic groups to enhance patient outcomes.

Keywords

moderate aortic stenosis

risk phenotypes

machine learning

aortic valve replacement

unsupervised clustering

calcified aortic valve

cardiovascular-comorbid

Jonathan Sen

JACC: Cardiovascular Imaging

patient management