Clinical, Echocardiographic, and Socioeconomic Predictors of Progression and Outcomes in Patients With Moderate Aortic Stenosis

Despite increased awareness of its clinical consequences, personalized risk stratification in patients with moderate aortic stenosis (AS) remains ambiguous. We studied predictors of progression and clinical outcomes in moderate AS to improve risk stratification and add to the existing literature.

Data collected through the Tempus Next care pathway intelligence platform at our tertiary referral center were retrospectively analyzed. The reports of echocardiograms performed from October 2017 to January 2020 were screened for descriptive or quantitative evidence of moderate AS. Follow-up extended until January 2022. Clinical data were extracted following manual chart review. Socioeconomic variables were collected based on zip-code-aggregated United States census data. The endpoints were progression from moderate to severe valvular AS, all-cause mortality, all-cause hospitalization, and heart failure (HF) hospitalization. The final multivariable model was selected using a variable selection algorithm inspired by greedy causal discovery algorithms.

A total of 34 450 echocardiograms (N = 25 204 patients) were screened during the inclusion period; 367 patients met inclusion criteria and were included in the final analysis. Progression to severe AS was noted in 172 patients (median time to progression 16 months). The final predictive models after variable selection exhibited modest predictive power: progression to severe AS, AUC = 0.68; all-cause mortality, 0.797; all-cause hospitalization, 0.629; heart failure hospitalization, 0.744. Variables predictive for the endpoints included comorbidities, echocardiographic variables, and demographics.

Our findings support further work and exploration of a paradigm shift in the assessment and management of AS, moving beyond traditional measures to a multiparametric model incorporating a broader spectrum of clinical, echocardiographic, and socioeconomic variables.