Impact of aortic stenosis progression rate on prognosis

Abstract

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Aortic stenosis (AoS) is a progressive disease of the aortic valve (AoV) and, ultimately, of the myocardium, potentially fatal. Most studies considerthat the rate of AoS progression is time-invariant while recognizing wide variability between patients (pts) and among the same patient. Aim 1) evaluate the rate of AoS progression, 2) cluster pts into rapid progressors (RP) and slow progressors (SP) and explore possible predictors, and 3) evaluate the impact of progression rate on cardiac damage and survival. Methods We retrospectively identified 914 pts (age 76 ± 8 years, 52% female, median follow-up time 6.8 years) with mild to severe AoS who had undergone > 1 echocardiogram from 2012 to 2020. Seriated echocardiograms, biomarkers, and clinical records were consulted, providing a multiparametric data frame for modeling AoS progression and outcomes. Bayesian hierarchical models were trained using machine learning algorithms (MLA) to predict aortic peak velocity (APV) as a function of time. After selecting the best model, individual AoS acceleration rates were estimated from the posterior distribution, and pts were clustered in RP and SP using MLA. Results APV was best modeled by a logistic function of time. 483 pts were clustered as RP (53%) and 431 as SP (47%), with acceleration rates estimated at 0.14 ± 0.02 years-1 and 0.09 ± 0.02 years-1, respectively (p< 0.01). There was no association between progression rate and clinical variables. RP had a higher incidence of cardiac damage at eight years than SP (p = 0.01). Rapid progression was associated with higher mortality (Hazard Ratio (HR) 1.28, p = 0.02), persisting after adjustment for demographics, comorbidities, AoS severity, and time-dependent AoV replacement (HR 1.36, p<0.01). A 5-year mortality prediction model incorporating AoS progression rate to age, gender, and AoS severity displayed higher performance (C-statistic= 0.82, change in C-statistic= 0.02, p<0.01, Brier score= 0.11). RP consistently displayed a higher risk of excess mortality across all ranges of aortic peak velocities, such that a velocity threshold of 3.2 m/s in RP carried the same risk of death as 4 m/s in SP. Conclusions A nonlinear model of AoS progression and two clusters of progressors were identified. Rapid progression was associated with earlier cardiac damage and higher mortality, independent of baseline AoS severity. Incorporating AS acceleration rate in clinical practice can improve AoS stratification and provide a proactive time frame for follow-up and intervention.