Sage Clinical Medicine & Research
Jul 15, 2026 · 3 min · 4 segments
Read the article here: https://journals.sagepub.com/doi/full/10.1177/30494826251413753
In this article, the authors uncover novel predictors of transcatheter valve replacement futility, which is a, an important issue, um, and also midterm outcomes using, uh, an interpretable machine learning approach.
So traditional risk models are poorly predictive of the futility of TAVR, failing to identify high-risk patient that will not benefit from the procedure.
Um, so the authors proposed an interpretable machine learning model which identifies a panel of novel predictors for poor midterm, uh, outcomes of TAVR, significantly outperforming traditional risk scores.
In particular, frailty and aortic stiffness appears, uh, to be, uh, very strong predictors of, uh, TAVR futility.
Interestingly, the authors also observed a, um, cholesterol paradox where in this high-risk population, uh, lower LDS cholesterol was, uh, strongly, uh, predictive of poor outcomes, and this has been, uh, reported in other studies.
In this article, the authors uncover novel predictors of transcatheter valve replacement futility, which is a, an important issue, um, and also midterm outcomes using, uh, an interpretable machine learning approach.
So traditional risk models are poorly predictive of the futility of TAVR, failing to identify high-risk patient that will not benefit from the procedure.
Um, so the authors proposed an interpretable machine learning model which identifies a panel of novel predictors for poor midterm, uh, outcomes of TAVR, significantly outperforming traditional risk scores.
In particular, frailty and aortic stiffness appears, uh, to be, uh, very strong predictors of, uh, TAVR futility.
Interestingly, the authors also observed a, um, cholesterol paradox where in this high-risk population, uh, lower LDS cholesterol was, uh, strongly, uh, predictive of poor outcomes, and this has been, uh, reported in other studies.
The rest of this transcript — segmented and speaker-labeled, so you land on the exact moment something was said
Search every transcript — by keyword, by phrase, or by meaning, across every show Radar indexes
Trends — what is surging across podcasts, measured against its own baseline
Alerts — when a name you follow appears in a newly indexed episode
No account is needed to search Radar.
