Key result
Conventional surgical and TAVR-specific mortality models show suboptimal predictive performance in external populations.
Why the study?
With expanding indications and growing numbers of TAVR procedures, accurately predicting mortality after TAVR is important.
How accurately do current mortality prediction models predict post-TAVR mortality in patients with severe symptomatic aortic stenosis?
How accurately do current mortality prediction models predict post-TAVR mortality in patients with severe symptomatic aortic stenosis?
Current mortality prediction models for TAVR have limited external validity, necessitating a comprehensive risk assessment approach incorporating frailty, imaging, and biomarkers.
Warrants caution against sole reliance on existing models for TAVR decisions; leaves open development of improved, externally validated tools.
Introduction: Over the last decade, transcatheter aortic valve replacement (TAVR) has emerged as a treatment option for most patients with severe symptomatic aortic stenosis (AS). With growing indications and exponential increase in the number of TAVR procedures, it is important to be able to accurately predict mortality after TAVR.Areas covered: Herein, we review the surgical and TAVR-specific mortality prediction models (MPMs) and their performance in their original derivation and external validation cohorts. We then discuss the role of other important risk assessment tools such as frailty, echocardiographic parameters, and biomarkers in patients, being considered for TAVR.Expert opinion: Conventional surgical MPMs have suboptimal predictive performance and are mis-calibrated when applied to TAVR populations. Although a number of TAVR-specific MPMs have been developed, their utility is also limited by their modest discriminative ability when applied to populations external to their original derivation cohorts. There is an unmet need for robust TAVR MPMs that accurately predict post TAVR mortality. In the interim, heart teams should utilize the currently available TAVR-specific MPMs in conjunction with other prognostic factors, such as frailty, echocardiographic or computed tomography (CT) imaging parameters, and biomarkers for risk assessment of patients, being considered for TAVR.
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Gupta et al. (2021) conducted a review in Severe symptomatic aortic stenosis undergoing TAVR. Mortality prediction models (MPMs) was evaluated on Post-TAVR mortality prediction. Conventional surgical and TAVR-specific mortality prediction models demonstrate suboptimal predictive performance and modest discriminative ability when applied to external TAVR populations.
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