Fighting time: the critical importance of pre-TAVR mortality risk prediction.

BACKGROUND

Symptomatic severe aortic valve stenosis (AS) is a life-threatening condition requiring prompt medical attention. While transcatheter aortic valve replacement (TAVR) is an effective treatment, current scheduling practices often do not account for individual patient risk profiles due to limited data on mortality rates during the waiting period and a lack of viable risk assessment. Consequently, non-prioritized wait times may be unacceptably long for high-risk patient populations.

OBJECTIVE

This study aimed to evaluate the mortality rate of patients with symptomatic severe AS awaiting TAVR and identify pragmatic clinical risk predictors during this period.

METHODS

Between January 2019 and December 2023, 2,454 patients with symptomatic severe AS, were scheduled for TAVR after an interdisciplinary Heart Team discussion at the Heart Center Bonn. Mortality during the waiting period was assessed, and the characteristics of survivors (patients who underwent TAVR) were compared to non-survivors (patients who died before the procedure).

RESULTS

The median waiting time for TAVR was 41 days. A total of 105 (4.3%) patients died during the waiting period, with a median time to death of 29 days. By comparison, 30 day post-TAVR mortality, including the intervention, was 1.7%. Multivariate regression analysis identified independent predictors of pre-TAVR mortality including reduced left ventricular ejection fraction, decreased estimated glomerular filtration rate, mitral regurgitation, tricuspid regurgitation, and advanced heart failure symptoms. An IMPACT score, incorporating these parameters, strongly predicted outcome with a hazard ratio for mortality of 2.1 greatly outperforming both EuroSCORE II and STS-PROM. The IMPACT score of ≥ 5 identified high-risk patients with a pre-TAVR mortality rate of 12.6%.

CONCLUSION

The mortality rate for patients with symptomatic severe AS awaiting TAVR is unacceptably high. Utilizing the IMPACT score could enable precise risk stratification, identifying patients who require urgent or prioritized intervention to improve outcomes.