Abstract 13862: Trends in Complication Rates Post-Transcatheter Aortic Valve Replacement

Abstract

Introduction: Transcatheter Aortic Valve Replacement (TAVR) is a mainstay of treatment for aortic valve stenosis for patients. It is unclear if this has resulted in a significant change in post-procedural complications over time. Hypothesis: We hypothesised a reduction in major complication rates across our study period given the improvement in delivery systems. Methods: This is a nationwide temporal trends study utilizing the 2016-2019 National In Patient Sample (NIS) registry. Patients who underwent TAVR including those with major procedural complications (i.e: need for transfusion or permanent pacemaker implantation [PPMI]) were identified. The trends in overall complication rate and individual complication rates between 2016 to 2019 were analysed. Multivariate model was built to predict the factors influencing complications. Results: Between 2016-2019, 217,110 patients underwent TAVR of which 12.6% had atleast one major complication. Proportion of complications decreased significantly across the study period(see Fig 1). Overall, females had a 10% higher complication rate (aOR 1.1, p=0.002) mainly driven by bleeding with over a 50% need for transfusion (aOR 1.57, p<0.001) while having a 12% lower risk of PPMI (aOR 0.88, p=0.001). The Northeast region had a significantly higher complication rate driven by higher bleeding, with PPMI rate not differing geographically. Charlson comorbidity index (CCI) score was predictive of higher bleeding with a score of >3 having over a threefold risk (aOR 3.4, p<0.001). Conclusions: Our study shows that although there is a reduction in complication rate post-TAVR, the changes are uneven across different complications and population groups. More than 10% of patients were still experiencing a complication as recently as 2019. This could be a reflection of moving towards lower risk population, recent improvements in valve profile and implantation technique and a better understanding of predictors of PPMI.