What is the incidence and what are the predictors of permanent pacemaker implantation following TAVI in patients with pre-existing right bundle branch block?
Patients with pre-existing RBBB undergoing TAVI have a high incidence (37-39%) of requiring permanent pacemaker implantation, highlighting the need for individualized procedural planning and risk stratification.
BACKGROUND Pre-existing right bundle branch block (RBBB) is the leading predictor of permanent pacemaker implantation (PPI) following transcatheter aortic valve implantation (TAVI). The applicability of conventional PPI predictors in this high-risk subgroup remains unclear. This review evaluates PPI incidence and associated predictors in TAVI patients with pre-existing RBBB. METHODS A systematic review of PubMed, Scopus, Embase, and Web of Science identified studies reporting PPI incidence and predictors in RBBB patients undergoing TAVI. Studies not addressing RBBB-specific factors were excluded. Pooled PPI incidence was calculated, and a qualitative narrative synthesis of predictors was performed. RESULTS Of 2,269 identified references, 22 studies with 429,342 patients met inclusion criteria. Within the RBBB cohort, the mean age was 81.6 ± 7.4 years, with 64.2% male, and 23.7% having atrial fibrillation. Balloon-expandable valves were used in 69.8% of cases, and the transfemoral approach in 88.6%. The pooled PPI incidence was 37% across 17 studies. Substantial interstudy heterogeneity necessitated further analysis amongst 13 studies reporting consistent 30-day follow-up, which yielded 39% incidence. PPI predictors in the RBBB cohort encompassed demographic, anatomical, electrophysiological, and procedural domains. CONCLUSION Patients with baseline RBBB have significantly higher post-TAVI PPI rates. Identifying RBBB specific predictors could facilitate individualised procedural planning and risk stratification. This review reinforces how both traditional (e.g. implantation depth) and non-traditional (e.g. female sex, myocardial fibrosis, calcium volume and distribution) factors have an amplified role in predicting PPI risk, emphasising the need for further research in this subgroup to improve risk stratification and reduce PPI incidence.
Prabhu et al. (Sun,) studied this question.