Transcatheter Aortic Valve Implantation: Addressing the Subsequent Risk of Permanent Pacemaker Implantation

Transcatheter aortic valve implantation (TAVI) is now a commonly used therapy in patients with severe aortic stenosis, even in those patients at low surgical risk. The indications for TAVI have broadened as the therapy has proven to be safe and effective. Most challenges associated with TAVI after its initial introduction have been impressively reduced; however, the possible need for post-TAVI permanent pacemaker implantation (PPI) secondary to conduction disturbances continues to be on the radar. Conduction abnormalities post-TAVI are always of concern given that the aortic valve lies in close proximity to critical components of the cardiac conduction system. This review will present a summary of noteworthy pre-and post-procedural conduction blocks, the best use of telemetry and ambulatory device monitoring to avoid unnecessary PPI or to recognize the need for late PPI due to delayed high-grade conduction blocks, predictors to identify those patients at greatest risk of requiring PPI, important CT measurements and considerations to optimize TAVI planning, and the utility of the MInimizing Depth According to the membranous Septum (MIDAS) technique and the cusp-overlap technique. It is stressed that careful membranous septal (MS) length measurement by MDCT during pre-TAVI planning is necessary to establish the optimal implantation depth before the procedure to reduce the risk of compression of the MS and consequent damage to the cardiac conduction system.

Automated summary

Transcatheter aortic valve implantation (TAVI) is a safe and effective therapy for severe aortic stenosis, and its indications have expanded. Post-TAVI conduction abnormalities remain a concern, and careful planning and measurements are needed to optimize the procedure and minimize the risk of cardiac conduction system damage. This review discusses important factors such as pre- and post-procedural conduction blocks, telemetry and ambulatory device monitoring, predictors for PPI, and techniques to optimize TAVI planning.