Predictors of Permanent Pacemaker Implantation in Patients With Severe Aortic Stenosis Undergoing TAVR A Meta-Analysis

BACKGROUND Atrioventricular (AV) conduction disturbances requiring permanent pacemaker (PPM) implantation may complicate transcatheter aortic valve replacement (TAVR). Available evidence on predictors of PPM is sparse and derived from small studies. OBJECTIVES The objective of this study was to provide summary effect estimates for clinically useful predictors of PPM implantation after TAVR. METHODS We performed a systematic search for studies that reported the incidence of PPM implantation after TAVR and that provided raw data for the predictors of interest. Data on study, patient, and procedural characteristics were abstracted. Crude risk ratios (RRs) and 95% confidence intervals for each predictor were calculated by use of random effects models. Stratified analyses by type of implanted valve were performed. RESULTS We obtained data from 41 studies that included 11,210 TAVR patients, of whom 17% required PPM implantation after intervention. The rate of PPM ranged from 2% to 51% in individual studies (with a median of 28% for the Medtronic CoreValve Revalving System [MCRS] and 6% for the Edwards SAPIEN valve [ESV]). The summary estimates indicated increased risk of PPM after TAVR for men (RR: 1.23; p < 0.01); for patients with first-degree AV block (RR: 1.52; p < 0.01), left anterior hemiblock (RR: 1.62; p < 0.01), or right bundle branch block (RR: 2.89; p < 0.01) at baseline; and for patients with intraprocedural AV block (RR: 3.49; p < 0.01). These variables remained significant predictors when only patients treated with the MCRS bioprosthesis were considered. The data for ESV were limited. Unadjusted estimates indicated a 2.5-fold higher risk for PPM implantation for patients who received the MCRS than for those who received the ESV. CONCLUSIONS Male sex, baseline conduction disturbances, and intraprocedural AV block emerged as predictors of PPM implantation after TAVR. This study provides useful tools to identify high-risk patients and to guide clinical decision making before and after intervention. (C) 2014 by the American College of Cardiology Foundation.