Risk Prediction Model for Permanent Pacemaker Implantation after Transcatheter Aortic Valve Replacement

ABSTRACT

Background: Atrioventricular conduction disturbance requiring permanent pacemaker (PPM) implantation is the most common complication after transcatheter aortic valve replacement (TAVR). Improved risk stratification for potential need for post-procedure PPM implant prior to the TAVR procedure is warranted. The aim of this study was to develop and validate a risk-prediction model for PPM implantation after TAVR.

Methods: This PPM risk assessment model was developed using the 2012&2013 National Inpatient Sample (NIS). A logistic regression model was built to identify the predictors of PPM placement. The performance of the model was validated using the NIS 2014 dataset.

Results: Of 18,400 patients in the development cohort, 1,825 (9.9%) patients required PPM implantation after TAVR. After multivariate analysis, final predictive covariates of PPM implantation included left or right bundle branch block, bradycardia, 2nd-degree AV block and transfemoral approach. The estimated regression coefficients associated with these predictors were used to develop a scoring system. The proposed scoring system showed good discrimination in both development and validation cohorts, with c-statistics of 0.754 (95% CI: 0.726–0.782) and 0.746 (95% CI: 0.721–0.772) respectively. Calibration analysis indicated a good agreement between the observed rate of PPM and predicted risks of PPM by the risk score.

Conclusions: This PPM risk prediction model derived using the NIS database is a simple tool that can estimate individual risk of PPM prior to TAVR procedure. The model displayed good discrimination and calibration indices. This risk score can provide valuable information for patients’ counseling and also help identify high-risk patients who need close monitoring immediately after the TAVR procedure.

KEYWORDS:

• Aortic stenosis
• conduction abnormalities
• National Inpatient Sample
• permanent pacemaker
• transcatheter aortic valve replacement

Supplemental data for this article can be accessed on the publiaher’s website.

Acknowledgments

We acknowledge the support provided by the Biostatistics/Epidemiology/Research Design (BERD) component of the Center for Clinical and Translational Sciences (CCTS) for this project. CCTS is mainly funded by a grant (UL1 TR000371) from the National Center for Advancing Translational Sciences (NCATS), awarded to University of Texas Health Science Center at Houston. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NCATS.

Disclosure statements

Dr. Dhoble is a consultant for Edwards Lifesciences and St. Jude Medical; Dr. Smalling is a consultant for Edwards Lifesciences, Abbott Vascular, and St. Jude Medical; Dr. Nguyen reports consulting/proctor fees from Edwards LifeSciences and St. Jude Medical. The other authors report no disclosures.