Predictors of early cerebrovascular events after transcatheter aortic valve replacement: a systematic review and meta-analysis

Background  Early cerebrovascular events (CVEs) following transcatheter aortic valve replacement (TAVR) are severe complications, but effective methods for predicting and preventing these events have not been well established. A systematic review and meta-analysis were performed to identify significant predictors of early CVEs post-TAVR.

Methods  MEDLINE/Embase databases were searched for articles published between December 2015 and April 2023. Original studies evaluating predictors of CVEs within 30 days post-TAVR after adjusting for confounders were included. Two investigators independently extracted data following the PRISMA statement. Meta-analyses of multivariable data were performed using DerSimonian and Laird random-effects models, with results expressed as odds ratios (ORs) and 95% confidence intervals (CIs). Robustness was assessed via Harbord’s test, nonparametric trim-and-fill analysis, leave-one-out sensitivity analysis, the QUIPS quality assessment tools, meta-regression, and subgroup analyses.

Results Among the 74 included studies, multivariate meta-analyses identified 11 predictors of early CVEs, including 9 patient-level predictors-a CHA₂DS₂-VASc ≥ 5, no prior heart failure, diabetes, isolated aortic stenosis, carotid artery stenosis, peripheral artery disease, advanced age, New York Heart Association class ≥ III, and significant left ventricular outflow tract calcification-and 2 procedure-level predictors: the absence of cerebral embolization protection and post-dilation. Additionally, 10 patient-level factors and 5 procedure-level factors were not associated with early CVEs, although significant heterogeneity was observed in most analyses.

Conclusions  This study identified multiple patient-level and procedure-level factors associated or not associated with early CVEs after TAVR. These findings support the development of a comprehensive risk prediction model that can accommodate diverse patient populations and evolving procedural techniques, thereby enhancing clinical risk management strategies.