Chronological comparison of TAVI and SAVR stratified to surgical risk: a systematic review, meta-analysis, and meta-regression
Dae Yong Park, Seokyung An, Kameel Kassab, Neeraj Jolly, Steve Attanasio, Ray Sawaqed, Saurabh Malhotra, Rami Doukky, Aviral Vij
Abstract
BACKGROUND: Transcatheter aortic valve implantation (TAVI) has been established as a reasonable alternative to surgical aortic valve replacement (SAVR) in patients with severe aortic stenosis. However, long-term outcomes including valve durability and the need for reintervention are unanswered, especially in younger patients who tend to be low surgical risk. We performed a meta-analysis comparing clinical outcomes after TAVI and SAVR over 5 years stratified to low, intermediate, and high surgical risks. METHODS: We identified propensity score-matched observational studies and randomised controlled trials comparing TAVI and SAVR. Primary outcomes, including all-cause mortality, moderate or severe aortic regurgitation, moderate or severe paravalvular regurgitation, pacemaker placement, and stroke, were extracted. Meta-analyses of outcomes after TAVI compared to SAVR were conducted for different periods of follow-up. Meta-regression was also performed to analyse the correlation of outcomes over time. RESULTS: A total of 36 studies consisting of 7 RCTs and 29 propensity score-matched studies were selected. TAVI was associated with higher all-cause mortality at 4-5 years in patients with low or intermediate surgical risk. Meta-regression time demonstrated an increasing trend in the risk of all-cause mortality after TAVI compared with SAVR. TAVI was generally associated with a higher risk of moderate or severe aortic regurgitation, moderate or severe paravalvular regurgitation, and pacemaker placement. CONCLUSIONS: TAVI demonstrated an increasing trend of all-cause mortality compared with SAVR when evaluated over a long-term follow-up. More long-term data from recent studies using newer-generation valves and state-of-the-art techniques are needed to accurately assign risks.