Efficacy and safety of trans-catheter repair devices for mitral regurgitation: A systematic review and meta-analysis.

Domenico D'Amario,Renzo Laborante,Marco Mennuni,Marianna Adamo,Marco Metra, Giuseppe Patti

International journal of cardiology(2024)

引用 0|浏览1
暂无评分
摘要
BACKGROUND:Several repair strategies emerged as possible treatment for severe mitral regurgitation (MR). A systematic review and meta-analysis was performed to compare the different percutaneous mitral valve repair approaches. METHODS:PubMed and Scopus electronic databases were scanned for eligible studies until December 11th, 2023. Clinical efficacy endpoints were all-cause mortality, major adverse cardiovascular events, and post-procedural NYHA functional class <3; the echocardiographic efficacy endpoint was a post-intervention residual MR less than moderate. Safety endpoints and procedural outcome measures were also assessed. RESULTS:Eleven studies were included: 8 [N = 1662 patients, mean follow-up (FUP) 294 days] compared MitraClip® vs Pascal® device, 2 (N = 195 patients) MitraClip® vs Carillon® and 1 study (N = 186 patients) evaluated MitraClip® against Cardioband®. The Pascal®-treated group had lower MR degree compared to the MitraClip®-treated group, without difference in post-intervention mean trans-mitral gradient and in clinical and safety endpoints. A longer procedure time was observed in the Pascal® group, albeit with a lower average number of implanted devices per procedure. The two studies comparing MitraClip® and Carillon® were inconsistent in terms of both efficacy and safety outcomes, while the study evaluating MitraClip® vs Cardioband® showed that the latter might confer a significant clinical benefit, with a similar reduction in MR. CONCLUSIONS:Pascal® is as safe and clinically effective as MitraClip® in treating patients with MR, with an apparent greater reduction in the magnitude of residual valve insufficiency over the long term. Data on Cardioband® and Carillon® are not robust enough to draw conclusions from the use of such devices.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要