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主动脉瓣植入术中冠状动脉阻塞的发生率:自膨胀式与球囊扩张式瓣膜假体的荟萃分析和混合治疗比较

Incidence of Coronary Obstruction During Aortic Valve Implantation: Meta-Analysis and Mixt-Treatment Comparison of Self-Expandable Versus Balloon-Expandable Valve Prostheses.

作者信息

Wang Yu Fei, Liu Zai Qiang, Ma Xiao Teng, Yang Li Xia, Wang Zhi Jian, Zhou Yu Jie

机构信息

Cardiology Division, Beijing Jishuitan Hospital, Capital Medical University, 100035 Beijing, China.

Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, 100029 Beijing, China.

出版信息

Rev Cardiovasc Med. 2025 Jul 29;26(7):36208. doi: 10.31083/RCM36208. eCollection 2025 Jul.

DOI:10.31083/RCM36208
PMID:40776940
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12326413/
Abstract

BACKGROUND

Recently, the transcatheter aortic valve replacement (TAVR) indications have expanded; meanwhile, valve systems have continuously evolved and improved. However, coronary occlusion (CO), a rare but catastrophic consequence of TAVR surgery, limits the expansion of indications for TAVR. Moreover, comparisons between different systems remain scarce. This study aimed to evaluate the incidence of CO associated with TAVR, specifically comparing self-expanding valves (SEVs) and balloon-expandable valves (BEVs), and further assess the safety profile of these valve subtypes.

METHODS

The primary outcome of interest was the incidence of CO during TAVR using BEVs or SEVs. Electronic databases were searched from January 2009 to June 2023, and this study included randomized controlled trials, observational studies, and propensity pair-matched studies. Heterogeneity and inter-study variance were assessed using Cochran's Q, I, and τ (Sidik-Jonkman estimator). Random effects models were used based on the Bayesian theory framework. The node-splitting approach was generated to determine study network inconsistency. The convergence of the model was evaluated using the trajectory map, density map, and the potential scale reduction factor (PSRF). Rank sort graphs illustrate the best valve deployment techniques or valve types.

RESULTS

A total of 830 articles were searched referring to the incidence of CO using the valve deployment system of SEVs or BEVs during the TAVR procedure, from which 51 were included (27,784 patients). The procedure incidence of coronary obstruction was 0.4% for the SEVs and 0.6% for the BEVs. Treatment ranking based on network analysis revealed SAPIEN 3 (Edwards Lifesciences (Irvine, CA, USA)) possessed the best procedural CO incidence (0.05%) performance, whereas SAPIEN (Edwards Lifesciences (Irvine, CA, USA)) produced the worst (1.04%).

CONCLUSIONS

Our study indicates that CO incidence was not reduced during TAVR with BEVs compared to SEVs. SAPIEN 3 and SAPIEN had the lowest and highest TAVR-associated CO rates, respectively. These findings suggest that the SAPIEN 3 valve may be the best choice for reducing CO risk, and future studies should focus on its applicability in different populations. More randomized controlled trials with head-to-head comparisons of SEVs and BEVs are needed to address this open question.

THE PROSPERO REGISTRATION

CRD42024528269, https://www.crd.york.ac.uk/PROSPERO/view/CRD42024528269.

摘要

背景

近年来,经导管主动脉瓣置换术(TAVR)的适应症不断扩大;与此同时,瓣膜系统也在持续发展和改进。然而,冠状动脉阻塞(CO)作为TAVR手术罕见但灾难性的后果,限制了TAVR适应症的扩大。此外,不同系统之间的比较仍然很少。本研究旨在评估与TAVR相关的CO发生率,特别是比较自膨胀瓣膜(SEV)和球囊扩张瓣膜(BEV),并进一步评估这些瓣膜亚型的安全性。

方法

感兴趣的主要结果是使用BEV或SEV进行TAVR期间CO的发生率。检索了2009年1月至2023年6月的电子数据库,本研究纳入了随机对照试验、观察性研究和倾向配对匹配研究。使用Cochran's Q、I和τ(Sidik-Jonkman估计器)评估异质性和研究间方差。基于贝叶斯理论框架使用随机效应模型。采用节点拆分方法来确定研究网络的不一致性。使用轨迹图、密度图和潜在缩减值因子(PSRF)评估模型的收敛性。排名排序图展示了最佳的瓣膜植入技术或瓣膜类型。

结果

共检索到830篇关于在TAVR手术中使用SEV或BEV瓣膜植入系统时CO发生率的文章,其中纳入了51篇(27784例患者)。SEV的冠状动脉阻塞手术发生率为0.4%,BEV为0.6%。基于网络分析的治疗排名显示,SAPIEN 3(美国加利福尼亚州尔湾市爱德华兹生命科学公司)的手术CO发生率表现最佳(0.05%),而SAPIEN(美国加利福尼亚州尔湾市爱德华兹生命科学公司)最差(1.04%)。

结论

我们的研究表明,与SEV相比,使用BEV进行TAVR时CO发生率并未降低。SAPIEN 3和SAPIEN的TAVR相关CO发生率分别最低和最高。这些发现表明,SAPIEN 3瓣膜可能是降低CO风险的最佳选择,未来的研究应关注其在不同人群中的适用性。需要更多对SEV和BEV进行直接比较的随机对照试验来解决这个悬而未决的问题。

PROSPERO注册号:CRD42024528269,https://www.crd.york.ac.uk/PROSPERO/view/CRD42024528269

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fa2/12326413/4f4fdf9457e7/2153-8174-26-7-36208-g8.jpg
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