Is Global Limb Anatomic Staging System Classification a Useful Tool in Predicting Lower Limb Revascularization Procedures' Success?

全球肢体解剖分期系统分类是预测下肢血管重建手术成功率的有效工具吗?

阅读:1

Abstract

BACKGROUND: GLASS (Global Limb Anatomic Staging System) classification is a classification proposed in 2019 by The Lower Extremity Guidelines Committee of the Society for Vascular Surgery, which aims to identify the anatomic substrate that defines the severity of a lower extremity arterial injury and predict the success rate of possible revascularization. The aim of the study is to demonstrate the usefulness of this classification and if it is a reliable tool in predicting the success of the revascularization procedures for patients with chronic limb-threatening ischemia (CLTI). METHODS: A retrospective study was conducted on patients undergoing revascularization for CLTI. Glass staging was applied to angiographic data, categorizing them into GLASS 1, 2, or 3 based on the complexity of the femoropopliteal and infrapopliteal lesions. We investigated the clinical characteristics and types of endovascular treatment in correlation with GLASS classification. We also evaluated the technical success of revascularization procedures and the specificity and accuracy of the GLASS classification. RESULTS: After the first testing, we found out that GLASS classification has a sensitivity of 63% and a specificity of 77%. After the second testing, the sensitivity was 82%. of 77% also. The follow-up of this sample was made after 1 year, with no patients lost to follow-up and with an amputation-free survival of 81.3%. CONCLUSIONS: GLASS 1 and 2 patients had significantly higher rates of success compared to GLASS 3. GLASS serves as a valuable tool in predicting revascularization success and provides a standardized approach to anatomical complexity, but further studies should integrate more data in order to enhance its predictive capability.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。