Suppr超能文献

前踝关节镜检查中神经血管结构的分布模式,以尽量减少结构损伤:解剖学研究。

The Distribution Pattern of the Neurovascular Structures for Anterior Ankle Arthroscopy to Minimize Structural Injury: Anatomical Study.

机构信息

Department of Anatomy, College of Medicine, Chung-Ang University, Seoul, Republic of Korea.

Anatomy Laboratory, College of Sports Science, Korea National Sport University, Seoul, Republic of Korea.

出版信息

Biomed Res Int. 2018 May 15;2018:3421985. doi: 10.1155/2018/3421985. eCollection 2018.

Abstract

INTRODUCTION

The aim of this study was to investigate entry points for anterior ankle arthroscopy that would minimize the risk of neurovascular injury.

METHODS

Thirty-eight specimens from 21 Korean cadavers (age range from 43 to 92 years, mean age of 62.3 years) were used for the study. For the measurements, the most prominent points of the lateral malleolus (LM) and the medial malleolus (MM) were identified before dissection. A line connecting the LM and MM, known as the intermalleolar line, was used as a reference line. We measured 14 variables passed on the reference line.

RESULTS

This study found that the nerves were located at 40.0%, 50.0%, and 82.0% of the reference line from the lateral malleolus. We also found that the arteries were located at 22.0%, 35.0%, and 60% of the reference line from the lateral malleolus.

DISCUSSION

If all the variables are combined (nerves, arteries, and veins), then there is no safety zone for anterior portal placement. Therefore, we recommend that surgeons concentrate primarily on the arteries and nerves in the clinical setting.

摘要

简介

本研究旨在探讨踝关节前侧关节镜入路,以降低神经血管损伤的风险。

方法

本研究使用了 21 具韩国尸体(年龄 43 岁至 92 岁,平均年龄 62.3 岁)的 38 个标本。在解剖前,确定外踝(LM)和内踝(MM)最突出的点。一条连接 LM 和 MM 的线,即踝间线,被用作参考线。我们在参考线上测量了 14 个变量。

结果

本研究发现,神经位于距外踝参考线的 40.0%、50.0%和 82.0%处。我们还发现,动脉位于距外踝参考线的 22.0%、35.0%和 60.0%处。

讨论

如果将所有变量(神经、动脉和静脉)组合在一起,那么前入路就没有安全区域。因此,我们建议外科医生在临床实践中主要关注动脉和神经。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/644d/5976955/bff7ec7c8739/BMRI2018-3421985.001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验