Literature DB >> 16284953

Are mechanical microvascular anastomoses easier to learn than suture anastomoses?

Johann Zdolsek1, Håkan Ledin, Disa Lidman.   

Abstract

Sutured anastomoses of small vessels are considered difficult to learn. Mechanical anastomosis systems allow a more rapidly performed anastomosis. In order to compare the process of learning to perform sutured and mechanical microvascular anastomoses, two surgeons, with limited microvascular experience, performed 30 aortic and 30 femoral vein anastomoses in 30 Wistar rats. The methods compared were conventional suture, vascular closure system (VCS) and microvascular anastomatic coupler system (MAC). There were no inter-surgeon differences regarding patency or time to perform anastomoses. The average time to perform a suture anastomosis was 39 min (patency 80%). Anastomoses with the VCS system took 24 min (patency 25%), whereas the MAC couplers took 13 min to perform (patency 95%). There was a significant learning effect with sutures, but no obvious reduction in time to perform MAC coupler or VCS clip anastomoses was seen. MAC couplers were easiest to use, and allowed us to perform rapid anastomoses with high patency. (c) 2005 Wiley-Liss, Inc. Microsurgery 25:596-598, 2005.

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Year:  2005        PMID: 16284953     DOI: 10.1002/micr.20172

Source DB:  PubMed          Journal:  Microsurgery        ISSN: 0738-1085            Impact factor:   2.425


  3 in total

1.  New Absorbable Microvascular Anastomotic Devices Representing a Modified Sleeve Technique: Evaluation of Two Types of Source Material and Design.

Authors:  Woonhyeok Jeong; Kyuhee Kim; Daegu Son; Yunkun Kim
Journal:  Sci Rep       Date:  2019-07-29       Impact factor: 4.379

2.  Venous Coupler in Pediatric Free Tissue Transfer: Case Series and Literature Review.

Authors:  Salah Aldekhayel; Feras Alshomer; Bushra Alhazmi
Journal:  Plast Reconstr Surg Glob Open       Date:  2020-02-26

3.  End-to-end vascular anastomosis using a novel magnetic compression device in rabbits: a preliminary study.

Authors:  Qiang Lu; Kang Liu; Wei Zhang; Tao Li; Ai-Hua Shi; Hong-Fan Ding; Xiao-Peng Yan; Xu-Feng Zhang; Rong-Qian Wu; Yi Lv; Shan-Pei Wang
Journal:  Sci Rep       Date:  2020-04-06       Impact factor: 4.379

  3 in total

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