Literature DB >> 24817458

Computational model for prediction of fistula outcome.

Andrea Remuzzi1, Simone Manini.   

Abstract

BACKGROUND: The creation and management of an autologous arteriovenous fistula (AVF) as vascular access (VA) for hemodialysis patients is still a critical procedure. The placement of a functional and long-lasting VA derives from adequate planning of the surgical procedure based on physical examination, vascular mapping and selection of the best modality for arteriovenous anastomosis. The risk of AVF non-maturation and early failure is high, even when all precautions are taken to minimize these events. In addition, AVF surgery may develop very high blood flow exposing the patient to the risk of heart failure or hand ischemia.
METHODS: The choices of the surgeons on the modalities to perform a surgical intervention for AVF should take into consideration several factors including patient clinical condition, arterial and venous vessel sizes and elasticity. However, these evaluations cannot give direct indication on VA outcome in terms of blood flow after AVF maturation. We then took advantage of theoretical models of vascular network hemodynamics and of computational fluid dynamics to develop a numerical tool for the prediction of potential blood flow of a planned VA surgery on the basis of preoperative ultrasound evaluation of arterial and venous sizes and blood flow.
RESULTS: Here we present the numerical model, previously developed and tested, and we describe the web-based application that has been developed to help during surgical planning.
CONCLUSIONS: The use of this tool in the clinical setting should allow to reduce the incidence of AVF non-maturation as well as incidence of VA complications.

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Mesh:

Year:  2014        PMID: 24817458     DOI: 10.5301/jva.5000241

Source DB:  PubMed          Journal:  J Vasc Access        ISSN: 1129-7298            Impact factor:   2.283


  2 in total

Review 1.  The importance of success prediction in angioaccess surgery.

Authors:  Branko Fila; Saša Magaš; Predrag Pavić; Renata Ivanac; Marko Ajduk; Marko Malovrh
Journal:  Int Urol Nephrol       Date:  2016-05-18       Impact factor: 2.370

2.  Clinical use of computational modeling for surgical planning of arteriovenous fistula for hemodialysis.

Authors:  Michela Bozzetto; Stefano Rota; Valentina Vigo; Francesco Casucci; Carlo Lomonte; Walter Morale; Massimo Senatore; Luigi Tazza; Massimo Lodi; Giuseppe Remuzzi; Andrea Remuzzi
Journal:  BMC Med Inform Decis Mak       Date:  2017-03-14       Impact factor: 2.796

  2 in total

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