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A Unifying Algorithm in Microvascular Reconstruction of Oral Cavity Defects Using the Trilaminar Concept

Although many algorithms exist to classify oral cavity defects, they are limited by either considering a single subsite or failing to provide a concise reconstructive algorithm for the breadth of defects. Based upon our experience as a tertiary referral center, a unifying algorithm is presented that...

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Autores principales: Butler, Daniel P., Dunne, Jonathan A., Wood, Simon H., Jallali, Navid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6952141/
https://www.ncbi.nlm.nih.gov/pubmed/31942327
http://dx.doi.org/10.1097/GOX.0000000000002267
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author Butler, Daniel P.
Dunne, Jonathan A.
Wood, Simon H.
Jallali, Navid
author_facet Butler, Daniel P.
Dunne, Jonathan A.
Wood, Simon H.
Jallali, Navid
author_sort Butler, Daniel P.
collection PubMed
description Although many algorithms exist to classify oral cavity defects, they are limited by either considering a single subsite or failing to provide a concise reconstructive algorithm for the breadth of defects. Based upon our experience as a tertiary referral center, a unifying algorithm is presented that guides free flap selection in this heterogenous population. METHODS: All intraoral defects requiring microvascular reconstruction from February 2012 to August 2018 were reviewed. Defects were classified according to their depth as unilaminar (type U = mucosa only), bilaminar (type B = mucosa and bone), or trilaminar (type T = mucosa, bone, and skin) and the number and side of mucosal zones involved (from 1 to 5). Hard palate defects were considered separately and excluded if part of a wider maxillectomy defect. RESULTS: A total of 118 patients were eligible for inclusion in the study. Of type U defects involving 1 mucosal zone, 98% were reconstructed with a radial forearm free flap. Ninety-two percentage of type U defects involving ≥2 mucosal zones were reconstructed with an anterolateral thigh flap. Among type B defects, 86% were reconstructed with a fibula osseocutaneous free flap if less than 4 mucosal zones were involved and 100% reconstructed with an ALT if ≥4 mucosal zones were involved. The algorithm presented was accurate for 93% of the cases. Ninety-eight percentage of patients achieved intelligible speech and 72% returned to a normal diet. Flap success rate was 100%. CONCLUSIONS: The algorithm presented provides a simple system to guide the reconstruction of oral cavity defects.
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spelling pubmed-69521412020-01-15 A Unifying Algorithm in Microvascular Reconstruction of Oral Cavity Defects Using the Trilaminar Concept Butler, Daniel P. Dunne, Jonathan A. Wood, Simon H. Jallali, Navid Plast Reconstr Surg Glob Open Original Article Although many algorithms exist to classify oral cavity defects, they are limited by either considering a single subsite or failing to provide a concise reconstructive algorithm for the breadth of defects. Based upon our experience as a tertiary referral center, a unifying algorithm is presented that guides free flap selection in this heterogenous population. METHODS: All intraoral defects requiring microvascular reconstruction from February 2012 to August 2018 were reviewed. Defects were classified according to their depth as unilaminar (type U = mucosa only), bilaminar (type B = mucosa and bone), or trilaminar (type T = mucosa, bone, and skin) and the number and side of mucosal zones involved (from 1 to 5). Hard palate defects were considered separately and excluded if part of a wider maxillectomy defect. RESULTS: A total of 118 patients were eligible for inclusion in the study. Of type U defects involving 1 mucosal zone, 98% were reconstructed with a radial forearm free flap. Ninety-two percentage of type U defects involving ≥2 mucosal zones were reconstructed with an anterolateral thigh flap. Among type B defects, 86% were reconstructed with a fibula osseocutaneous free flap if less than 4 mucosal zones were involved and 100% reconstructed with an ALT if ≥4 mucosal zones were involved. The algorithm presented was accurate for 93% of the cases. Ninety-eight percentage of patients achieved intelligible speech and 72% returned to a normal diet. Flap success rate was 100%. CONCLUSIONS: The algorithm presented provides a simple system to guide the reconstruction of oral cavity defects. Wolters Kluwer Health 2019-07-24 /pmc/articles/PMC6952141/ /pubmed/31942327 http://dx.doi.org/10.1097/GOX.0000000000002267 Text en Copyright © 2019 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The American Society of Plastic Surgeons. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (http://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.
spellingShingle Original Article
Butler, Daniel P.
Dunne, Jonathan A.
Wood, Simon H.
Jallali, Navid
A Unifying Algorithm in Microvascular Reconstruction of Oral Cavity Defects Using the Trilaminar Concept
title A Unifying Algorithm in Microvascular Reconstruction of Oral Cavity Defects Using the Trilaminar Concept
title_full A Unifying Algorithm in Microvascular Reconstruction of Oral Cavity Defects Using the Trilaminar Concept
title_fullStr A Unifying Algorithm in Microvascular Reconstruction of Oral Cavity Defects Using the Trilaminar Concept
title_full_unstemmed A Unifying Algorithm in Microvascular Reconstruction of Oral Cavity Defects Using the Trilaminar Concept
title_short A Unifying Algorithm in Microvascular Reconstruction of Oral Cavity Defects Using the Trilaminar Concept
title_sort unifying algorithm in microvascular reconstruction of oral cavity defects using the trilaminar concept
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6952141/
https://www.ncbi.nlm.nih.gov/pubmed/31942327
http://dx.doi.org/10.1097/GOX.0000000000002267
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