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Learning Curve for Using Intraoperative Neural Monitoring Technology of Thyroid Cancer
We investigated the learning curve for using intraoperative neural monitoring technology in thyroid cancer, with a view to reducing recurrent laryngeal nerve injury complications. Radical or combined radical surgery for thyroid cancer was performed in 82 patients with thyroid cancer and 147 recurren...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6388327/ https://www.ncbi.nlm.nih.gov/pubmed/30886865 http://dx.doi.org/10.1155/2019/8904736 |
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author | Zhao, Ning Bai, Zhigang Teng, Changsheng Zhang, Zhongtao |
author_facet | Zhao, Ning Bai, Zhigang Teng, Changsheng Zhang, Zhongtao |
author_sort | Zhao, Ning |
collection | PubMed |
description | We investigated the learning curve for using intraoperative neural monitoring technology in thyroid cancer, with a view to reducing recurrent laryngeal nerve injury complications. Radical or combined radical surgery for thyroid cancer was performed in 82 patients with thyroid cancer and 147 recurrent laryngeal nerves were dissected. Intraoperative neural monitoring technology was applied and the “four-step method” used to monitor recurrent laryngeal nerve function. When the intraoperative signal was attenuated by more than 50%, recurrent laryngeal nerve injury was diagnosed, and the point and causes of injury were determined. The time required to identify the recurrent laryngeal nerve was 0.5–2 min and the injury rate was 2.7%; injuries were diagnosed intraoperatively. Injury most commonly occurred at or close to the point of entry of the nerve into the larynx and was caused by stretching, tumor adhesion, heat, and clamping. The groups are divided in chronological order; a learning curve for using intraoperative neural monitoring technology in thyroid cancer surgery was generated based on the time to identify the recurrent laryngeal nerve and the number of cases with nerve injury. The time to identify the recurrent laryngeal nerve and the number of injury cases decreased markedly with increasing patient numbers. There is a clear learning curve in applying intraoperative neural monitoring technology to thyroid cancer surgery; appropriate use of such technology aids in the protection of the recurrent laryngeal nerve. |
format | Online Article Text |
id | pubmed-6388327 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-63883272019-03-18 Learning Curve for Using Intraoperative Neural Monitoring Technology of Thyroid Cancer Zhao, Ning Bai, Zhigang Teng, Changsheng Zhang, Zhongtao Biomed Res Int Clinical Study We investigated the learning curve for using intraoperative neural monitoring technology in thyroid cancer, with a view to reducing recurrent laryngeal nerve injury complications. Radical or combined radical surgery for thyroid cancer was performed in 82 patients with thyroid cancer and 147 recurrent laryngeal nerves were dissected. Intraoperative neural monitoring technology was applied and the “four-step method” used to monitor recurrent laryngeal nerve function. When the intraoperative signal was attenuated by more than 50%, recurrent laryngeal nerve injury was diagnosed, and the point and causes of injury were determined. The time required to identify the recurrent laryngeal nerve was 0.5–2 min and the injury rate was 2.7%; injuries were diagnosed intraoperatively. Injury most commonly occurred at or close to the point of entry of the nerve into the larynx and was caused by stretching, tumor adhesion, heat, and clamping. The groups are divided in chronological order; a learning curve for using intraoperative neural monitoring technology in thyroid cancer surgery was generated based on the time to identify the recurrent laryngeal nerve and the number of cases with nerve injury. The time to identify the recurrent laryngeal nerve and the number of injury cases decreased markedly with increasing patient numbers. There is a clear learning curve in applying intraoperative neural monitoring technology to thyroid cancer surgery; appropriate use of such technology aids in the protection of the recurrent laryngeal nerve. Hindawi 2019-02-11 /pmc/articles/PMC6388327/ /pubmed/30886865 http://dx.doi.org/10.1155/2019/8904736 Text en Copyright © 2019 Ning Zhao et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Clinical Study Zhao, Ning Bai, Zhigang Teng, Changsheng Zhang, Zhongtao Learning Curve for Using Intraoperative Neural Monitoring Technology of Thyroid Cancer |
title | Learning Curve for Using Intraoperative Neural Monitoring Technology of Thyroid Cancer |
title_full | Learning Curve for Using Intraoperative Neural Monitoring Technology of Thyroid Cancer |
title_fullStr | Learning Curve for Using Intraoperative Neural Monitoring Technology of Thyroid Cancer |
title_full_unstemmed | Learning Curve for Using Intraoperative Neural Monitoring Technology of Thyroid Cancer |
title_short | Learning Curve for Using Intraoperative Neural Monitoring Technology of Thyroid Cancer |
title_sort | learning curve for using intraoperative neural monitoring technology of thyroid cancer |
topic | Clinical Study |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6388327/ https://www.ncbi.nlm.nih.gov/pubmed/30886865 http://dx.doi.org/10.1155/2019/8904736 |
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