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Prognostic value of a three-dimensional dynamic quantitative analysis system to measure facial motion in acute facial paralysis patients
BACKGROUND: To investigate the prognostic value of a three-dimensional dynamic quantitative analysis system to measure facial motion (3D ASFM) in acute facial palsy patients and compare it with subjective grading methods and electroneurography. METHODS: We continuously recruited 37 patients with acu...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7368680/ https://www.ncbi.nlm.nih.gov/pubmed/32682430 http://dx.doi.org/10.1186/s13005-020-00230-6 |
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author | Zhao, Yang Feng, Guodong Wu, Haiyan Aodeng, Surita Tian, Xu Volk, Gerd Fabian Guntinas-Lichius, Orlando Gao, Zhiqiang |
author_facet | Zhao, Yang Feng, Guodong Wu, Haiyan Aodeng, Surita Tian, Xu Volk, Gerd Fabian Guntinas-Lichius, Orlando Gao, Zhiqiang |
author_sort | Zhao, Yang |
collection | PubMed |
description | BACKGROUND: To investigate the prognostic value of a three-dimensional dynamic quantitative analysis system to measure facial motion (3D ASFM) in acute facial palsy patients and compare it with subjective grading methods and electroneurography. METHODS: We continuously recruited 37 patients with acute (< 1 month) Bell’s palsy. An integrated evaluation of facial palsy was performed for each patient. The integrated evaluation included the House-Brackmann grading system (H-BGS), Sunnybrook Facial Grading System (SFGS), electroneurography and three-dimensional objective measurements. Then, the entire set of evaluations were repeated for each patient 1 month later. The patients were followed up monthly until recovery or for up to more than 6 months. We adopted the SFGS and H-BGS as the representative subjective grading system and final criteria for recovery. Poor recovery was defined as an SFGS score less than 70 or H-BGS score higher than II. RESULTS: Multiple regression analysis was performed to find the best prognostic indicators. In less than 1 month from onset, ENoG had the highest prognostic value. However, in the second month from onset, the results of SFGS and 3D ASFM were identified as the best prognostic parameters, and a prediction formula with a determination coefficient of 0.673 was established. The receiver operating characteristic curves revealed that a gross score of the 3D ASFM less than 31 in the first evaluation and 49 in the second evaluation had higher sensitivity and specificity to predict poor recovery. CONCLUSIONS: In different phases of Bell’s palsy, the best predictor of prognosis is different. ENOG is the most effective predictor of the prognosis in the first month after onset. In the second month after onset, the combination of SFGS and 3D ADSM is considered to be the best prognostic predictor. |
format | Online Article Text |
id | pubmed-7368680 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-73686802020-07-20 Prognostic value of a three-dimensional dynamic quantitative analysis system to measure facial motion in acute facial paralysis patients Zhao, Yang Feng, Guodong Wu, Haiyan Aodeng, Surita Tian, Xu Volk, Gerd Fabian Guntinas-Lichius, Orlando Gao, Zhiqiang Head Face Med Methodology BACKGROUND: To investigate the prognostic value of a three-dimensional dynamic quantitative analysis system to measure facial motion (3D ASFM) in acute facial palsy patients and compare it with subjective grading methods and electroneurography. METHODS: We continuously recruited 37 patients with acute (< 1 month) Bell’s palsy. An integrated evaluation of facial palsy was performed for each patient. The integrated evaluation included the House-Brackmann grading system (H-BGS), Sunnybrook Facial Grading System (SFGS), electroneurography and three-dimensional objective measurements. Then, the entire set of evaluations were repeated for each patient 1 month later. The patients were followed up monthly until recovery or for up to more than 6 months. We adopted the SFGS and H-BGS as the representative subjective grading system and final criteria for recovery. Poor recovery was defined as an SFGS score less than 70 or H-BGS score higher than II. RESULTS: Multiple regression analysis was performed to find the best prognostic indicators. In less than 1 month from onset, ENoG had the highest prognostic value. However, in the second month from onset, the results of SFGS and 3D ASFM were identified as the best prognostic parameters, and a prediction formula with a determination coefficient of 0.673 was established. The receiver operating characteristic curves revealed that a gross score of the 3D ASFM less than 31 in the first evaluation and 49 in the second evaluation had higher sensitivity and specificity to predict poor recovery. CONCLUSIONS: In different phases of Bell’s palsy, the best predictor of prognosis is different. ENOG is the most effective predictor of the prognosis in the first month after onset. In the second month after onset, the combination of SFGS and 3D ADSM is considered to be the best prognostic predictor. BioMed Central 2020-07-18 /pmc/articles/PMC7368680/ /pubmed/32682430 http://dx.doi.org/10.1186/s13005-020-00230-6 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Methodology Zhao, Yang Feng, Guodong Wu, Haiyan Aodeng, Surita Tian, Xu Volk, Gerd Fabian Guntinas-Lichius, Orlando Gao, Zhiqiang Prognostic value of a three-dimensional dynamic quantitative analysis system to measure facial motion in acute facial paralysis patients |
title | Prognostic value of a three-dimensional dynamic quantitative analysis system to measure facial motion in acute facial paralysis patients |
title_full | Prognostic value of a three-dimensional dynamic quantitative analysis system to measure facial motion in acute facial paralysis patients |
title_fullStr | Prognostic value of a three-dimensional dynamic quantitative analysis system to measure facial motion in acute facial paralysis patients |
title_full_unstemmed | Prognostic value of a three-dimensional dynamic quantitative analysis system to measure facial motion in acute facial paralysis patients |
title_short | Prognostic value of a three-dimensional dynamic quantitative analysis system to measure facial motion in acute facial paralysis patients |
title_sort | prognostic value of a three-dimensional dynamic quantitative analysis system to measure facial motion in acute facial paralysis patients |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7368680/ https://www.ncbi.nlm.nih.gov/pubmed/32682430 http://dx.doi.org/10.1186/s13005-020-00230-6 |
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