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Ultrasound-derived muscle assessment system for older adults: a promising muscle mass estimation tool

BACKGROUND: Quantitative assessment of muscle mass is a critical step in sarcopenia disease management. Expanding upon the use of ultrasound in foetal growth assessment, we established and validated an ultrasound-derived muscle assessment system for older adults at a risk of sarcopenia. METHODS: A t...

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Autores principales: Tang, Xinyi, Huang, Songya, Huang, Li, Feng, Ziyan, Wang, Ziyao, Yue, Jirong, Qiu, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9799249/
https://www.ncbi.nlm.nih.gov/pubmed/36580560
http://dx.doi.org/10.1093/ageing/afac298
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author Tang, Xinyi
Huang, Songya
Huang, Li
Feng, Ziyan
Wang, Ziyao
Yue, Jirong
Qiu, Li
author_facet Tang, Xinyi
Huang, Songya
Huang, Li
Feng, Ziyan
Wang, Ziyao
Yue, Jirong
Qiu, Li
author_sort Tang, Xinyi
collection PubMed
description BACKGROUND: Quantitative assessment of muscle mass is a critical step in sarcopenia disease management. Expanding upon the use of ultrasound in foetal growth assessment, we established and validated an ultrasound-derived muscle assessment system for older adults at a risk of sarcopenia. METHODS: A total of 669 older adults were recruited in three cohorts in this cross-sectional study. In cohort 1(n = 103), the most valuable sites for skeletal muscle mass index (SMI) estimation were located among 11 ultrasound scanning sites. An ultrasound-derived SMI estimating algorithm based on muscle thickness (MT) was obtained in the modelling group composed of cohorts 1 and 2 (n = 309). The reliability of the muscle mass estimation equation and the validity of the obtained cut-off values were verified in cohort 3 (n = 257), which was selected as the verification group. RESULTS: In the modelling group, the cut-off values of ultrasound-derived e-SMI for low SMI were 7.13 kg/m(2) for men and 5.81 kg/m(2) for women. In the verification group, the intraclass correlation between e-SMI and SMI was 0.885. The sensitivity of the e-SMI in detecting low SMI was 93.6% for men and 89.7% for women, and the negative predictive value was 94.9% for men and 94.7% for women. Combined with the handgrip strength and gait speed, the e-SMI had an overall diagnostic sensitivity of 92.7% and a specificity of 91.0% for sarcopenia. CONCLUSION: The ultrasound-derived muscle assessment system can be a promising muscle mass estimation tool and a potential disease classification tool.
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spelling pubmed-97992492023-01-03 Ultrasound-derived muscle assessment system for older adults: a promising muscle mass estimation tool Tang, Xinyi Huang, Songya Huang, Li Feng, Ziyan Wang, Ziyao Yue, Jirong Qiu, Li Age Ageing Research Paper BACKGROUND: Quantitative assessment of muscle mass is a critical step in sarcopenia disease management. Expanding upon the use of ultrasound in foetal growth assessment, we established and validated an ultrasound-derived muscle assessment system for older adults at a risk of sarcopenia. METHODS: A total of 669 older adults were recruited in three cohorts in this cross-sectional study. In cohort 1(n = 103), the most valuable sites for skeletal muscle mass index (SMI) estimation were located among 11 ultrasound scanning sites. An ultrasound-derived SMI estimating algorithm based on muscle thickness (MT) was obtained in the modelling group composed of cohorts 1 and 2 (n = 309). The reliability of the muscle mass estimation equation and the validity of the obtained cut-off values were verified in cohort 3 (n = 257), which was selected as the verification group. RESULTS: In the modelling group, the cut-off values of ultrasound-derived e-SMI for low SMI were 7.13 kg/m(2) for men and 5.81 kg/m(2) for women. In the verification group, the intraclass correlation between e-SMI and SMI was 0.885. The sensitivity of the e-SMI in detecting low SMI was 93.6% for men and 89.7% for women, and the negative predictive value was 94.9% for men and 94.7% for women. Combined with the handgrip strength and gait speed, the e-SMI had an overall diagnostic sensitivity of 92.7% and a specificity of 91.0% for sarcopenia. CONCLUSION: The ultrasound-derived muscle assessment system can be a promising muscle mass estimation tool and a potential disease classification tool. Oxford University Press 2022-12-29 /pmc/articles/PMC9799249/ /pubmed/36580560 http://dx.doi.org/10.1093/ageing/afac298 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Research Paper
Tang, Xinyi
Huang, Songya
Huang, Li
Feng, Ziyan
Wang, Ziyao
Yue, Jirong
Qiu, Li
Ultrasound-derived muscle assessment system for older adults: a promising muscle mass estimation tool
title Ultrasound-derived muscle assessment system for older adults: a promising muscle mass estimation tool
title_full Ultrasound-derived muscle assessment system for older adults: a promising muscle mass estimation tool
title_fullStr Ultrasound-derived muscle assessment system for older adults: a promising muscle mass estimation tool
title_full_unstemmed Ultrasound-derived muscle assessment system for older adults: a promising muscle mass estimation tool
title_short Ultrasound-derived muscle assessment system for older adults: a promising muscle mass estimation tool
title_sort ultrasound-derived muscle assessment system for older adults: a promising muscle mass estimation tool
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9799249/
https://www.ncbi.nlm.nih.gov/pubmed/36580560
http://dx.doi.org/10.1093/ageing/afac298
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