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Brain CT can predict low lean mass in the elderly with cognitive impairment: a community-dwelling study
BACKGROUND: The coexistence of sarcopenia and dementia in aging populations is not uncommon, and they may share common risk factors and pathophysiological pathways. This study aimed to evaluate the relationship between brain atrophy and low lean mass in the elderly with impaired cognitive function....
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8722183/ https://www.ncbi.nlm.nih.gov/pubmed/34979925 http://dx.doi.org/10.1186/s12877-021-02626-8 |
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author | Chen, Yun-Ting Yu, Chiun-Chieh Lin, Yu-Ching Chan, Shan-Ho Lin, Yi-Yun Chen, Nai-Ching Lin, Wei-Che |
author_facet | Chen, Yun-Ting Yu, Chiun-Chieh Lin, Yu-Ching Chan, Shan-Ho Lin, Yi-Yun Chen, Nai-Ching Lin, Wei-Che |
author_sort | Chen, Yun-Ting |
collection | PubMed |
description | BACKGROUND: The coexistence of sarcopenia and dementia in aging populations is not uncommon, and they may share common risk factors and pathophysiological pathways. This study aimed to evaluate the relationship between brain atrophy and low lean mass in the elderly with impaired cognitive function. METHODS: This cross-sectional study included 168 elderly patients who visited the multi-disciplinary dementia outpatient clinic at Kaohsiung Chang Gung Memorial Hospital for memory issues, between 2017 and 2019. The body composition was assessed by dual energy X-ray absorptiometry (DEXA) and CT based skeletal muscle index including L3 skeletal muscle index (L3SMI) and masseter muscle mass index (MSMI). The brain atrophy assessment was measured by CT based visual rating scale. Possible predictors of low lean mass in the elderly with cognitive impairement were identified by binary logistic regression. ROC curves were generated from binary logistic regression. RESULTS: Among the 81 participants, 43 (53%) remained at a normal appendicular skeletal muscle index (ASMI), whereas 38 (47%) showed low ASMI. Compared with the normal ASMI group, subjects with low ASMI exhibited significantly lower BMI, L3SMI, and MSMI (all p < 0.05), and showed significant brain atrophy as assessed by visual rating scale (p < 0.001). The accuracy of predictive models for low ASMI in the elderly with cognitive impairment were 0.875, (Area under curve (AUC) = 0.926, 95% confidence interval [CI] 0.844–0.972) in model 1 (combination of BMI, GCA and L3SMI) and 0.885, (Area under curve (AUC) = 0.931, [CI] 0.857–0.979) in model 2 (combination of BMI, GCA and MSMI). CONCLUSIONS: Global cortical atrophy and body mass index combined with either L3 skeletal muscle index or masseter skeletal muscle index can predict low lean mass in the elderly with cognitive impairment. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-021-02626-8. |
format | Online Article Text |
id | pubmed-8722183 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-87221832022-01-06 Brain CT can predict low lean mass in the elderly with cognitive impairment: a community-dwelling study Chen, Yun-Ting Yu, Chiun-Chieh Lin, Yu-Ching Chan, Shan-Ho Lin, Yi-Yun Chen, Nai-Ching Lin, Wei-Che BMC Geriatr Research BACKGROUND: The coexistence of sarcopenia and dementia in aging populations is not uncommon, and they may share common risk factors and pathophysiological pathways. This study aimed to evaluate the relationship between brain atrophy and low lean mass in the elderly with impaired cognitive function. METHODS: This cross-sectional study included 168 elderly patients who visited the multi-disciplinary dementia outpatient clinic at Kaohsiung Chang Gung Memorial Hospital for memory issues, between 2017 and 2019. The body composition was assessed by dual energy X-ray absorptiometry (DEXA) and CT based skeletal muscle index including L3 skeletal muscle index (L3SMI) and masseter muscle mass index (MSMI). The brain atrophy assessment was measured by CT based visual rating scale. Possible predictors of low lean mass in the elderly with cognitive impairement were identified by binary logistic regression. ROC curves were generated from binary logistic regression. RESULTS: Among the 81 participants, 43 (53%) remained at a normal appendicular skeletal muscle index (ASMI), whereas 38 (47%) showed low ASMI. Compared with the normal ASMI group, subjects with low ASMI exhibited significantly lower BMI, L3SMI, and MSMI (all p < 0.05), and showed significant brain atrophy as assessed by visual rating scale (p < 0.001). The accuracy of predictive models for low ASMI in the elderly with cognitive impairment were 0.875, (Area under curve (AUC) = 0.926, 95% confidence interval [CI] 0.844–0.972) in model 1 (combination of BMI, GCA and L3SMI) and 0.885, (Area under curve (AUC) = 0.931, [CI] 0.857–0.979) in model 2 (combination of BMI, GCA and MSMI). CONCLUSIONS: Global cortical atrophy and body mass index combined with either L3 skeletal muscle index or masseter skeletal muscle index can predict low lean mass in the elderly with cognitive impairment. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-021-02626-8. BioMed Central 2022-01-03 /pmc/articles/PMC8722183/ /pubmed/34979925 http://dx.doi.org/10.1186/s12877-021-02626-8 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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 | Research Chen, Yun-Ting Yu, Chiun-Chieh Lin, Yu-Ching Chan, Shan-Ho Lin, Yi-Yun Chen, Nai-Ching Lin, Wei-Che Brain CT can predict low lean mass in the elderly with cognitive impairment: a community-dwelling study |
title | Brain CT can predict low lean mass in the elderly with cognitive impairment: a community-dwelling study |
title_full | Brain CT can predict low lean mass in the elderly with cognitive impairment: a community-dwelling study |
title_fullStr | Brain CT can predict low lean mass in the elderly with cognitive impairment: a community-dwelling study |
title_full_unstemmed | Brain CT can predict low lean mass in the elderly with cognitive impairment: a community-dwelling study |
title_short | Brain CT can predict low lean mass in the elderly with cognitive impairment: a community-dwelling study |
title_sort | brain ct can predict low lean mass in the elderly with cognitive impairment: a community-dwelling study |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8722183/ https://www.ncbi.nlm.nih.gov/pubmed/34979925 http://dx.doi.org/10.1186/s12877-021-02626-8 |
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