Abstract

Sarcopenia is becoming prevalent in an increasing number of older adults undergoing total knee replacement (TKR) surgery. Metal implants may overestimate lean mass (LM) measured using dual-energy X-ray absorptiometry (DXA). This study aimed to examine the effects of TKR on LM measurements according to automatic metal detection (AMD) processing. The participants from Korean Frailty and Aging Cohort Study, who had underwent TKR were enrolled. A total of 24 older adults (mean age 76.4 ± 4.0 years, 92% female) were included in the analysis. The SMI with AMD processing was 6.1 ± 0.6 kg/m2, which was lower than that without AMD processing of 6.5 ± 0.6 kg/m2 (p < 0.001). The LM of the right leg with AMD processing was lower than that without AMD in 20 participants who had underwent TKR surgery on the right (5.5 ± 0.2 kg vs. 6.0 ± 0.2 kg, p < 0.001), and that of the left leg was also lower in with AMD processing than in without AMD processing in 18 participants who had underwent TKR surgery on the left (5.7 ± 0.2 kg vs. 5.2 ± 0.2 kg, p < 0.001). Only one participant was classified as having low muscle mass without AMD processing, but this came to four after AMD processing. LM assessment in individuals who had TKR could be significantly different according to the use of AMD.

Details

Title
Effect of total knee replacement on skeletal muscle mass measurements using dual energy X-ray absorptiometry
Author
Jang, Jae Young 1 ; Kim, Miji 2 ; Lee, Daehyun 1 ; Won, Chang Won 3 

 Kyung Hee University, Department of Biomedical Science and Technology, Graduate School, Seoul, South Korea (GRID:grid.289247.2) (ISNI:0000 0001 2171 7818) 
 Kyung Hee University, Department of Biomedical Science and Technology, College of Medicine, East-West Medical Research Institute, Seoul, South Korea (GRID:grid.289247.2) (ISNI:0000 0001 2171 7818) 
 Kyung Hee University, Department of Family Medicine, Elderly Frailty Research Center, College of Medicine, Seoul, South Korea (GRID:grid.289247.2) (ISNI:0000 0001 2171 7818) 
Pages
2908
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2777940759
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.