Predictors of discordance in the assessment of skeletal muscle mass between computed tomography and bioimpedance analysis

Min Ho Jo, Tae Seop Lim, Mi Young Jeon, Hye Won Lee, Beom Kyung Kim, Jun Yong Park, Do Young Kim, Sang Hoon Ahn, Kwang Hyub Han, Seung Up Kim

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9 Citations (Scopus)

Abstract

Computed tomography (CT) and bioimpedance analysis (BIA) can assess skeletal muscle mass (SMM). Our objective was to identify the predictors of discordance between CT and BIA in assessing SMM. Participants who received a comprehensive medical health check-up between 2010 and 2018 were recruited. The CT and BIA-based diagnostic criteria for low SMM are as follows: Defined CT cutoff values (lumbar skeletal muscle index (LSMI) <1 standard deviation (SD) and means of 46.12 cm2/m2 for men and 34.18 cm2/m2 for women) and defined BIA cutoff values (appendicular skeletal muscle/height2 <7.0 kg/m2 for men and <5.7 kg/m2 for women). A total of 1163 subjects were selected. The crude and body mass index (BMI)-adjusted SMM assessed by CT were significantly associated with those assessed by BIA (correlation coefficient = 0.78 and 0.68, respectively; p < 0.001). The prevalence of low SMM was 15.1% by CT and 16.4% by BIA. Low SMM diagnosed by CT was significantly associated with advanced age, female gender, and lower serum albumin level, whereas low SMM diagnosed by BIA was significantly associated with advanced age, female gender, and lower BMI (all p < 0.05). Upon multivariate analysis, age >65 years, female and BMI <25 kg/m2 had significantly higher risks of discordance than their counterparts (all p < 0.05). We found a significant association between SMM assessed by CT and BIA. SMM assessment using CT and BIA should be interpreted cautiously in older adults (>65 years of age), female and BMI <25 kg/m2. View Full-Text.

Original languageEnglish
Article number322
JournalJournal of Clinical Medicine
Volume8
Issue number3
DOIs
Publication statusPublished - 2019 Mar

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© 2019 by the authors.

All Science Journal Classification (ASJC) codes

  • General Medicine

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