Reference values for low muscle mass and myosteatosis using tomographic muscle measurements in living kidney donors

Low muscle mass and myosteatosis are associated with poor clinical outcomes. Computed tomography (CT) imaging is an objective method for muscle mass and quality assessment; however consensus on cut-off values is lacking. This study assessed age-, sex-, and body mass index (BMI)-specific reference va...

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Published inScientific reports Vol. 13; no. 1; pp. 5835 - 8
Main Authors Westenberg, Lisa B., Zorgdrager, Marcel, Swaab, Tim D. A., van Londen, Marco, Bakker, Stephan J. L., Leuvenink, Henri G. D., Viddeleer, Alain R., Pol, Robert A.
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 10.04.2023
Nature Publishing Group
Nature Portfolio
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Summary:Low muscle mass and myosteatosis are associated with poor clinical outcomes. Computed tomography (CT) imaging is an objective method for muscle mass and quality assessment; however consensus on cut-off values is lacking. This study assessed age-, sex-, and body mass index (BMI)-specific reference values of skeletal muscle parameters and correlated muscle mass with 24-h urinary creatinine excretion (24-h UCE). In total, 960 healthy subjects were included in this study. Muscle mass and quality were determined using axial CT slices at the vertebral level L3. The muscle area was indexed for height (skeletal muscle index [SMI]). The mean age was 53 ± 11 years, and 50% were male. The SMI reference values for low muscle mass in males were 38.8 cm 2 /m 2 (20–29 years), 39.2 (30–39 years), 39.9 (40–49 years), 39.0 (50–59 years), 37.0 (60–69 years), and 36.8 (70–79 years). For females, these reference values were 37.5 cm 2 /m 2 (20–29 years), 35.5 (30–39 years), 32.8 (40–49 years), 33.2 (50–59 years), 31.2 (60–69 years), and 31.5 (70–79 years). 24-h UCE and SMI were significantly correlated ( r  = 0.54, p  < 0.001) without bias between the two methods of assessing muscle mass. This study provides age-, sex-, and BMI-specific reference values for skeletal muscle parameters that will support clinical decision making.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-023-33041-1