Rationale: Sarcopenia is a major problem and is common in community-dwelling elderly. In daily practice, there is need for low cost and easily assessable measurement tools to assess depletion of skeletal muscle (SM) mass, for example as one of the indicators of sarcopenia. Bio-electrical impedance analysis (BIA) is often used to estimate body composition, whereas ultrasound measurement is an upcoming and promising tool, as it is quick, easy to use and inexpensive in comparison with other tools that assess SM mass. Ultrasound could assess site-specific loss of SM mass and determine myoesteatosis. Therefore, in this pilot study we aimed to assess agreement between muscle thickness of rectus femoris (RF) by ultrasound and SM mass by BIA in an older population. Methods: Twenty-six older adults (mean± standard deviation (SD) age 64 ±5.0 y, 62% women) from the Hanze Health and Ageing Study were included. SM mass by BIA was estimated using the Janssen equation. Muscle thickness of RF was assessed by analyzing ultrasound images from the right leg. Two non-parametric tests were used for analysis. Correlation between ultrasound and BIA was assessed with Spearman Rho. Agreement was determined with Kendall’s coefficient of concordance (Kendall’s W). In both tests a score ≥ 0.7 was considered a strong correlation.Results: Mean (±SD) RF thickness was 18.9 (±3.8) mm. Median SM mass (Interquartile range) was 23.5 (20.8-34.7) kg. Correlation between RF thickness and SM mass was moderately positive (Spearman r=0.611; P = 0.001), whereas Kendall’s W showed a strong agreement (W= 0.835; P=0.002).Conclusion: Ultrasound measurement of RF showed an acceptable agreement with skeletal muscle mass assessed by BIA in our sample of older adults. Therefore, ultrasound could be a promising portable tool to estimate muscle size.
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The world population is ageing rapidly. As society ages, the incidence of physical limitations is dramatically increasing, which reduces the quality of life and increases healthcare expenditures. In western society, ~30% of the population over 55 years is confronted with moderate or severe physical limitations. These physical limitations increase the risk of falls, institutionalization, co-morbidity, and premature death. An important cause of physical limitations is the age-related loss of skeletal muscle mass, also referred to as sarcopenia. Emerging evidence, however, clearly shows that the decline in skeletal muscle mass is not the sole contributor to the decline in physical performance. For instance, the loss of muscle strength is also a strong contributor to reduced physical performance in the elderly. In addition, there is ample data to suggest that motor coordination, excitation-contraction coupling, skeletal integrity, and other factors related to the nervous, muscular, and skeletal systems are critically important for physical performance in the elderly. To better understand the loss of skeletal muscle performance with ageing, we aim to provide a broad overview on the underlying mechanisms associated with elderly skeletal muscle performance. We start with a system level discussion and continue with a discussion on the influence of lifestyle, biological, and psychosocial factors on elderly skeletal muscle performance. Developing a broad understanding of the many factors affecting elderly skeletal muscle performance has major implications for scientists, clinicians, and health professionals who are developing therapeutic interventions aiming to enhance muscle function and/or prevent mobility and physical limitations and, as such, support healthy ageing.
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Background & aims: Low muscle mass and -quality on ICU admission, as assessed by muscle area and -density on CT-scanning at lumbar level 3 (L3), are associated with increased mortality. However, CT-scan analysis is not feasible for standard care. Bioelectrical impedance analysis (BIA) assesses body composition by incorporating the raw measurements resistance, reactance, and phase angle in equations. Our purpose was to compare BIA- and CT-derived muscle mass, to determine whether BIA identified the patients with low skeletal muscle area on CT-scan, and to determine the relation between raw BIA and raw CT measurements. Methods: This prospective observational study included adult intensive care patients with an abdominal CT-scan. CT-scans were analysed at L3 level for skeletal muscle area (cm2) and skeletal muscle density (Hounsfield Units). Muscle area was converted to muscle mass (kg) using the Shen equation (MMCT). BIA was performed within 72 h of the CT-scan. BIA-derived muscle mass was calculated by three equations: Talluri (MMTalluri), Janssen (MMJanssen), and Kyle (MMKyle). To compare BIA- and CT-derived muscle mass correlations, bias, and limits of agreement were calculated. To test whether BIA identifies low skeletal muscle area on CT-scan, ROC-curves were constructed. Furthermore, raw BIA and CT measurements, were correlated and raw CT-measurements were compared between groups with normal and low phase angle. Results: 110 patients were included. Mean age 59 ± 17 years, mean APACHE II score 17 (11–25); 68% male. MMTalluri and MMJanssen were significantly higher (36.0 ± 9.9 kg and 31.5 ± 7.8 kg, respectively) and MMKyle significantly lower (25.2 ± 5.6 kg) than MMCT (29.2 ± 6.7 kg). For all BIA-derived muscle mass equations, a proportional bias was apparent with increasing disagreement at higher muscle mass. MMTalluri correlated strongest with CT-derived muscle mass (r = 0.834, p < 0.001) and had good discriminative capacity to identify patients with low skeletal muscle area on CT-scan (AUC: 0.919 for males; 0.912 for females). Of the raw measurements, phase angle and skeletal muscle density correlated best (r = 0.701, p < 0.001). CT-derived skeletal muscle area and -density were significantly lower in patients with low compared to normal phase angle. Conclusions: Although correlated, absolute values of BIA- and CT-derived muscle mass disagree, especially in the high muscle mass range. However, BIA and CT identified the same critically ill population with low skeletal muscle area on CT-scan. Furthermore, low phase angle corresponded to low skeletal muscle area and -density. Trial registration: ClinicalTrials.gov (NCT02555670).
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