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Purpose Measurement of muscle mass is paramount in the screening and diagnosis of sarcopenia. Besides muscle quantity however, also quality assessment is important. Ultrasonography (US) has the advantage over dual-energy X-ray absorptiometry (DEXA) and bio-impedance analysis (BIA) to give both quantitative and qualitative information on muscle. However, before its use in clinical practice, several methodological aspects still need to be addressed. Both standardization in measurement techniques and the availability of reference values are currently lacking. This review aims to provide an evidence-based standardization of assessing appendicular muscle with the use of US. Methods A systematic review was performed for ultrasonography to assess muscle in older people. Pubmed, SCOPUS and Web of Sciences were searched. All articles regarding the use of US in assessing appendicular muscle were used. Description of US-specific parameters and localization of the measurement were retrieved. Results Through this process, five items of muscle assessment were identified in the evaluated articles: thickness, crosssectional area, echogenicity, fascicle length and pennation angle. Different techniques for measurement and location of measurement used were noted, as also the different muscles in which this was evaluated. Then, a translation for a clinical setting in a standardized way was proposed. Conclusions The results of this review provide thus an evidence base for an ultrasound protocol in the assessment of skeletal muscle. This standardization of measurements is the first step in creating conditions to further test the applicability of US for use on a large scale as a routine assessment and follow-up tool for appendicular muscle.
Diabetes is a chronic illness that has an effect on multiple organ systems. Frailty is a state of increased vulnerability to stressors and a limited capacity to maintain homeostasis. It is a multidimensional concept and a dynamic condition that can improve or worsen over time. Frailty is either physical or psychological or a combination of these two components. Sarcopenia, which is the age-related loss of skeletal muscle mass and strength, is the main attributor to the physical form of frailty. Although the pathophysiology of diabetes is commonly focused on impaired insulin secretion, overload of gluconeogenesis and insulin resistance, newer insights broaden this etiologic horizon. Immunologic factors that create a chronic state of low-grade inflammation -'inflammaging' -have an influence on both the ageing process and diabetes. Persons with diabetes mellitus already tend to have an accelerated ageing process that places them at greater risk for developing frailty at an earlier age. The development of frailty -and sarcopenia -is multifactorial and includes nutritional, physical and hormonal elements; these elements are interlinked with those of diabetes. A lower muscle mass will lead to poorer glycaemic control through lower muscle glucose uptake. This leads to higher insulin secretion and insulin resistance, which is the stepping stone for diabetes itself.
Background: Recent studies associated gait patterns with cognitive impairment stages. The current study examined the relation between dementia type and spatiotemporal gait characteristics under different walking conditions in pre and mild neurocognitive disorder stage. Methods: Community-dwelling older adults (age 50+) with memory complaints consulting a memory clinic underwent, at baseline and during follow-up (every 4 months), a standard dementia assessment and a comprehensive spatiotemporal gait analysis [walking on an electronic walkway at usual pace (UP) with and without a counting-backwards (CW) or animal-reciting dual-task (AW), at fast (FP) and at slow (SP) pace]. At baseline the participants were categorized according to the Clinical Dementia Rating (CDR) scale. At the end of the study, the dementia diagnosis was used to stratify the categories in three outcome groups: developed “No-dementia,” “AD+FTD” (grouping Alzheimer's or Fronto-temporal dementia) or “VascD+LBD” dementia (grouping Vascular dementia or Lewy body dementia). The gait characteristics were compared per category in paired groups. Sub-analyzing in the ≥70-years-old participants evaluated the age effect. Results: Five hundred and thirty-six participants, age 50-to-95-years old were followed for 31-to-41 months. In the CDR 0, no differences were seen between eventual dementia and no-dementia individuals. In the CDR 0.5, CW dual task cost (DTC) step width was larger in the imminent “AD+FTD” and AW (normalized) gait speed was slower in the future “VascD+LBD” group compared to the no-dementia participants. Slower UP (normalized) gait speed differed the future “VascD+LBD” from the “AD+FTD” individuals. In the CDR 1: Wider steps in UP, SP and CW differed the “VascD+LBD” from the “AD+FTD” group. In the ≥70-years old CDR 0 category, higher AW cycle time variability in the imminent “AD+FTD” dementia group, wider UP step width and higher AW cycle time variability in the “VascD+LBD” group differed them from the no-dementia group up to 3 years before dementia diagnosis. The distinctive gait characteristics between the no-dementia and the imminent dementia groups in CDR 0.5 and CDR 1 remained the same as in the overall group. However, no gait differences were found between “VascD+LBD” and “AD+FTD” groups in the pre-dementia stages. Conclusion: Distinctive spatiotemporal gait characteristics were associated with specific dementia types up to 3 years before diagnosis. The association is influenced by the cognitive stage and age.
Background & aims: This systematic review aims to systematically assess and summarize the equation models developed to estimate muscle mass with bioelectric impedance analysis (BIA) instruments against a reference instrument (DXA, MRI, CT-scan, Ultrasonography), in order to help researchers and clinicians choose the most adapted equation, depending on the device and the population in question. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) statement was followed. Medline (via Ovid) and Scopus were searched in January 2019 for observational (transversal, longitudinal, retrospective) studies developing an equation prediction model to validate BIA against another reference method for the assessment of muscle mass. Study selection and data extraction was performed independently by two researchers. Methodological quality of the included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Results: 25 studies matched the inclusion criteria and were included in the present systematic review. Among them, 10 studies proposed an equation for subjects aged 65 years and older, 9 for adults, 4 for infants and 2 did not report the age of the population. A large heterogeneity was observed regarding the brand and type of BIA as well as the administration protocol (mode, frequency, number of electrodes, administration position and empty bladder/stomach or not). Most of the studies used DXA as the reference instrument, except 4 that used MRI. In each of the included papers authors provided, through simple or multiple regression, a predictive equation for muscle mass. BIA resistance index, sex, weight, age, BIA reactance and height were most frequently included as predictive variables. The majority of the equations developed explained more than 80% of the variance between both instruments. Out of the 25 equations available, only 9 were also validated in another population within the same paper. Conclusion: This systematic review of the literature offers clinicians and researchers the opportunity to verify the existence of a prediction equation when using a BIA device for estimating muscle mass. This will help them to obtain a valid estimation of muscle mass in a specific population and with a specific instrument. If the equation exists and has been validated by a study free of high risk of bias, it's use is recommended because the development of a new equation in the same context seems redundant and undesirable. If a validation has not been carried out for a specific brand of BIA, reference method or population, we recommend the development and cross-validation of a new equation.
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