Charlotte Beaudart1, Olivier Bruyère2, Anton Geerinck2, Manon Hajaoui2, Aldo Scafoglieri3, Stany Perkisas4, Ivan Bautmans5, Evelien Gielen6, Jean-Yves Reginster2, Fanny Buckinx2. 1. Division of Public Health, Epidemiology and Health Economics & WHO Collaborating Centre for Public Health Aspects of Musculo-Skeletal Health and Ageing, University of Liège, Belgium. Electronic address: c.beaudart@uliege.be. 2. Division of Public Health, Epidemiology and Health Economics & WHO Collaborating Centre for Public Health Aspects of Musculo-Skeletal Health and Ageing, University of Liège, Belgium. 3. Department of Experimental Anatomy, VUB, Brussels, Belgium. 4. Department of Geriatric Medicine, University of Antwerp, Antwerp, Belgium. 5. Gerontology Department, Vrije Universiteit Brussel (VUB), Brussels, Belgium; Frailty in Ageing Research Department, Vrije Universiteit Brussel (VUB), Brussels, Belgium. 6. Gerontology and Geriatrics Unit, Department of Chronic Diseases, Metabolism and Ageing (CHROMETA), University of Leuven, Belgium.
Abstract
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.
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.
Authors: Luís B Sardinha; Gil B Rosa; Megan Hetherington-Rauth; Inês R Correia; João P Magalhães; Analiza M Silva; Henry Lukaski Journal: Eur J Clin Nutr Date: 2022-10-17 Impact factor: 4.884
Authors: Roberto Fernandes da Costa; Analiza M Silva; Kalina Veruska da Silva Bezerra Masset; Tatianny de Macêdo Cesário; Breno Guilherme de Araújo Tinoco Cabral; Gerson Ferrari; Paulo Moreira Silva Dantas Journal: Front Nutr Date: 2022-03-17