Nilanjana Tewari1, Sherif Awad2, Ian A Macdonald3, Dileep N Lobo4. 1. Gastrointestinal Surgery, Nottingham Digestive Diseases Centre, National Institute for Health Research (NIHR) Nottingham Biomedical Research Centre, Nottingham University Hospitals and University of Nottingham, Queen's Medical Centre, Nottingham, United Kingdom. 2. The East-Midlands Bariatric & Metabolic Institute, Royal Derby Hospital, Derby Hospitals NHS Foundation Trust, Derby, United Kingdom. 3. Metabolic Physiology Group, School of Life Sciences, University of Nottingham, Nottingham, United Kingdom. 4. Gastrointestinal Surgery, Nottingham Digestive Diseases Centre, National Institute for Health Research (NIHR) Nottingham Biomedical Research Centre, Nottingham University Hospitals and University of Nottingham, Queen's Medical Centre, Nottingham, United Kingdom. Electronic address: Dileep.Lobo@nottingham.ac.uk.
Abstract
OBJECTIVE: The aim of this study was to compare the accuracy of measurements of body composition made using dual x-ray absorptiometry (DXA), analysis of computed tomography (CT) scans at the L3 vertebral level, and bioelectrical impedance analysis (BIA). METHODS: DXA, CT, and BIA were performed in 47 patients recruited from two clinical trials investigating metabolic changes associated with major abdominal surgery or neoadjuvant chemotherapy for esophagogastric cancer. DXA was performed the week before surgery and before and after commencement of neoadjuvant chemotherapy. BIA was performed at the same time points and used with standard equations to calculate fat-free mass (FFM). Analysis of CT scans performed within 3 mo of the study was used to estimate FFM and fat mass (FM). RESULTS: There was good correlation between FM on DXA and CT (r2 = 0.6632; P < 0.0001) and FFM on DXA and CT (r2 = 0.7634; P < 0.0001), as well as FFM on DXA and BIA (r2 = 0.6275; P < 0.0001). Correlation between FFM on CT and BIA also was significant (r2 = 0.2742; P < 0.0001). On Bland-Altman analysis, average bias for FM on DXA and CT was 0.2564 with 95% limits of agreement (LOA) of -9.451 to 9.964. For FFM on DXA and CT, average bias was -0.1477, with LOA of -8.621 to 8.325. For FFM on DXA and BIA, average bias was -3.792, with LOA of -15.52 to 7.936. For FFM on CT and BIA, average bias was -2.661, with LOA of -22.71 to 17.39. CONCLUSION: Although a systematic error underestimating FFM was demonstrated with BIA, it may be a useful modality to quantify body composition in the clinical situation.
OBJECTIVE: The aim of this study was to compare the accuracy of measurements of body composition made using dual x-ray absorptiometry (DXA), analysis of computed tomography (CT) scans at the L3 vertebral level, and bioelectrical impedance analysis (BIA). METHODS: DXA, CT, and BIA were performed in 47 patients recruited from two clinical trials investigating metabolic changes associated with major abdominal surgery or neoadjuvant chemotherapy for esophagogastric cancer. DXA was performed the week before surgery and before and after commencement of neoadjuvant chemotherapy. BIA was performed at the same time points and used with standard equations to calculate fat-free mass (FFM). Analysis of CT scans performed within 3 mo of the study was used to estimate FFM and fat mass (FM). RESULTS: There was good correlation between FM on DXA and CT (r2 = 0.6632; P < 0.0001) and FFM on DXA and CT (r2 = 0.7634; P < 0.0001), as well as FFM on DXA and BIA (r2 = 0.6275; P < 0.0001). Correlation between FFM on CT and BIA also was significant (r2 = 0.2742; P < 0.0001). On Bland-Altman analysis, average bias for FM on DXA and CT was 0.2564 with 95% limits of agreement (LOA) of -9.451 to 9.964. For FFM on DXA and CT, average bias was -0.1477, with LOA of -8.621 to 8.325. For FFM on DXA and BIA, average bias was -3.792, with LOA of -15.52 to 7.936. For FFM on CT and BIA, average bias was -2.661, with LOA of -22.71 to 17.39. CONCLUSION: Although a systematic error underestimating FFM was demonstrated with BIA, it may be a useful modality to quantify body composition in the clinical situation.
Authors: Kiley B Vander Wyst; Micah L Olson; Colleen S Keller; Erica G Soltero; Allison N Williams; Armando Peña; Stephanie L Ayers; Justin Jager; Gabriel Q Shaibi Journal: Pediatr Obes Date: 2020-02-18 Impact factor: 3.910
Authors: Rafaela C E Santo; Kevin Z Fernandes; Priscila S Lora; Lidiane I Filippin; Ricardo M Xavier Journal: J Cachexia Sarcopenia Muscle Date: 2018-08-21 Impact factor: 12.910
Authors: Carlos Magno Sousa; Ewaldo Santana; Marcus Vinicius Lopes; Guilherme Lima; Luana Azoubel; Érika Carneiro; Allan Kardec Barros; Nilviane Pires Journal: Int J Environ Res Public Health Date: 2019-08-17 Impact factor: 3.390
Authors: Patrick Naumann; Jonathan Eberlein; Benjamin Farnia; Jakob Liermann; Thilo Hackert; Jürgen Debus; Stephanie E Combs Journal: Cancers (Basel) Date: 2019-10-26 Impact factor: 6.639