Bioelectrical impedance analysis (BIA) may be used to assess fat free mass (FFM) with reasonable validity based on mean-level comparisons, but differences between BIA and DXA may vary by about 4 kg in an individual patient. These results require confirmation in a larger sample of HNC (Head and neck cancer) patients.
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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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Background: Body composition measurements provide importanti nformation about physical fitness and nutritional status. People with severe intellectual and visual disabilities (SIVD) have an increased risk for altered body composition. Bioelectrical impedance analysis (BIA) has been evidenced as a reliable and non-invasive method to assess body composition in healthy persons and various patient populations; however, currently, there is no feasible method available to determine body composition in people with SIVD.In this study, therefore, we aimed to assess the feasibility of BIA measurements in persons with SIVD. Methods: In 33 participants with SIVD and Gross Motor Functioning Classification System (GMFCS) Scale I, II, III, or IV, two BIA measurements were sequentially performed employing Resistance and Reactance in Ohm and fat-free mass (FFM) in kg as outcome variables, utilizing the Bodystat QuadScan 4000. Feasibility was considered sufficient if >=80% of the first measurement was performed successfully. Agreement between two repeated measurements was determined by using the paired t-test and Intraclass Correlation Coefficient (ICC; two way random, absolute agreement). Bland–Altman analyses were utilized to determine limits of agreement (LOAs) and systematic error. Agreement was considered acceptable if LOAs were <10% of the mean of the first measurement.
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BACKGROUND: In critically ill patients, muscle loss is associated with adverse outcomes. Raw bioelectrical impedance analysis (BIA) parameters (eg, phase angle [PA] and impedance ratio [IR]) have received attention as potential markers of muscularity, nutrition status, and clinical outcomes. Our objective was to test whether PA and IR could be used to assess low muscularity and predict clinical outcomes.METHODS: Patients (≥18 years) having an abdominal computed tomography (CT) scan and admitted to intensive care underwent multifrequency BIA within 72 hours of scan. CT scans were landmarked at the third lumbar vertebra and analyzed for skeletal muscle cross-sectional area (CSA). CSA ≤170 cm(2) for males and ≤110 cm(2) for females defined low muscularity. The relationship between PA (and IR) and CT muscle CSA was evaluated using multivariate regression and included adjustments for age, sex, body mass index, Charlson Comorbidity Index, and admission type. PA and IR were also evaluated for predicting discharge status using dual-energy X-ray absorptiometry-derived cut-points for low fat-free mass index.RESULTS: Of 171 potentially eligible patients, 71 had BIA and CT scans within 72 hours. Area under the receiver operating characteristic (c-index) curve to predict CT-defined low muscularity was 0.67 (P ≤ .05) for both PA and IR. With covariates added to logistic regression models, PA and IR c-indexes were 0.78 and 0.76 (P < .05), respectively. Low PA and high IR predicted time to live ICU discharge.CONCLUSION: Our study highlights the potential utility of PA and IR as markers to identify patients with low muscularity who may benefit from early and rigorous intervention.
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Assessment and monitoring of fat-free mass (FFM) is of clinical importance, because FFM is reflective of body cell mass, the total mass of protein-rich, metabolically active cells which is affected during malnutrition and therefore related to clinical outcome.Bioelectrical impedance analysis (BIA) is a non-invasive, portable and inexpensive method to assess body composition. Currently validity of BIA in head and neck cancer patients is unknown. Therefore, we tested our hypothesis that BIA, using the Geneva equation, is a valid method to assess FFM in head and neck cancer patients.
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STUDY DESIGN: Cross-sectional study.OBJECTIVES: This study: (1) investigated the accuracy of bioelectrical impedance analysis (BIA) and skinfold thickness relative to dual-energy X-ray absorptiometry (DXA) in the assessment of body composition in people with spinal cord injury (SCI), and whether sex and lesion characteristics affect the accuracy, (2) developed new prediction equations to estimate fat free mass (FFM) and percentage fat mass (FM%) in a general SCI population using BIA and skinfolds outcomes.SETTING: University, the Netherlands.METHODS: Fifty participants with SCI (19 females; median time since injury: 15 years) were tested by DXA, single-frequency BIA (SF-BIA), segmental multi-frequency BIA (segmental MF-BIA), and anthropometry (height, body mass, calf circumference, and skinfold thickness) during a visit. Personal and lesion characteristics were registered.RESULTS: Compared to DXA, SF-BIA showed the smallest mean difference in estimating FM%, but with large limits of agreement (mean difference = -2.2%; limits of agreement: -12.8 to 8.3%). BIA and skinfold thickness tended to show a better estimation of FM% in females, participants with tetraplegia, or with motor incomplete injury. New equations for predicting FFM and FM% were developed with good explained variances (FFM: R2 = 0.94; FM%: R2 = 0.66).CONCLUSIONS: None of the measurement techniques accurately estimated FM% because of the wide individual variation and, therefore, should be used with caution. The accuracy of the techniques differed in different subgroups. The newly developed equations for predicting FFM and FM% should be cross-validated in future studies.
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Purpose of reviewTo help guide metabolic support in critical care, an understanding of patients’ nutritional status and risk is important. Several methods to monitor lean body mass are increasingly used in the ICU and knowledge about their advantages and limitations is essential.Recent findingsComputed tomography scan analysis, musculoskeletal ultrasound, and bioelectrical impedance analysis are emerging as powerful clinical tools to monitor lean body mass during ICU stay. Accuracy, expertise, ease of use at the bedside, and costs are important factors, which play a role in determining, which method is most suitable. Exciting new research provides an insight into not only quantitative measurements, but also qualitative measurements of lean body mass, such as infiltration of adipose tissue and intramuscular glycogen storage.SummaryMethods to monitor lean body mass in the ICU are under constant development, improving upon bedside usability and offering new modalities to measure. This provides clinicians with valuable markers with which to identify patients at high nutritional risk and to evaluate metabolic support during critical illness.
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RationaleIn bioelectrical impedance analysis (BIA) measurements, one pair of electrodes is typically placed dorsal on the right hand (position A) and one pair on the foot. In patients with fragile skin, scars or wounds, this dorsal hand placement is not always possible. This study compares agreement of BIA measurements at seven alternative placements with position A. MethodsBIA measurements were performed with the Bodystat-500 using eight combinations of hand electrodes: at the dorsal side of the hand (position A) or dorsal side hand-forearm (position B and C); at the palmar side of the hand (position D) or palmar side hand-forearm (position E and F) or mixed palmar-dorsal side of the hand (position G and H). ICCs were used to compare alle outcomes to position A. Changes in fat mass ∆FM, fat-free mass ∆FFM and appendicular skeletal muscle mass ∆ASMM were calculated using Kyle’s formula.ResultsSeventy healthy Caucasian participants were measured: median age 22 years, IQR 21-23; mean BMI 22.8 ± 2.5 kg/m². Electrode positions D,G and H showed an ICC 0.99-1.00 for ∆FM, ∆FFM and ∆ASMM with minimal changes in ∆FFM and ∆FM: 0.1–0.4 kg ± 0.3 kg and ∆ASMM: 0.0–0.2 kg ± 0.2 kg. Measurements at position B, C, E, and F showed significant and clinically relevant differences with ∆FM and ∆FFM: 3.8–4.0 kg ± 1.1 kg and ∆ASMM: 2.0–2.1 kg ± 0.6 kg, with ICCs 0.96-0.97.ConclusionAlternatively to the typical electrode placement on the dorsal side of the hand, this study demonstrates that three alternative placements results in an excellent agreement with only minimal changes in FFM, FM and ASMM. In practice, placing electrodes at more proximal positions on the forearm should be avoided. Alternatively, we recommend a mixed or palmar electrode placement on the hand.
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The aim of this study was to gain insight into the nutritional status, dietary intake and muscle health of older Dutch hip fracture patients to prevent recurrent fractures and to underpin rehabilitation programs. This cross-sectional study enrolled 40 hip fracture patients (mean ± SD age 82 ± 8.0 years) from geriatric rehabilitation wards of two nursing homes in the Netherlands. Assessments included nutritional status (Mini Nutritional Assessment), dietary intake on three non-consecutive days which were compared with Dietary Reference Intake values, and handgrip strength. Muscle mass was measured using Bioelectrical Impedance Analysis and ultrasound scans of the rectus femoris. Malnutrition or risk of malnutrition was present in 73% of participants. Mean energy, protein, fibre and polyunsaturated fat intakes were significantly below the recommendations, while saturated fat was significantly above the UL. Protein intake was
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