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      Mean Expected Error in Prediction of Total Body Water: A True Accuracy Comparison between Bioimpedance Spectroscopy and Single Frequency Regression Equations

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          For several decades electrical bioimpedance (EBI) has been used to assess body fluid distribution and body composition. Despite the development of several different approaches for assessing total body water (TBW), it remains uncertain whether bioimpedance spectroscopic (BIS) approaches are more accurate than single frequency regression equations. The main objective of this study was to answer this question by calculating the expected accuracy of a single measurement for different EBI methods. The results of this study showed that all methods produced similarly high correlation and concordance coefficients, indicating good accuracy as a method. Even the limits of agreement produced from the Bland-Altman analysis indicated that the performance of single frequency, Sun's prediction equations, at population level was close to the performance of both BIS methods; however, when comparing the Mean Absolute Percentage Error value between the single frequency prediction equations and the BIS methods, a significant difference was obtained, indicating slightly better accuracy for the BIS methods. Despite the higher accuracy of BIS methods over 50 kHz prediction equations at both population and individual level, the magnitude of the improvement was small. Such slight improvement in accuracy of BIS methods is suggested insufficient to warrant their clinical use where the most accurate predictions of TBW are required, for example, when assessing over-fluidic status on dialysis. To reach expected errors below 4-5%, novel and individualized approaches must be developed to improve the accuracy of bioimpedance-based methods for the advent of innovative personalized health monitoring applications.

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          Most cited references 35

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          A concordance correlation coefficient to evaluate reproducibility.

           Aigu L. Lin (1989)
          A new reproducibility index is developed and studied. This index is the correlation between the two readings that fall on the 45 degree line through the origin. It is simple to use and possesses desirable properties. The statistical properties of this estimate can be satisfactorily evaluated using an inverse hyperbolic tangent transformation. A Monte Carlo experiment with 5,000 runs was performed to confirm the estimate's validity. An application using actual data is given.
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            Error measures for generalizing about forecasting methods: Empirical comparisons

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              Predicting body cell mass with bioimpedance by using theoretical methods: a technological review.

              The body cell mass (BCM), defined as intracellular water (ICW), was estimated in 73 healthy men and women by total body potassium (TBK) and by bioimpedance spectroscopy (BIS). In 14 other subjects, extracellular water (ECW) and total body water (TBW) were measured by bromide dilution and deuterium oxide dilution, respectively. For all subjects, impedance spectral data were fit to the Cole model, and ECW and ICW volumes were predicted by using model electrical resistance terms RE and Rt in an equation derived from Hanai mixture theory, respectively. The BIS ECW prediction bromide dilution was r = 0.91, standard error of the estimate (SEE) 0.90 liter. The BIS TBW prediction of deuterium space was r = 0.95, SEE 1.33 liters. The BIS ICW prediction of the dilution-determined ICW was r = 0.87, SEE 1.69 liters. The BIS ICW prediction of the TBK-determined ICW for the 73 subjects was r = 0.85, SEE = 2.22 liters. These results add further support to the validity of the Hanai theory, the equation used, and the conclusion that ECW and ICW volume can be predicted by an approach based solely on fundamental principles.

                Author and article information

                Biomed Res Int
                Biomed Res Int
                BioMed Research International
                Hindawi Publishing Corporation
                2 June 2015
                : 2015
                1Faculty of Care Science, Work Life and Social Welfare, University of Borås, 501 90 Borås, Sweden
                2School of Technology and Health, Royal Institute of Technology, 141 52 Huddinge, Sweden
                3Department of Oncology, Karolinska University Hospital, 171 76 Stockholm, Sweden
                4Department of Clinical Science, Intervention and Technology, Karolinska Institute, Hälsovägen 7, 141 57 Stockholm, Sweden
                5Department of Clinical Nutrition, The Sahlgrenska Academy, The University of Gothenburg, Sahlgrenska University Hospital, 405 30 Göteborg, Sweden
                6School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, AU 7072, Australia
                Author notes
                *Fernando Seoane: fsm@ 123456kth.se

                Academic Editor: Germán Vicente-Rodriguez

                Copyright © 2015 Fernando Seoane et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Research Article


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