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Clinical nutrition

Bioelectric impedance vector analysis (BIVA) in hospitalised children; predictors and associations with clinical outcomes

Abstract

Background

Clinical use of bioelectric impedance is limited by variability in hydration. Analysis of raw bioelectric impedance vectors (BIVA), resistance (R), reactance (Xc) and phase angle (PA) may be an alternative for monitoring disease progression/treatment. Clinical experience of BIVA in children is limited. We investigated predictors of BIVA and their ability to predict clinical outcomes in children with complex diagnoses.

Methods

R, Xc and PA were measured (BODYSTAT Quadscan 4000) on admission in 108 patients (4.6–16.8 years, mean 10.0). R and Xc were indexed by height (H) and BIVA-SDS for age and sex calculated using data from healthy children. Potential predictors and clinical outcomes (greater-than-expected length-of-stay (LOS), complications) were recorded.

Results

Mean R/H-SDS was significantly higher (0.99 (SD 1.32)) and PA-SDS lower (−1.22 (1.68))) than expected, with a wide range for all parameters. In multivariate models, the Strongkids risk category predicted R/H-SDS (adjusted mean for low, medium and high risk = 0.49, 1.28, 2.17, p = 0.009) and PA-SDS (adjusted mean −0.52, −1.53, −2.36, p = 0.01). BIVA-SDS were not significantly different in patients with or without adverse outcomes.

Conclusions

These complex patients had abnormal mean BIVA-SDS suggestive of reduced hydration and poor cellular health according to conventional interpretation. R/H-SDS was higher and PA-SDS lower in those classified as higher malnutrition risk by the StrongKids tool. Further investigation in specific patient groups, including those with acute fluid shifts and using disease-specific outcomes, may better define the clinical role of BIV.

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References

  1. Wells JC, Fewtrell MS. Is body composition important for paediatricians? Arch Dis Child. 2008;93:168–72.

    Article  PubMed  Google Scholar 

  2. Wells JC, Fewtrell MS. Measuring body composition. Arch Dis Child. 2006;91:612–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Piccoli A, Rossi B, Pillon L, Bucciante G. A new method for monitoring body fluid variation by bioimpedance analysis: the RXc graph. Kidney Int. 1994;46:534–9.

    Article  CAS  PubMed  Google Scholar 

  4. Piccoli A. Bioelectric impedance measurement for fluid status assessment. Contrib Nephrol. 2010;164:143–52.

    Article  PubMed  Google Scholar 

  5. Ott M, Fischer H, Polat H, Helm EB, Frenz M, Caspary WF, et al. Bioelectrical impedance analysis as a predictor of survival in patients with human immunodeficiency virus infection. J Acquir immune Defic Syndr Hum Retrovirology. 1995;9:20–25.

    CAS  Google Scholar 

  6. Stobaus N, Pirlich M, Valentini L, Schulzke JD, Norman K. Determinants of bioelectrical phase angle in disease. Br J Nutr. 2012;107:1217–20.

    Article  PubMed  Google Scholar 

  7. Abad S, Sotomayor G, Vega A, Perez de Jose A, Verdalles U, Jofre R, et al. The phase angle of the electrical impedance is a predictor of long-term survival in dialysis patients. Nefrologia. 2011;31:670–6.

    CAS  PubMed  Google Scholar 

  8. Paiva SI, Borges LR, Halpern-Silveira D, Assuncao MC, Barros AJ, Gonzalez MC. Standardized phase angle from bioelectrical impedance analysis as prognostic factor for survival in patients with cancer. Support Care Cancer. 2010;19:187–92.

    Article  PubMed  Google Scholar 

  9. Gonzalez MC, Barbosa-Silva TG, Bielemann RM, Gallagher D, Heymsfield SB. Phase angle and its determinants in healthy subjects: influence of body composition. Am J Clin Nutr. 2016;103:712–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Piccoli A. Estimation of fluid volumes in hemodialysis patients: comparing bioimpedance with isotopic and dilution methods. Kidney Int. 2014;85:738–41.

    Article  CAS  PubMed  Google Scholar 

  11. Bosy-Westphal A, Danielzik S, Dorhofer RP, Piccoli A, Muller MJ. Patterns of bioelectrical impedance vector distribution by body mass index and age: implications for body-composition analysis. Am J Clin Nutr. 2005;82:60–68.

    Article  CAS  PubMed  Google Scholar 

  12. Redondo-Del-Rio MP, Camina-Martin MA, Marugan-de-Miguelsanz JM, de-Mateo-Silleras B. Bioelectrical impedance vector reference values for assessing body composition in a Spanish child and adolescent population. Am J Hum Biol. 2017. https://doi.org/10.1002/ajhb.22978.

  13. Wells JCK, Williams JE, Quek R, Fewtrell MS. Bio-electrical impedance vector analysis: testing Piccoli’s model against objective body composition data in children and adolescents. Eur J Clin Nutr. 2018. https://doi.org/10.1038/s41430-018-0292-x.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Gerasimidis K, Keane O, Macleod I, Flynn DM, Wright CM. A four-stage evaluation of the Paediatric Yorkhill Malnutrition Score in a tertiary paediatric hospital and a district general hospital. Br J Nutr. 2010;104:751–6.

    Article  CAS  PubMed  Google Scholar 

  15. McCarthy H, Dixon M, Crabtree I, Eaton-Evans MJ, McNulty H. The development and evaluation of the Screening Tool for the Assessment of Malnutrition in Paediatrics (STAMP©) for use by healthcare staff. J Hum Nutr Diet. 2012;25:311–8.

    Article  CAS  PubMed  Google Scholar 

  16. Hulst JM, Zwart H, Hop WC, Joosten KFM. Dutch national survey to test the STRONGkids nutritional risk screening tool in hospitalized children. Clin Nutr. 2010;29:106–11.

    Article  PubMed  Google Scholar 

  17. Freeman JV, Cole TJ, Chinn S, Jones PR, White EM, Preece Ma. Cross sectional stature and weight reference curves for the UK, 1990. Arch Dis Child. 1995;73:17–24.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Wells JC, Williams JE, Chomtho S, Darch T, Grijalva-Eternod C, Kennedy K, et al. Body-composition reference data for simple and reference techniques and a 4-component model: a new UK reference child. Am J Clin Nutr. 2012;96:1316–26.

    Article  CAS  PubMed  Google Scholar 

  19. Hauschild DB, Barbosa E, Moreira EAM, Neto NL, Platt VB, Filho EP, et al. Nutirtion status parameters and hydration status by biolectrocial impedence vector analysis were associated with lung function impairment in children and adolescents with cystic fibrosis. Nutr Clin Pract. 2016;31:378–86.

    Article  PubMed  Google Scholar 

  20. De Palo T, Messina G, Edefonti A, et al. Normal values of the bioimpedence vector in childhood and puberty. Nutrition. 2000;16:417–24.

    Article  PubMed  Google Scholar 

  21. Girma T, Hother Nielsen AL, Kæstel P, Abdissa A, Michaelsen KF, Friis H, et al. Biochemical and anthropometric correlates of bio-electrical impedance parameters in severely malnourished children: a cross-sectional study. Clin Nutr. 2018;37:701–5.

    Article  CAS  PubMed  Google Scholar 

  22. Girma T, Kaestel P, Workeneh N, Molgaard C, Eaton S, Andersen GS, et al. Bioimpedance index for measurement of total body water in severely malnourished children: assessing the effect of nutritional oedema. Clin Nutr. 2016;35:713–7.

    Article  PubMed  Google Scholar 

  23. Bozzetto S, Piccoli A, Montini G. Bioelectrical impedance vector analysis to evaluate relative hydration status. Pedia Nephrol. 2010;25:329–34.

    Article  Google Scholar 

  24. Azevedo ZM, Moore DC, de Matos FA, Fonseca VM, Peixoto MV, Gaspar-Elsas MI, et al. Bioelectrical impedance parameters in critically ill children: importance of reactance and resistance. Clin Nutr. 2013;32:824–9.

    Article  PubMed  Google Scholar 

  25. Buffa R, Saragat B, Cabras S, Rinaldi AC, Marini E. Accuracy of specific BIVA for the assessment of body composition in the United States population. PLoS ONE. 2013;8:e58533.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Buffa R, Mereu E, Succa V, Latini V, Marini E. Specific BIVA recognizes variation of body mass and body composition: Two related but different facets of nutritional status. Nutrition. 2017;35:1–5.

    Article  PubMed  Google Scholar 

  27. Buffa R, Floris G, Marini E. Bioelectrical impedance vector in pre- and postmenarcheal females. Nutrition . 2002;18:474–8.

    Article  PubMed  Google Scholar 

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Acknowledgements

We thank all the children and parents who participated in the study.

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Correspondence to M. S. Fewtrell.

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Conflict of interest

Professor Wells has received two BIA machines gratis from Bodystat, used in previous research. Bodystat had no role or influence over the research reported here. The remaining authors declare that they have no conflict of interest.

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Roche, S., Lara-Pompa, N.E., Macdonald, S. et al. Bioelectric impedance vector analysis (BIVA) in hospitalised children; predictors and associations with clinical outcomes. Eur J Clin Nutr 73, 1431–1440 (2019). https://doi.org/10.1038/s41430-019-0436-7

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