Although the importance of assessing hydration is well recognized, traditional laboratory methods and clinical impressions are impractical or lack sensitivity to be useful in physiological and clinical conditions. Alternate approaches using bioelectrical impedance measurements to estimate fluid volumes utilize regression equations and depend on physical models unproven in physiological systems; they result in large errors in the prediction of fluid volumes notably in individuals with altered hydration. Bioelectrical impedance vector analysis (BIVA) overcomes these limitations because it only uses determinations of resistance (R) and reactance (Xc) normalized for height and yields a vector of specific magnitude (length) and direction (phase angle). This vector, for either an individual or a group, is evaluated on the bivariate R–Xc graph, which is a probability distribution derived from a reference population of healthy, matched controls. Comparison of an individual or group vector to the mean vector of the reference population provides reliable and accurate classification and ranking of hydration that is independent of body weight. Applications of BIVA in healthy adults include assessment of over-hydration in pregnancy and weight loss in obesity. BIVA also has broad uses in the evaluation and management of clinical groups including the characterization of patterns of hydration change during hemodialysis (HD) and peritoneal dialysis and use of this information to prescribe dialytic therapy; identification of under-hydration in critically ill patients and guidance for administration of fluid therapy; assessment and monitoring of tissue hydration status in congestive heart failure; and identification of regional edema in patients after vascular surgery. Because of its practicality and reliability, BIVA can be used in observational and longitudinal studies of hydration in patient care and management and in field conditions.

Bioelectrical Impedance Vector Analysis for Assessment of Hydration in Physiological States and Clinical Conditions

PICCOLI, ANTONIO
2012

Abstract

Although the importance of assessing hydration is well recognized, traditional laboratory methods and clinical impressions are impractical or lack sensitivity to be useful in physiological and clinical conditions. Alternate approaches using bioelectrical impedance measurements to estimate fluid volumes utilize regression equations and depend on physical models unproven in physiological systems; they result in large errors in the prediction of fluid volumes notably in individuals with altered hydration. Bioelectrical impedance vector analysis (BIVA) overcomes these limitations because it only uses determinations of resistance (R) and reactance (Xc) normalized for height and yields a vector of specific magnitude (length) and direction (phase angle). This vector, for either an individual or a group, is evaluated on the bivariate R–Xc graph, which is a probability distribution derived from a reference population of healthy, matched controls. Comparison of an individual or group vector to the mean vector of the reference population provides reliable and accurate classification and ranking of hydration that is independent of body weight. Applications of BIVA in healthy adults include assessment of over-hydration in pregnancy and weight loss in obesity. BIVA also has broad uses in the evaluation and management of clinical groups including the characterization of patterns of hydration change during hemodialysis (HD) and peritoneal dialysis and use of this information to prescribe dialytic therapy; identification of under-hydration in critically ill patients and guidance for administration of fluid therapy; assessment and monitoring of tissue hydration status in congestive heart failure; and identification of regional edema in patients after vascular surgery. Because of its practicality and reliability, BIVA can be used in observational and longitudinal studies of hydration in patient care and management and in field conditions.
2012
Handbook of Anthropometry: Physical Measures of Human Form in Health and Disease
9781441917881
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/2530219
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