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Biavector - Vector Analysis

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Background of BIAVECTOR®

The conventional approach to the bioelectrical impedance analysis (BIA) uses simple or multiple regression equations to make predictions of masses and volumes of body compartments in subjects with fixed and normal 73% hydration of soft tissues. In abnormal hydration conditions these algorithms can produce biased estimates of body compartments.

 Why is BIA based on models and prediction equations? During stable periods, relations between body components are constant and correlated with each other, which allows investigators to estimate an unknown body component (e.g. TBW, ICW, ECW, FFM, FM, and BCM) from a related measured property (bioimpedance) through regression equations. Hundreds of excellent validation studies established a solid relationship between body impedance and body fluid volume (isotope dilution), but with population specific accuracy of prediction. However, since criterion methods have their own errors, the standard error of the estimate of the best BIA regression equations is too large (95% prediction interval greater than ± 3 to 6 kg or L) to be useful in the clinical setting [1,2].

Patterns vs. models and quantitative estimates.

In BIA literature, an electrical model (e.g. series, parallel, Cole's, and Hanai's model) is used as an electrical equivalent [3], that is a circuit that electrically behaves like the original, is expressed through mathematical equations, and represents anatomical structures or physical processes (e.g. 75 trillion cells, 3 to 6 body compartments, cellular/vascular fluid shifts, etc).  

According to dictionary definition, a model is "A representation of the supposed structure of something", and a pattern is "A set of forms used as a guide in making things".

In the clinical setting, operational patterns based on direct laboratory data are more useful than complex, explanatory or descriptive models of phenomena.

Both electrocardiography and BIA aim to transform electrical properties of tissues into clinical information. The electrocardiogram (ECG) is a graphic recording through surface electrodes (as in BIA) of electric potentials generated by the heart. Abnormalities of individual waveforms are defined with respect to reference values of healthy subjects. An ECG is interpreted using diagnostic ECG patterns which are a combination of waveforms that was associated with specific cardiac disorders in clinical validation studies (e.g. bundle branch blocks, myocardial ischemia, infarction, etc.) [4]. Calculations of heart volume, ischemic mass volume, infarction volume, etc., from ECG waveforms through electrical models and prediction equations are not used in the clinical setting. 

Clinical utility of BIA can be achieved following the methodology of ECG interpretation, that is using vector BIA (Bioelectrical Impedance Vector Analysis, BIAVECTOR®) as a stand-alone procedure based on patterns of direct impedance measurements (impedance vectors) [5]. Body soft tissues (i.e. lean plus fat soft tissues, or the FFM without bone plus the FM, according to [2]) actually generate the body impedance [1-3,6,7] and therefore can be directly evaluated with vector BIA. Contribution of bone to impedance is negligible, and lean contributes more than fat soft tissue because adipocyte droplets of triacylglycerols are non-conductors [1-3,6,7].





Studies and Papers Biavector

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