Body composition monitoring-derived urea distribution volume in children on chronic hemodialysis

Abstract Background and Aims Monitoring of fluid, body composition and nutritional changes is important in clinical nephrology. The Body Composition Monitor (BCM; Fresenius Medical Care, Bad Homburg, Germany) measures whole-body bioimpedance and determines extracellular and intracellular resistance by using the Cole-model to estimate total body water (TBW-BCM) and its partition into extracellular and intracellular water. Both can then be used to define body composition and separate body weight into lean tissue mass, adipose tissue mass, and fluid overload. Urea kinetic modeling (UKM) allows the estimation of dialysis dose (double-pooled Kt/V), urea distribution volume (V-UKM) and dietary protein intake. We studied the bias between estimated V-UKM to anthropometric and measured TBW-BCM (Vant, TBW-BCM). Method Pre-hemodialysis (HD), electrodes for the BCM assessments were placed on the non-arteriovenous access arm and ipsilateral leg, respectively, with the patient in a supine position. Vant was calculated using the Watson equation. In addition to these assessments we entered the specified values from the most recent urea kinetic modeling (UKM) treatment into the online solute-solver calculator (http://ureakinetics.org). We chose a baseline ratio of modeled/anthropometric volume of 0.6 to 1.3 L to exclude values with data entry errors and/or UKM sampling errors. We calculated the post HD TBW-BCM by subtracting the intradialytic weight loss and adjusted these estimates by the differences in post HD weight between sessions to make both estimates comparable. We depicted the comparison between the estimated V-UKM versus the TBW-BCM in a scatter- and Bland-Altman (BA) plot (Figure). For the purpose of error investigation we studied the computed bias (V-UKM minus TBW-BCM) as a function of body mass index (BMI) and stray capacitance (td) in a BA plot. We then calculated the difference between Vant and V-UKM and illustrated the comparison in a scatter and BA plot. Results In a cross-sectional design, we studied 161 stable prevalent HD patients (61.3±14.7 years, 98 (60.9%) males, height of 167.5±10.7 cm) prior to their treatment. The regression plot showed slight agreement (R2= 0.69) and the Bland-Altman plot no systematic trends or proportional error in the main analysis (Figure 1a and b). Neither BMI or td explained bias and variance in the bias between both estimates. Vant and V-UKM plots showed agreement (R2 of 0.68) with a mean bias of -2.3±5.1 and no proportional error. Conclusion Both TBW-BCM and the V-UKM as the “bronze standard” of TBW estimation seemed to agree reasonably well. Neither body composition measurement or kinetic modeling approach showed any significant influence on the accuracy and precision of the estimate. According to BCM availability, estimated V-UKM or measured TBW-BCM could be used alternatively in practice to support clinical decision when pharmacokinetic considerations are concerned.

Download Full-text

MO663THE UTILITY OF SMART SCALES TO MONITOR BODY COMPOSITION IN HEMODIALYSIS PATIENTS

Nephrology Dialysis Transplantation ◽

10.1093/ndt/gfab099.008 ◽

2021 ◽

Vol 36 (Supplement_1) ◽

Author(s):

Lucia Cordero ◽

Marta Rivero Martínez ◽

Paula Jara Caro Espada ◽

Elena Gutiérrez ◽

Evangelina Mérida ◽

...

Keyword(s):

Body Composition ◽

Fat Tissue ◽

Lean Tissue ◽

Tissue Mass ◽

Composition Data ◽

The Mean ◽

Good Concordance ◽

Urea Distribution Volume ◽

Assess Body Composition

Abstract Background and Aims Overhydration (OH) is an independent predictor of mortality on hemodialysis (HD). The gold standard to assess OH is BCM monitor from Fresenius®, however BCM is a hospital hold device limiting its use. New smart scales have emerged as household devices reporting daily body composition data. Objective To determine if Renpho ES-CS20M® could be useful on a 52 HD patient to estimate body composition data. Method 72 body composition assessments (BCA) during mid-week HD session were performed. Each BCA included: (1) Predialysis Renpho measurement, (2) Predialysis BCM monitor measurement, (3) Postdialysis Renpho measurement. To track the fluid balance during the HD session: (1) we recorded ultrafiltration, (2) food or fluid intake was not allowed, and (3) none of the HD patients urinated during the HD session. If any intravenous fluids were needed during the HD session, we subtracted them off from UF. Results Data from 52 HD patients were studied (age 58.8 ± 16.8 years, 56.9 % males, 14.7% diabetics), with a mean pre-HD weight of 70.0 ± 13. 4 Kg, overhydration of 1.7 ± 1.5 L and urea distribution volume of 31.7 ± 5.7 L. The mean ultrafiltration during HD session was -1.8 ± 0.9 L. Renpho estimated a Pre – HD hydration of 34.25 ± 6.02 Kg vs 33.4 ± 5.7 Kg by BCM, showing a good concordance between methods (ICC 0.788 [0.67-0.86], B -0.58, p <0.01). Renpho poorly estimated pre – HD lean tissue mass at 45.4 ± 6.9 Kg compared with 33.8 ± 8.0 Kg by BCM. Although Renpho was able to provide a moderate concordant estimation of fat tissue mass (33.8 ± 8.0 % with Renpho vs 34.7 ± 9.6%), the bias proportion was unacceptable. Post- HD hydration by Renpho was not able to reproduce the ultrafiltracion achieved during the HD session (pre-HD 34.25 ± 6.02 Kg vs post-HD 34.08 ± 6.00 Kg). Conclusion Renpho has a proportional bias estimating predialysis hydration compared with BCM monitor, but is not able to assess changes produced with ultrafiltration or other parameters of body composition (as lean or fat tissue mass). Although smart scales are unacurate to assess body composition on HD patients, they could be useful on the follow up of them changing the accuracy for frequency.

Download Full-text