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ASN / Education & Meetings / Kidney Week /
Abstract: SA-PO489

Assessment of Body Composition by Whole-Body Bioimpedance and Body Cardio Scale in Patients on Peritoneal Dialysis

Session Information

  • Home Dialysis - 2
    October 26, 2024 | Location: Exhibit Hall, Convention Center
    Abstract Time: 10:00 AM - 12:00 PM

Category: Dialysis

  • 802 Dialysis: Home Dialysis and Peritoneal Dialysis

Authors

  • Yi, Jun, Renal Research Institute, New York, New York, United States
  • Zhu, Fansan, Renal Research Institute, New York, New York, United States
  • Rosales M., Laura, Renal Research Institute, New York, New York, United States
  • Tisdale, Lela, Renal Research Institute, New York, New York, United States
  • Villarama, Maricar, Mount Sinai Health System, New York, New York, United States
  • Gusmao Bittencourt, Valeria, Renal Research Institute, New York, New York, United States
  • Murphy, Barbara M., Renal Research Institute, New York, New York, United States
  • Golnabi, Amir, Renal Research Institute, New York, New York, United States
  • Kotanko, Peter, Renal Research Institute, New York, New York, United States
Background

Quantitative assessment of body composition is important for optimizing individualized treatment regimens in peritoneal dialysis (PD) patients. This study aims to compare body composition using the body cardio scale (BCS) and whole-body bioimpedance based on a body composition model (BCM).

Methods

Nine PD patients (6 males, age 50.1±12.8 years) were stuided. BCS (Withings) was used (Fig.1) with the patient standing on the scale. Total body water (TBWBCS), fat (FatBCS), and muscle mass (MMBCS) were provided. Whole body bioimpedance spectroscopy (Hydra 4200) was used to estimate extracellular (ECV) and intracellular (ICV) volume. Four electrodes were donned on the hand and foot (Fig 2). Overhydration (OH), fat (FatBCM), muscle mass (MMBCM) andTBWBCM (ECV+ICV) were calculated (Chamney, Am J Clin Nutr 85:80-9, 2007). Linear regression analysis and Bland-Altman plots were applied to evaluate the correlation and agreement between BCS and BCM.

Results

A strong correlation was observed between TBWBCS and TBWBCM (R2=0.94, p<0.0001), with a minor bias (0.67±2.47 kg) (Fig.3a and 3b). FatBCS and FatBCM were also highly correlated (R2=0.97, p<0.0001), albeit with a substantial negative bias (-12.06±7.92 kg) which inversely correlated with fat mass (Fig.3c and 3d). MMBCS correlated reasonably well with MMBCM (R2=0.82, p<0.001), but MMBCS overestimated muscle mass (bias, 12.75±4.68 kg) (Fig.3e and 3f). Furthermore, BCM indicated the degree of overhydration (OH =1.47±2.0 kg).

Conclusion

While BCS offers easy-of-use and no specific electrodes, the big biases limit its applicability in dialysis patients. The bias may be attributed to a calculation of fat-free mass (FFM) by a general formular (FFM=TBW/0.73) which may not be appropriate for dialysis patients. We refrain from recommending it as a precise assessment of body composition in dialysis patients.