#2234 A new formula for total body water in peritoneal dialysis patients
Authors: Ramos Ana Rita , Duarte Rui , Alves Rita Valerio , Gonçalves Hernâni , Santos Paulo 
Published: May 2024

Abstract

Background and Aims
Peritoneal dialysis (PD) adequacy, assessed primarily by Kt/V, is crucial in routine clinical practice for detecting issues with PD treatment. This metric relies on urea levels and its volume (V) distribution, classically equivalent to total body water (TBW). TBW estimation, commonly achieved through the Watson and Watson (WW) formula, lacks dialysis patients in its original study, it also excluded patients with water metabolism disturbances, raising concerns about its generalizability to this population. Despite limitations, WW has been widely used in trials assessing optimal dialysis dosage in the PD population. Body composition monitoring (BCM) with bioimpedance (BI) offers a more reliable method for TBW determination, commonly used in dialysis programs for quantifying overhydration. However, its higher cost and limited availability compared to estimate formulas pose challenges.
Thereby, this study aims to compare TBW values derived from the WW formula and BCM analysis with BI. Additionally, intends to create a new, patient-specific TBW formula based on biometric measurements for PD.

Method
We retrospectively analyzed adequacy measurements and BCM data from a Portuguese PD center. Patient information included age, sex, height, weight, and BCM-TBW and Percentage Body Fat (PBF). Derived parameters encompassed WW-derived TBW, Body Surface Area (BSA) via the DuBois formula and Body Mass Index (BMI). Statistical analysis, using Microsoft Excel 2017 and IBM SPSS version 25, with a p-value&lt;0.05 considered significant, followed by a step-wise approach:

Results
400 measurements were collected from 90 chronic PD patients. 25.1% (n = 23) were female (101 measurements), with a mean age of 56.2 ± 11.9 years. Mean weight was 74.0 ± 12.5 kg, BMI 26.4 ± 4.1 and BSA 1.80 ± 0.80. BCM TBW obtained was significantly lower compared to WW-TBW (33.7 and 38.4 litters respectively, mean difference −4.65 ± 4.17, P &lt; .001). This difference correlated positively with increased PBF (ρ = 0.73, P &lt; .001). BCM TBW correlated positively with weight, height, BMI and BSA (ρ = 0.62, ρ = 0.68, ρ = 0.28 and ρ = 0.62, respectively, with P &lt; .001 overall), without correlation with age (ρ = 0.0, P = .99).
For linear regression analysis, the first step was to exclude outlier values for BCM TBW using median ± 1.5 x interquartile range resulting in 383 measurements comprised between 22.15 and 44.95 L. A multiple linear regression using BSA, height, weight and sex to predict BCM TBW. The overall regression model was statistically significant (R2 = 0.59, F (4 378) = 138.17, P &lt; .001). All the variables significantly contributed to the model at predicting BCM TBW (BSA: β = −0.283, P &lt; .001; Height: β = 0.495, P &lt; .001; Weight: β = 0.56, P &lt; .001; Sex: β = 0.237, P &lt; .001). Two formulas were extrapolated from this regression:

Conclusion
We present a pivotal formula for TBW calculation in PD patients, aiming to improve the correlation between provided Kt/V and clinical outcomes. This addresses the exclusion of diverse patient characteristics in previous studies. However, given the new evidence challenging the association between Kt/V and clinical outcomes in PD, it becomes imperative to appropriate measures for PD adequacy and subject them to examination in novel randomized clinical trials.