Evaluating Peritoneal Fluid Transport in Continuous Peritoneal Dialysis Patients: A Practical Approach

Abstract

Background/Aims: Evaluating the peritoneal fluid kinetics is of clinical importance in peritoneal dialysis treatment. We have previously developed a simple way to evaluate the peritoneal fluid transport characteristics in continuous ambulatory peritoneal dialysis patients which, however, cannot be applied to those patients on a fixed dialysis schedule. Therefore, in the present study, we tested the possibility to vary the peritoneal dwell time and tried to develop a more patient-friendly ultrafiltration (UF) collection protocol. Methods: The patients’ UF volume was recorded for 10 days. All patients recruited were asked to perform their usual dialysis exchanges with, however, a special UF data collection protocol to improve the accuracy of computer simulation: at least one dwell of 2–4 h, one of 4–7 h, and one of more than 7 h. The fluid transport model was applied to the pooled UF volume for fluid kinetics simulation, and the data from the following day’s UF records using the same glucose concentration and dwell time were used to evaluate reliability and accuracy of the simulated UF value. Results: Fifty-two chronic peritoneal dialysis patients were included in the present study. All of the UF data could be used in the computer simulation, and there was a significant negative correlation between fluid absorption rate ( K_e ; see text) and actual UF volume on the following day using a glucose concentration of 1.5% and a dwell time of 4 h (r = –0.336, p < 0.05). The estimated UF values correlated significantly with the actually measured UF values. The variability of the results, expressed by the width between the 95% limits of agreement, fell within –139.2 to 131.9 ml, while the mean difference was –3.7 ml. Conclusions: Our present study showed that varying the peritoneal dwell time was a patient-friendly UF data collection protocol for continuous ambulatory peritoneal dialysis patients on a fixed dialysis schedule. Applying the fluid transport model and nonlinear least squares regression analysis to pooled UF values might be a good and simple way to predict the peritoneal UF capacity.