Key Points: Ultrafiltration (UF) is a key component of clinical peritoneal dialysis prescription, but the traditional method to assess UF is hampered by large inaccuracies. Here we propose a novel method, based on a computational model and on a single dialysate sodium measurement, to accurately estimate UF and osmotic conductance to glucose in patients on peritoneal dialysis.

Background: Volume overload is highly prevalent among patients treated with peritoneal dialysis (PD), contributes to hypertension, and is associated with an increased risk of cardiovascular events and death in this population. As a result, optimizing peritoneal ultrafiltration (UF) is a key component of high-quality dialysis prescription. Osmotic conductance to glucose (OCG) reflects the water transport properties of the peritoneum, but measuring it requires an accurate quantification of UF, which is often difficult to obtain because of variability in catheter patency and peritoneal residual volume.

Methods: In this study, we derived a new mathematical model for estimating UF during PD, on the basis of sodium sieving, using a single measure of dialysate sodium concentration. The model was validated experimentally in a rat model of PD, using dialysis fluid with two different sodium concentrations (125 and 134 mmol/L) and three glucose strengths (1.5%, 2.3%, and 4.25%). Then, the same model was tested in a cohort of PD patients to predict UF.

Results: In experimental and clinical conditions, the sodium-based estimation of UF rate correlated with UF rate measurements on the basis of volumetry and albumin dilution, with a =0.35 and =0.76, respectively. UF on the basis of sodium sieving was also successfully used to calculate OCG in the clinical cohort, with a Pearson of 0.77.

Conclusions: Using the novel mathematical models in this study, the sodium dip can be used to accurately estimate OCG, and therefore, it is a promising measurement method for future clinical use.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10914194PMC
http://dx.doi.org/10.34067/KID.0000000000000358DOI Listing

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