Can the response to dialysis treatment be predicted by using patient-specific modeling of fluid and solute exchanges? A multicentric evaluation

Abstract

Background: Parametric multipool kinetic models were used to describe the intradialytic trends of electrolytes, breakdown products, and body fluids volumes during hemodialysis. Therapy customization can be achieved by the identification of parameters, allowing patient-specific modulation of mass and fluid balance across dialyzer, capillary, and cell membranes. This study wants to evaluate the possibility to use this approach to predict the patient's intradialytic response. Methods: 6 sessions of 68 patients (DialysIS© project) were considered. Data from the first three sessions were used to train the model, identifying the patient-specific parameters, that, together with the treatment settings and the patient's data at the session start, could be used for predicting the patient's specific time course of solutes and fluids along the sessions. Na+, K+, Cl−, Ca2+, HCO3−, and urea plasmatic concentrations and hematic volume deviations from clinical data were evaluated. Results: nRMSE predictive error is on average equal to 4.76% when describing the training sessions, and only increases by 0.97 percentage points on average in independent sessions of the same patient. Conclusions: The proposed predictive approach represents a first step in the development of tools to support the clinician in tailoring the patient's prescription.