Same therapy, same calcium mobilization? Exploring calcium exchange across body compartments using a patient-specific predictive model

Background: Comprehensive, patient-specific models are essential to study calcium deposition and mobilization during dialysis. We aim to develop tools to support clinical prescriptions with a more accurate approach for the prediction of calcium mobilization while also considering major electrolytes and catabolites. Methods: We modified a multi-solute model predicting patient-specific dialysis response by incorporating a calcium buffer to represent bone exchanges. Data from four centers, involving 127 patients with six sessions each, were utilized. For each patient, three sessions were allocated for model training (ID123), while the remaining sessions were for validation (PRED456). The normalized root mean square error (nRMSE%) was used to evaluate both descriptive and predictive accuracy. Correlations between initial data and calcium exchanges were also assessed. Results: The overall nRMSE% for ID123 was 3.92%. For PRED456, it was 3.46% (ranging from a minimum of 1.17% for [Na+] to a maximum of 6.62% for [urea]). The median nRMSE% for plasma calcium varied between 1.13 and 8.32 for SHD sessions, depending on whether Ca_dialysis fluid (Ca-d) was >= or <1.50 mmol/L, respectively. For HDF sessions, the range was between 2.90 and 5.89. A significant and moderate correlation was found between overall calcium removal and the buffer balance. The most robust correlation observed was between the amount of calcium administered via post-dilution fluid and the overall calcium removal in the dialysis filter. Conclusions: Identical therapy settings do not uniformly affect calcium mobilization, and our approach offers insight into calcium distribution across body compartments. This understanding will enhance clinical prescription practices.