RESUMO
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 (Cad) 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.
RESUMO
BACKGROUND: End-stage renal disease (ESRD) represents a situation in which persistently elevated levels of cardiac troponins I (cTnI) are frequently found in the absence of clinically evident cardiac disease. Moreover, the effect of hemodialysis (HD) on cTnI levels is not definitively elucidated. The aim of this study was to investigate the effects of HD on cTnI levels in ESRD patients. METHODS: We enrolled 30 asymptomatic ESRD patients on maintenance HD. All the patients were dialyzed thrice weekly. We compared each other's cTnI levels obtained before HD sessions (pre-HD) and cTnI levels obtained before and after HD sessions (post-HD). RESULTS: The median value of baseline cTnI, measured before the first dialysis session of the week, was 0.018 ng/mL (interquartile range 0.012-0.051) and elevated levels (>0.034 ng/mL) were found in 9 (30%) patients. Pre-HD cTnI levels showed a statistically significant decrease between the first and the second weekly HD sessions (from 0.018 to 0.016 ng/mL; p = 0.002), while no difference was observed between the second and the third sessions over the week. Finally, no statistically significant differences were found between pre-HD and post-HD cTnI levels, considering each HD session and the averaged cTnI values. CONCLUSIONS: Our results indicate that HD does not significantly affect cTnI levels. Even when statistically significant, the observed changes were without clinical relevance indicating that HD does not affect by itself the diagnostic accuracy of cTnI assay in ESRD patients.