Correlation and Dissociation Factors between Ionized, Total, and Corrected Calcium in Patients on Hemodialysis

Background: It is important to optimize serum calcium concentrations in dialysis patients because abnormal calcium levels are associated with the risk of all-cause mortality and cardiovascular events. Ionized calcium (iCa) has physiological activity in the body; however, the direct measurement of iCa is limited technically. Although total serum calcium (tCa) and corrected calcium (cCa) using the Payne correction formula have been utilized to assess calcium levels, their limitations have been pointed out. The degree to which the correlation between ionized, total, and corrected calcium is dissociated in dialysis patients has rarely been examined, and the factors influencing this correlation are poorly understood. This study aimed to clarify the degree of correlation and dissociation among iCa, tCa, and cCa levels in patients undergoing hemodialysis. Methods: A cross-sectional study assessed the correlation between iCa, tCa, and cCa levels in patients undergoing hemodialysis. Factors involved in the correlation between the iCa and tCa levels were evaluated using multiple regression analysis. Based on these results, we proposed a novel iCa prediction equation. Results: Two hundred thirteen patients were enrolled. Patients were 65 ± 10.2 years, and 67.1% of patients were male. The correlation coefficients were 0.8665 for iCa and tCa and 0.8537 for iCa and cCa. Correlations were also observed when the albumin concentration and pH were divided by known correlation factors. In multiple regression analysis of the relationship between tCa and iCa, albumin, pH, phosphorus, and Mg levels were significant factors. Based on these results, a new corrected calcium equation (mg/dL) = 0.828×total calcium - 0.314×albumin (g/dL) + 0.007×age + 2.922 was derived using age and albumin. Conclusion: There was a correlation between iCa, tCa, and cCa in hemodialysis patients, with a stronger correlation with tCa in iCa assessments. Correcting for tCa levels may not be necessary when predicting iCa levels. We propose a novel prediction equation for estimating iCa by age and albumin without blood gas analysis.