The multivariate predictive model to estimate ionized calcium concentration from serum biochemical results in dogs: External validation.

Background: Predicted ionized calcium (piCa) can be calculated from routine biochemistry variables using a recently developed predictive model in dogs. However, it has not been evaluated with variables measured from multiple laboratories.

Objectives: We aimed to (a) externally validate piCa in dogs where biochemistry results were obtained from different analyzers, and (b) compare the diagnostic performances of piCa and total calcium (tCa).

Methods: A cross-sectional multicentric study on 138 dogs from three different hospitals was performed. The sensitivity (Sen), specificity (Spe), positive (PPV) and negative predictive values (NPV), and diagnostic discordance of piCa and tCa were calculated using logistic regression for ionized hypercalcemia and hypocalcemia. Diagnostic performance fluctuations across hospitals were also assessed.

Results: For ionized hypercalcemia, the Sen (81.8%), Spe (96.1%), PPV (69.2%), NPV (97.7%), and diagnostic discordance (5.1%) of piCa were not significantly different among hospitals or from those of tCa. For ionized hypocalcemia, the Sen (range: 9.7%-53.8%) and Spe (range: 95.6%-99.6%) of piCa and tCa (Sen range: 16.2%-87.8%; Spe range: 58.3%-98.1%) varied across hospitals, although to a lesser extent for piCa. The diagnostic discordances of piCa (20.3%) and tCa (25.4%) were close. The prediction interval (PI) of piCa demonstrated high Sen to screen for ionized hypercalcemia (100%) and hypocalcemia (range: 75%-93.3%), and high Spe to diagnose ionized hypercalcemia and hypocalcemia (100% for both).

Conclusions: These results support the external validation of piCa in dogs. Its PI represents a notable advantage over tCa to help clinicians explore calcium-related disorders when ionized calcium cannot be readily measured.