Development of a Multivariate Predictive Model to Estimate Ionized Calcium Concentration from Serum Biochemical Profile Results in Dogs

Abstract

BackgroundIonized calcium concentration is the gold standard to assess calcium status in dogs, but measurement is not always available.Objectives(1) To predict ionized calcium concentration from biochemical results and compare the diagnostic performance of predicted ionized calcium concentration (piCa) to those of total calcium concentration (tCa) and 2 corrected tCa formulas; and (2) to study the relationship between biochemical results and variation of measured ionized calcium concentration (miCa).AnimalsA total of 1,719 dogs with both miCa and biochemical profile results available.MethodsCross‐sectional study. Using 1,200 dogs, piCa was determined using a multivariate adaptive regression splines model. Its accuracy and performance were tested on the remaining 519 dogs.ResultsThe final model included creatinine, albumin, tCa, phosphorus, sodium, potassium, chloride, alkaline phosphatase, triglycerides, and age, with tCa, albumin, and chloride having the highest impact on miCa variation. Measured ionized calcium concentration was better correlated with piCa than with tCa and corrected tCa and had higher overall diagnostic accuracy to diagnose hypocalcemia and hypercalcemia, but not significantly for hypercalcemia. For hypercalcemia, piCa was as sensitive (64%) but more specific (99.6%) than tCa and corrected tCa. For hypocalcemia, piCa was more sensitive (21.8%) and as specific (98.4%) as tCa. Positive and negative predictive values of piCa were high for both hypercalcemia (90% and 98%, respectively) and hypocalcemia (70.8% and 87.7%, respectively).Conclusions and clinical importancePredicted ionized calcium concentration can be obtained from readily available biochemical and patient results and seems more useful than tCa and corrected tCa to assess calcium disorders in dogs when miCa is unavailable. Validation on external data, however, is warranted.

Development and validation of a multivariate predictive model to estimate serum ionized calcium concentration from serum biochemical profile results in cats

“…MARS model statistics were performed by the software of the public domain R version 3.4.2 (R project, Vienna, Austria). A MARS model was used to create the predictive algorithm in the same way as it was done in dogs . Briefly, a MARS model is a nonparametric regression technique that approximates complex non‐linear relationships by a series of hinge functions of the predictors expressed by the formula: where a 0 is the intercept of the model, p is the total number of hinge functions, a k is the coefficient of the k th hinge function h k (x) , and x is a predictor.…”

Determination of a serum total calcium concentration threshold for accurate prediction of ionized hypercalcemia in dogs with and without hyperphosphatemia

“…A recent study developed a model for predicting iCa status in dogs based on numerous results available on a biochemical profile in dogs . This model had high PPV (90%) and specificity (99.6%), and moderate sensitivity (64%).…”

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

“…Ionized calcium measurements were performed using an ion‐selective electrode analyzer. The other inclusion criteria were: (1) availability of a measured ionized calcium (miCa) reference interval (RI) specific to each analyzer, and (2) the use of biochemistry analyzers that were different from the Roche Hitachi 917 (Roche Diagnostics, Indianapolis, Indiana) and Olympus AU680 (Beckman Coulter, Inc, Brea, California), which were previously used for development and internal validation of the predictive model . Measured iCa RIs must have been determined using more than 20 healthy dogs and should have been specific to the sampling methods used; otherwise, transference of the RIs must have been verified for each sampling method using 20 healthy dogs .…”

“…However, previous studies have demonstrated that tCa might not adequately reflect the ionized calcium status of dogs . There have been several attempts to create formulas to correct tCa and improve the prediction of ionized calcium . However, the older formulas are not currently recommended.…”

“…However, the older formulas are not currently recommended. Recently, Danner et al developed a new model, allowing the prediction of ionized calcium in dogs based on tCa value and other biochemistry and patient results . Although the predicted ionized calcium (piCa) value presented better positive predictive values and diagnostic likelihood ratios than tCa and corrected tCa to assess ionized calcium status, the use of this model has not been validated with the variables measured from multiple laboratories.…”