Title: 2017 ACVIM Forum Research Abstract Program Document date: 2017_6_15
ID: ri2w5iby_250
Snippet: In dogs with increased or decreased tCa, a multivariate adaptive regression splines model was used to predict miCa from creatinine, albumin, tCa, phosphorus, sodium, potassium, chloride, alkaline phosphatase (ALP), triglycerides, and age. Sensitivity and specificity of predicted ionized calcium (piCa) were compared to those of corrected tCa for true hyper/hypocalcemia (McNemar's test). The impact of missing biochemistry values on predictive model.....
Document: In dogs with increased or decreased tCa, a multivariate adaptive regression splines model was used to predict miCa from creatinine, albumin, tCa, phosphorus, sodium, potassium, chloride, alkaline phosphatase (ALP), triglycerides, and age. Sensitivity and specificity of predicted ionized calcium (piCa) were compared to those of corrected tCa for true hyper/hypocalcemia (McNemar's test). The impact of missing biochemistry values on predictive model accuracy was assessed by replacing missing biochemistry variables by their mid-reference interval value. Accuracy was considered altered if piCa became significantly different from miCa (Wilcoxon test).
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