Factors influencing the derivation and clinical application of blood calcium adjustment equations. (January 2023)

• Record Type: Journal Article
• Authors: Conrich-Wilks, Georgia; Ivison, Fiona; Kilpatrick, Eric S
• Is Part Of: Annals of clinical biochemistry. Volume 60:Number 1(2023)
• Page Start: 54
• Page End: 62
• Publication Date: 2023-01
• Subjects: Adjusted calcium -- calcium status -- calcium metabolism; Clinical chemistry -- Periodicals; Clinical biochemistry -- Periodicals; 616.075
• DOI: 10.1177/00045632221131673
• Languages: English
• ISSNs: 0004-5632

Abstract

Background: Laboratories are recommended to use patient data to derive their local adjusted calcium (adjCa) equation, using numerous criteria to exclude patients with potential calcium metabolism abnormalities. It is not known which, if any, of the exclusions influence the final equation formula, or to what extent. This study investigated the effect using fewer exclusions has on adjCa equations and on patient results when compared to a reference equation. Methods: A reference ACB adjCa equation was derived from the total calcium and albumin pairs of 1305 individuals who, from an initial 22, 906 adults, met recommended criteria (excluding abnormalities in either calcium, albumin, creatinine, magnesium, ALP or ALT, and specific clinical areas). This reference equation was compared to seven alternatives derived using fewer criteria, including one with no exclusions. All equations were applied to a validation cohort ( n =19, 640) to determine their effect on adjCa results and on categorizing patients into hypo-, normo- or hypercalcaemia. Results: Most alternative adjCa equations, including the one without any exclusions, showed no statistical ( p < 0.05) difference in their slope or intercept compared to the ACB reference. Nor did any of the validation cohort have a clinically significantly different adjCa result (>5% and >0.1 mmol/L different) when applying an alternative rather than the reference equation. Additionally, no alternative equation changed the kappa categorization of the validation population's calcium status. Conclusions: When deriving adjCa equations, most exclusion criteria have little influence on the equation or patient results, including using none at all. This knowledge could simplify deployment of local equations.