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Updated: Aug 27, 2025

A Semi-Automated and Reproducible Biological-Based Method to Quantify Calcium Deposition In Vitro
Published on: June 2, 2022
Factors influencing the derivation and clinical application of blood calcium adjustment equations
Georgia Conrich-Wilks1, Fiona Ivison2, Eric S Kilpatrick2
1Department of Medical Sciences, University of Manchester, Manchester, UK.
Insights
Simplified patient data exclusions for adjusted calcium (adjCa) equations do not significantly alter results. This finding supports easier implementation of local adjCa equations in laboratories.
Area of Science:
- Clinical Chemistry
- Biochemistry
- Laboratory Medicine
Background:
- Laboratories often derive local adjusted calcium (adjCa) equations using patient data and specific exclusion criteria to account for calcium metabolism abnormalities.
- The impact of these exclusion criteria on the final adjCa equation formula and patient results remains unclear.
- This study aimed to investigate how reducing exclusion criteria affects adjCa equations and patient outcomes compared to a reference equation.
Purpose of the Study:
- To evaluate the influence of varying exclusion criteria on the derivation of adjusted calcium (adjCa) equations.
- To compare adjCa equations derived with fewer exclusions against a reference equation.
- To assess the impact of different adjCa equations on patient categorization (hypo-, normo-, or hypercalcaemia).
Main Methods:
- A reference adjCa equation was established using data from 1305 individuals meeting strict exclusion criteria.
- Seven alternative adjCa equations were derived using progressively fewer exclusion criteria, including one with no exclusions.
- All derived equations were applied to a validation cohort of 19,640 patients to assess their effect on adjCa results and calcium status categorization.
Main Results:
- Most alternative adjCa equations, even those with no exclusions, showed no statistically significant difference in slope or intercept compared to the reference equation.
- No patient in the validation cohort exhibited a clinically significant difference (>5% and >0.1 mmol/L) in adjCa results when using alternative equations versus the reference.
- The categorization of patients' calcium status (hypo-, normo-, or hypercalcaemia) remained consistent across all tested adjCa equations.
Conclusions:
- The majority of exclusion criteria used in deriving adjCa equations have minimal impact on the equation itself or the resulting patient adjCa values.
- Even equations derived without any exclusions perform comparably to those with extensive criteria.
- These findings suggest that the process of developing local adjCa equations can be simplified, potentially facilitating wider adoption.
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.
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