Predicting ionized hypocalcemia: External validation of an ionized calcium prediction model in patients with COVID-19 and renal failure.

BACKGROUND

Ionized hypocalcemia is common in critically ill patients with COVID-19 and is associated with adverse outcomes. We previously developed a linear model that estimates ionized calcium (I) by adjusting total calcium (T) for the three components of the anion gap and albumin. On internal validation, it outperformed the popular method that corrects T for albumin alone (cT) in diagnosing low I. In this study, we sought to externally validate our I model in hospitalized COVID-19 positive patients.

METHODS

We retrospectively studied all 200 patients with COVID-19 who were admitted to the State University of New York Downstate Medical Center between March 11 and April 30 2020 and referred to the nephrology service for renal failure, and who had I measured on a venous blood gas within 25 min of a comprehensive metabolic panel. We compared the performance of the I model and cT in diagnosing low I by ROC analysis, and also examined the accuracy of the absolute values predicted by the two methods relative to measured I.

RESULTS

On ROC analysis, the I model was better than cT (area under ROC curve: 0.872 [0.025] vs. 0.835 [0.028]; = 0.045). The I model estimated I accurately, but the cT method seemed to overcorrect T as a substantial number of patients with clearly normal cT values had low I.

CONCLUSIONS

In an external validation cohort, the I model estimated I accurately and was better than cT in the diagnosis of low I. This finding can be useful in guiding direct I testing.