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. 2024 Feb 5;28(1):e12–e21. doi: 10.1055/s-0043-1777450

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The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution 4.0 International License, permitting copying and reproduction so long as the original work is given appropriate credit ( https://creativecommons.org/licenses/by/4.0/ )

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Fig. 3 — ROC curves of correlations between calcium correction formulas and symptomatic hypocalcemia. ( A ) The Clase correction formula predicts the development of symptomatic hypocalcemia with a sensitivity of 65.26% and specificity of 89.91% at the cut-off value of ≤1,801 mmol/L (ROC analysis; AUC 0.751; 95% CI 0.686–0.809; P value <0.0001). ( B ) The Jain correction formula predicts the development of symptomatic hypocalcemia with a sensitivity of 65.26% and a specificity of 89.91% at a cut-off value of ≤1.847 mmol/L (ROC analysis; AUC 0.756; 95% CI 0.691–0.814; P value <0.0001). ( C ) The Payne correction formula predicts the development of symptomatic hypocalcemia with a sensitivity of 63.16% and specificity of 88.99% at a cut-off value of ≤1.8525 mmol/L (ROC analysis; AUC 0.746; 95% CI 0.680–0.804; P value <0.0001). ( D ) The Ridefelt correction formula predicts the development of symptomatic hypocalcemia with a sensitivity of 66.32% and a specificity of 88.99% at a cut-off value of ≤1.8426 mmol/L (ROC analysis; AUC 0.753; 95% CI 0.688–0.811; P value <0.0001).