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. 2021 Feb 15;21:176. doi: 10.1186/s12879-021-05856-8

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© The Author(s) 2021

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 5 — The discriminative power and calibration of the nomogram for predicting critical type in COVID-19 patients. a: A nomogram, containing LDH, D-dimer, PE and TBIL was created to predict critical type of COVID-19. b: The predicted probabilities by nomogram were coincident with the actual outcomes, indicating the calibration of the nomogram was good. c: decision curve analysis (DCA) highlighted the clinical utility of the nomogram. d: ROC curve exhibited good discriminative power (AUC = 0.817) for predicting critical type of COVID-19