Derivation and validation of a prognostic model for predicting in-hospital mortality in patients admitted with COVID-19
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RESEARCH ARTICLE
Open Access
Derivation and validation of a prognostic model for predicting in-hospital mortality in patients admitted with COVID-19 in Wuhan, China: the PLANS (platelet lymphocyte age neutrophil sex) model Jiong Li1†, Yuntao Chen2†, Shujing Chen3†, Sihua Wang4, Dingyu Zhang5, Junfeng Wang6, Douwe Postmus2, Hesong Zeng7, Guoyou Qin8, Yin Shen9*, Jinjun Jiang3* and Yongfu Yu8*
Abstract Background: Previous published prognostic models for COVID-19 patients have been suggested to be prone to bias due to unrepresentativeness of patient population, lack of external validation, inappropriate statistical analyses, or poor reporting. A high-quality and easy-to-use prognostic model to predict in-hospital mortality for COVID-19 patients could support physicians to make better clinical decisions. Methods: Fine-Gray models were used to derive a prognostic model to predict in-hospital mortality (treating discharged alive from hospital as the competing event) in COVID-19 patients using two retrospective cohorts (n = 1008) in Wuhan, China from January 1 to February 10, 2020. The proposed model was internally evaluated by bootstrap approach and externally evaluated in an external cohort (n = 1031). (Continued on next page)
* Correspondence: [email protected]; [email protected]; [email protected] † Jiong Li, Yuntao Chen and Shujing Chen contributed equally to this work. 9 Eye Center, Medical Research Institute, Wuhan University Renmin Hospital, Wuhan University, Wuhan, China 3 Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China 8 Department of Biostatistics, School of Public Health, and The Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China Full list of author information is available at the end of the article © The Author(s). 2020 Open Access This 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.
Li et al. BMC Infectious Diseases
(2020) 20:959
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Results: The derivation cohort
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