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Development and validation of prognostic model for predicting mortality of COVID-19 patients in Wuhan, China
Novel coronavirus 2019 (COVID-19) infection is a global public health issue, that has now affected more than 200 countries worldwide and caused a second wave of pandemic. Severe adult respiratory syndrome-CoV-2 (SARS-CoV-2) pneumonia is associated with a high risk of mortality. However, prognostic f...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775455/ https://www.ncbi.nlm.nih.gov/pubmed/33384422 http://dx.doi.org/10.1038/s41598-020-78870-6 |
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author | Mei, Qi Wang, Amanda Y. Bryant, Amy Yang, Yang Li, Ming Wang, Fei Zhao, Jia Wei Ma, Ke Wu, Liang Chen, Huawen Luo, Jinlong Du, Shangming Halfter, Kathrin Li, Yong Kurts, Christian Hu, Guangyuan Yuan, Xianglin Li, Jian |
author_facet | Mei, Qi Wang, Amanda Y. Bryant, Amy Yang, Yang Li, Ming Wang, Fei Zhao, Jia Wei Ma, Ke Wu, Liang Chen, Huawen Luo, Jinlong Du, Shangming Halfter, Kathrin Li, Yong Kurts, Christian Hu, Guangyuan Yuan, Xianglin Li, Jian |
author_sort | Mei, Qi |
collection | PubMed |
description | Novel coronavirus 2019 (COVID-19) infection is a global public health issue, that has now affected more than 200 countries worldwide and caused a second wave of pandemic. Severe adult respiratory syndrome-CoV-2 (SARS-CoV-2) pneumonia is associated with a high risk of mortality. However, prognostic factors predicting poor clinical outcomes of individual patients with SARS-CoV-2 pneumonia remain under intensive investigation. We conducted a retrospective, multicenter study of patients with SARS-CoV-2 who were admitted to four hospitals in Wuhan, China from December 2019 to February 2020. Mortality at the end of the follow up period was the primary outcome. Factors predicting mortality were also assessed and a prognostic model was developed, calibrated and validated. The study included 492 patients with SARS-CoV-2 who were divided into three cohorts: the training cohort (n = 237), the validation cohort 1 (n = 120), and the validation cohort 2 (n = 135). Multivariate analysis showed that five clinical parameters were predictive of mortality at the end of follow up period, including advanced age [odds ratio (OR), 1.1/years increase (p < 0.001)], increased neutrophil-to-lymphocyte ratio [(NLR) OR, 1.14/increase (p < 0.001)], elevated body temperature on admission [OR, 1.53/°C increase (p = 0.005)], increased aspartate transaminase [OR, 2.47 (p = 0.019)], and decreased total protein [OR, 1.69 (p = 0.018)]. Furthermore, the prognostic model drawn from the training cohort was validated with validation cohorts 1 and 2 with comparable area under curves (AUC) at 0.912, 0.928, and 0.883, respectively. While individual survival probabilities were assessed, the model yielded a Harrell’s C index of 0.758 for the training cohort, 0.762 for the validation cohort 1, and 0.711 for the validation cohort 2, which were comparable among each other. A validated prognostic model was developed to assist in determining the clinical prognosis for SARS-CoV-2 pneumonia. Using this established model, individual patients categorized in the high risk group were associated with an increased risk of mortality, whereas patients predicted to be in the low risk group had a higher probability of survival. |
format | Online Article Text |
id | pubmed-7775455 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-77754552021-01-07 Development and validation of prognostic model for predicting mortality of COVID-19 patients in Wuhan, China Mei, Qi Wang, Amanda Y. Bryant, Amy Yang, Yang Li, Ming Wang, Fei Zhao, Jia Wei Ma, Ke Wu, Liang Chen, Huawen Luo, Jinlong Du, Shangming Halfter, Kathrin Li, Yong Kurts, Christian Hu, Guangyuan Yuan, Xianglin Li, Jian Sci Rep Article Novel coronavirus 2019 (COVID-19) infection is a global public health issue, that has now affected more than 200 countries worldwide and caused a second wave of pandemic. Severe adult respiratory syndrome-CoV-2 (SARS-CoV-2) pneumonia is associated with a high risk of mortality. However, prognostic factors predicting poor clinical outcomes of individual patients with SARS-CoV-2 pneumonia remain under intensive investigation. We conducted a retrospective, multicenter study of patients with SARS-CoV-2 who were admitted to four hospitals in Wuhan, China from December 2019 to February 2020. Mortality at the end of the follow up period was the primary outcome. Factors predicting mortality were also assessed and a prognostic model was developed, calibrated and validated. The study included 492 patients with SARS-CoV-2 who were divided into three cohorts: the training cohort (n = 237), the validation cohort 1 (n = 120), and the validation cohort 2 (n = 135). Multivariate analysis showed that five clinical parameters were predictive of mortality at the end of follow up period, including advanced age [odds ratio (OR), 1.1/years increase (p < 0.001)], increased neutrophil-to-lymphocyte ratio [(NLR) OR, 1.14/increase (p < 0.001)], elevated body temperature on admission [OR, 1.53/°C increase (p = 0.005)], increased aspartate transaminase [OR, 2.47 (p = 0.019)], and decreased total protein [OR, 1.69 (p = 0.018)]. Furthermore, the prognostic model drawn from the training cohort was validated with validation cohorts 1 and 2 with comparable area under curves (AUC) at 0.912, 0.928, and 0.883, respectively. While individual survival probabilities were assessed, the model yielded a Harrell’s C index of 0.758 for the training cohort, 0.762 for the validation cohort 1, and 0.711 for the validation cohort 2, which were comparable among each other. A validated prognostic model was developed to assist in determining the clinical prognosis for SARS-CoV-2 pneumonia. Using this established model, individual patients categorized in the high risk group were associated with an increased risk of mortality, whereas patients predicted to be in the low risk group had a higher probability of survival. Nature Publishing Group UK 2020-12-31 /pmc/articles/PMC7775455/ /pubmed/33384422 http://dx.doi.org/10.1038/s41598-020-78870-6 Text en © 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/. |
spellingShingle | Article Mei, Qi Wang, Amanda Y. Bryant, Amy Yang, Yang Li, Ming Wang, Fei Zhao, Jia Wei Ma, Ke Wu, Liang Chen, Huawen Luo, Jinlong Du, Shangming Halfter, Kathrin Li, Yong Kurts, Christian Hu, Guangyuan Yuan, Xianglin Li, Jian Development and validation of prognostic model for predicting mortality of COVID-19 patients in Wuhan, China |
title | Development and validation of prognostic model for predicting mortality of COVID-19 patients in Wuhan, China |
title_full | Development and validation of prognostic model for predicting mortality of COVID-19 patients in Wuhan, China |
title_fullStr | Development and validation of prognostic model for predicting mortality of COVID-19 patients in Wuhan, China |
title_full_unstemmed | Development and validation of prognostic model for predicting mortality of COVID-19 patients in Wuhan, China |
title_short | Development and validation of prognostic model for predicting mortality of COVID-19 patients in Wuhan, China |
title_sort | development and validation of prognostic model for predicting mortality of covid-19 patients in wuhan, china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775455/ https://www.ncbi.nlm.nih.gov/pubmed/33384422 http://dx.doi.org/10.1038/s41598-020-78870-6 |
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