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Development and Validation of a Prognostic Risk Score System for COVID-19 Inpatients: A Multi-Center Retrospective Study in China
Coronavirus disease 2019 (COVID-19) has become a worldwide pandemic. Hospitalized patients of COVID-19 suffer from a high mortality rate, motivating the development of convenient and practical methods that allow clinicians to promptly identify high-risk patients. Here, we have developed a risk score...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7695569/ https://www.ncbi.nlm.nih.gov/pubmed/33282444 http://dx.doi.org/10.1016/j.eng.2020.10.013 |
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author | Yuan, Ye Sun, Chuan Tang, Xiuchuan Cheng, Cheng Mombaerts, Laurent Wang, Maolin Hu, Tao Sun, Chenyu Guo, Yuqi Li, Xiuting Xu, Hui Ren, Tongxin Xiao, Yang Xiao, Yaru Zhu, Hongling Wu, Honghan Li, Kezhi Chen, Chuming Liu, Yingxia Liang, Zhichao Cao, Zhiguo Zhang, Hai-Tao Paschaldis, Ioannis Ch. Liu, Quanying Goncalves, Jorge Zhong, Qiang Yan, Li |
author_facet | Yuan, Ye Sun, Chuan Tang, Xiuchuan Cheng, Cheng Mombaerts, Laurent Wang, Maolin Hu, Tao Sun, Chenyu Guo, Yuqi Li, Xiuting Xu, Hui Ren, Tongxin Xiao, Yang Xiao, Yaru Zhu, Hongling Wu, Honghan Li, Kezhi Chen, Chuming Liu, Yingxia Liang, Zhichao Cao, Zhiguo Zhang, Hai-Tao Paschaldis, Ioannis Ch. Liu, Quanying Goncalves, Jorge Zhong, Qiang Yan, Li |
author_sort | Yuan, Ye |
collection | PubMed |
description | Coronavirus disease 2019 (COVID-19) has become a worldwide pandemic. Hospitalized patients of COVID-19 suffer from a high mortality rate, motivating the development of convenient and practical methods that allow clinicians to promptly identify high-risk patients. Here, we have developed a risk score using clinical data from 1479 inpatients admitted to Tongji Hospital, Wuhan, China (development cohort) and externally validated with data from two other centers: 141 inpatients from Jinyintan Hospital, Wuhan, China (validation cohort 1) and 432 inpatients from The Third People’s Hospital of Shenzhen, Shenzhen, China (validation cohort 2). The risk score is based on three biomarkers that are readily available in routine blood samples and can easily be translated into a probability of death. The risk score can predict the mortality of individual patients more than 12 d in advance with more than 90% accuracy across all cohorts. Moreover, the Kaplan–Meier score shows that patients can be clearly differentiated upon admission as low, intermediate, or high risk, with an area under the curve (AUC) score of 0.9551. In summary, a simple risk score has been validated to predict death in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); it has also been validated in independent cohorts. |
format | Online Article Text |
id | pubmed-7695569 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company. |
record_format | MEDLINE/PubMed |
spelling | pubmed-76955692020-12-01 Development and Validation of a Prognostic Risk Score System for COVID-19 Inpatients: A Multi-Center Retrospective Study in China Yuan, Ye Sun, Chuan Tang, Xiuchuan Cheng, Cheng Mombaerts, Laurent Wang, Maolin Hu, Tao Sun, Chenyu Guo, Yuqi Li, Xiuting Xu, Hui Ren, Tongxin Xiao, Yang Xiao, Yaru Zhu, Hongling Wu, Honghan Li, Kezhi Chen, Chuming Liu, Yingxia Liang, Zhichao Cao, Zhiguo Zhang, Hai-Tao Paschaldis, Ioannis Ch. Liu, Quanying Goncalves, Jorge Zhong, Qiang Yan, Li Engineering (Beijing) Research Coronavirus Disease 2019—Article Coronavirus disease 2019 (COVID-19) has become a worldwide pandemic. Hospitalized patients of COVID-19 suffer from a high mortality rate, motivating the development of convenient and practical methods that allow clinicians to promptly identify high-risk patients. Here, we have developed a risk score using clinical data from 1479 inpatients admitted to Tongji Hospital, Wuhan, China (development cohort) and externally validated with data from two other centers: 141 inpatients from Jinyintan Hospital, Wuhan, China (validation cohort 1) and 432 inpatients from The Third People’s Hospital of Shenzhen, Shenzhen, China (validation cohort 2). The risk score is based on three biomarkers that are readily available in routine blood samples and can easily be translated into a probability of death. The risk score can predict the mortality of individual patients more than 12 d in advance with more than 90% accuracy across all cohorts. Moreover, the Kaplan–Meier score shows that patients can be clearly differentiated upon admission as low, intermediate, or high risk, with an area under the curve (AUC) score of 0.9551. In summary, a simple risk score has been validated to predict death in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); it has also been validated in independent cohorts. THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company. 2022-01 2020-11-28 /pmc/articles/PMC7695569/ /pubmed/33282444 http://dx.doi.org/10.1016/j.eng.2020.10.013 Text en © 2020 THE AUTHORS Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Research Coronavirus Disease 2019—Article Yuan, Ye Sun, Chuan Tang, Xiuchuan Cheng, Cheng Mombaerts, Laurent Wang, Maolin Hu, Tao Sun, Chenyu Guo, Yuqi Li, Xiuting Xu, Hui Ren, Tongxin Xiao, Yang Xiao, Yaru Zhu, Hongling Wu, Honghan Li, Kezhi Chen, Chuming Liu, Yingxia Liang, Zhichao Cao, Zhiguo Zhang, Hai-Tao Paschaldis, Ioannis Ch. Liu, Quanying Goncalves, Jorge Zhong, Qiang Yan, Li Development and Validation of a Prognostic Risk Score System for COVID-19 Inpatients: A Multi-Center Retrospective Study in China |
title | Development and Validation of a Prognostic Risk Score System for COVID-19 Inpatients: A Multi-Center Retrospective Study in China |
title_full | Development and Validation of a Prognostic Risk Score System for COVID-19 Inpatients: A Multi-Center Retrospective Study in China |
title_fullStr | Development and Validation of a Prognostic Risk Score System for COVID-19 Inpatients: A Multi-Center Retrospective Study in China |
title_full_unstemmed | Development and Validation of a Prognostic Risk Score System for COVID-19 Inpatients: A Multi-Center Retrospective Study in China |
title_short | Development and Validation of a Prognostic Risk Score System for COVID-19 Inpatients: A Multi-Center Retrospective Study in China |
title_sort | development and validation of a prognostic risk score system for covid-19 inpatients: a multi-center retrospective study in china |
topic | Research Coronavirus Disease 2019—Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7695569/ https://www.ncbi.nlm.nih.gov/pubmed/33282444 http://dx.doi.org/10.1016/j.eng.2020.10.013 |
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