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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...

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Autores principales: 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
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
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.
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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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