Early prediction of disease progression in COVID-19 pneumonia patients with chest CT and clinical characteristics

Early identification of COVID-19 patients at risk of progression may facilitate more individually aligned treatment plans. Here the authors develop an online nomogram incorporating CT severity score and clinical characteristics for early predicting the disease progression risk among COVID-19 pneumon...

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Autores principales:	Zhichao Feng, Qizhi Yu, Shanhu Yao, Lei Luo, Wenming Zhou, Xiaowen Mao, Jennifer Li, Junhong Duan, Zhimin Yan, Min Yang, Hongpei Tan, Mengtian Ma, Ting Li, Dali Yi, Ze Mi, Huafei Zhao, Yi Jiang, Zhenhu He, Huiling Li, Wei Nie, Yin Liu, Jing Zhao, Muqing Luo, Xuanhui Liu, Pengfei Rong, Wei Wang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/8a311c85bc0a4ba896ced8d4511c5331
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spelling	oai:doaj.org-article:8a311c85bc0a4ba896ced8d4511c53312021-12-02T17:37:42ZEarly prediction of disease progression in COVID-19 pneumonia patients with chest CT and clinical characteristics10.1038/s41467-020-18786-x2041-1723https://doaj.org/article/8a311c85bc0a4ba896ced8d4511c53312020-10-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-18786-xhttps://doaj.org/toc/2041-1723Early identification of COVID-19 patients at risk of progression may facilitate more individually aligned treatment plans. Here the authors develop an online nomogram incorporating CT severity score and clinical characteristics for early predicting the disease progression risk among COVID-19 pneumonia patients.Zhichao FengQizhi YuShanhu YaoLei LuoWenming ZhouXiaowen MaoJennifer LiJunhong DuanZhimin YanMin YangHongpei TanMengtian MaTing LiDali YiZe MiHuafei ZhaoYi JiangZhenhu HeHuiling LiWei NieYin LiuJing ZhaoMuqing LuoXuanhui LiuPengfei RongWei WangNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-9 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Zhichao Feng Qizhi Yu Shanhu Yao Lei Luo Wenming Zhou Xiaowen Mao Jennifer Li Junhong Duan Zhimin Yan Min Yang Hongpei Tan Mengtian Ma Ting Li Dali Yi Ze Mi Huafei Zhao Yi Jiang Zhenhu He Huiling Li Wei Nie Yin Liu Jing Zhao Muqing Luo Xuanhui Liu Pengfei Rong Wei Wang Early prediction of disease progression in COVID-19 pneumonia patients with chest CT and clinical characteristics
description	Early identification of COVID-19 patients at risk of progression may facilitate more individually aligned treatment plans. Here the authors develop an online nomogram incorporating CT severity score and clinical characteristics for early predicting the disease progression risk among COVID-19 pneumonia patients.
format	article
author	Zhichao Feng Qizhi Yu Shanhu Yao Lei Luo Wenming Zhou Xiaowen Mao Jennifer Li Junhong Duan Zhimin Yan Min Yang Hongpei Tan Mengtian Ma Ting Li Dali Yi Ze Mi Huafei Zhao Yi Jiang Zhenhu He Huiling Li Wei Nie Yin Liu Jing Zhao Muqing Luo Xuanhui Liu Pengfei Rong Wei Wang
author_facet	Zhichao Feng Qizhi Yu Shanhu Yao Lei Luo Wenming Zhou Xiaowen Mao Jennifer Li Junhong Duan Zhimin Yan Min Yang Hongpei Tan Mengtian Ma Ting Li Dali Yi Ze Mi Huafei Zhao Yi Jiang Zhenhu He Huiling Li Wei Nie Yin Liu Jing Zhao Muqing Luo Xuanhui Liu Pengfei Rong Wei Wang
author_sort	Zhichao Feng
title	Early prediction of disease progression in COVID-19 pneumonia patients with chest CT and clinical characteristics
title_short	Early prediction of disease progression in COVID-19 pneumonia patients with chest CT and clinical characteristics
title_full	Early prediction of disease progression in COVID-19 pneumonia patients with chest CT and clinical characteristics
title_fullStr	Early prediction of disease progression in COVID-19 pneumonia patients with chest CT and clinical characteristics
title_full_unstemmed	Early prediction of disease progression in COVID-19 pneumonia patients with chest CT and clinical characteristics
title_sort	early prediction of disease progression in covid-19 pneumonia patients with chest ct and clinical characteristics
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/8a311c85bc0a4ba896ced8d4511c5331
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Early prediction of disease progression in COVID-19 pneumonia patients with chest CT and clinical characteristics

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