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Early prediction of disease progression in COVID-19 pneumonia patients with chest CT and clinical characteristics
The outbreak of coronavirus disease 2019 (COVID-19) has rapidly spread to become a worldwide emergency. Early identification of patients at risk of progression may facilitate more individually aligned treatment plans and optimized utilization of medical resource. Here we conducted a multicenter retr...
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/PMC7532528/ https://www.ncbi.nlm.nih.gov/pubmed/33009413 http://dx.doi.org/10.1038/s41467-020-18786-x |
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author | Feng, Zhichao Yu, Qizhi Yao, Shanhu Luo, Lei Zhou, Wenming Mao, Xiaowen Li, Jennifer Duan, Junhong Yan, Zhimin Yang, Min Tan, Hongpei Ma, Mengtian Li, Ting Yi, Dali Mi, Ze Zhao, Huafei Jiang, Yi He, Zhenhu Li, Huiling Nie, Wei Liu, Yin Zhao, Jing Luo, Muqing Liu, Xuanhui Rong, Pengfei Wang, Wei |
author_facet | Feng, Zhichao Yu, Qizhi Yao, Shanhu Luo, Lei Zhou, Wenming Mao, Xiaowen Li, Jennifer Duan, Junhong Yan, Zhimin Yang, Min Tan, Hongpei Ma, Mengtian Li, Ting Yi, Dali Mi, Ze Zhao, Huafei Jiang, Yi He, Zhenhu Li, Huiling Nie, Wei Liu, Yin Zhao, Jing Luo, Muqing Liu, Xuanhui Rong, Pengfei Wang, Wei |
author_sort | Feng, Zhichao |
collection | PubMed |
description | The outbreak of coronavirus disease 2019 (COVID-19) has rapidly spread to become a worldwide emergency. Early identification of patients at risk of progression may facilitate more individually aligned treatment plans and optimized utilization of medical resource. Here we conducted a multicenter retrospective study involving patients with moderate COVID-19 pneumonia to investigate the utility of chest computed tomography (CT) and clinical characteristics to risk-stratify the patients. Our results show that CT severity score is associated with inflammatory levels and that older age, higher neutrophil-to-lymphocyte ratio (NLR), and CT severity score on admission are independent risk factors for short-term progression. The nomogram based on these risk factors shows good calibration and discrimination in the derivation and validation cohorts. These findings have implications for predicting the progression risk of COVID-19 pneumonia patients at the time of admission. CT examination may help risk-stratification and guide the timing of admission. |
format | Online Article Text |
id | pubmed-7532528 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-75325282020-10-19 Early prediction of disease progression in COVID-19 pneumonia patients with chest CT and clinical characteristics Feng, Zhichao Yu, Qizhi Yao, Shanhu Luo, Lei Zhou, Wenming Mao, Xiaowen Li, Jennifer Duan, Junhong Yan, Zhimin Yang, Min Tan, Hongpei Ma, Mengtian Li, Ting Yi, Dali Mi, Ze Zhao, Huafei Jiang, Yi He, Zhenhu Li, Huiling Nie, Wei Liu, Yin Zhao, Jing Luo, Muqing Liu, Xuanhui Rong, Pengfei Wang, Wei Nat Commun Article The outbreak of coronavirus disease 2019 (COVID-19) has rapidly spread to become a worldwide emergency. Early identification of patients at risk of progression may facilitate more individually aligned treatment plans and optimized utilization of medical resource. Here we conducted a multicenter retrospective study involving patients with moderate COVID-19 pneumonia to investigate the utility of chest computed tomography (CT) and clinical characteristics to risk-stratify the patients. Our results show that CT severity score is associated with inflammatory levels and that older age, higher neutrophil-to-lymphocyte ratio (NLR), and CT severity score on admission are independent risk factors for short-term progression. The nomogram based on these risk factors shows good calibration and discrimination in the derivation and validation cohorts. These findings have implications for predicting the progression risk of COVID-19 pneumonia patients at the time of admission. CT examination may help risk-stratification and guide the timing of admission. Nature Publishing Group UK 2020-10-02 /pmc/articles/PMC7532528/ /pubmed/33009413 http://dx.doi.org/10.1038/s41467-020-18786-x 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Feng, Zhichao Yu, Qizhi Yao, Shanhu Luo, Lei Zhou, Wenming Mao, Xiaowen Li, Jennifer Duan, Junhong Yan, Zhimin Yang, Min Tan, Hongpei Ma, Mengtian Li, Ting Yi, Dali Mi, Ze Zhao, Huafei Jiang, Yi He, Zhenhu Li, Huiling Nie, Wei Liu, Yin Zhao, Jing Luo, Muqing Liu, Xuanhui Rong, Pengfei Wang, Wei Early prediction of disease progression in COVID-19 pneumonia patients with chest CT and clinical characteristics |
title | 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_short | 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 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7532528/ https://www.ncbi.nlm.nih.gov/pubmed/33009413 http://dx.doi.org/10.1038/s41467-020-18786-x |
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