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CIRPMC: An online model with simplified inflammatory signature to predict the occurrence of critical illness in patients with COVID-19.

作者信息

Gao Yue, Chen Lingxi, Zeng Shaoqing, Feng Xikang, Chi JianHua, Wang Ya, Li Huayi, Jiang Tengping, Yu Yang, Jiao XiaoFei, Liu Dan, Feng XinXia, Wang SiYuan, Yu RuiDi, Yuan Yuan, Xu Sen, Cai Guangyao, Xiong Xiaoming, Chen Pingbo, Mo Qingqing, Jin Xin, Wu Yuan, Ma Ding, Li Chunrui, Li Shuai Cheng, Gao Qinglei

机构信息

National Medical Center for Major Public Health Events, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.

Cancer Biology Research Center (Key Laboratory of Chinese Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.

出版信息

Clin Transl Med. 2020 Oct;10(6):e210. doi: 10.1002/ctm2.210.

DOI:10.1002/ctm2.210
PMID:33135353
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7577323/
Abstract
摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8a/7577323/3ad4854af090/CTM2-10-e210-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8a/7577323/537a09568846/CTM2-10-e210-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8a/7577323/c202816503b3/CTM2-10-e210-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8a/7577323/3ad4854af090/CTM2-10-e210-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8a/7577323/537a09568846/CTM2-10-e210-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8a/7577323/c202816503b3/CTM2-10-e210-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8a/7577323/3ad4854af090/CTM2-10-e210-g003.jpg

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本文引用的文献

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Machine learning-based CT radiomics method for predicting hospital stay in patients with pneumonia associated with SARS-CoV-2 infection: a multicenter study.基于机器学习的CT影像组学方法预测新型冠状病毒肺炎患者住院时间:一项多中心研究
Ann Transl Med. 2020 Jul;8(14):859. doi: 10.21037/atm-20-3026.
2
Clinical characteristics and risk factors associated with COVID-19 disease severity in patients with cancer in Wuhan, China: a multicentre, retrospective, cohort study.中国武汉癌症患者 COVID-19 疾病严重程度相关的临床特征和危险因素:一项多中心、回顾性、队列研究。
Lancet Oncol. 2020 Jul;21(7):893-903. doi: 10.1016/S1470-2045(20)30309-0. Epub 2020 May 29.
3
如何将新冠病毒的知识转化为对奥密克戎变异株的预防。
Clin Transl Med. 2021 Dec;11(12):e680. doi: 10.1002/ctm2.680.
4
[Blood viscosity in COVID-19 patients with sudden deafness].[新型冠状病毒肺炎合并突发性耳聋患者的血液黏度]
Acta Otorrinolaringol Esp. 2022 Mar-Apr;73(2):104-112. doi: 10.1016/j.otorri.2021.07.001. Epub 2021 Jul 15.
Longitudinal hematologic and immunologic variations associated with the progression of COVID-19 patients in China.
中国 COVID-19 患者病情进展相关的纵向血液学和免疫学变化。
J Allergy Clin Immunol. 2020 Jul;146(1):89-100. doi: 10.1016/j.jaci.2020.05.003. Epub 2020 May 11.
4
Pathological inflammation in patients with COVID-19: a key role for monocytes and macrophages.COVID-19 患者的病理性炎症:单核细胞和巨噬细胞的关键作用。
Nat Rev Immunol. 2020 Jun;20(6):355-362. doi: 10.1038/s41577-020-0331-4. Epub 2020 May 6.
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