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Predicting Illness Severity and Short-Term Outcomes of COVID-19: A Retrospective Cohort Study in China

Among 417 COVID-19 patients in Shenzhen, demographic characteristics, clinical manifestations and baseline laboratory tests showed significant differences between mild-moderate cohort and severe-critical cohort.Based on these differences, a convenient mathematical model was established to predict th...

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Autores principales: Chen, Chuming, Wang, Haihui, Liang, Zhichao, Peng, Ling, Zhao, Fang, Yang, Liuqing, Cao, Mengli, Wu, Weibo, Jiang, Xiao, Zhang, Peiyan, Li, Yinfeng, Chen, Li, Feng, Shiyan, Li, Jianming, Meng, Lingxiang, Wu, Huishan, Wang, Fuxiang, Liu, Quanying, Liu, Yingxia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7237911/
https://www.ncbi.nlm.nih.gov/pubmed/33554186
http://dx.doi.org/10.1016/j.xinn.2020.04.007
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author Chen, Chuming
Wang, Haihui
Liang, Zhichao
Peng, Ling
Zhao, Fang
Yang, Liuqing
Cao, Mengli
Wu, Weibo
Jiang, Xiao
Zhang, Peiyan
Li, Yinfeng
Chen, Li
Feng, Shiyan
Li, Jianming
Meng, Lingxiang
Wu, Huishan
Wang, Fuxiang
Liu, Quanying
Liu, Yingxia
author_facet Chen, Chuming
Wang, Haihui
Liang, Zhichao
Peng, Ling
Zhao, Fang
Yang, Liuqing
Cao, Mengli
Wu, Weibo
Jiang, Xiao
Zhang, Peiyan
Li, Yinfeng
Chen, Li
Feng, Shiyan
Li, Jianming
Meng, Lingxiang
Wu, Huishan
Wang, Fuxiang
Liu, Quanying
Liu, Yingxia
author_sort Chen, Chuming
collection PubMed
description Among 417 COVID-19 patients in Shenzhen, demographic characteristics, clinical manifestations and baseline laboratory tests showed significant differences between mild-moderate cohort and severe-critical cohort.Based on these differences, a convenient mathematical model was established to predict the illness severity of COVID-19. The model includes four parameters: age, BMI, CD4(+) lymphocytes and IL-6 levels. The AUC of the model is 0.911.The high risk factors for developing to severe COVID-19 are: age ≥ 55 years, BMI > 27 kg / m(2), IL-6 ≥ 20 pg / ml, CD4(+) T cell ≤ 400 count / μ L.Among 249 discharged COVID-19 patients, those who recovered after 20 days had a lower count of platelet, a higher level of estimated glomerular filtration rate, and higher level of interleukin-6 and myoglobin than those who recovered within 20 days.
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spelling pubmed-72379112020-05-20 Predicting Illness Severity and Short-Term Outcomes of COVID-19: A Retrospective Cohort Study in China Chen, Chuming Wang, Haihui Liang, Zhichao Peng, Ling Zhao, Fang Yang, Liuqing Cao, Mengli Wu, Weibo Jiang, Xiao Zhang, Peiyan Li, Yinfeng Chen, Li Feng, Shiyan Li, Jianming Meng, Lingxiang Wu, Huishan Wang, Fuxiang Liu, Quanying Liu, Yingxia Innovation (Camb) Report Among 417 COVID-19 patients in Shenzhen, demographic characteristics, clinical manifestations and baseline laboratory tests showed significant differences between mild-moderate cohort and severe-critical cohort.Based on these differences, a convenient mathematical model was established to predict the illness severity of COVID-19. The model includes four parameters: age, BMI, CD4(+) lymphocytes and IL-6 levels. The AUC of the model is 0.911.The high risk factors for developing to severe COVID-19 are: age ≥ 55 years, BMI > 27 kg / m(2), IL-6 ≥ 20 pg / ml, CD4(+) T cell ≤ 400 count / μ L.Among 249 discharged COVID-19 patients, those who recovered after 20 days had a lower count of platelet, a higher level of estimated glomerular filtration rate, and higher level of interleukin-6 and myoglobin than those who recovered within 20 days. Elsevier 2020-04-22 /pmc/articles/PMC7237911/ /pubmed/33554186 http://dx.doi.org/10.1016/j.xinn.2020.04.007 Text en © 2020 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Report
Chen, Chuming
Wang, Haihui
Liang, Zhichao
Peng, Ling
Zhao, Fang
Yang, Liuqing
Cao, Mengli
Wu, Weibo
Jiang, Xiao
Zhang, Peiyan
Li, Yinfeng
Chen, Li
Feng, Shiyan
Li, Jianming
Meng, Lingxiang
Wu, Huishan
Wang, Fuxiang
Liu, Quanying
Liu, Yingxia
Predicting Illness Severity and Short-Term Outcomes of COVID-19: A Retrospective Cohort Study in China
title Predicting Illness Severity and Short-Term Outcomes of COVID-19: A Retrospective Cohort Study in China
title_full Predicting Illness Severity and Short-Term Outcomes of COVID-19: A Retrospective Cohort Study in China
title_fullStr Predicting Illness Severity and Short-Term Outcomes of COVID-19: A Retrospective Cohort Study in China
title_full_unstemmed Predicting Illness Severity and Short-Term Outcomes of COVID-19: A Retrospective Cohort Study in China
title_short Predicting Illness Severity and Short-Term Outcomes of COVID-19: A Retrospective Cohort Study in China
title_sort predicting illness severity and short-term outcomes of covid-19: a retrospective cohort study in china
topic Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7237911/
https://www.ncbi.nlm.nih.gov/pubmed/33554186
http://dx.doi.org/10.1016/j.xinn.2020.04.007
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