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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Detalles Bibliográficos
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:
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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
Descripción
Sumario: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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