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 Position: Home > Editorial  
Predicting Illness Severity and Short-term Outcomes of COVID-19: A Retrospective Cohort Study in China
EditorInnovation   Time2020/5/21


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 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 mathematical model was established to predict the illness severity of COVID-19. The model includes four variables: age, BMI, CD4+ lymphocytes and IL-6 levels. The AUC of the model is 0.911.

 The high risk factors on developing to severe COVID-19 are: age 55 years, BMI > 27 kg / m2, IL-6 20 pg/ml and CD4 + T cell 400 count/ L.

 Among 249 discharged COVID-19 patients, those who recovered after 20 days had a lower platelet count, a higher level of estimated glomerular filtration rate, and a higher level of interleukin-6 and myoglobin than those who recovered within 20 days.


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