A Multi-center Study of COVID-19 with Multivariate Prognostic Analysis
Abstract
Purpose
Coronavirus disease (COVID-19) pandemic is now a global health concern. However, there is no detailed analysis of the factors related to patients’ improvement.
Patients and methods
We compared the clinical characteristics, laboratory findings, CT images, and treatment of COVID-19 patients from two different cities in China. One hundred and sixty-nine patients were recruited from January 27 to March 17, 2020 at five hospitals in Hubei and Guangxi. They were divided into four groups according to age and into two groups according to presence of comorbidities. Multivariate statistical analyses were performed for the prognosis of the disease.
Results
Fifty-two patients (30.8%) had comorbidities, and the percentage of critical COVID-19was higher in the comorbidities group (11.6%vs.0.9%, p<0.05). Older patients had higher proportion of severe or critical disease. The results showed that lymphocyte count was significantly associated with the number of days from positive COVID-19 nucleic acid test to negative test; number of days from onset of symptoms to confirmation of diagnosis was significantly associated with the time it took for symptoms to improve; and number of days from onset of symptoms to confirmation of diagnosis and disease severity were significantly associated with chest computed tomography improvement.
Conclusions
Age, comorbidities, lymphocyte count, and SpO2 may predict the risk of severity of COVID-19. Early isolation, early diagnosis, and early initiation of management can slow down the progression and spread of COVID-19.
Key Points
Age and comorbidities can predict the risk of severity of COVID-19, Lymphocyte count and SpO2 may predict the risk of severity of COVID-19. Early isolation, Early diagnosis can slow down the progression of COVID-19
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