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A Study on the Predictors of Disease Severity of COVID-19

Liang Li, Wei Sun, Mingfeng Han, Yunli Ying, Quanzhi Wang

Department of Infectious Diseases, Fuyang Second People’s Hospital, Fuyang, Anhui, China (mainland)

Med Sci Monit 2020; 26:e927167

DOI: 10.12659/MSM.927167

Available online: 2020-08-20

Published: 2020-09-23

BACKGROUND: Early and rapid identification of severe coronavirus disease 2019 (COVID-19) cases is important. The present study aimed to investigate the predictors of disease severity and thus determine the trends for disease progression early.
MATERIAL AND METHODS: Patients with COVID-19 were recruited from Fuyang Second People’s Hospital from January to February 2020. Patients’ demographic, epidemiological, and clinical data were collected, and the relationships between these variables and disease severity were analyzed.
RESULTS: A total of 158 cases were included according to COVID-19 diagnosis, and the treatment schemes were analyzed for identification of early indicators affecting COVID-19 progression. Severe cases accounted for 18.99% of the diagnosed cases. Analysis showed that patients’ age (χ²=10.640,=0.041); the time interval between onset and diagnosis (χ²=7.278, P=0.026); the source of cases (χ²=5.557, P=0.018); fever (χ²=5.676, P=0.014); dyspnea (χ²=113.085, P<0.001); muscle or joint pain (χ²=3.900, P=0.048); chest pain (χ²=13.446, P=0.006); the levels of lymphocytes (t=2.917, P=0.014), C-reactive protein (U=730.00, P<0.001), and aspartate aminotransferase (U=1235.00, P=0.002); damage in both lungs within 3 days of admission (χ²=7.632, P=0.003); and diabetes (χ²=6.675, P=0.010) were significantly correlated with the trend of intensification.
CONCLUSIONS: Older age, a long time interval from onset to diagnosis, imported cases from an affected area, dyspnea, muscle or joint pain, chest pain during the course of the disease, reduced lymphocytes, elevated C-reactive protein, computed tomography scan showing damage to both lungs within 3 days of admission, and diabetes mellitus are predictors for severe COVID-19.

Keywords: COVID-19, Epidemiology, SARS Virus