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Epidemiol Infect ; 148: e129, 2020 06 30.
Article in English | MEDLINE | ID: covidwho-619996

ABSTRACT

To describe the laboratory findings of cases of death with coronavirus disease 2019 (COVID-19) and to establish a scoring system for predicting death, we conducted this single-centre, retrospective, observational study including 336 adult patients (≥18 years old) with severe or critically ill COVID-19 admitted in two wards of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology in Wuhan, who had definite outcomes (death or discharge) between 1 February 2020 and 13 March 2020. Single variable and multivariable logistic regression analyses were performed to identify mortality-related factors. We combined multiple factors to predict mortality, which was validated by receiver operating characteristic curves. As a result, in a total of 336 patients, 34 (10.1%) patients died during hospitalisation. Through multivariable logistic regression, we found that decreased lymphocyte ratio (Lymr, %) (odds ratio, OR 0.574, P < 0.001), elevated blood urea nitrogen (BUN) (OR 1.513, P = 0.009), and raised D-dimer (DD) (OR 1.334, P = 0.002) at admission were closely related to death. The combined prediction model was developed by these factors with a sensitivity of 100.0% and specificity of 97.2%. In conclusion, decreased Lymr, elevated BUN, and raised DD were found to be in association with death outcomes in critically ill patients with COVID-19. A scoring system was developed to predict the clinical outcome of these patients.


Subject(s)
Coronavirus Infections/blood , Coronavirus Infections/mortality , Pneumonia, Viral/blood , Pneumonia, Viral/mortality , Age Factors , Aged , Area Under Curve , Blood Chemical Analysis , Blood Urea Nitrogen , C-Reactive Protein/analysis , COVID-19 , Causality , Coronavirus Infections/complications , Coronavirus Infections/epidemiology , Critical Illness , Female , Fibrin Fibrinogen Degradation Products/analysis , Humans , Logistic Models , Lymphocyte Count , Male , Middle Aged , Pandemics , Pneumonia, Viral/complications , Pneumonia, Viral/epidemiology , ROC Curve , Respiration, Artificial , Retrospective Studies
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