Laboratory findings and a combined multifactorial approach to predict death in critically ill patients with COVID-19: a retrospective study. (30th June 2020)

• Record Type: Journal Article
• Authors: Liu, Q.; Song, N. C.; Zheng, Z. K.; Li, J. S.; Li, S. K.
• Is Part Of: Epidemiology and infection. Volume 148(2020)
• Publication Date: 2020-06-30
• Subjects: Blood urea nitrogen (BUN), -- coronavirus disease 2019 (COVID-19), -- D-dimer (DD), -- death, -- lymphocyte ratio; Communicable diseases -- Periodicals; Epidemiology -- Periodicals; 614.4
• DOI: 10.1017/S0950268820001442
• Languages: English
• ISSNs: 0950-2688

Abstract

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.