Background: Coronavirus disease 2019 (COVID-19) has now brought major challenges to public health and economy globally since December 2019, which requires effective treatment and prevention strategies to adapt for the impact of the pandemic. We therefore explored the prognostic factors for patients with COVID-19 and the contribution of immunomodulatory therapy on COVID-19 outcome. Methods: From 1 Feb to 16 March 2020, consecutive cases with COVID-19 were analyzed in the West Campus of Wuhan Union Hospital, a tertiary care center that is designated to care for patients with COVID-19 in Wuhan, China. The observation was based on follow-up until in-hospital death or discharge. Logistic regressions were performed for prognostic factors associated with in-hospital death. Furthermore, a propensity score-matched analysis was done using a multivariable logistic regression model to analyze the contributions of multiple treatments on COVID-19 death. Results: Three hundred and seventeen patients with COVID-19 were enrolled, of whom 269 were discharged and 48 died in hospital. After propensity score-matching based on age, gender, symptoms and comorbidities, multivariable logistic regression was performed with the adjustment of other variables that were significant risk factors in the univariate regression. Treatments with glucocorticoids, immunoglobulin, thymosin, and ammonium glycyrrhizinate were significantly associated with a higher rate of COVID-19 death. Conclusions: For in-hospital patients with COVID-19 of all severity levels, high risk for fatal outcome was observed in those treated with glucocorticoids, immunoglobulin, thymosin, and ammonium glycyrrhizinate. The results of this study do not support immunomodulatory therapy in patients admitted to hospital with COVID-19. Further prospective studies are essential to clarify our findings, especially for non-critically ill patients.
Risk factors of mortality and contribution of treatment in patients infected with COVID-19: a retrospective propensity score matched study