ABSTRACT
BACKGROUND The worldwide COVID-19 pandemic develops rapidly. There is a pressing need to find an effective therapy. METHODS We have assembled a cohort consisting 504 hospitalized COVID-19. Information of patients characteristics and antiviral medication use during hospital stay is collected. The study objective is to evaluate the treatment efficacy of selected antiviral medications on mortality and lesion absorption based on chest CT scan. RESULTS The overall mortality rate was 15.67% in the cohort. Older age, lower SpO2 level, bigger lesion, early admission data, and the presence of pre-existing conditions were associated with higher mortality. After adjusting for sex, pre-existing condition, age, SpO2, lesion size, admission data, hospital, and anti-viral medications use, Arbidol and Oseltamivir use is associated with a reduction in mortality. The OR is 0.183 (95% CI, 0.075 to 0.446; p<0.001) for Arbidol and 0.220 (95% CI, 0.069 to 0.707; p=0.011) for Oseltamivir. Compared with patients taking neither Arbidol nor Oseltamivir, the OR is 0.253 (95% CI, 0.064 to 1.001; p=0.050) for patients taking Oseltamivir only; 0.190 (95% CI, 0.076 to 0.473; p<0.001) for patients taking Arbidol only; and 0.030 (95% CI, 0.003 to 0.310; p=0.003) for patients taking both, after adjusting for patients characteristics and Lopinavir/Ritonavir use. Similarly, Arbidol is also associated with faster lesion absorption after adjusting for patients characteristics as well as Oseltamivir and Lopinavir/Ritonavir use. CONCLUSIONS Arbidol is able to substantially associated with a reduction in mortality among hospitalized COVID-19 patients. The combination of Arbidol and Oselmativir may further associated with a reduction in mortality. There is no proven treatment benefit of Lopinavir/Ritonavir.
Subject(s)
COVID-19ABSTRACT
Background Wuhan, China was the epicenter of the 2019 coronavirus outbreak. As a designated hospital, Wuhan Pulmonary Hospital has received over 700 COVID-19 patients. With the COVID-19 becoming a pandemic all over the world, we aim to share our epidemiological and clinical findings with the global community. Methods In this retrospective cohort study, we studied 340 confirmed COVID-19 patients from Wuhan Pulmonary Hospital, including 310 discharged cases and 30 death cases. We analyzed their demographic, epidemiological, clinical and laboratory data and implemented our findings into an interactive, free access web application. Findings Baseline T lymphocyte Subsets differed significantly between the discharged cases and the death cases in two-sample t-tests: Total T cells (p < 2.2e-16), Helper T cells (p < 2.2e-16), Suppressor T cells (p = 1.8-14), and TH/TS (Helper/Suppressor ratio, p = 0.0066). Multivariate logistic regression model with death or discharge as the outcome resulted in the following significant predictors: age (OR 1.05, p 0.04), underlying disease status (OR 3.42, p 0.02), Helper T cells on the log scale (OR 0.22, p 0.00), and TH/TS on the log scale (OR 4.80, p 0.00). The McFadden pseudo R-squared for the logistic regression model is 0.35, suggesting the model has a fair predictive power. Interpretation While age and underlying diseases are known risk factors for poor prognosis, patients with a less damaged immune system at the time of hospitalization had higher chance of recovery. Close monitoring of the T lymphocyte subsets might provide valuable information of the patients condition change during the treatment process. Our web visualization application can be used as a supplementary tool for the evaluation.