Analysis of the Factors Associated with Negative Conversion of Severe Acute Respiratory Syndrome Coronavirus 2 RNA of Coronavirus Disease 2019

AIM: To understand the factors associated with negative conversion of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA, targeted surveillance and control measures can be taken to provide scientific basis for the treatment of the disease and to improve the prognosis of the disease. METHODS: Using the method of retrospective cohort study, we collected the data of Coronavirus Disease 2019 (COVID-19) patients in Tongji Hospital of Wuhan, China from 10 January to 25 March, 2020. Among the data of 282 cases, 271 patients, according to whether the negative conversion happened, were divided into negative conversion group and control group. We made the quantitative variables into classification; Chi-square test single-factor and Cox regression were used in univariate analysis and extracted 30 meaningful variables, then through the collinearity diagnosis, excluded the existence of collinear variables. Finally, 22 variables were included in Cox regression analysis. RESULTS: The gender distribution was statistically significant between two groups (p < 0.05). While in the negative conversion group, the patients of non-severe group occupied a large proportion (p < 0.001). The median time for the negative conversion group was 17 days, and at the end of the observation period, the virus duration in control group was 24 days (p < 0.05). A total of 55 variables were included in univariate analysis, among which 30 variables were statistically different between the two groups. After screening variables through collinearity diagnosis, 22 variables were included in the Cox regression analysis. Last, lactate dehydrogenase (LDH), age, fibrinogen (FIB), and disease severity were associated with negative conversion of SARS-CoV-2 RNA. CONCLUSION: Our results suggest that in the treatment of COVID-19, focus on the age of more than 65 years old, severe, high level of LDH, FIB patients, and take some targeted treatment, such as controlling of inflammation, reducing organ damage, so as to provide good conditions for virus clearance in the body

Comparison of peripheral blood T, B, and NK lymphocytes between frontline medical workers for treating patients of COVID-19 and normal outpatient and emergency medical workers in China

The outbreak of the novel coronavirus disease 2019 (COVID-19) has led to significant mental stress for frontline medical workers treating patients with confirmed COVID-19 in China. Psychological stress has an impact on the immune system. The number and percentage of lymphocyte subsets are standard indicators of cellular immune detection. Here, we reported the differences in CD3, CD4, CD8, CD19, and CD56 lymphocytes between 158 frontline medical workers and 24 controls from medical staffs of the outpatient and emergency departments. We found that frontline medical workers had significantly lower absolute values and percentages of CD19+ B cells, especially in the female and the aged ≥40 years subgroup. Stratification analysis showed that the absolute values of CD4+ T cells were significantly lower in the aged <40 years subgroup, while percentages of CD8+ T cells were lower and percentages of CD56+ NK cells were higher in the aged ≥40 years subgroup. In summary, this study suggests paying more attention to frontline medical workers’ mental health and immune function, and properly providing them with psychological interventions and measures of care

Peripheral Inflammatory Cytokines and Lymphocyte Subset Features of Deceased COVID-19 Patients

Objective. To compare the difference of inflammatory cytokines and lymphocyte subsets between deceased patients and survivors with COVID-19. Methods. This retrospective study included 254 confirmed patients from 10 January to 11 March, 2020, at Tongji Hospital of Wuhan, China. Laboratory and immunologic features were collected and analyzed, and the main outcomes focused on inflammatory cytokines and lymphocyte subsets. Results. A trend of markedly higher levels of inflammatory cytokines as well as lower lymphocyte subset levels in deceased patients was observed compared with survivors. ROC curve analyses indicated that inflammatory cytokines and the decrease levels of T cell, Th (helper T cells) cell, Ts (suppressor T cells) cell, B cell, and NK cell along with Th/Ts ratio increase could be used to predict the death of COVID-19. Multivariate analyses showed that higher levels of IL-6, IL-8, and IL-10 remained significantly correlated with shorter survival time and that the amount of Ts cells was negatively associated with the possibility of death in COVID-19 patients. In conclusion, SARS-CoV-2 would cause lymphopenia and result in decreased lymphocyte subset cells, particularly in Ts cell counts, which further induces hyperinflammatory response and cytokine storm. IL-6, IL-8, IL-10, and Ts cell might be independent predictors for the poor outcome of COVID-19