COVID-19 associated EBV reactivation and effects of ganciclovir treatment.

BACKGROUND: Systemic reactivation of Epstein-Barr virus (EBV) may occur in novel coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). However, the clinical consequences of EBV reactivation remain uncertain. METHODS: In this retrospective study, we screened 1314 patients with confirmed COVID-19 who died or were discharged between January 1, 2020 and March 12, 2020, in Wuhan Infectious Disease Hospital, Wuhan, China. Patients who had complete data for EBV serology and cytomegalovirus (CMV) serology were eligible. Serum levels of viral capsid antigen (VCA)-immunoglobulin G (IgG), Epstein-Barr nuclear antigen-IgG, VCA-IgM, early antigen (EA)-IgG, CMV-IgG, and CMV-IgM were compared between survivors and nonsurvivors. Dynamic changes of laboratory tests and outcomes were compared in patients with and without ganciclovir treatment. We used 1:1 matching based on age, gender, and illness severity to balance baseline characteristics. RESULTS: EBV reactivation was present in 55 of 217 patients. EBV reactivation was associated with age (57.91 [13.19] vs. 50.28 [12.66] years, p < .001), female gender (31 [56%] vs. 60 [37%], p = .02). Patients with EBV reactivation have statistically nonsignificant higher mortality rate (12 [22%] vs. 18 [11%], p = .08). EA-IgG levels were significantly higher in nonsurvivors than in survivors (median difference: -0.00005, 95% confidence interval, CI [-3.10, 0.00], p = .05). As compared to patients with COVID-19 who did not receive ganciclovir therapy, ganciclovir-treated patients had improved survival rate (0.98, 95% CI [0.95, 1.00] vs. 0.88, 95% CI [0.81, 0.95], p = .01). Hemoglobin (p < .001) and prealbumin (p = .02) levels were significantly higher in ganciclovir-treated patients. CONCLUSION: A high proportion of COVID-19 patients had EBV reactivation that may be associated with an increased risk of death. Whether treatment with ganciclovir may decrease the mortality of COVID-19 patients complicated with EBV reactivation warrants to be addressed in a placebo-controlled randomized trial in the future.

Multi-biomarker is an early-stage predictor for progression of Coronavirus disease 2019 (COVID-19) infection.

Coronavirus disease 2019 (COVID-19) has spread widely in the communities in many countries. Although most of the mild patients could be cured by their body's ability to self-heal, many patients quickly progressed to severe disease and had to undergo treatment in the intensive care unit (ICU). Thus, it is very important to effectively predict which patients with mild disease are more likely to progress to severe disease. A total of 72 patients hospitalized with COVID-19 in Shandong Provincial Public Health Clinical Center and 1141 patients included in the published papers were enrolled in this study. We determined that the combination of interleukin-6 (IL-6), Neutrophil (NEUT), and Natural Killer (NK) cells had the highest prediction accuracy (with 75% sensitivity and 95% specificity) for progression of COVID-19 infection. A binomial regression equation that accounted for a multiple risk score for the combination of IL-6, NEUT, and NK was also established. The multiple risk score is a good indicator for early stratification of mild patients into risk categories, which is very important for adjusting the treatment plan and preventing death.

Viral loads, lymphocyte subsets and cytokines in asymptomatic, mildly and critical symptomatic patients with SARS-CoV-2 infection: a retrospective study.

BACKGROUND: Tens of million cases of coronavirus disease-2019 (COVID-19) have occurred globally. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) attacks the respiratory system, causing pneumonia and lymphopenia in infected individuals. The aim of the present study is to investigate the laboratory characteristics of the viral load, lymphocyte subset and cytokines in asymptomatic individuals with SARS-CoV-2 infection in comparison with those in symptomatic patients with COVID-19. METHODS: From January 24, 2020, to April 11, 2020, 48 consecutive subjects were enrolled in this study. Viral loads were detected by RT-PCR from throat-swab, sputum and feces samples. Lymphocyte subset levels of CD3 + , CD4 + , and CD8 + T lymphocytes, B cells and NK cells were determined with biological microscope and flow cytometric analysis. Plasma cytokines (IL2, IL4, IL5, IL6, IL8, IL10, TNF-α, IFN-α and IFN-γ) were detected using flow cytometer. Analysis of variance (ANOVA), Chi-square or Fisher's exact test and Pearson's Correlation assay was used for all data. RESULTS: Asymptomatic (AS), mild symptoms (MS) and severe or critical cases (SCS) with COVID-19 were 11 (11/48, 22.9%), 26 (54.2%, 26/48) and 11 cases (11/48, 22.9%), respectively. The mean age of AS group (47.3 years) was lower than SCS group (63.5 years) (P < 0.05). Diabetes mellitus in AS, MS and SCS patients with COVID-19 were 0, 6 and 5 cases, respectively, and there was a significant difference between AS and SCS (P < 0.05). No statistical differences were found in the viral loads of SARS-CoV-2 between AS, MS and SCS groups on admission to hospital and during hospitalization. The concentration of CD 3 + T cells (P < 0.05), CD3 + CD4 + T cells (P < 0.05), CD3 + CD8 + T cells (P < 0.01), and B cells (P < 0.05) in SCS patients was lower than in AS and MS patients, while the level of IL-5 (P < 0.05), IL-6 (P < 0.05), IL-8 (P < 0.01) and IL-10 (P < 0.01), and TNF-α (P < 0.05) was higher. The age was negatively correlated with CD3 + T cells (P < 0.05), CD3 + CD4 + T cells (P < 0.05), and positively correlated with IL-2 (P < 0.001), IL-5 (P < 0.05), IL-6 (P < 0.05) IL-8 (P < 0.05), and IL-10 (P < 0.05). The viral loads were positively correlated with IL-2 (P < 0.001), IL-5 (P < 0.05), IL-6 (P < 0.05) IL-8 (P < 0.05) and IL-10 (P < 0.05), while negatively correlated with CD 3 + T cells (P < 0.05) and CD3 + CD4 + T cells (P < 0.05). CONCLUSIONS: The viral loads are similar between asymptomatic, mild and severe or critical patients with COVID-19. The severity of COVID-19 may be related to underlying diseases such as diabetes mellitus. Lymphocyte subset and plasma cytokine levels may be as the markers to distinguish severely degrees of disease, and asymptomatic patients may be as an important source of infection for the COVID-19.

Treatment of coronavirus disease 2019 in Shandong, China: a cost and affordability analysis.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is now a global public threat. Given the pandemic of COVID-19, the economic impact of COVID-19 is essential to add value to the policy-making process. We retrospectively conducted a cost and affordability analysis to determine the medical costs of COVID-19 patients in China, and also assess the factors affecting their costs. METHODS: This analysis was retrospectively conducted in Shandong Provincial Chest Hospital between 24 January and 16 March 2020. The total direct medical expenditures were analyzed by cost factors. We also assessed affordability by comparing the simulated out-of-pocket expenditure of COVID-19 cases relative to the per capita disposable income. Differences between groups were tested by student t test and Mann-Whitney test when appropriate. A multiple logistic regression model was built to determine the risk factors associated with high cost. RESULTS: A total of 70 COVID-19 patients were included in the analysis. The overall mean cost was USD 6827 per treated episode. The highest mean cost was observed in drug acquisition, accounting for 45.1% of the overall cost. Total mean cost was significantly higher in patients with pre-existing diseases compared to those without pre-existing diseases. Pre-existing diseases and the advanced disease severity were strongly associated with higher cost. Around USD 0.49 billion were expected for clinical manage of COVID-19 in China. Among rural households, the proportions of health insurance coverage should be increased to 70% for severe cases, and 80% for critically ill cases to avoid catastrophic health expenditure. CONCLUSIONS: Our data demonstrate that clinical management of COVID-19 patients incurs a great financial burden to national health insurance. The cost for drug acquisition is the major contributor to the medical cost, whereas the risk factors for higher cost are pre-existing diseases and severity of COVID-19. Improvement of insurance coverage will need to address the barriers of rural patients to avoid the occurrence of catastrophic health expenditure.