Characteristics of humoral and cellular responses to coronavirus disease 2019 (COVID-19) inactivated vaccine in central China: A prospective, multicenter, longitudinal study

Introduction In China, the long-term immunogenicity and adverse effects of inactivated vaccines produced by different or the same manufacturer remain unclear. Therefore, the objective of this study was to evaluate the cellular immune responses and neutralizing antibody kinetics of homologous and heterologous administrations of an inactivated coronavirus disease 2019 (COVID-19) vaccine 240 days after the second vaccination. Methods This prospective, multicenter, observational, longitudinal study involved 595 participants with a negative SARS-CoV-2 polymerase chain reaction result who were serologically tested and followed for 8 months after vaccination. Neutralizing antibodies, interferon-gamma (IFN-γ), interleukin (IL)-6, CD4+ T-lymphocyte, and B-lymphocyte counts were evaluated in serum samples after stimulation with 2 μg/mL SARS-CoV-2 spike protein for 16 h at follow-up intervals of 2 months. Results Most participants [582/595;146 male participants, 449 female participants;mean age 35 (26–50 years)] rapidly developed neutralizing antibodies after two doses of the vaccine administered 3-weeks apart. The positive rate of neutralizing antibodies peaked at 97.7% at 60–90 days, decreased, and stabilized at 82.9% at 181–240 days post-vaccination. Lower antibody concentrations were correlated with older age, longer duration after vaccination, non-health care workers, mixed-manufacturer vaccinations, and intervals of less than 40 days between two doses of vaccination, whereas lower IFN-γ levels and B-lymphocyte counts were associated with older age, blood type A, and non-health care workers. A higher IL-6 level was associated with older age, mixed-manufacturer vaccinations, intervals of less than 40 days between two doses of vaccination, and medical staff. Adverse reactions were mild or moderate and self-limited, with no serious events reported. Discussion Two doses of the Chinese inactivated vaccine induced robust and rapid antibody expression and cellular immune responses. Boosting vaccination is considered important, as antibodies and cellular immune responses were reduced in susceptible populations.

Characteristics of humoral and cellular responses to coronavirus disease 2019 (COVID-19) inactivated vaccine in central China: A prospective, multicenter, longitudinal study.

Introduction: In China, the long-term immunogenicity and adverse effects of inactivated vaccines produced by different or the same manufacturer remain unclear. Therefore, the objective of this study was to evaluate the cellular immune responses and neutralizing antibody kinetics of homologous and heterologous administrations of an inactivated coronavirus disease 2019 (COVID-19) vaccine 240 days after the second vaccination. Methods: This prospective, multicenter, observational, longitudinal study involved 595 participants with a negative SARS-CoV-2 polymerase chain reaction result who were serologically tested and followed for 8 months after vaccination. Neutralizing antibodies, interferon-gamma (IFN-γ), interleukin (IL)-6, CD4+ T-lymphocyte, and B-lymphocyte counts were evaluated in serum samples after stimulation with 2 µg/mL SARS-CoV-2 spike protein for 16 h at follow-up intervals of 2 months. Results: Most participants [582/595; 146 male participants, 449 female participants; mean age 35 (26-50 years)] rapidly developed neutralizing antibodies after two doses of the vaccine administered 3-weeks apart. The positive rate of neutralizing antibodies peaked at 97.7% at 60-90 days, decreased, and stabilized at 82.9% at 181-240 days post-vaccination. Lower antibody concentrations were correlated with older age, longer duration after vaccination, non-health care workers, mixed-manufacturer vaccinations, and intervals of less than 40 days between two doses of vaccination, whereas lower IFN-γ levels and B-lymphocyte counts were associated with older age, blood type A, and non-health care workers. A higher IL-6 level was associated with older age, mixed-manufacturer vaccinations, intervals of less than 40 days between two doses of vaccination, and medical staff. Adverse reactions were mild or moderate and self-limited, with no serious events reported. Discussion: Two doses of the Chinese inactivated vaccine induced robust and rapid antibody expression and cellular immune responses. Boosting vaccination is considered important, as antibodies and cellular immune responses were reduced in susceptible populations.

Early predictors of severe COVID-19 among hospitalized patients.

BACKGROUND: Limited research has been conducted on early laboratory biomarkers to identify patients with severe coronavirus disease (COVID-19). This study fills this gap to ensure appropriate treatment delivery and optimal resource utilization. METHODS: In this retrospective, multicentre, cohort study, 52 and 64 participants with severe and mild cases of COVID-19, respectively, were enrolled during January-March 2020. Least absolute shrinkage and selection operator and binary forward stepwise logistic regression were used to construct a predictive risk score. A prediction model was then developed and verified using data from four hospitals. RESULTS: Of the 50 variables assessed, eight were independent predictors of COVID-19 and used to calculate risk scores for severe COVID-19: age (odds ratio (OR = 14.01, 95% confidence interval (CI) 2.1-22.7), number of comorbidities (OR = 7.8, 95% CI 1.4-15.5), abnormal bilateral chest computed tomography images (OR = 8.5, 95% CI 4.5-10), neutrophil count (OR = 10.1, 95% CI 1.88-21.1), lactate dehydrogenase (OR = 4.6, 95% CI 1.2-19.2), C-reactive protein OR = 16.7, 95% CI 2.9-18.9), haemoglobin (OR = 16.8, 95% CI 2.4-19.1) and D-dimer levels (OR = 5.2, 95% CI 1.2-23.1). The model was effective, with an area under the receiver-operating characteristic curve of 0.944 (95% CI 0.89-0.99, p < 0.001) in the derived cohort and 0.8152 (95% CI 0.803-0.97; p < 0.001) in the validation cohort. CONCLUSION: Predictors based on the characteristics of patients with COVID-19 at hospital admission may help predict the risk of subsequent critical illness.