Dynamics of CD4+ T-Cells and Neutralizing Antibody Responses to Three Consecutive Doses of Inactivated COVID-19 Vaccines in PLWH.

Background: Comprehensive characterization of safety and immune responses to vaccines is crucial for the prevention and treatment of COVID-19 among people living with HIV (PLWH). This study aimed to investigate the dynamic changes in SARS-CoV-2-specific CD4+ T-cell subsets and neutralizing antibody after three consecutive doses of inactivated COVID-19 vaccines (BBIBP-CorV) among PLWH. Methods: The blood samples were collected from 165 PLWH, including 66 PLWH in the 3-month interval between the second and third dose (cohort 1) and 99 PLWH in the 5-month interval (cohort 2). Blood collection for immunogenicity analysis was performed at 1-month post-2nd vaccination, pre-3rd vaccination, and within 2-month post-3rd vaccination. Wilcoxon matched-pairs signed-rank test was applied to compare the SARS-CoV-2-specific CD4+ T cell subsets and neutralizing antibody level at different time points. The relationship among CD4+ T-cells, Tregs subpopulations and SARS-CoV-2-specific neutralizing antibody level were evaluated with Spearman non-parametric correlation test. Results: No serious adverse reactions were found among PLWH. After two-dose or three-dose inactivated COVID-19 vaccination, the absolute counts of CD4+ T-cells and Tregs subpopulations (CD4+CD25HighCD127Low Tregs, CD45RA+ rTregs and CD45RO+ eTregs) increased in two cohorts. Satisfactory SARS-CoV-2-specific neutralizing antibody responses to the third-dose vaccination were found in two cohorts, including significantly enhanced neutralizing antibody level and high neutralizing antibody seroconversion rate. In addition, SARS-CoV-2-specific neutralizing antibody level were positively associated with the absolute counts of CD4+ T-cells and Tregs subpopulations as well as the frequency of CD45RO+ eTregs in PLWH after three doses of vaccinations. Conclusion: The three doses of inactivated COVID-19 vaccination were both safe and effective to increase SARS-CoV-2-specific CD4+ T-cells and neutralizing antibody in two PLWH cohorts with different inoculation intervals.

Extending the dosing interval of COVID-19 vaccination leads to higher rates of seroconversion in people living with HIV

Introduction Vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is an effective way of protecting individuals from severe coronavirus disease 2019 (COVID-19). However, immune responses to vaccination vary considerably. This study dynamically assessed the neutralizing antibody (NAb) responses to the third dose of the inactivated COVID-19 vaccine administered to people living with human immunodeficiency virus (HIV;PLWH) with different inoculation intervals. Methods A total of 171 participants were recruited: 63 PLWH were placed in cohort 1 (with 3-month interval between the second and third doses), while 95 PLWH were placed in cohort 2 (with 5-month interval between the second and third doses);13 individuals were enrolled as healthy controls (HCs). And risk factors associated with seroconversion failure after vaccination were identified via Cox regression analysis. Results At 6 months after the third vaccination, PLWH in cohort 2 had higher NAb levels (GMC: 64.59 vs 21.99, P < 0.0001) and seroconversion rate (68.42% vs 19.05%, P < 0.0001). A weaker neutralizing activity against the SARSCoV-2 Delta variant was observed (GMT: 3.38 and 3.63, P < 0.01) relative to the wildtype strain (GMT: 13.68 and 14.83) in both cohorts. None of the participants (including HCs or PLWH) could mount a NAb response against Omicron BA.5.2. In the risk model, independent risk factors for NAb seroconversion failure were the vaccination interval (hazed ration [HR]: 0.316, P < 0.001) and lymphocyte counts (HR: 0.409, P < 0.001). Additionally, PLWH who exhibited NAb seroconversion after vaccination had fewer initial COVID-19 symptoms when infected with Omicron. Discussion This study demonstrated that the third vaccination elicited better NAb responses in PLWH, when a longer interval was used between vaccinations. Since post-vaccination seroconversion reduced the number of symptoms induced by Omicron, efforts to protect PLWH with risk factors for NAb seroconversion failure may be needed during future Omicron surges. Clinical trial registration https://beta.clinicaltrials.gov/study/NCT05075070, identifier NCT05075070.

Extending the dosing interval of COVID-19 vaccination leads to higher rates of seroconversion in people living with HIV.

Introduction: Vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is an effective way of protecting individuals from severe coronavirus disease 2019 (COVID-19). However, immune responses to vaccination vary considerably. This study dynamically assessed the neutralizing antibody (NAb) responses to the third dose of the inactivated COVID-19 vaccine administered to people living with human immunodeficiency virus (HIV; PLWH) with different inoculation intervals. Methods: A total of 171 participants were recruited: 63 PLWH were placed in cohort 1 (with 3-month interval between the second and third doses), while 95 PLWH were placed in cohort 2 (with 5-month interval between the second and third doses); 13 individuals were enrolled as healthy controls (HCs). And risk factors associated with seroconversion failure after vaccination were identified via Cox regression analysis. Results: At 6 months after the third vaccination, PLWH in cohort 2 had higher NAb levels (GMC: 64.59 vs 21.99, P < 0.0001) and seroconversion rate (68.42% vs 19.05%, P < 0.0001). A weaker neutralizing activity against the SARSCoV-2 Delta variant was observed (GMT: 3.38 and 3.63, P < 0.01) relative to the wildtype strain (GMT: 13.68 and 14.83) in both cohorts. None of the participants (including HCs or PLWH) could mount a NAb response against Omicron BA.5.2. In the risk model, independent risk factors for NAb seroconversion failure were the vaccination interval (hazed ration [HR]: 0.316, P < 0.001) and lymphocyte counts (HR: 0.409, P < 0.001). Additionally, PLWH who exhibited NAb seroconversion after vaccination had fewer initial COVID-19 symptoms when infected with Omicron. Discussion: This study demonstrated that the third vaccination elicited better NAb responses in PLWH, when a longer interval was used between vaccinations. Since post-vaccination seroconversion reduced the number of symptoms induced by Omicron, efforts to protect PLWH with risk factors for NAb seroconversion failure may be needed during future Omicron surges. Clinical trial registration: https://beta.clinicaltrials.gov/study/NCT05075070, identifier NCT05075070.

Trends in respiratory diseases before and after the COVID-19 pandemic in China from 2010 to 2021.

BACKGROUND: The ongoing benefits of coronavirus disease 2019 (COVID-19) nonpharmaceutical interventions (NPIs) for respiratory infectious diseases in China are still unclear. We aimed to explore the changes in seven respiratory infectious diseases before, during, and after COVID-19 in China from 2010 to 2021. METHODS: The monthly case numbers of seven respiratory infectious diseases were extracted to construct autoregressive integrated moving average (ARIMA) models. Eight indicators of NPIs were chosen from the COVID-19 Government Response Tracker system. The monthly case numbers of the respiratory diseases and the eight indicators were used to establish the Multivariable generalized linear model (GLM) to calculate the incidence rate ratios (IRRs). RESULTS: Compared with the year 2019, the percentage changes in 2020 and 2021 were all below 100% ranging from 3.81 to 84.71%. Pertussis and Scarlet fever started to increase in 2021 compared with 2020, with a percentage change of 183.46 and 171.49%. The ARIMA model showed a good fit, and the predicted data fitted well with the actual data from 2010 to 2019, but the predicted data was bigger than the actual number in 2020 and 2021. All eight indicators could negatively affect the incidence of respiratory diseases. The seven respiratory diseases were significantly reduced during the COVID-19 pandemic in 2020 and 2021 compared with 2019, with significant estimated IRRs ranging from 0.06 to 0.85. In the GLM using data for the year 2020 and 2021, the IRRs were not significant after adjusting for the eight indicators in multivariate analysis. CONCLUSION: Our study demonstrated the incidence of the seven respiratory diseases decreased rapidly during the COVID-19 pandemic in 2020 and 2021. At the end of 2021, we did see a rising trend for the seven respiratory diseases compared to the year 2020 when the NPIs relaxed in China, but the rising trend was not significant after adjusting for the NPIs indicators. Our study showed that NPIs have an effect on respiratory diseases, but Relaxation of NPIs might lead to the resurgence of respiratory diseases.

[Clinical features of 19 children infected with the Omicron variant of severe acute respiratory syndrome coronavirus 2 in Hangzhou, China]. / 杭州市19ä¾‹æ–°åž‹å† çŠ¶ç— æ¯’Omicronå˜å¼‚æ ªæ„ŸæŸ“å„¿ç«¥çš„ä¸´åºŠç‰¹å¾.

OBJECTIVES: To study the clinical features of children infected with the Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: The medical data of 19 children who were diagnosed with SARS-CoV-2 Omicron variant infection from January 28 to March 3, 2022 in Hangzhou were retrospectively reviewed. RESULTS: Among the 19 children, there were 7 boys (37%) and 12 girls (63%), and their age ranged from 6 months to 16 years, with a median age of 2 years and 1 month. Most of these children were infants and young children (aged ≤3 years, accounting for 53%). Among these children, 11 (58%) were unvaccinated with SARS-CoV-2 vaccine and 8 (42%) were vaccinated with SARS-CoV-2 vaccine, and 3 children (16%) had a history of underlying diseases. All 19 children had a clear history of close contact with persons infected with SARS-CoV-2, and 10 children (53%) were involved in the cluster outbreak in a maternal and infant care center. In terms of clinical classification, 13 children (68%) had mild coronavirus disease 2019 (COVID-19) and 6 (32%) had common COVID-19, with no severe cases of COVID-19. The most common clinical symptoms were cough (100%) and fever (63%). The children with a normal peripheral white blood cell count accounted for 84%, and those with a normal lymphocyte count accounted for 68%. There were no significant abnormalities in platelet count, procalcitonin, liver function parameters (alanine aminotransferase and aspartate aminotransferase), and renal function parameters (creatinine and urea). Six children (32%) had obvious signs of pneumonia on chest CT. All 19 children were given symptomatic treatment, and 12 children (63%) were given aerosol inhalation of interferon α. All children were cured and discharged. CONCLUSIONS: Children infected with Omicron variant strains are more common in infants and young children, with mild symptoms and good prognosis. Most of the children have a history of close contact with persons infected with SARS-CoV-2, and epidemic prevention and control should be strengthened in places with many infants and children, such as maternal and infant care centers.

A prediction model for COVID-19 liver dysfunction in patients with normal hepatic biochemical parameters.

Coronavirus disease 2019 (COVID-19) patients with liver dysfunction (LD) have a higher chance of developing severe and critical disease. The routine hepatic biochemical parameters ALT, AST, GGT, and TBIL have limitations in reflecting COVID-19-related LD. In this study, we performed proteomic analysis on 397 serum samples from 98 COVID-19 patients to identify new biomarkers for LD. We then established 19 simple machine learning models using proteomic measurements and clinical variables to predict LD in a development cohort of 74 COVID-19 patients with normal hepatic biochemical parameters. The model based on the biomarker ANGL3 and sex (AS) exhibited the best discrimination (time-dependent AUCs: 0.60-0.80), calibration, and net benefit in the development cohort, and the accuracy of this model was 69.0-73.8% in an independent cohort. The AS model exhibits great potential in supporting optimization of therapeutic strategies for COVID-19 patients with a high risk of LD. This model is publicly available at https://xixihospital-liufang.shinyapps.io/DynNomapp/.

Treatment Effects of Integrated TCM and Western Medicine Treatment Scheme on COVID-19: A Single-armed Clinical Trial

Backgroud : The outbreak of COVID-19 has brought unprecedented perils to human health and raised public health concerns in more than two hundred countries. Safe and effective treatment scheme is needed urgently. Objective : To evaluate the effects of integrated TCM and western medicine treatment scheme on COVID-19. Methods : A single-armed clinical trial was carried out in Hangzhou Xixi Hospital, an affiliated hospital with Zhejiang Chinese Medical University. 102 confirmed cases were screened out from 725 suspected cases and 93 of them were treated with integrated TCM and western medicine treatment scheme. Results : 83 cases were cured, 5 cases deteriorated, and 5 cases withdrew from the study. No deaths were reported. The mean relief time of fever, cough, diarrhea, and fatigue were (4.78±4.61) days, (7.22±4.99) days, (5.28± 3.39) days, and (5.28± 3.39) days, respectively. It took (14.84±5.50) days for SARS-CoV-2 by nucleic acid amplification-based testing to turn negative. Multivariable cox regression analysis revealed that age, BMI, PISCT, BPC, AST, CK, BS, and UPRO were independent risk factors for COVID-19 treatment. Conclusion : Our study suggested that integrated TCM and western medicine treatment scheme was effective for COVID-19.

Severity-associated markers and assessment model for predicting the severity of COVID-19: a retrospective study in Hangzhou, China.

BACKGROUND: The severity of COVID-19 associates with the clinical decision making and the prognosis of COVID-19 patients, therefore, early identification of patients who are likely to develop severe or critical COVID-19 is critical in clinical practice. The aim of this study was to screen severity-associated markers and construct an assessment model for predicting the severity of COVID-19. METHODS: 172 confirmed COVID-19 patients were enrolled from two designated hospitals in Hangzhou, China. Ordinal logistic regression was used to screen severity-associated markers. Least Absolute Shrinkage and Selection Operator (LASSO) regression was performed for further feature selection. Assessment models were constructed using logistic regression, ridge regression, support vector machine and random forest. The area under the receiver operator characteristic curve (AUROC) was used to evaluate the performance of different models. Internal validation was performed by using bootstrap with 500 re-sampling in the training set, and external validation was performed in the validation set for the four models, respectively. RESULTS: Age, comorbidity, fever, and 18 laboratory markers were associated with the severity of COVID-19 (all P values < 0.05). By LASSO regression, eight markers were included for the assessment model construction. The ridge regression model had the best performance with AUROCs of 0.930 (95% CI, 0.914-0.943) and 0.827 (95% CI, 0.716-0.921) in the internal and external validations, respectively. A risk score, established based on the ridge regression model, had good discrimination in all patients with an AUROC of 0.897 (95% CI 0.845-0.940), and a well-fitted calibration curve. Using the optimal cutoff value of 71, the sensitivity and specificity were 87.1% and 78.1%, respectively. A web-based assessment system was developed based on the risk score. CONCLUSIONS: Eight clinical markers of lactate dehydrogenase, C-reactive protein, albumin, comorbidity, electrolyte disturbance, coagulation function, eosinophil and lymphocyte counts were associated with the severity of COVID-19. An assessment model constructed with these eight markers would help the clinician to evaluate the likelihood of developing severity of COVID-19 at admission and early take measures on clinical treatment.