SARS-CoV-2 omicron BA.1.1 is highly resistant to antibody neutralization of convalescent serum from the origin strain.

The emergence and rapid spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant (BA.1.1) has attracted global attention. The numerous mutations in the spike protein suggest that it may have altered susceptibility to immune protection elicited by the existing coronavirus disease 2019 (COVID-19) infection. We used a live virus neutralization test and SARS-CoV-2 pseudotype vesicular stomatitis virus vector-based neutralization assay to assess the degree of immune escape efficiency of the original, Delta (B1.617.2), and Omicron strains against the serum antibodies from 64 unvaccinated patients who had recovered from COVID-19 and the results were strongly correlated. The convalescent serum neutralization was more markedly reduced against the Omicron variant (9.4-57.9-fold) than the Delta variant (2.0-4.5-fold) as compared with the original strain. Our results demonstrate the reduced fusion and notable immune evasion capabilities of the Omicron variants, highlighting the importance of accelerating the development of vaccines targeting them.

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.

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.

The Associations of Lymphocyte Ratio and Neutrophil Ratio on Liver Dysfunction in COVID-19 Patients.

Data on the impact of lymphocytes and neutrophils on the incidence of liver dysfunction in COVID-19 patients are limited. This study aimed to investigate the lateral and longitudinal associations of lymphocyte ratio (LR) and neutrophil ratio (NR) on liver dysfunction in COVID-19 patients. We tested 1,409 blood samples from 245 COVID-19 patients in China between January 2020 and June 2021. The lateral U-shaped relationships, determined by smooth curve fitting and the piecewise-linear mixed-effect model, were observed between LR, NR, and AST and the incidence of AST-linked liver dysfunction, with the threshold cutoffs of 26.1 and 62.0, respectively. Over the 1,409 tests, the LR ≤ 26.1 and NR ≥ 62.0 related to the occurrence of mild liver dysfunction (HR: 1.36; 95% CI: 1.01, 1.82), moderate liver dysfunction (HR: 1.37; 95% CI: 1.01, 1.85), and severe liver dysfunction (HR: 1.72; 95% CI: 1.02, 2.90). For the patients with preexisting AST ≥ 35 U/L, the baseline LR ≤ 26.1 and NR ≥ 62.0 (b.LLCHN) groups had a fully adjusted 8.85-, 7.88-, and 5.97-fold increased risk of mild and moderate liver dysfunction after being hospitalized of 3, 6, and 9 days compared to the baseline LR > 26.1 and NR < 62.0 (b.normal) groups. Severe liver dysfunction only presents significant differences after being adjusted for age, sex, and BMI. Consistently, Kaplan-Meier analyses showed that b.LLCHN reflects a better predictive value for different subsequent magnitude liver dysfunctions after admission of 3 and 6 days. To improve liver function in patients with preexisting AST ≥35 U/L, future management strategies should pay more attention to baseline LR ≤ 26.1 and NR ≥ 62.0 patients.

Glycyrrhizic acid: a potential drug against COVID-19

Pneumonia caused by SARS-CoV-2 has seriously threatened human life and health worldwide and caused a large number of deaths. Viral infection and acute inflammation are important causes of death, so it is particularly important to combine antiviral therapy with anti-inflammatory therapy. Glycyrrhizic acid, the main component of the glycyrrhizic root extract, has a wide range of pharmacological effects as well as high efficiency and low toxicity, its preparation has been widely used in the treatment of chronic hepatitis and other diseases. Glycyrrhizic acid can regulate the expression and release of a variety of cytokines and play a significant anti-inflammatory effect. At the same time, glycyrrhizic acid also showed significant inhibition towards a variety types of viruses. Therefore, the potential application of glycyrrhizic acid as COVID-19 treatment should be explored.

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.

Repeated COVID-19 relapse during post-discharge surveillance with viral shedding lasting for 67 days in a recovered patient infected with SARS-CoV-2.

A case who revealed the longest duration of viral shedding (67 days) in current reports, presented complicated characteristic on the relapse of COVID-19 due to the inconsistent performance of chest radiography and SARS-CoV-2-RNA detection after discharge. Lopinavir-interferon α2b boosted ribavirin following with lopinavir boosted budesonide might be a potent treatment for viral clearance.

Positive SARS-CoV-2 RNA recurs repeatedly in a case recovered from COVID-19: dynamic results from 108 days of follow-up.

The evidence of long-term clinical dynamic on Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) RNA re-positive case are less. We performed a 108 days follow-up on dynamic clinical presentations in a case, who hospitalized three times due to the positive recurrence of SARS-CoV-2 RNA after discharge, to understand the prognosis of the 2019-Coronavirus disease (COVID-19). In this case, positive SARS-CoV-2 recurred even after apparent recovery (normal CT imaging, no clinical symptoms, negative SARS-CoV-2 on stool sample and negative serum IgM test) from COVID-19, viral shedding duration lasted for 65 days, the time from symptom onset to disappearance was up to 95 days. Erythrocyte-associated indicators, liver function and serum lipid metabolism presented abnormal throughout during the observation period. Awareness of atypical presentations such as this one is important to prompt the improvement of the management of COVID-19.