Clinical Features and Vaccine Efficacy Analysis of COVID-19 patients in a Chongqing Shelter hospital in 2022 (preprint)

BackgroundThe long-term impact of coronavirus disease 2019 (COVID-19) on many aspects of society emphasizes the necessity of vaccination and nucleic acid conversion time as markers of prevention and diagnosis. However, little research has been conducted on the immunological effects of vaccines and the influencing factors of virus clearance. Epidemiological characteristics and factors related to disease prognosis and nucleic acid conversion time need to be explored. Design and participantsWe reviewed published documentation to create an initial draft. The data were then statistically evaluated to determine their link. Given that a Chongqing shelter hospital is typical in terms of COVID-19 patients receiving hospital management and treatment effects, a retrospective analysis was conducted on 4,557 cases of COVID-19 infection in a shelter hospital in Chongqing in December 2022, which comprised 2,291 males and 2,266 females. The variables included age, medical history, nucleic acid conversion time, vaccination status, and clinical symptoms. ResultsUnivariate survival analysis using the Log-rank test (P < 0.05) showed that factors such as age significantly affected nucleic acid conversion time. COX regression analysis indicated a significant association between a history of hypertension and nucleic acid conversion time, which had a hazard ratio of 0.897 (95% CI: 0.811-0.992). A statistically significant difference was observed between vaccinated and unvaccinated infected individuals in terms of the presence of symptoms such as cough and sensory system manifestations (P < 0.05). ConclusionThe effect of vaccination against COVID-19 on symptoms such as coughing, nasal congestion, muscle aches, runny nose, and sensory system symptoms in COVID-19 patients was determined. Typical symptoms, such as runny nose, were generally higher in vaccinated than in unvaccinated ones; previous hypertension was an influential factor in nucleic acid conversion time in patients with COVID-19 infection. STRENGTHS AND LIMITATIONSThis study clarifies the advantages of vaccination by comparing the symptom development between patients who had received vaccinations and those who had not. This research suggests potential future study directions, such as investigating the impact of pre-existing diseases like hypertension on viral clearance time and assessing vaccine efficacy and safety in certain demographic groups. This work investigated data from 4,557 coronavirus disease 2019 patients admitted to a shelter hospital, which offered significant insights into patients clinical features and outcomes over a defined time span. This study has several flaws because a retrospective analysis method was used and not all confounding variables that might have affected the results were appropriately controlled. The overall research sample may not be representative of other communities because it was drawn from a shelter hospital in Chongqing, and the types of immunizations used were not disclosed. These factors might have had an impact on the precision and extent of the research findings.

Severe/critical COVID-19 early warning system based on machine learning algorithms using novel imaging scores.

BACKGROUND: Early identification of severe/critical coronavirus disease 2019 (COVID-19) is crucial for timely treatment and intervention. Chest computed tomography (CT) score has been shown to be a significant factor in the diagnosis and treatment of pneumonia, however, there is currently a lack of effective early warning systems for severe/critical COVID-19 based on dynamic CT evolution. AIM: To develop a severe/critical COVID-19 prediction model using a combination of imaging scores, clinical features, and biomarker levels. METHODS: This study used an improved scoring system to extract and describe the chest CT characteristics of COVID-19 patients. The study also took into consideration the general clinical indicators such as dyspnea, oxygen saturation, alternative lengthening of telomeres (ALT), and androgen suppression treatment (AST), which are commonly associated with severe/critical COVID-19 cases. The study employed lasso regression to evaluate and rank the significance of different disease characteristics. RESULTS: The results showed that blood oxygen saturation, ALT, IL-6/IL-10, combined score, ground glass opacity score, age, crazy paving mode score, qsofa, AST, and overall lung involvement score were key factors in predicting severe/critical COVID-19 cases. The study established a COVID-19 severe/critical early warning system using various machine learning algorithms, including XGBClassifier, Logistic Regression, MLPClassifier, RandomForestClassifier, and AdaBoost Classifier. The study concluded that the prediction model based on the improved CT score and machine learning algorithms is a feasible method for early detection of severe/critical COVID-19 evolution. CONCLUSION: The findings of this study suggest that a prediction model based on improved CT scores and machine learning algorithms is effective in detecting the early warning signals of severe/critical COVID-19.

Evaluation of the Position Error of Wearing Surgical Masks During Radiotherapy in Head and Neck Cancer Patients.

Purpose: Wearing a mask during the coronavirus disease 2019 epidemic (COVID-19) is a preventive way to reduce droplet and aerosol transmission. The purpose of this study was to evaluate the position error of wearing a surgical mask during radiotherapy in head and neck cancer patients. Patients and Methods: We collected and analyzed 2351 kV X-ray image records of 81 patients with head and neck cancer who underwent image-guided radiotherapy (IGRT). Patients with/without a surgical mask were divided into the head-neck (HN) mask group and head-neck-shoulder (HNS) mask group. The position error in the X (left-right), Y (superior-inferior), Z (anterior-posterior), 3D (three dimensional) vectors, as well as the pitch and yaw axes were compared between the four groups. Results: We found that patients wearing surgical masks in the HN mask group showed no significant differences in the mean position error of the different types of headrest (p>0.05). In the HNS mask group, only the type C headrest group showed significant differences (P < 0.05). The X axis values were -0.05±0.07 and -0.11± 0.01 cm (P = 0.04), and the pitch axis values were 0.34±0.29° and 0.83±0.08° (P = 0.01). Conclusion: The mean position error of most patients wearing surgical masks was not greater than patients without a surgical mask. Patients wearing while receiving treatment is a low-cost and easy-to-implement prevention method.

Efficacy of Probiotic Treatment as Post-Exposure Prophylaxis for COVID-19: A Double-Blind, Placebo Controlled Randomized Trial (preprint)

The COVID-19 pandemic continues to pose unprecedented challenges to worldwide health. While vaccines are effective, additional strategies to mitigate the spread/severity of COVID-19 are urgently needed. Emerging evidence suggests susceptibility to respiratory tract infections in healthy subjects can be reduced by probiotic interventions; therefore, probiotics may be a low-risk, easily implementable modality to reduce risk of COVID-19, particularly in areas with low vaccine availability/uptake. In this study, we conducted a randomized, double-blind, placebo-controlled trial across the United States testing probiotic Lactobacillus rhamnosus GG (LGG) as postexposure prophylaxis for COVID-19 in 182 participants who had household exposure to someone with confirmed COVID-19 diagnosed within ≤ 7 days. Participants were randomized to receive oral LGG or placebo for 28 days. The primary outcome was development of illness symptoms within 28 days of COVID-19 exposure. Stool was collected to evaluate microbiome changes. Intention-to-treat analysis showed LGG treatment led to a lower likelihood of developing illness symptoms versus placebo (26.4% vs. 42.9%, p = 0.02). Further, LGG was associated with a statistically significant reduction in COVID-19 diagnosis (log rank, p = 0.049) via time-to-event analysis. Overall incidence of COVID-19 diagnosis did not significantly differ between LGG and placebo groups (8.8% vs. 15.4%, p = 0.17). This data suggests LGG is associated with prolonged time to COVID-19 infection, reduced incidence of illness symptoms, and gut microbiome changes when used as prophylaxis ≤ 7 days post-COVID-19 exposure. This initial work may inform future COVID-19 prevention studies worldwide, particularly in underdeveloped nations where Lactobacillus probiotics have previously been utilized to reduce non-COVID infectious-morbidity. Trial registration: ClinicalTrials.gov, NCT04399252, Date: 22/05/2020 https://clinicaltrials.gov/ct2/show/NCT04399252

Resign or carry-on? District and principal leadership as drivers of change in teacher turnover intentions during the COVID-19 crisis: A latent growth model examination.

During the COVID-19 pandemic, teachers in the United States, an already at-risk occupation group, experienced new work-related stressors, safety concerns, and work-life challenges, magnifying on-going retention concerns. Integrating the crisis management literature with the unfolding model of turnover, we theorize that leader actions trigger initial employee responses but also set the stage for on-going crisis response that influence changes in teachers' turnover intentions. We apply latent growth curve modelling to test our hypotheses based on a sample of 617 K-12 teachers using nine waves of data, including a baseline survey at the start of the 2020-2021 school year and eight follow-up surveys (2-week lags) through the Fall 2020 semester. In terms of overall adaptation, teachers on average, experienced an increase in work-life balance and a decrease in turnover intentions over the course of the semester. Results also suggest that district and school leadership provide unique and complementary resources, but leader behaviours that shape initial crisis responses do not similarly affect employee responses during crisis, contrary to theory. Instead, teachers' adaptive crisis response trajectories were triggered by continued resource provision over the semester; increasing provision of valued resources (i.e., continued refinement of safety practices) and improvements in work-life balance prevented turnover intentions from spiralling throughout the crisis. Crisis management theory and research should continue to incorporate temporal dynamics and identify factors that contribute to crisis response trajectories, using designs and analyses that allow for examination as crises unfold in real time.

Course and clinical severity of the SARS-CoV-2 Omicron variant infection in Tianjin, China (preprint)

There is limited information describing the course and severity of illness in subjects infected by the SARS-CoV-2 Omicron variant, especially in children. In this population-based cohort study, subjects with Omicron variant infection during the outbreak between January 8 and February 12, 2022 in Tianjin, China were included. The main outcomes were the distribution of illness severity and clinical courses. Of the 429 subjects (113 [26.3%] children; 239 [55.7%] female; median age, 36 years [IQR 15.0 to 55.0 years]), the proportion (95% CI) of symptomatic subjects on admission was 95.6% (93.2%, 97.2%), including 60.4% (55.7%, 64.9%) mild, 35.0% (30.6%, 39.6%) moderate, and 0.2% (0.0%, 1.3%) severe. Compared with adults, children had lower proportion of moderate Covid-19 (8.8% vs 44.3%). The median (IQR) length of hospital stay was 14.0 (12.0, 15.0) days. Symptomatic and moderate Covid-19 in Omicron infections was common in adults and children.

Tracking SARS-CoV-2 Omicron diverse spike gene mutations identifies multiple inter-variant recombination events (preprint)

The current pandemic of COVID-19 is fueled by more infectious emergent Omicron variants. Ongoing concerns of emergent variants include possible recombinants, as genome recombination is an important evolutionary mechanism for the emergence and re-emergence of human viral pathogens. Although recombination events among SARS-CoV-1 and MERS-CoV were well-documented, it has been difficult to detect the recombination signatures in SARS-CoV-2 variants due to their high degree of sequence similarity. In this study, we identified diverse recombination events between two Omicron major subvariants (BA.1 and BA.2) and other variants of concern (VOCs) and variants of interest (VOIs), suggesting that co-infection and subsequent genome recombination play important roles in the ongoing evolution of SARS-CoV-2. Through scanning high-quality completed Omicron spike gene sequences, eighteen core mutations of BA.1 variants (frequency >99%) were identified (eight in NTD, five near the S1/S2 cleavage site, and five in S2). BA.2 variants share three additional amino acid deletions with the Alpha variants. BA.1 subvariants share nine common amino acid mutations (three more than BA.2) in the spike protein with most VOCs, suggesting a possible recombination origin of Omicron from these VOCs. There are three more Alpha-related mutations (del69-70, del144) in BA.1 than BA.2, and therefore BA.1 may be phylogenetically closer to the Alpha variant. Revertant mutations are found in some dominant mutations (frequency >95%) in the BA.1 subvariant. Most notably, multiple additional amino acid mutations in the Delta spike protein were also identified in the recently emerged Omicron isolates, which implied possible recombination events occurred between the Omicron and Delta variants during the on-going pandemic. Monitoring the evolving SARS-CoV-2 genomes especially for recombination is critically important for recognition of abrupt changes to viral attributes including its epitopes which may call for vaccine modifications.

Recent Advances in the Development of Toll-like Receptor Agonist-Based Vaccine Adjuvants for Infectious Diseases.

Vaccines are powerful tools for controlling microbial infections and preventing epidemic diseases. Efficient inactive, subunit, or viral-like particle vaccines usually rely on a safe and potent adjuvant to boost the immune response to the antigen. After a slow start, over the last decade there has been increased developments on adjuvants for human vaccines. The development of adjuvants has paralleled our increased understanding of the molecular mechanisms for the pattern recognition receptor (PRR)-mediated activation of immune responses. Toll-like receptors (TLRs) are a group of PRRs that recognize microbial pathogens to initiate a host's response to infection. Activation of TLRs triggers potent and immediate innate immune responses, which leads to subsequent adaptive immune responses. Therefore, these TLRs are ideal targets for the development of effective adjuvants. To date, TLR agonists such as monophosphoryl lipid A (MPL) and CpG-1018 have been formulated in licensed vaccines for their adjuvant activity, and other TLR agonists are being developed for this purpose. The COVID-19 pandemic has also accelerated clinical research of vaccines containing TLR agonist-based adjuvants. In this paper, we reviewed the agonists for TLR activation and the molecular mechanisms associated with the adjuvants' effects on TLR activation, emphasizing recent advances in the development of TLR agonist-based vaccine adjuvants for infectious diseases.

Daily Lactobacillus Probiotic versus Placebo in COVID-19-Exposed Household Contacts (PROTECT-EHC): A Randomized Clinical Trial (preprint)

Background: The COVID-19 pandemic continues to pose unprecedented challenges to worldwide health. While vaccines are effective, supplemental strategies to mitigate the spread and severity of COVID-19 are urgently needed. Emerging evidence suggests susceptibility to infections, including respiratory tract infections, may be reduced by probiotic interventions. Therefore, probiotics may be a low-risk, widely implementable modality to mitigate risk of COVID-19 disease, particularly in areas with low vaccine availability and/or uptake. Methods: We conducted a randomized, double-blind, placebo-controlled trial across the United States testing the probiotic Lactobacillus rhamnosus GG (LGG) as post-COVID-19-exposure prophylaxis. We enrolled individuals > 1 year of age with a household contact with a recent ([≤] 7 days) diagnosis of COVID-19. Participants were randomized to receive daily LGG or placebo for 28 days. Stool was collected to evaluate the microbiome. The primary outcome was development of symptoms of illness compatible with COVID-19 within 28 days. Findings: We enrolled 182 COVID-19-exposed participants. Intention-to-treat analysis showed that participants randomized to LGG were less likely to develop symptoms versus those randomized to placebo (26.4% vs. 42.9%, p=0.02). Further, LGG was associated with a statistically significant reduction in COVID-19 diagnosis (log rank p=0.049) via time-to-event analysis. Overall incidence of COVID-19 diagnosis was not significantly different between LGG (8.8%) and placebo (15.4%) (p=0.17). LGG was well-tolerated with no increased side effects versus placebo. Interpretation: These findings suggest that LGG probiotic may protect against the development of COVID-19 infection and symptoms when used as post-exposure prophylaxis within 7 days after exposure. Funding: This work was supported by a grant from the Duke Microbiome Center to A.D.S. and P.E.W. and private philanthropic donations to A.D.S. DSM/iHealth donated the LGG and placebo for the trial but had no role in its design, conduct, analysis, or writing. Trial registration: NCT04399252

The Effects of a Comprehensive Rehabilitation Program Involving Traditional Chinese Medicine in Severe and Critical COVID-19 Patients: a Clinical Study (preprint)

Background: A year ago, a new type of coronavirus emerged. Once treated for severe and critical COVID-19 infections, patients are discharged from the hospital for further treatment and rehabilitation. The aim of this study was to  evaluate the efficacy and safety of a newly developed comprehensive rehabilitation program based on traditional Chinese medicine (TCM) in the rehabilitation of patients with severe and critical COVID-19.Methods: We recruited a total of 72 patients who had suffered from severe and critical COVID-19 infections and were undergoing rehabilitation in Chongqing, China. A comprehensive rehabilitation program was formulated according to the TCM syndromes of these patients. Specific treatments included oral TCM, Baduanjin, Moxibustion, Acupoint application, and foot baths. Prior to the initiation of treatment, and four weeks after the initiation of treatment, we carried out a range of assessments, including the TCM Syndrome curative effect score, the modified Medical Research Council (mMRC) dyspnea score, the St. George's Respiratory Questionnaire, the Short Form (SF)-36 Quality of Life Scale, and the 6-minute walking test. We also carried out CT scans, serology tests. Statistical analysis was also conducted to evaluate the efficacy and safety of TCM on severe and critical COVID-19 patients.Results: Analysis showed that there were significant differences (P < 0.05) when compared before and after four weeks of TCM treatment, in terms of the TCM syndrome curative effect score, mMRC dyspnea score, St. George's Respiratory Questionnaire score, SF-36 Quality of Life Scale score, and the 6-minute walking test. We also identified significant differences (P < 0.05) between these two timepoints, with regards to the neutrophil ratio, lymphoid cell ratio, lymphocytes, platelets, red blood cells, and hemoglobin. There were no significant differences when compared between the two timepoints with regards to white blood cells and neutrophils (P > 0.05). The efficacy of chest CT scans was 83.9%. Logistic regression showed that the CT scans of patients who did not take the TCM decoction did not improve significantly. The higher a patient’s score on the 6-minute walking test, the higher the probability of no significant improvement on the CT scan.Conclusions: A comprehensive rehabilitation program based on TCM improved a number of clinical parameters in patients suffering from severe and critical COVID-19 infections, including quality of life, clinical symptoms, exercise endurance, and respiratory function. TCM also enhanced lymphocytes, lymphocyte ratio, platelet, red blood cell (RBC) count, and hemoglobin content. TCM also appeared to contribute to the absorption of lung lesions.

Associations Between the Use of Renin-Angiotensin System Inhibitors and the Risks of Severe COVID-19 and Mortality in COVID-19 Patients With Hypertension: A Meta-Analysis of Observational Studies.

Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) share a target receptor with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The use of ACEIs/ARBs may cause angiotensin-converting enzyme 2 receptor upregulation, facilitating the entry of SARS-CoV-2 into host cells. There is concern that the use of ACEIs/ARBs could increase the risks of severe COVID-19 and mortality. The impact of discontinuing these drugs in patients with COVID-19 remains uncertain. We aimed to assess the association between the use of ACEIs/ARBs and the risks of mortality and severe disease in patients with COVID-19. A systematic search was performed in PubMed, EMBASE, Cochrane Library, and MedRxiv.org from December 1, 2019, to June 20, 2020. We also identified additional citations by manually searching the reference lists of eligible articles. Forty-two observational studies including 63,893 participants were included. We found that the use of ACEIs/ARBs was not significantly associated with a reduction in the relative risk of all-cause mortality [odds ratio (OR) = 0.87, 95% confidence interval (95% CI) = 0.75-1.00; I 2 = 57%, p = 0.05]. We found no significant reduction in the risk of severe disease in the ACEI subgroup (OR = 0.95, 95% CI = 0.88-1.02, I 2 = 50%, p = 0.18), the ARB subgroup (OR = 1.03, 95% CI = 0.94-1.13, I 2 = 62%, p = 0.48), or the ACEI/ARB subgroup (OR = 0.83, 95% CI = 0.65-1.08, I 2 = 67%, p = 0.16). Moreover, seven studies showed no significant difference in the duration of hospitalization between the two groups (mean difference = 0.33, 95% CI = -1.75 to 2.40, p = 0.76). In conclusion, the use of ACEIs/ARBs appears to not have a significant effect on mortality, disease severity, or duration of hospitalization in COVID-19 patients. On the basis of the findings of this meta-analysis, there is no support for the cessation of treatment with ACEIs or ARBs in patients with COVID-19.

Performance Evaluation of the Serological Test and Dynamic Changes of Anti-2019-nCoV Antibodies Among COVID‐19 Patients (preprint)

BackgroundSerological tests for anti-2019-nCoV antibodies have been developed, however, validation with clinical samples was insufficient and mixed. MethodsA total of 197 patients with COVID-19 hospitalized in the Wuhan Pulmonary Hospital and 114 healthy people were enrolled in this study. The IgM/IgG was measured by chemiluminescence detection kit and the performance of IgM/IgG was assessed through diagnostic test. A smooth spline function was used to fit a possible dynamic changes of antibody content.ResultsThe sensitivity and specificity to diagnose COVID-19 were 96.95% and 92.98% for IgG, and 65.99% and 98.25% for IgM, respectively. The period with the highest IgM positive rate (93.75%) was 11 to 13 days after the onset, while the IgG positive rate was almost 100% in the patients whose serum was collected 7 days after onset. Small differences were found in IgM content among mild/regular, severe and critical patients. IgG content in critical patients were highest in the 2-week post-symptom onset group, while the IgG in the severe patients were highest in the 15-28 days and more than 28 days post-symptom onset.ConclusionsSerological testing performed well in the diagnosis for COVID-19, and the positive rate and variance of IgG are higher than those of IgM.

A Randomized Controlled Study of Muscle Training Exercise Based Pulmonary Rehabilitation on Activity of Daily Living in Patients with Coronavirus Disease 2019 (preprint)

Background: Hospitalized patients with Coronavirus Disease 2019 (COVID-19) pneumonia showed a severve loss of muscle mass and strength over admission. Therefore, early physical interventions might be conducive to prevent disability and fasten recovery. Methods: We designed a prospective, randomized controlled trial to identify the effectiveness and safety of pulmonary rehabilitation based on muscle exercise in COVID-19 patients. The study was conducted between February 7th and March 31st 2020 in Union Hospital. Patients were randomly assigned to the pulmonary rehabilitation exercise group or the control group. Primary outcome was improvement of activity of daily living (ADL). Secondary outcome was changes of muscle strength assessed by manual muscle test (MMT) and arterial blood gas analysis. Length of hospital staying (LOS) and adverse events related to physical activity were also observed.Results: A total of sixty patients were in analysis, and thirty patients were in PR group. Patients had a mean age of 54.43±10.57 years. A statistically and clinically significant increase in ADL was observed in PR group (75.00 [66.25,90.00] to 100.00 [100.00,100.00], p<0.001). We also found that the improvement of ADL was related to younger age and higher PaO2 (p<0.01). Both groups had MMT improvement and there was no statistical difference between groups. There was a significant increase in PaO2 (80.23±6.49 vs. 90.47±7.82, respectively, p<0.001) between two groups before discharge. There was no statically significant difference in LOS between study group and control group (p=0.62). None of these patients had severe complications during the study.Conclusions: The protocal of pulmonary rehabilitation based on muscle training exercise was feasible in COVID-19 patients and it might accelerate recovery in ADL as compared with the spontaneous recovery in the control group.Clinical Trial Registration: ChiCTR, ChiCTR2000032457. Registered 29 April 2020- Retrospectively registered, http://www.chictr.org.cn/showproj.aspx?proj=52925.

Targeting SARS-CoV-2 with AI- and HPC-enabled Lead Generation: A First Data Release (preprint)

Researchers across the globe are seeking to rapidly repurpose existing drugs or discover new drugs to counter the the novel coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). One promising approach is to train machine learning (ML) and artificial intelligence (AI) tools to screen large numbers of small molecules. As a contribution to that effort, we are aggregating numerous small molecules from a variety of sources, using high-performance computing (HPC) to computer diverse properties of those molecules, using the computed properties to train ML/AI models, and then using the resulting models for screening. In this first data release, we make available 23 datasets collected from community sources representing over 4.2 B molecules enriched with pre-computed: 1) molecular fingerprints to aid similarity searches, 2) 2D images of molecules to enable exploration and application of image-based deep learning methods, and 3) 2D and 3D molecular descriptors to speed development of machine learning models. This data release encompasses structural information on the 4.2 B molecules and 60 TB of pre-computed data. Future releases will expand the data to include more detailed molecular simulations, computed models, and other products.