Global incidence pattern and factors associated with common cutaneous reactions related to COVID-19 vaccination of 2.55 million participants in real-world settings: A systematic review and meta-analysis.

Background: Understanding the incidence pattern of cutaneous reactions is crucial for promoting COVID-19 vaccination. We aimed to report the global incidence pattern of, and factors associated with common cutaneous reactions related to COVID-19 vaccination in real-world settings. Methods: We searched five databases (PubMed, Web of Science, Embase, CNKI, and Wanfang) from inception to May 13, 2022, for studies reporting the incidence of common cutaneous reactions related to COVID-19 vaccines in real-world settings. The outcomes were the systematic skin reactions (rash and urticaria) and the local injection site reactions (pain, swelling, redness, and erythema). We conducted random-effects meta-analyses and explored associated factors using multi-step statistical analyses. Results: We included 35 studies and assessed 2 549 968 participants from 23 countries. The pooled incidence of overall systemic skin reactions was 3.8% (95% confidence interval (CI) = 2.4%-5.5%) with short duration (about one week). Specifically, the pooled incidence rates of rash and urticaria were 3.0% (95% CI = 2.1%-3.9%) and 1.1% (95% CI = 0.7%-1.5%), respectively. For overall local injection site reactions, the pooled incidence was 72.4% (95% CI = 65.7%-78.7%) with short duration (1 to 4.5 days). Except for local pain (72.2%, 95% CI = 65.3%-78.5%), other localized reactions had low incidence, including swelling (13.3%, 95% CI = 9.5%-17.7%), redness (11.5%, 95% CI = 5.7%-19.0%), and erythema (5.8%, 95% CI = 0.7%-15.4%). Geographically, different distribution patterns were observed for these reactions. Regarding associated factors, mRNA vaccines showed lower incidence of urticaria (P < 0.001). Asia population showed higher incidence of urticaria (P < 0.001). We observed lower incidence rates of overall local injection site reactions and pain among inactivated vaccines (P < 0.001). We found no significant difference among reactions between the first and the second dose of vaccines. Conclusions: We examined the global incidence pattern of common cutaneous reactions related to COVID-19 vaccination and found low incidence and short duration of systemic skin reactions and local injection site reactions (except for pain); discrepancies in these reactions were observed across different vaccine types. The cutaneous side effects related to COVID-19 vaccination do not seem to cause concern. Registration: PROSPERO: CRD42021258012.

3- to 24-month Follow-up on COVID-19 with Pulmonary Tuberculosis Survivors after Discharge: Results from a Prospective, Multicenter Study.

Objective: Coronavirus disease 2019 (COVID-19) and tuberculosis (TB) are major public health and social issues worldwide. The long-term follow-up of COVID-19 with pulmonary TB (PTB) survivors after discharge is unclear. This study aimed to comprehensively describe clinical outcomes, including sequela and recurrence at 3, 12, and 24 months after discharge, among COVID-19 with PTB survivors. Methods: From January 22, 2020 to May 6, 2022, with a follow-up by August 26, 2022, a prospective, multicenter follow-up study was conducted on COVID-19 with PTB survivors after discharge in 13 hospitals from four provinces in China. Clinical outcomes, including sequela, recurrence of COVID-19, and PTB survivors, were collected via telephone and face-to-face interviews at 3, 12, and 24 months after discharge. Results: Thirty-two COVID-19 with PTB survivors were included. The median age was 52 (45, 59) years, and 23 (71.9%) were men. Among them, nearly two-thirds (62.5%) of the survivors were moderate, three (9.4%) were severe, and more than half (59.4%) had at least one comorbidity (PTB excluded). The proportion of COVID-19 survivors with at least one sequela symptom decreased from 40.6% at 3 months to 15.8% at 24 months, with anxiety having a higher proportion over a follow-up. Cough and amnesia recovered at the 12-month follow-up, while anxiety, fatigue, and trouble sleeping remained after 24 months. Additionally, one (3.1%) case presented two recurrences of PTB and no re-positive COVID-19 during the follow-up period. Conclusion: The proportion of long symptoms in COVID-19 with PTB survivors decreased over time, while nearly one in six still experience persistent symptoms with a higher proportion of anxiety. The recurrence of PTB and the psychological support of COVID-19 with PTB after discharge require more attention.

Non-structure protein ORF1ab (NSP8) in SARS-CoV-2 contains potential γδT cell epitopes.

Upon activation by the pathogen through T-cell receptors (TCRs), γδT cells suppress the pathogenic replication and thus play important roles against viral infections. Targeting SARS-CoV-2 via γδT cells provides alternative therapeutic strategies. However, little is known about the recognition of SARS-CoV-2 antigens by γδT cells. We discovered a specific Vγ9/δ2 CDR3 by analyzing γδT cells derived from the patients infected by SARS-CoV-2. Using a cell model exogenously expressing γδ-TCR established, we further screened the structural motifs within the CDR3 responsible for binding to γδ-TCR. Importantly, these sequences were mapped to NSP8, a non-structural protein in SARS-CoV-2. Our results suggest that NSP8 mediates the recognition by γδT cells and thus could serve as a potential target for vaccines.

Quantitative CT imaging features for COVID-19 evaluation: The ability to differentiate COVID-19 from non- COVID-19 (highly suspected) pneumonia patients during the epidemic period.

OBJECTIVES: COVID-19 and Non-Covid-19 (NC) Pneumonia encountered high CT imaging overlaps during pandemic. The study aims to evaluate the effectiveness of image-based quantitative CT features in discriminating COVID-19 from NC Pneumonia. MATERIALS AND METHODS: 145 patients with highly suspected COVID-19 were retrospectively enrolled from four centers in Sichuan Province during January 23 to March 23, 2020. 88 cases were confirmed as COVID-19, and 57 patients were NC. The dataset was randomly divided by 3:2 into training and testing sets. The quantitative CT radiomics features were extracted and screened sequentially by correlation analysis, Mann-Whitney U test, the least absolute shrinkage and selection operator (LASSO) logistic regression (LR) and backward stepwise LR with minimum AIC methods. The selected features were used to construct the LR model for differentiating COVID-19 from NC. Meanwhile, the differentiation performance of traditional quantitative CT features such as lesion volume ratio, ground glass opacity (GGO) or consolidation volume ratio were also considered and compared with Radiomics-based method. The receiver operating characteristic curve (ROC) analysis were conducted to evaluate the predicting performance. RESULTS: Compared with traditional CT quantitative features, radiomics features performed best with the highest Area Under Curve (AUC), sensitivity, specificity and accuracy in the training (0.994, 0.942, 1.0 and 0.965) and testing sets (0.977, 0.944, 0.870, 0.915) (Delong test, P < 0.001). Among CT volume-ratio based models using lesion or GGO component ratio, the model combining CT lesion score and component ratio performed better than others, with the AUC, sensitivity, specificity and accuracy of 0.84, 0.692, 0.853, 0.756 in the training set and 0.779, 0.667, 0.826, 0.729 in the testing set. The significant difference of the most selected wavelet transformed radiomics features between COVID-19 and NC might well reflect the CT signs. CONCLUSIONS: The differentiation between COVID-19 and NC could be well improved by using radiomics features, compared with traditional CT quantitative values.

Integrative COVID-19 biological network inference with probabilistic core decomposition.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for millions of deaths around the world. To help contribute to the understanding of crucial knowledge and to further generate new hypotheses relevant to SARS-CoV-2 and human protein interactions, we make use of the information abundant Biomine probabilistic database and extend the experimentally identified SARS-CoV-2-human protein-protein interaction (PPI) network in silico. We generate an extended network by integrating information from the Biomine database, the PPI network and other experimentally validated results. To generate novel hypotheses, we focus on the high-connectivity sub-communities that overlap most with the integrated experimentally validated results in the extended network. Therefore, we propose a new data analysis pipeline that can efficiently compute core decomposition on the extended network and identify dense subgraphs. We then evaluate the identified dense subgraph and the generated hypotheses in three contexts: literature validation for uncovered virus targeting genes and proteins, gene function enrichment analysis on subgraphs and literature support on drug repurposing for identified tissues and diseases related to COVID-19. The major types of the generated hypotheses are proteins with their encoding genes and we rank them by sorting their connections to the integrated experimentally validated nodes. In addition, we compile a comprehensive list of novel genes, and proteins potentially related to COVID-19, as well as novel diseases which might be comorbidities. Together with the generated hypotheses, our results provide novel knowledge relevant to COVID-19 for further validation.

Association between the nasopharyngeal microbiome and metabolome in patients with COVID-19.

SARS-CoV-2, the causative agent for COVID-19, infect human mainly via respiratory tract, which is heavily inhabited by local microbiota. However, the interaction between SARS-CoV-2 and nasopharyngeal microbiota, and the association with metabolome has not been well characterized. Here, metabolomic analysis of blood, urine, and nasopharyngeal swabs from a group of COVID-19 and non-COVID-19 patients, and metagenomic analysis of pharyngeal samples were used to identify the key features of COVID-19. Results showed lactic acid, l-proline, and chlorogenic acid methyl ester (CME) were significantly reduced in the sera of COVID-19 patients compared with non-COVID-19 ones. Nasopharyngeal commensal bacteria including Gemella morbillorum, Gemella haemolysans and Leptotrichia hofstadii were notably depleted in the pharynges of COVID-19 patients, while Prevotella histicola, Streptococcus sanguinis, and Veillonella dispar were relatively increased. The abundance of G. haemolysans and L. hofstadii were significantly positively associated with serum CME, which might be an anti-SARS-CoV-2 bacterial metabolite. This study provides important information to explore the linkage between nasopharyngeal microbiota and disease susceptibility. The findings were based on a very limited number of patients enrolled in this study; a larger size of cohort will be appreciated for further investigation.

Cytokine Storm: The Primary Determinant for the Pathophysiological Evolution of COVID-19 Deterioration.

The coronavirus disease 2019 (COVID-19) pandemic caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an ongoing major threat to global health and has posed significant challenges for the treatment of severely ill COVID-19 patients. Several studies have reported that cytokine storms are an important cause of disease deterioration and death in COVID-19 patients. Consequently, it is important to understand the specific pathophysiological processes underlying how cytokine storms promote the deterioration of COVID-19. Here, we outline the pathophysiological processes through which cytokine storms contribute to the deterioration of SARS-CoV-2 infection and describe the interaction between SARS-CoV-2 and the immune system, as well as the pathophysiology of immune response dysfunction that leads to acute respiratory distress syndrome (ARDS), multi-organ dysfunction syndrome (MODS), and coagulation impairment. Treatments based on inhibiting cytokine storm-induced deterioration and occurrence are also described.

Physical activity, screen exposure and sleep among students during the pandemic of COVID-19.

This study aimed to determine the levels of health-related behaviours (physical activity, screen exposure and sleep status) among Chinese students from primary, secondary and high schools during the pandemic of COVID-19, as well as their changes compared with their status before the pandemic. A cross-sectional online survey of 10,933 students was conducted among 10 schools in Guangzhou, China, between 8th and 15th March, 2020. After getting the informed consent from student's caregivers, an online questionnaire was designed and used to obtain time spending on health-related behaviours during the pandemic of COVID-19, as well as the changes compared with 3 months before the pandemic, which was completed by students themselves or their caregivers. Students were stratified by regions (urban, suburban, exurban), gender (boys and girls), and grades (lower grades of primary school, higher grades of primary schools, secondary schools and high schools). Data were expressed as number and percentages and Chi-square test was used to analyse difference between groups. Overall, the response rate of questionnaire was 95.3% (10,416/10,933). The median age of included students was 13.0 (10.0, 16.0) years and 50.1% (n = 5,219) were boys. 41.4%, 53.6% and 53.7% of total students reported less than 15 min per day in light, moderate and vigorous activities and 58.7% (n = 6,113) reported decreased participation in physical activity compared with the time before pandemic. Over 5 h of screen time spending on online study was reported by 44.6% (n = 4,649) of respondents, particular among high school students (81.0%). 76.9% of students reported increased screen time compared with the time before pandemic. Inadequate sleep was identified among 38.5% of students and the proportion was highest in high school students (56.9%). Our study indicated that, during the COVID-19 pandemic, the school closure exerted tremendous negative effects on school-aged children's health habits, including less physical activity, longer screen exposure and irregular sleeping pattern.

The clinical characteristics and prognosis of COVID-19 patients with comorbidities: a retrospective analysis of the infection peak in Wuhan.

BACKGROUND: This study aims to determine the clinical characteristics and prognosis of COVID-19 patients with comorbidities and to identify survival factors. METHODS: A retrospective study was conducted in Wuhan, China, between February 8, 2020, and March 9, 2020. Based on underlying diseases, patients were assigned to either the comorbidity group or the non-comorbidity group. The clinical characteristics and outcomes of COVID-19 were analyzed and a Kaplan-Meier survival analysis was used to evaluate the prognosis predictive value of each comorbidity. RESULTS: During the study period, 278 COVID-19 patients were enrolled, 175 (62.95%) were assigned to the comorbidity group, and 103 (37.05%) to the non-comorbidity group. Of the patients in the comorbidity group, 34.86% were classified as critical. Further, patients in the comorbidity group had lower lymphocyte cell counts, and higher concentrations of D-dimer, high sensitivity C-reactive protein, interleukin 6, and serum ferritin as well as higher critical illness severity scores than patients in the non-comorbidity group (P<0.05). Patients in the comorbidity group also had higher mortality, acute respiratory distress syndrome, and ventilation treatment rates than patients in the non-comorbidity group (P<0.05). The length of hospital stay was longer in the comorbidity group than in the non-comorbidity group (P<0.05). The most common underlying diseases included hypertension (40.65%), diabetes mellitus (20.5%), and cardiovascular disease (19.42%). Patients with comorbidities were more likely to develop cardiovascular sequelae associated with COVID-19, shock, acute kidney injury, and multiple organ dysfunction syndrome (30.86% vs. 12.62%, P=0.001; 18.86% vs. 8.74%, P=0.023; 24.57% vs. 11.65%, P=0.009; 33.71% vs. 14.56%, P=0.000, respectively). In the Kaplan-Meier survival analysis, older patients (¡Ý65 years) (log-rank test: χ2=4.202, P=0.040) and patients with chronic obstructive pulmonary disease (COPD) (log-rank test: χ2=4.839, P=0.028) or diabetes mellitus (log-rank test: χ2=4.377, P=0.036) had shorter survival than those without comorbidities. CONCLUSIONS: Patients with comorbidities were more severely affected and had a higher mortality rate. Age, COPD and diabetes mellitus were the main factors affecting the survival of patients.

Higher expression of monocyte chemotactic protein 1 in mild COVID-19 patients might be correlated with inhibition of Type I IFN signaling.

BACKGROUND: Chemokine levels in severe coronavirus disease 2019 (COVID-19) patients have been shown to be markedly elevated. But the role of chemokines in mild COVID-19 has not yet been established. According to the epidemiological statistics, most of the COVID-19 cases in Shiyan City, China, have been mild. The purpose of this study was to evaluate the level of chemokines in mild COVID-19 patients and explore the correlation between chemokines and host immune response. METHODS: In this study, we used an enzyme-linked immunosorbent assay to detect serum levels of chemokines in COVID-19 patients in Shiyan City. Expression of chemokine receptors and of other signaling molecules was measured by real-time polymerase chain reaction. RESULTS: We first demonstrated that COVID-19 patients, both sever and mild cases, are characterized by higher level of chemokines. Specifically, monocyte chemotactic protein 1 (MCP-1) is expressed at higher levels both in severe and mild cases of COVID-19. The receptor of MCP-1, C-C chemokine receptor type 2, was expressed at higher levels in mild COVID-19 patients. Finally, we observed a significant negative correlation between expression levels of interferon (IFN) regulatory factor 3 (IRF3) and serum levels of MCP-1 in mild COVID-19 patients. CONCLUSION: Higher expression of MCP-1 in mild COVID-19 patients might be correlated with inhibition of IFN signaling. The finding adds to our understanding of the immunopathological mechanisms of severe acute respiratory syndrome coronavirus 2 infection and provides potential therapeutic targets and strategies.

Influence of aging on deterioration of patients with COVID-19.

Aging is an important factor affecting the deterioration of patients with coronavirus disease 2019 (COVID-19). The aging and degeneration of various tissues and organs in the elderly lead to impaired organ function. Underlying conditions such as chronic lung disease, cardiovascular disease, and diabetes in aged patients are associated with higher mortality. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) primarily interacts with the cell surface receptor angiotensin-converting enzyme (ACE) 2 and other accessory proteins such as 78 kDa glucose-regulated protein 78 (GRP78) and CD147. Thus, altered receptor signals in aging and chronic disease play a role in SARS-CoV-2 infection, and are associated with a higher risk of deterioration in different organs. In this review, after a brief introduction to the link between aging and receptors for SARS-CoV-2, we focus on the risk of deterioration in different organs of COVID-19 patients considering aging as the main factor. We further discuss the structural and/or physiological changes in the immune system and organs (lung, heart, kidney, vessels, nerve system), as well as those associated with diabetes, in aging patients, and speculate on the most likely mechanisms underlying the deterioration of COVID-19 patients.

[Clinical characteristics of liver damage in 30 patients with severe coronavirus disease 2019 in Sichuan area].

OBJECTIVE: To describe the characteristics of liver damage in severe coronavirus disease 2019 (COVID-19) patients in Sichuan area and the effect of antiviral drugs on liver function. METHODS: The clinical data of severe COVID-19 patients admitted to Chengdu Public Health Clinical Medical Center from January 21 to February 24, 2020 were retrospectively collected, including demographic data, clinical manifestations and liver function changes within 1 week after admission to intensive care unit (ICU). The changes of liver function during the course of disease in severe COVID-19 patients were analyzed and summarized, and group analysis was performed. RESULTS: A total of 30 COVID-19 patients with complete clinical data were enrolled. The incidence of severe COVID-19 in elderly men was higher (60.0%), with median age of 61 (47, 79) years old, and those aged 80 or above accounted for 23.3%. The severe COVID-19 patients mainly presented with respiratory symptoms such as fever (96.7%), cough (80.0%) and dyspnea (66.7%). The alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TBil) and prothrombin time (PT) of 30 patients were increased to various degrees within 1 week after ICU admission, and albumin (ALB) was decreased. (1) The patients were divided into two groups according to whether to take lopinavir/ritonavir (kaletra). It was shown that the incidence of liver dysfunction in patients taking kaletra was significantly higher than those who did not take kaletra (7-day abnormal rate of ALT was 54% vs. 33%, the abnormal rate of AST was 38% vs. 33%, the abnormal rate of TBil was 8% vs. 0%), but there were no statistical differences (all P > 0.05). (2) The patients were divided into normal dose group (500 mg, twice a day, n = 19) and reduced dose group (250 mg, twice a day, n = 5) according to the dosage of kaletra. It was shown that patients taking low-dose kaletra had a smaller effect on liver function within 1 week after ICU admission than those receiving normal dosage, and ALB, TBil in the reduced dose group were significantly lower than those in the normal dose group on the 2nd day after ICU admission [ALB (g/L): 33.3±2.0 vs. 37.5±4.0, TBil (µmol/L): 6.3±3.3 vs. 11.3±4.8, both P < 0.05]. CONCLUSIONS: Severe COVID-19 patients in Sichuan area suffered obvious liver damage in the early course of the disease and have a slower recovery. It is important to pay attention to avoid using drugs that can aggravate liver damage while treating the disease. If there is no alternative drug, liver protection treatment should be considered appropriately.

Prominent coagulation disorder is closely related to inflammatory response and could be as a prognostic indicator for ICU patients with COVID-19.

The new outbreak of Coronavirus Disease 2019 (COVID-19) has emerged as a serious global public health concern. A more in-depth study of blood coagulation abnormality is needed. We retrospectively analyzed 147 consecutive patients with COVID-19 who were admitted to three ICUs in Wuhan from February 9th, 2020 to March 20th, 2020. The baseline coagulation and other characteristics were studied. Our results showed that the prolonged PT, FDP, DD were positively correlated with the levels of neutrophils, ferritin, LDH, total bilirubin, multi-inflammation cytokines, and negatively correlated with the lymphocytes level (p < 0.01). The level of ATIII was significantly negatively correlated with the levels of neutrophils, ferritin, LDH, total bilirubin, IL2R, IL6 and IL8 (p < 0.05). The patients in the ARDS group had a more prominent abnormality in PT, FDP, DD and ATIII, while the patients in the AKI group had more prolonged PT, more severe FDP and DD level, more inferior ATIII and Fib level than those in the non-AKI group (p < 0.01). The value of PT, DD and FDP were positively correlated with the classical APACHE II, SOFA and qSOFA scores, while the ATIII was negatively correlated with them (p < 0.001). The high levels of PT, FDP and DD were correlated with in-hospital mortality (p < 0.001). In conclusion, blood coagulation disorder was prominent in ICU patients with COVID-19 and was correlated with multi-inflammation factors. The abnormality of blood coagulation parameters could be an adverse prognostic indicator for ICU patients with COVID-19.

T-Cell Subset Counts in Peripheral Blood Can Be Used as Discriminatory Biomarkers for Diagnosis and Severity Prediction of Coronavirus Disease 2019.

This study evaluated the significance of lymphocyte subset detection in peripheral blood in the diagnosis and prognosis of coronavirus disease 2019 (COVID-19). Our results revealed that CD3+ T cells, CD4+ T cells, CD8+ T cells, and natural killer cells were significantly decreased in patients with COVID-19. These patients had a relatively slight decrease in CD4+ T cells but a severe decrease in CD8+ T cells. The significantly elevated CD4/CD8 ratio was observed in COVID-19 patients. T-cell subset counts were related to the severity and prognosis of COVID-19, suggesting that the counts of CD8+ T and CD4+ T cells can be used as diagnostic markers of COVID-19 and predictors of disease severity.