COVID-19 vaccine uptake and hesitancy in Chinese patients with asthma.

OBJECTIVE: Both patients and physicians may be hesitant toward vaccination in patients with asthma, which may result in lower vaccine uptake. The aim of this work was to investigate the vaccination rate, the adverse reactions, as well as the factors associated with vaccine acceptance and hesitancy toward COVID-19 vaccination among asthmatic patients in Beijing. METHODS: A multi-center, cross-sectional face-to-face survey was conducted in patients with asthma consecutively recruited from December 2021 to April 2022. The survey included asthma status, COVID-19 vaccine uptake and adverse reactions, and knowledge of and attitude toward COVID-19 vaccination. RESULTS: A total of 261 patients were enrolled. The rate of COVID-19 vaccination during the study period was 73.6%, as compared to 87.64% in the general population in China. Patients who were currently working, had received other vaccines in the past, and had had no adverse reactions to other vaccines, showed a higher rate of COVID-19 vaccination. Patients believing that the vaccination of family members and colleagues had a positive impact on their decision to get vaccinated, were more likely to get the COVID-19 vaccines. The COVID-19 vaccination rate was lower in those with poorly monitored asthma and those using biologic therapies. The adverse effects of COVID-19 vaccines in asthmatic patients were similar to those in the general population. CONCLUSION: The COVID-19 vaccination rate in asthmatic patients was lower than the general population in China. Active measures should be taken to control asthma and increase vaccination rates in these patients.

Stand against anti-Asian racial discrimination during COVID-19: A call for action

Racial discrimination against people of Chinese and other Asian ethnicities has risen sharply in number and severity globally amid the COVID-19 pandemic. This rise has been especially rapid and severe in the United States, fueled by xenophobic political rhetoric and racist language on social media. It has endangered the lives of many Asian Americans and is likely to have long-term negative impacts on the economic, social, physical, and psychological well-being of Asian Americans. This essay reviews the prevalence and consequences of anti-Asian racial discrimination during COVID-19 and calls for actions in practice, policy, and research to stand against it. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

A perspective on SARS-CoV-2 virus-like particles vaccines.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) first appeared in Wuhan, China, in December 2019. The 2019 coronavirus disease (COVID-19) pandemic, caused by SARS-CoV-2, has spread to almost all corners of the world at an alarming rate. Vaccination is important for the prevention and control of the COVID-19 pandemic. Efforts are underway worldwide to develop an effective vaccine against COVID-19 using both traditional and innovative vaccine strategies. Compared to other vaccine platforms, SARS-CoV-2 virus-like particles （VLPs ）vaccines, as a new vaccine platform, have unique advantages: they have artificial nanostructures similar to natural SARS-CoV-2, which can stimulate good cellular and humoral immune responses in the organism; they have no viral nucleic acids, have good safety and thermal stability, and can be mass-produced and stored; their surfaces can be processed and modified, such as the adjuvant addition, etc.; they can be considered as an ideal platform for COVID-19 vaccine development. This review aims to shed light on the current knowledge and progress of VLPs vaccines against COVID-19, especially those undergoing clinical trials.

New-onset COVID-19-related diabetes: an early indicator of multi-organ injury and mortally of SARS-CoV-2 infection.

Objective: The pandemic of 2019 coronavirus (SARS-CoV-2) disease (COVID-19) has imposed a severe public health burden worldwide. Most patients with COVID-19 were mild. Severe patients progressed rapidly to critical condition including acute respiratory distress syndrome (ARDS), multi-organ failure and even death. This study aims to find early multi-organ injury indicators and blood glucose for predicting mortality of COVID-19. Methods: Fasting blood glucose (FBG) ≥7.0 mmol/L for two times during hospitalization and without a history of diabetes were defined as new-onset COVID-19-related diabetes (CRD). Indicators of injuries for multiple organs, including the lung, heart, kidney and liver, and glucose homeostasis were specifically analyzed for predicting death. Results: A total of 120 patients with a severity equal to or greater than Moderate were hospitalized. After excluding patients with history of diabetes, chronic heart, kidney, and liver disease, 69 patients were included in the final analysis. Of the 69 patients, 23 were Moderate, 20 were Severe, and 26 were Critical (including 16 deceased patients). Univariable analysis indicated that CRD, lactate dehydrogenase (LDH), hydroxybutyrate dehydrogenase (HBDH), creatine kinase (CK) and creatinine (Cr) were associated with death. Multivariable analysis indicated that CRD was an independent predictor for death (HR = 3.75, 95% CI 1.26-11.15). Abnormal glucose homeostasis or CRD occurred earlier than other indicators for predicting poor outcomes. Indicators of multiple organ injury were in parallel with the expression patterns of ACE2 (the SARS-CoV-2 receptor) in different organs including pancreatic islet. Conclusions: New-onset COVID-19-related diabetes is an early indicator of multi-organ injury and predictor for poor outcomes and death in COVID-19 patients. As it is easy to perform for clinical practices and self-monitoring, glucose testing will be helpful for predicting poor outcomes to facilitate appropriate intensive care.

Epidemiological characteristics of 17 imported patients infected with SARS-CoV-2 Omicron variant. / 17ä¾‹æ–°åž‹å† çŠ¶ç— æ¯’Omicronå˜å¼‚æ ªå¢ƒå¤–è¾“å ¥æ„ŸæŸ“è€ çš„æµè¡Œç— å­¦ç‰¹å¾.

OBJECTIVES: With the continuous generation of new variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pressure of epidemic prevention and control continues to increase in China. Omicron with stronger infectiousness, immune escape ability and repeated infection ability spread to many countries and regions around the world in a short period of time. China has also successively reported cases of imported Omicron infections. This study aims to understand the epidemiological characteristics of Omicron variant via analyzing the epidemiological characteristics of imported patients with Omicron in Hunan Province, and to provide reference for preventing and controlling the imported epidemics. METHODS: The clinical data of imported patients with coronavirus disease 2019 admitted to Hunan Province from December 16 to December 31, 2021 were retrospectively collected. The epidemiological information, general information, clinical classification, clinical symptoms, vaccination status, and lung CT were analyzed. Nasopharyngeal swabs and blood samples were collected. Virus nucleic acid was detected by magnetic beads method using SARS-CoV-2 detection kit. Ct values of ORF1ab gene and N gene were compared between asymptomatic infected patients and confirmed patients. The specific IgM and IgG antibodies were detected by chemiluminescence assay using SARS-CoV-2 IgM test kit and SARS-CoV-2 IgG test kit, respectively. Ct values of IgM and IgG antibodies were compared between asymptomatic infected patients and confirmed patients. RESULTS: Seventeen patients with Omicron variant infection were treated in Hunan, including 15 confirmed patients (5 common type and 10 mild type) and 2 asymptomatic infection patients. The 17 patients were all Chinese, they were generally young, and 16 were male. There were 9 patients with diseases. Of them 3 patients had respiratory diseases. All 17 patients had completed the whole process of vaccination, but only one person received a booster shot of SARS-CoV-2 vaccine. The clinical manifestations of the patients were mild, mainly including dry/painful/itchy throat, cough, and fatigue. The total protein and creatine in the asymptomatic infection and confirmed cases infected with Omicron variant were all within the normal range, but other biochemical indicators were abnormal. There were the significant differences in C-reactive protein and fibrinogen between asymptomatic infection and confirmed patients (both P<0.05). There were more patients with elevated C-reactive protein in confirmed patients than without confirmed ones. The detection rate of specific IgM and IgG antibodies on admission was 100%, and there was no significant difference in the specific antibody levels between asymptomatic infection and confirmed patients (P>0.05). There were no significant differences in Ct values of ORF1ab gene and N gene (21.35 and 18.39 vs 19.22 and 15.67) between the asymptomatic infection and the confirmed patients (both P>0.05). Only 3 patients had abnormal lung CT, showing a small amount of patchy and cord-like shadows. One of them had no abnormality on admission but had pulmonary lesions and migratory phenomenon after admission. CONCLUSIONS: The patients with Omicron variant tend to be young people and have milder clinical symptoms, but the viral load is high and the infectiveness is strong. Therefore, the timely identification and effective isolation and control for asymptomatic infections and confirmed patients with mild symptoms are extremely important. In terms of epidemic prevention and control, the government still needs to strengthen the risk control of overseas input, adhere to normalized epidemic prevention and control measures, to effectively control the source of infection, cut off the route of transmission, and protect vulnerable people.

The Current Status of Vaccine Uptake and the Impact of COVID-19 on Intention to Vaccination in Patients with COPD in Beijing.

Background: SARS-CoV-2 tends to cause more severe disease in patients with COPD once they are infected. We aimed to investigate the rates of influenza, pneumococcal and COVID-19 vaccination uptake in patients with COPD and to determine whether the COVID-19 pandemic and widespread vaccination against COVID-19 had any impact on the intention to accept influenza vaccines in these patients. Methods: We conducted a multi-center and cross-sectional survey in seven tertiary hospitals in Beijing and consecutively recruited outpatients with COPD from June 1st to July 30th, 2021. The survey included patient's clinical characteristics, uptake of influenza, pneumococcal and COVID-19 vaccination, vaccine knowledge, attitude towards vaccines, and the change of intention to receive influenza vaccination after COVID-19 epidemic and COVID-19 vaccination in Beijing. Results: A total of 264 patients were enrolled. The rate of COVID-19 vaccination during the study period was 39.0%. The rates of influenza vaccination in the past season and pneumococcal vaccination in the past year were 22.7% and 5.7%, respectively. Of the patients who had not received COVID-19 vaccination (n = 161), only 16.2% reported that COVID-19 vaccination was recommended by clinicians, while 23.5% had no knowledge regarding COVID-19 vaccination. About 51.1% of the patients reported that their intention to receive influenza vaccination was influenced by the COVID-19 pandemic. COVID-19 vaccination was independently associated with a positive change in intention to receive influenza vaccination. Conclusion: The coverage rate of COVID-19 vaccination among patients with COPD in Beijing was 39.0%, and that of influenza and pneumococcal vaccination was very low. The COVID-19 pandemic and the COVID-19 vaccination campaign showed a significant, positive impact on patients with COPD in terms of influenza vaccination. Improving awareness of the effectiveness and safety of vaccines among both healthcare professionals and patients could increase vaccination coverage in patients with COPD.

Severity Assessment and Progression Prediction of COVID-19 Patients Based on the LesionEncoder Framework and Chest CT

Automatic severity assessment and progression prediction can facilitate admission, triage, and referral of COVID-19 patients. This study aims to explore the potential use of lung lesion features in the management of COVID-19, based on the assumption that lesion features may carry important diagnostic and prognostic information for quantifying infection severity and forecasting disease progression. A novel LesionEncoder framework is proposed to detect lesions in chest CT scans and to encode lesion features for automatic severity assessment and progression prediction. The LesionEncoder framework consists of a U-Net module for detecting lesions and extracting features from individual CT slices, and a recurrent neural network (RNN) module for learning the relationship between feature vectors and collectively classifying the sequence of feature vectors. Chest CT scans of two cohorts of COVID-19 patients from two hospitals in China were used for training and testing the proposed framework. When applied to assessing severity, this framework outperformed baseline methods achieving a sensitivity of 0.818, specificity of 0.952, accuracy of 0.940, and AUC of 0.903. It also outperformed the other tested methods in disease progression prediction with a sensitivity of 0.667, specificity of 0.838, accuracy of 0.829, and AUC of 0.736. The LesionEncoder framework demonstrates a strong potential for clinical application in current COVID-19 management, particularly in automatic severity assessment of COVID-19 patients. This framework also has a potential for other lesion-focused medical image analyses.

Observation on distribution of TCM patterns and changes of peripheral blood cell count and chest imaging in mild and moderate COVID-19 patients

Objective: To observe distribution of traditional Chinese medicine(TCM) patterns and changes of peripheral blood cell count and chest imaging in mild and moderate COVID-19 patients.

Development and Validation of a Machine Learning Approach for Automated Severity Assessment of COVID-19 Based on Clinical and Imaging Data: Retrospective Study.

BACKGROUND: COVID-19 has overwhelmed health systems worldwide. It is important to identify severe cases as early as possible, such that resources can be mobilized and treatment can be escalated. OBJECTIVE: This study aims to develop a machine learning approach for automated severity assessment of COVID-19 based on clinical and imaging data. METHODS: Clinical data-including demographics, signs, symptoms, comorbidities, and blood test results-and chest computed tomography scans of 346 patients from 2 hospitals in the Hubei Province, China, were used to develop machine learning models for automated severity assessment in diagnosed COVID-19 cases. We compared the predictive power of the clinical and imaging data from multiple machine learning models and further explored the use of four oversampling methods to address the imbalanced classification issue. Features with the highest predictive power were identified using the Shapley Additive Explanations framework. RESULTS: Imaging features had the strongest impact on the model output, while a combination of clinical and imaging features yielded the best performance overall. The identified predictive features were consistent with those reported previously. Although oversampling yielded mixed results, it achieved the best model performance in our study. Logistic regression models differentiating between mild and severe cases achieved the best performance for clinical features (area under the curve [AUC] 0.848; sensitivity 0.455; specificity 0.906), imaging features (AUC 0.926; sensitivity 0.818; specificity 0.901), and a combination of clinical and imaging features (AUC 0.950; sensitivity 0.764; specificity 0.919). The synthetic minority oversampling method further improved the performance of the model using combined features (AUC 0.960; sensitivity 0.845; specificity 0.929). CONCLUSIONS: Clinical and imaging features can be used for automated severity assessment of COVID-19 and can potentially help triage patients with COVID-19 and prioritize care delivery to those at a higher risk of severe disease.

Stand against anti-Asian racial discrimination during COVID-19: A call for action

Racial discrimination against people of Chinese and other Asian ethnicities has risen sharply in number and severity globally amid the COVID-19 pandemic. This rise has been especially rapid and severe in the United States, fueled by xenophobic political rhetoric and racist language on social media. It has endangered the lives of many Asian Americans and is likely to have long-term negative impacts on the economic, social, physical, and psychological well-being of Asian Americans. This essay reviews the prevalence and consequences of anti-Asian racial discrimination during COVID-19 and calls for actions in practice, policy, and research to stand against it.

Predictive role of clinical features in patients with coronavirus disease 2019 for severe disease. / 2019å† çŠ¶ç— æ¯’ç— æ‚£è€ ä¸´åºŠç‰¹å¾å¯¹é‡ç—‡åŒ–çš„é¢„æµ‹ä½œç”¨.

OBJECTIVES: Since the outbreak of coronavirus disease 2019 (COVID-19), it has spread rapidly in China and many other countries. The rapid increase in the number of cases has caused widespread panic among people and has become the main public health problem in the world. Severe patients often have difficult breathing and/or hypoxemia after 1 week of onset. A few critically ill patients may not only rapidly develop into acute respiratory distress syndrome, but also may cause coagulopathy, as well as multiple organs failure (such as heart, liver and kidney) or even death. This article is to analyze the predictive role of clinical features in patients with COVID-19 for severe disease, so as to help doctor monitor the severity-related features, restrain the disease progress, and provide a reference for improvement of medical treatment. METHODS: The clinical data of 208 patients with COVID-19 who were isolated and treated in Changsha Public Health Treatment Center from January 17, 2020 to March 14, 2020 were collected. All patients were the mild and ordinary adult patients on admission, including 105 males and 103 females from 19 to 84 (median age 44) years old. According to the "Program for the diagnosis and treatment of novel coronavirus (COVID-19) infected pneumonia (Trial version 7)" issued by the General Office of National Health Committee and Office of State Administration of Traditional Chinese Medicine as the diagnostic and typing criteria. According to progression from mild to severe disease during hospitalization, the patients were divided into a mild group (n=183) and a severe transformation group (n=25). The clinical features such as age, underlying disease, blood routine, coagulation function, blood biochemistry, oxygenation index, and so on were analyzed. Among them, laboratory tests included white blood cell (WBC), lymphocytes (LYM), neutrophil (NEU), hemoglobin (Hb), platelet (PLT), prothrombin time (PT), plasma fibrinogen (Fib), activated partial prothrombin time (APTT), thrombin time (TT), D-dimer, total bilirubin (TBIL), albumin (ALB), alanine aminotransferase (ALT), aspartate aminotransferase (AST), blood urea nitrogen (BUN), serum creatinine (Cr), creatine kinase (CK), creatine kinase isoenzyme-MB (CK-MB), lactate dehydrogenase (LDH), C-reactive protein (CRP), and oxygen partial pressure in arterial blood. Partial pressure of oxygen in arterial blood/fractional concentration of inspiratory oxygen (PaO2/FiO2) was calculated. The variables with statistical significance were analyzed by logistic regression analysis. RESULTS: Patients in the severe transformation group had more combined underlying diseases than those in the mild group (P<0.05). From the perspective of disease distribution, patients in the severe transformation group had more combined hypertension (P<0.05). In the severe transformation group, PT was significantly longer, the levels of Fib, ALT, AST, CK, LDH, and CRP were significantly higher than those in the mild group (P<0.05 or P<0.001), while LYM, ALB, and PaO2/FiO2 were significantly lower than those in the mild group (P<0.05 or P<0.001). Logistic regression analysis was performed on clinical features with statistically significant differences. Combined with hypertension, LYM, PT, Fib, ALB, ALT, AST, CK, LDH, and CRP as independent variables, and having severe disease or not was the dependent variable. The results show that combined hypertension, decreased LYM, longer PT, and increased CK level were independent risk factors that affected the severity of COVID-19 (P<0.05). CONCLUSIONS: The patients with mild COVID-19 who are apt to develop severe diseases may be related to combined hypertension, decreased LYM, and longer PT, and increased CK level. For the mild patients with these clinical features, early intervention may effectively prevent the progression to severe diseases.