ObjectiveTo investigate the anxious level of people with epilepsy (PWE) during the outbreak of 2019 Novel Coronavirus Diseases (COVID-19) and explore the reasons of anxiety.MethodsAn internet questionnaire survey were conducted on the anxiety state of PWE and health controls (HC) aged 18 to 45 years old between Feb 9, 2020 and Feb 17, 2020. The questionnaire included demographic information, general status and the State-Trait Anxiety Inventory (STAI).ResultsIn all, 148 PWE and 300 HC were included in this study. The total SAI score (46.72±9.98 vs. 41.77±10.20, P<0.001) and the total TAI score (44.18±8.88 vs. 31.27±17.44, P<0.001) were significantly higher in PWE than in HC. PWE concerned most (69.9%) about the difficulty of obtaining antiepileptic drugs (AEDs) while HC concerned most about the lack of face masks (73.3%).ConclusionHigh anxious level in PWE during the outbreak of COVID is probably due to the difficulty of obtaining AEDs. Thus, the society should strengthen the solution of the problem of purchasing AEDs and conduct timely psychological counseling.
From December 2022 to January 2023, 4 lung transplant recipients (3 males and 1 female, aged 52-60 years, all received transplantation less than 1 year) were hospitalized in the Department of Thoracic Surgery of the First Affiliated Hospital of Xi'an Jiaotong University due to COVID-19 after surgery. The clinical manifestations were mostly characterized by elevated body temperature accompanied by shortness of breath, and indicators such as heart rate, oxygen saturation, and oxygenation index could reflect the severity of the condition. The therapy was timely adjusted to immunosuppressive drugs, upgraded oxygen therapy, anti-bacterial and anti-fungal therapy, prone ventilation, general treatment, and anticoagulant therapy, depending on the situation. Finally, 3 patients were cured and discharged from hospital, and 1 died.
When a clustered coronavirus disease 2019 epidemic occurs, how to prevent and control hospital infection is a challenge faced by each medical institution. Under the normalization situation, building an effective prevention and control system is the premise and foundation for medical institutions to effectively prevent and control infection when dealing with clustered epidemics. According to the principles of control theory, medical institutions should quickly switch to an emergency state, and effectively deal with the external and internal infection risks brought by clustered epidemics by strengthening source control measures, engineering control measures, management control measures and personal protection measures. This article summarizes the experience of handling clustered outbreaks in medical institutions in the prevention and control of coronavirus disease 2019, and aims to provide a reference for medical institutions to take effective prevention and control measures when dealing with clustered outbreaks.
Objective To conduct a scoping review on the clinical research evidence for the treatment of coronavirus disease 2019 (COVID-19) with traditional Chinese medicine, identify relevant problems in the literature, and provide ideas for the follow-up research. Methods PubMed, Embase, the Cochrane Library, China National Knowledge Infrastructure, Wanfang Digital Journal Full-text Database, and China Biomedical Literature Database were searched from inception to July 21st, 2022. The clinical research evidence for the treatment of COVID-19 with traditional Chinese medicine was included, the data information was sorted out, and the results were descriptively analyzed. Results A total of 132 studies were included, including 53 randomized controlled trials, 17 non-randomized controlled trials, and 62 retrospective cohort studies, all of which were published between 2020 and 2022. The clinical studies were carried out in 19 provincial level regions, among which Hubei province had the largest number of studies (49.2%, 65/132). The sample sizes of the studies were mostly between 50 and 100 cases (43.2%, 57/132). Most of the studies had a treatment course of 0-14 days (50.0%, 66/132). The most compared intervention measures were traditional Chinese medicine + conventional western medicine treatment vs. conventional western medicine treatment, accounting for 75.0% (99/132) of the studies. The COVID-19 patients included in the studies were mainly mild and moderate. Outcome indicators included changes in symptoms/signs, laboratory indicators, CT indicators, clinical outcomes, safety indicators, functional scales, etc. The main adverse reactions/events in intervention/exposure groups were gastrointestinal reactions. Conclusions There has been a lot of clinical research evidence on the treatment of COVID-19 by traditional Chinese medicine. To provide strong evidence support for the treatment of COVID-19 by traditional Chinese medicine, more clinical trials with large samples and international collaboration are needed in the future.
ObjectiveTo investigate the antibody concentration and immune status of intensive care medical staff after vaccination against COVID-19. Methods From October 1, 2021 to February 28, 2022, the serial numbers of 47 hospitals were randomly selected by cluster stratified random sampling method. Blood samples were collected from 192 medical staff in intensive care department who had received inactivated novel coronavirus vaccine in 7 hospitals. The antibody concentration was determined by chemiluminescence method to find the antibody rule. Logistic regression analysis was used to determine the related factors affecting the production of antibodies. ResultsTotal antibody concentration of 192 blood samples was 23.25 (5.09, 270.22), IgG concentration was 0.94 (0.15, 4.48), IgM concentration was 0.05 (0.03, 0.12). Logistic regression analysis showed that the total antibody concentration might be related to gender and age, and the IgG concentration was significantly related to whether the third injection was administered. One hundred and twenty-seven people received 2 doses of inactivated vaccine, and the positive rate of IgG was the highest within 1 to 2 months, and decreased significantly after 3 months. The positive rate of IgG antibody was 95.4% within 60 days after receiving 3 doses of vaccine, 70% within 1 month after receiving the third dose of vaccine, and 100.0% within 1 to 2 months (P<0.05). The total antibody positive rate was 96.3% in people aged 17 to 35 years and 73.3% in people aged 36 to 58 years, showing statistical difference (P<0.05). The total antibody production rate of those who received the third dose of vaccine was 100.0%, and no severe case of COVID-19 occurred during the sampling period. Conclusions After the first, second, and third doses of COVID-19 vaccine, the total antibody concentration of the virus gradually increases to 100.0%, indicating initial immunity. However, the antibody concentration decreased gradually after 3 months of inoculation. The concentration of IgG in women is higher than that in men, and the concentration of antibody in young people is higher than that in middle-aged and elderly people during the same period.
Coronavirus disease 2019 (COVID-19) has spread rapidly around the world. In order to diagnose COVID-19 more quickly, in this paper, a depthwise separable DenseNet was proposed. The paper constructed a deep learning model with 2 905 chest X-ray images as experimental dataset. In order to enhance the contrast, the contrast limited adaptive histogram equalization (CLAHE) algorithm was used to preprocess the X-ray image before network training, then the images were put into the training network and the parameters of the network were adjusted to the optimal. Meanwhile, Leaky ReLU was selected as the activation function. VGG16, ResNet18, ResNet34, DenseNet121 and SDenseNet models were used to compare with the model proposed in this paper. Compared with ResNet34, the proposed classification model of pneumonia had improved 2.0%, 2.3% and 1.5% in accuracy, sensitivity and specificity respectively. Compared with the SDenseNet network without depthwise separable convolution, number of parameters of the proposed model was reduced by 43.9%, but the classification effect did not decrease. It can be found that the proposed DWSDenseNet has a good classification effect on the COVID-19 chest X-ray images dataset. Under the condition of ensuring the accuracy as much as possible, the depthwise separable convolution can effectively reduce number of parameters of the model.
ObjectiveBy summarizing the clinical characteristics of perioperative patients with cross infection of novel coronavirus in thoracic surgery ward, to guide the prevention and treatment of nosocomial infection during the anti-epidemic period.MethodsThe clinical data of 451 patients with chest diseases in the Department of Thoracic Surgery of Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology from January 1st to 24th, 2020 were analyzed and followed up. There were 245 surgical patients and 206 non-surgical patients.ResultsIn the department, 7 patients (7/451, 1.55%) were infected with the novel coronavirus and all of them were surgical patients, whose preoperative imaging data did not reveal the imaging changes of novel coronavirus. There were 5 males and 2 females, aged 56 to 68 years. The patients with old age, smoking, surgery, coronary heart disease, chronic liver disease and tumor history were more susceptible to infection. From the spatial distribution of patient beds, it was found that the distance among infected patients was greater than 1 m, and no cross infection was found in the other patients of the same ward. During follow-up, two family members of noninfected patients were found to be infected one week after discharge. However, there was no overlap of spatiotemporal distribution between the family members and the infected patients during the hospitalization period.ConclusionThe novel coronavirus pneumonia rate in the department of thoracic surgery is low, which may be opportunistic infection. At the same time, a good control and prevention of epidemic disease can reduce the occurrence of cross infection in the department of thoracic surgery.
ObjectiveTo provide recommendations for the management of intensive care unit patients without novel coronavirus disease 2019 (COVID-19).MethodsWe set up a focus group urgently and identified five key clinical issues through discussion. Total 23 databases or websites including PubMed, National Guideline Clearing-House, Chinese Center for Disease Control and Prevention and so on were searched from construction of the library until February 28, 2020. After group discussion and collecting information, we used GRADE system to classify the evidence and give recommendations. Then we apply the recommendations to manage pediatric intensive care unit in the department of critical care medicine in our hospital. ResultsWe searched 13 321 articles and finally identified 21 liteteratures. We discussed twice, and five recommendations were proposed: (1) Patients should wear medical surgical masks; (2) Family members are not allowed to visit the ward and video visitation are used; (3) It doesn’t need to increase the frequency of environmental disinfection; (4) We should provide proper health education about the disease to non-medical staff (workers, cleaners); (5) Medical staff do not need wear protective clothing. We used these recommendations in intensive care unit management for 35 days and there was no novel coronavirus infection in patients, medical staff or non-medical staff. ConclusionThe use of evidence-based medicine for emergency recommendation is helpful for the scientific and efficient management of wards, and is also suitable for the management of general intensive care units in emergent public health events.
This study reports the surgical treatment of a female patient at age of 64 years with novel coronavirus (SARS-CoV-2) latent infection complicated with esophageal foreign body perforation with no significant changes in the lung CT. The patient was confirmed as SARS-CoV-2 infection on the 4th day after surgery and then was transferred into the Department of Infectious Disease in our hospital for treatment. This case has guiding value for the operation of thoracic surgery during the outbreak of novel coronavirus pneumonia.
Recently a COVID-19 pneumonia pandemic caused by a novel coronavirus 2019-nCoV has broken out over the world. In order to better control the spread of the pandemic, there’s an urgent need to extensively study the virus’ origin and the mechanisms for its infectivity and pathogenicity. Spike protein is a special structural protein on the surface of coronavirus. It contains important information about the evolution of the virus and plays critical roles in the processes of cellular recognition and entry. In the past decades, spike protein has always been one of the most important objects in research works on coronaviruses closely related to human life. In this review we introduce these research works related to spike proteins, hoping it will provide reasonable ideas for the control of the current pandemic, as well as for the diagnosis and treatment of COVID-19.
