Long-Term Follow-Up Study of COVID-19: Evaluation on Thin-Slice CT

Purpose To retrospectively analyse the CT imaging during the long-term follow-up of COVID-19 patients after discharge. Patients and Methods A total of 122 patients entered the study group. All patients underwent CT examinations. The CT images, which included distribution and imaging signs, were evaluated by two chest radiologists. Laboratory examinations included routine blood work, biochemical testing, and SARS-CoV-2 antibody screening. Statistical methods include chi-square, Fisher’s exact test, one-way analysis of variance, rank sum test and logistic regression by SPSS 17.0. Results There were 22 (18.0%) patients in the mild group, 74 (60.7%) patients in the moderate group, and 26 (21.3%) patients in the severe–critical group. The median follow-up interval was 405 days (378.0 days, 462.8 days). Only monocytes, prothrombin activity, and γ-glutamyltransferase showed significant differences among the three groups. We found that the more severe the patient’s condition, the more SARS-CoV-2 IgG antibodies existed. Only 11 patients (11.0%) showed residual lesions on CT. The CT manifestations included irregular linear opacities in nine cases (9.0%), reticular patterns in six cases (6.0%), and GGOs in five cases (5.0%). Conclusion The proportion of residual lesions on CT in COVID-19 patients was significantly reduced after long-term follow-up. The patients’ age and disease conditions were positively correlated with residual lesions.

A Bioinformatic Approach Based on Systems Biology to Determine the Effects of SARS-CoV-2 Infection in Patients with Hypertrophic Cardiomyopathy

Recently, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), has infected millions of individuals worldwide. While COVID-19 generally affects the lungs, it also damages other organs, including those of the cardiovascular system. Hypertrophic cardiomyopathy (HCM) is a common genetic cardiovascular disorder. Studies have shown that HCM patients with COVID-19 have a higher mortality rate;however, the reason for this phenomenon is not yet elucidated. Herein, we conducted transcriptomic analyses to identify shared biomarkers between HCM and COVID-19 to bridge this knowledge gap. Differentially expressed genes (DEGs) were obtained using the Gene Expression Omnibus ribonucleic acid (RNA) sequencing datasets, GSE147507 and GSE89714, to identify shared pathways and potential drug candidates. We discovered 30 DEGs that were common between these two datasets. Using a combination of statistical and biological tools, protein-protein interactions were constructed in response to these findings to support hub genes and modules. We discovered that HCM is linked to COVID-19 progression based on a functional analysis under ontology terms. Based on the DEGs identified from the datasets, a coregulatory network of transcription factors, genes, proteins, and microRNAs was also discovered. Lastly, our research suggests that the potential drugs we identified might be helpful for COVID-19 therapy.

Experimental Investigations of a Solar Water Treatment System for Remote Desert Areas of Pakistan

Pakistan is among the countries that have already crossed the water scarcity line, and the situation is worsened due to the recent pandemic. This is because the major budget of the country is shifted to primary healthcare activities from other development projects that included water treatment and transportation infrastructure. Consequently, water-borne diseases have increased drastically in the past few months. Therefore, there is a dire need to address this issue on a priority basis to ameliorate the worsening situation. One possible solution is to shift the focus/load from mega-projects that require a plethora of resources, money, and time to small domestic-scale systems for water treatment. For this purpose, domestic-scale solar stills are designed, fabricated, and tested in one of the harshest climatic condition areas of Pakistan, Rahim Yar Khan. A comprehensive overview of the regional climatology, including wind speed, solar potential, and ambient temperature is presented for the whole year. The analysis shows that the proposed system can adequately resolve the drinking water problems of deprived areas of Pakistan. The average water productivity of 1.5 L/d/m2 is achieved with a total investment of PKR 3000 (<$20). This real site testing data will serve as a guideline for similar system design in other arid areas globally.

The application of WeChat applet and integrity propaganda and education in outpatient pre-examination during the prevalence of COVID-19 / 医学研究生学报

ObjectiveDuring the prevention and control of COVID-19, it is a difficult problem to obtain the individual epidemiological status of outpatients efficiently and accurately in a large comprehensive third-grade class-A hospital. To discuss the application and effect of WeChat applet and integrity propaganda and education in outpatient pre-examination during the prevention and control of COVID-19.MethodsFirstly, the outpatients were treated with integrity propaganda and education (like informing the law and regulations, recording the personal credit) at the outpatient pre-examination office. Secondly, let them take real-name authentication in the hospital self-developed WeChat applet. Thirdly, the outpatients filled in the epidemiological questionnaire related to COVID-19 by WeChat. The differences between before using the application (8,186 patients) and after using (7,361 patients) were compared in pre-examination time and concealing the incidence of an individual's epidemiological history.ResultsAfter the application of WeChat applet and integrity propaganda and education, the pre-examination time after using application [(1.07±0.23)min] was shorter than that before using[(2.15±0.37) min] (P<0.05). The concealment rate of epidemiological history was 0.05% before using application and zero after using.ConclusionWeChat applet and integrity propaganda and education can shorten the pre-examination time of covid-19 and reduce the occurrence of concealing personal epidemiological history.

What is Discussed about COVID-19: A Multi-Modal Framework for Analyzing Microblogs from Sina Weibo without Human Labeling

Starting from late 2019, the new coronavirus disease (COVID-19) has become a global crisis. With the development of online social media, people prefer to express their opinions and discuss the latest news online. We have witnessed the positive influence of online social media, which helped citizens and governments track the development of this pandemic in time. It is necessary to apply artificial intelligence (AI) techniques to online social media and automatically discover and track public opinions posted online. In this paper, we take Sina Weibo, the most widely used online social media in China, for analysis and experiments. We collect multi-modal microblogs about COVID-19 from 2020/1/1 to 2020/3/31 with a web crawler, including texts and images posted by users. In order to effectively discover what is being discussed about COVID-19 without human labeling, we propose a unified multi-modal framework, including an unsupervised short-text topic model to discover and track bursty topics, and a self-supervised model to learn image features so that we can retrieve related images about COVID-19. Experimental results have shown the effectiveness and superiority of the proposed models, and also have shown the considerable application prospects for analyzing and tracking public opinions about COVID-19.

Coping Abilities of Nursing Graduates Under Public Health Emergency (COVID-19): A Cross-Sectional Study (preprint)

Background: Public health emergencies are serious social problems, threatening people's lives, causing considerable economic losses, and related to all mankind life and health and safety. Nurses are essential in the fight against the public health emergency, corona virus disease 2019 (COVID-19). Nursing graduates are considered as backup health care providers for licensed nurses, the coping abilities and crisis management of nursing students at present deserve attention all around the world. Methods: 2035 graduating nursing graduates were invited to participate in mobile phone app-based survey from Feb 6 to 20, 2020. The demographic items, psychological and behavioral responses, and the coping abilities were conducted. Multiple linear regression was used to identify the independent factors to nursing graduates’ coping abilities under COVID-19.Results: 1992 submitted were valid. Multiple linear regression analysis showed that Confidence to overcome difficulties, Optimism, Active coping, Help seeking and Practice hospital as designated treatment unit were independently associated with the positive coping of graduates. Fear of COVID-19, Optimism, Avoidance, Help seeking and Severity of epidemic around were independently associated with the negative coping of graduates.

Corticosteroid Therapy of Patients in ICU with Coronavirus Disease 2019(COVID-19): A Single-center, Retrospective, Observational study (preprint)

The authors have withdrawn this preprint due to author disagreement.

An Antioxidant Enzyme Therapeutic for COVID-19 (preprint)

The COVID-19 pandemic has taken a significant toll on people worldwide, and there are currently no specific antivirus drugs or vaccines. We report herein a therapeutic based on catalase, an antioxidant enzyme that can effectively breakdown hydrogen peroxide and minimize the downstream reactive oxygen species, which are excessively produced resulting from the infection and inflammatory process. Catalase assists to regulate production of cytokines, protect oxidative injury, and repress replication of SARS-CoV-2, as demonstrated in human leukocytes and alveolar epithelial cells, and rhesus macaques, without noticeable toxicity. Such a therapeutic can be readily manufactured at low cost as a potential treatment for COVID-19.

Systematic investigations of COVID-19 in 283 cancer patients (preprint)

Background: Cancer patients are considered to be highly susceptible to viral infections, however, the comprehensive features of COVID-19 in these patients remained largely unknown. The present study aimed to assess the clinical characteristics and outcomes of COVID-19 in a large cohort of cancer patients. Design, Setting, and Participants: Data of consecutive cancer patients admitted to 33 designated hospitals for COVID-19 in Hubei province, China from December 17, 2019 to March 18, 2020 were retrospectively collected. The follow-up cutoff date was April 02, 2020. The clinical course and survival status of the cancer patients with COVID-19 were measured, and the potential risk factors of severe events and death were assessed through univariable and multivariable analyses. Results: A total of 283 laboratory confirmed COVID-19 patients (50% male; median age, 63.0 years [IQR, 55.0 to 70.0]) with more than 20 cancer types were included. The overall mortality rate was 18% (50/283), and the median hospitalization stay for the survivors was 26 days. Amongst all, 76 (27%) were former cancer patients with curative resections for over five years without recurrence. The current cancer patients exhibited worse outcomes versus former cancer patients (overall survival, HR=2.45, 95%CI 1.10 to 5.44, log-rank p=0.02; mortality rate, 21% vs 9%). Of the 207 current cancer patients, 95 (46%) have received recent anti-tumor treatment, and the highest mortality rate was observed in the patients receiving recent chemotherapy (33%), followed by surgery (26%), other anti-tumor treatments (19%), and no anti-tumor treatment (15%). In addition, a higher mortality rate was observed in patients with lymphohematopoietic malignancies (LHM) (53%, 9/17), and all seven LHM patients with recent chemotherapy died. Multivariable analysis indicated that LHM (p=0.001) was one of the independent factors associating with critical illness or death. Conclusions: This is the first systematic study comprehensively depicting COVID-19 in a large cancer cohort. Patients with tumors, especially LHM, may have poorer prognosis of COVID-19. Additional cares are warranted and non-emergency anti-tumor treatment should be cautiously used for these patients under the pandemic.

Toilets dominate environmental detection of SARS-CoV-2 virus in a hospital (preprint)

Background: Respiratory and faecal aerosols play a suspected role in transmitting the SARS-CoV-2 virus. We performed extensive environmental sampling in a dedicated hospital building for Covid-19 patients in both toilet and non-toilet environments, and analysed the associated environmental factors. Methods: We collected data of the Covid-19 patients. 107 surface samples, 46 air samples, two exhaled condensate samples, and two expired air samples were collected were collected within and beyond the four three-bed isolation rooms. We reviewed the environmental design of the building and the cleaning routines. We conducted field measurement of airflow and CO2 concentrations. Findings: The 107 surface samples comprised 37 from toilets, 34 from other surfaces in isolation rooms (ventilated at 30-60 L/s), and 36 from other surfaces outside isolation rooms in the hospital. Four of these samples were positive, namely two ward door-handles, one bathroom toilet-seat cover and one bathroom door-handle; and three were weakly positive, namely one bathroom toilet seat, one bathroom washbasin tap lever and one bathroom ceiling-exhaust louvre. One of the 46 air samples was weakly positive, and this was a corridor air sample. The two exhaled condensate samples and the two expired air samples were negative. Interpretation: The faecal-derived aerosols in patients' toilets contained most of the detected SARS-CoV-2 virus in the hospital, highlighting the importance of surface and hand hygiene for intervention.