Epidemiological Characteristics and Antimicrobial Resistance Changes of Carbapenem-Resistant Klebsiella pneumoniae and Acinetobacter baumannii under the COVID-19 Outbreak: An Interrupted Time Series Analysis in a Large Teaching Hospital.

BACKGROUND: To investigate the epidemiological characteristics and resistance changes of carbapenem-resistant organisms (CROs) under the COVID-19 outbreak to provide evidence for precise prevention and control measures against hospital-acquired infections during the pandemic. METHODS: The distribution characteristics of CROs (i.e., carbapenem-resistant Klebsiella pneumoniae and Acinetobacter baumannii) were analyzed by collecting the results of the antibiotic susceptibility tests of diagnostic isolates from all patients. Using interrupted time series analysis, we applied Poisson and linear segmented regression models to evaluate the effects of COVID-19 on the numbers and drug resistance of CROs. We also conducted a stratified analysis using the Cochran-Mantel-Haenszel test. RESULTS: The resistance rate of carbapenem-resistant Acinetobacter baumannii (CRAB) was 38.73% higher after the COVID-19 outbreak compared with before (p < 0.05). In addition, the long-term effect indicated that the prevalence of CRAB had a decreasing trend (p < 0.05). However, the overall resistance rate of Klebsiella pneumoniae did not significantly change after the COVID-19 outbreak. Stratified analysis revealed that the carbapenem-resistant Klebsiella pneumoniae (CRKP) rate increased in females (OR = 1.98, p < 0.05), those over 65 years old (OR = 1.49, p < 0.05), those with sputum samples (OR = 1.40, p < 0.05), and those in the neurology group (OR = 2.14, p < 0.05). CONCLUSION: The COVID-19 pandemic has affected the change in nosocomial infections and resistance rates in CROs, highlighting the need for hospitals to closely monitor CROs, especially in high-risk populations and clinical departments. It is possible that lower adherence to infection control in crowded wards and staffing shortages may have contributed to this trend during the COVID-19 pandemic, which warrants further research.

Ascertaining the Online Learning Behaviors and Formative Assessments Affecting Students' Academic Performance during the COVID-19 Pandemic: A Case Study of a Computer Science Course

Prior education research has focused on using learning analytics to predict the academic performance of Massive Online Learning Courses (MOOCs) and e- learning courses in universities. There is limited research on online learning that has been transitioned from physical classes and that has continued to use active learning approaches in an online environment. This study aims to determine the variables affecting students' academic performance for a computing course in a research-intense university during the COVID-19 pandemic. Variables that are indicative of self-regulated learning such as time management, frequency of accessing learning materials and the Learning Management System (LMS), participation in assessment activities and discussions, and the results of formative assessments were extracted from the LMS reports and log files to predict the students' total marks and final exam results. The findings revealed that good time management and active participation are important for academic success. The results also supported the model for the early prediction of summative assessment performance using formative assessment results. Additionally, this study concludes that the gap in predictive power between formative assessment results and online learning behaviors is small. This research is considered unique because it demonstrates predictive models for students' academic success for an institution that was forced to transition from physical to online learning. It highlights the importance of self-regulated learning behavior and formative assessments in the contemporary era.

Analysis of 4 cases of children with false-positive results of novel coronavirus-specific antibody.

BACKGROUND: This study attempts to explore the influencing factors and solutions of the colloidal gold method for novel coronavirus (2019-nCoV)-specific IgM/IgG antibody detection, summarize the clinical experience and perfect the examination process, improving the application value of antibody detection in COVID-19 diagnosis. METHODS: A total of 13,329 peripheral whole blood/plasma/serum samples were obtained for COVID-19 screening from children who visited the Children's Hospital of the Capital Institute of Pediatrics outpatient clinic from April 22, 2020, to November 30, 2020. The colloidal gold method was adopted for 2019-nCoV-specific IgM/IgG antibody detection. The virus nucleic acid test results, clinical records, and serum protein fingerprint results of antibody-positive patients were collected. RESULTS: All samples were examined using the colloidal gold method with two 2019-nCoV-specific IgM/IgG antibody detection kits. Four patients were tested single antibody-positive using both kits. The details were as follows: two cases of IgM ( +) and IgG (-) using plasma and serum separately, two cases of IgM (-) and IgG ( +) using serum and whole blood. The protein fingerprinting results and nucleic acid tests of 2019-nCoV antibodies were negative in the 4 cases. Considering the epidemiological history, clinical manifestations, and test results, these 4 children were ruled out for 2019-nCoV infection. CONCLUSIONS: When the colloidal gold method was used to detect 2019-nCoV-specific IgM/IgG antibodies, it was important to ascertain the test results as precisely as possible. Specimen type and patient history may interfere with the diagnosis.

A Smarter and Greener Olympics: Mediatization and Public Reception in the Preparation Stage of the Beijing 2022 Winter Olympics

In the post-COVID-19 era, the mediatization of sports mega-events is timely and notable. This study focuses on the 2022 Olympic Winter Games in Beijing and investigates how mediated processes influenced the Olympics. The data were gathered in two ways: we examined 783 WeChat posts from three salient Chinese media institutions, namely, the Beijing 2022 Winter Olympics Organising Committee (BOCOG), China Central Television (CCTV), and Beijing Television (BTV), as well as conducted 21 semi-structured interviews with BOCOG staff and members of the general public. We discovered that the Games were narrated around two major themes?the development of technology and ?going green??both of which were heavily influenced by the country?s national agenda. As a result, the Chinese public was thoroughly immersed in the tech-savvy Olympics scenario, and the Green Olympics concept was widely shared in their daily practices. This study adds to the literature by incorporating communicative figuration as an analytical framework to improve the quantitative and qualitative dimensions of media saturation theory. Additionally, this research sheds light on the study of sports mediatization in China in the context of a pandemic.

Effects of different delivery modes on teaching biomedical science practical skills in higher education during the 2021 pandemic measures.

The COVID-19 pandemic related measures had augmented the rise of online education. While online teaching had mitigated the negative impacts from educational institutional closures, it was unable to displace hands-on biomedical laboratory practical lessons effectively. Without practical sessions, there was concern over the imparting of laboratory skills even with video demonstrations. To investigate the effectiveness of different delivery modes in imparting laboratory skills, theoretical and practical student assessments were analyzed alongside an anonymous survey on their motivation and prior experience. The undergraduate students were exposed to (1) instructor-live demonstration; (2) video demonstration or (3) no demonstration prior to the practical test which was a plasmid extraction. Significantly higher mini-prep yields and purity were found for both instructor-live and video demonstrations compared to no demonstration. Comparison with pre-pandemic theoretical assessment performance showed no significant differences despite longer contact hours during pre-pandemic times. Prior lab experience and motivation for selecting the course did not significantly affect student mini-prep yields. In conclusion, our findings suggest that video demonstrations were as effective as instructor-live demonstrations during the pandemic without noticeably compromising the teaching and learning of biomedical laboratory skills.

Free riding and insurer carbon-linked investment

The paper develops a two-insurer contingent claim framework to evaluate their equities. One insurer conducts carbon-linked investment, while the other conducts conventional (non-carbon-linked) investment. The free-riding issue becomes essential because of the carbon-emission externality. We show that the life insurance policyholders are free riders when either the return of carbon-linked or the conventional investment increases. But the cost burden of policyholder protection is the reduced insurer interest margin. The results also apply to the increased carbon-linked investment volatility and the different coronavirus COVID-19 impacts on the two-insurer interest margins. In the soundness test, we show that insurance stability at the cost of insurer profits is less significant when the carbon-linked investor's barrier increases. Free riding would be intimately relevant to insurance and carbon-emission environments in the barrier option model.

Preliminary estimates of the reproduction number of the Coronavirus disease (COVID-19) outbreak in Republic of Korea and Italy by 5 March 2020

The novel coronavirus disease 2019 (COVID-19) outbreak has caused 6088 cases and 41 deaths in Republic of Korea, and 3144 cases and 107 death in Italy by 5 March 2020, respectively. We modelled the transmission process in the Republic of Korea and Italy with a stochastic model, and estimated the basic reproduction number R0 as 2.6 (95% CI: 2.3-2.9) or 3.2 (95% CI: 2.9-3.5) in the Republic of Korea, under the assumption that the exponential growth starting on 31 January or 5 February 2020, and 2.6 (95% CI: 2.3-2.9) or 3.3 (95% CI: 3.0-3.6) in Italy, under the assumption that the exponential growth starting on 5 February or 10 February 2020, respectively.

Preliminary estimation of the novel Coronavirus disease (COVID-19) cases in Iran: a modelling analysis based on overseas cases and air travel data. (Coronavirus (COVID-19) collection.)

As of March 1, 2020, Iran had reported 987 novel coronavirus disease (COVID-19) cases, including 54 associated deaths. At least six neighboring countries (Bahrain, Iraq, Kuwait, Oman, Afghanistan, and Pakistan) had reported imported COVID-19 cases from Iran. In this study, air travel data and the numbers of cases from Iran imported into other Middle Eastern countries were used to estimate the number of COVID-19 cases in Iran. It was estimated that the total number of cases in Iran was 16 533 (95% confidence interval: 5925-35 538) by February 25, 2020, before the UAE and other Gulf Cooperation Council countries suspended inbound and outbound flights from Iran.

The relative transmissibility of asymptomatic COVID-19 infections among close contacts. (Coronavirus (COVID-19) collection.)

Asymptomatic transmission of the coronavirus disease 2019 is an important topic. A recent study in China showed that transmissibility of the asymptomatic cases is comparable to that of symptomatic cases. Here, we discuss that the conclusion may depend on how we interpret the data. To the best of our knowledge, this is the first time the relative transmissibility of asymptomatic COVID-19 infections is quantified.

Pandemic of the aging society - sporadic cerebral small vessel disease.

ABSTRACT: Age-related sporadic cerebral small vessel disease (CSVD) has gained increasing attention over the past decades because of its increasing prevalence associated with an aging population. The widespread application of and advances in brain magnetic resonance imaging in recent decades have significantly increased researchers' understanding in the in vivo evolution of CSVD, its impact upon the brain, its risk factors, and the mechanisms that explain the various clinical manifestation associated with sporadic CSVD. In this review, we aimed to provide an update on the pathophysiology, risk factors, biomarkers, and the determinants and spectrum of the clinical manifestation of sporadic CSVD.

Artificial intelligence for prediction of COVID-19 progression using CT imaging and clinical data.

OBJECTIVES: Early recognition of coronavirus disease 2019 (COVID-19) severity can guide patient management. However, it is challenging to predict when COVID-19 patients will progress to critical illness. This study aimed to develop an artificial intelligence system to predict future deterioration to critical illness in COVID-19 patients. METHODS: An artificial intelligence (AI) system in a time-to-event analysis framework was developed to integrate chest CT and clinical data for risk prediction of future deterioration to critical illness in patients with COVID-19. RESULTS: A multi-institutional international cohort of 1,051 patients with RT-PCR confirmed COVID-19 and chest CT was included in this study. Of them, 282 patients developed critical illness, which was defined as requiring ICU admission and/or mechanical ventilation and/or reaching death during their hospital stay. The AI system achieved a C-index of 0.80 for predicting individual COVID-19 patients' to critical illness. The AI system successfully stratified the patients into high-risk and low-risk groups with distinct progression risks (p < 0.0001). CONCLUSIONS: Using CT imaging and clinical data, the AI system successfully predicted time to critical illness for individual patients and identified patients with high risk. AI has the potential to accurately triage patients and facilitate personalized treatment. KEY POINT: • AI system can predict time to critical illness for patients with COVID-19 by using CT imaging and clinical data.

How psychiatrists coordinate treatment for COVID-19: a retrospective study and experience from China.

BACKGROUND: Patients with COVID-19 are at high risk of developing mental health problems; however, the prevalence and management of mental disorders and how psychiatrists coordinate the treatment are unclear. AIMS: We aimed to investigate the mental health problems of patients infected with COVID-19 and to identify the role of psychiatrists in the clinical treatment team during the pandemic. We also share the experience of psychiatric consultations of patients with COVID-19 in Shanghai, China. METHODS: We analysed data from the psychiatric medical records of 329 patients with COVID-19 in the Shanghai Public Health Clinical Center from 20 January to 8 March 2020. We collected information including sociodemographic characteristics, whether patients received psychiatric consultation, mental health symptoms, psychiatric diagnoses, psychiatric treatments and severity level of COVID-19. RESULTS: Psychiatric consultations were received by 84 (25.5%) patients with COVID-19. The most common symptoms of mental health problems were sleep disorders (75%), anxiety (58.3%) and depressive symptoms (11.9%). The psychiatric consultation rate was highest in critically ill patients (69.2%), with affective symptoms or disturbed behaviour as their main mental health problems. Psychiatric diagnoses for patients who received consultation included acute stress reaction (39.3%), sleep disorders (33.3%), anxiety (15.5%), depression (7.1%) and delirium (4.8%). In terms of psychiatric treatments, 86.9% of patients who received psychiatric consultation were treated with psychotropic medications, including non-benzodiazepine sedative-hypnotic agents (54.8%), antidepressants (26.2%), benzodiazepines (22.6%) and antipsychotics (10.7%). Among the 76 patients who were discharged from the hospital, 79% had recovered from mental health problems and were not prescribed any psychotropic medications. The symptoms of the remaining 21% of patients had improved and they were prescribed medications to continue the treatment. CONCLUSIONS: This is the first study to report psychiatric consultations for patients with COVID-19. Our study indicated that a considerable proportion of patients with COVID-19, especially critically ill cases, experienced mental health problems. Given the remarkable effect of psychiatric treatments, we recommend that psychiatrists be timely and actively involved in the treatment of COVID-19.

Social Support and Loneliness Among Chinese Caregivers of Children With Chronic Kidney Disease During the COVID-19 Pandemic: A Propensity Score Matching Analysis.

To evaluate social support and loneliness as well as their association among caregivers of children with chronic kidney disease (CKD) from China during the coronavirus disease 2019 (COVID-19) pandemic. We collected data for caregivers of children with CKD and caregivers of healthy children and matched the two groups using propensity score matching (PSM). We compared the differences in social support and loneliness between the two groups after matching and analyzed the relationship between social support and loneliness in the observation group. Before PSM, we analyzed the data for 247 caregivers of children with CKD and 315 caregivers of healthy children from 13 provinces. After PSM, the two groups each included 202 caregivers. The social support score of caregivers of children with CKD was lower than that of caregivers of healthy children (P < 0.002), while the loneliness score was higher for caregivers of children with CKD than for caregivers of healthy children (P < 0.008). The social support score was negatively correlated with the loneliness score (r = -0.598, P < 0.001). Caregivers of children with CKD experienced less social support and greater loneliness than caregivers of healthy children during the COVID-19 pandemic. Therefore, greater attention should be paid to providing social support for caregivers of CKD children and to improving the ability of these caregivers to cope with loneliness.

The phenotypic changes of γδ T cells in COVID-19 patients.

A novel pneumonia-associated respiratory syndrome named coronavirus disease-2019 (COVID-19), which was caused by SARS-CoV-2，broke out in Wuhan, China, in the end of 2019. Unfortunately, there is no specific antiviral agent or vaccine available to treat SARS-CoV-2 infections. The information regarding the immunological characteristics in COVID-19 patients remains limited. Here, we collected the blood samples from 18 healthy donors (HD) and 38 COVID-19 patients to analyze changes on γδ T cell population. In comparison with HD, the γδ T cell percentage decreased, while the activation marker CD25 expression increased in response to SARS-CoV-2 infection. Interestingly, the CD4 expression was upregulated in γδ T cells reflecting the occurrence of a specific effector cell population, which may serve as a biomarker for the assessment of SARS-CoV-2 infection.

Naturally activated adaptive immunity in COVID-19 patients.

Coronavirus disease-2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus (SARS-CoV-2) has rapidly spread worldwide, threatening the health and lives of many people. Unfortunately, information regarding the immunological characteristics of COVID-19 patients remains limited. Herein, we collected blood samples from 18 healthy donors (HDs) and 38 COVID-19 patients to analyse changes in the adaptive immune cell populations and their phenotypes. We observed that the lymphocyte percentage moderately decreased, CD4 and CD8 T cell percentage among lymphocytes were similar, and B cell percentage was increased in COVID-19 patients in comparison to that in HDs. T cells, especially CD8 T cells, showed an enhanced expression of late activation marker CD25 and exhaustion marker PD-1. Importantly, SARS-CoV-2 infection increased the percentage of T follicular helper- and germinal centre B-like cells in the blood. The parameters in COVID-19 patients remained unchanged across various age groups. Therefore, we demonstrated that the T and B cells are activated naturally and are functional during SARS-CoV-2 infection. These data provide evidence that the adaptive immunity in most patients could be primed to induce a significant immune response against SARS-CoV-2 infection upon receiving standard medical care.

Artificial Intelligence Augmentation of Radiologist Performance in Distinguishing COVID-19 from Pneumonia of Other Origin at Chest CT.

Background Coronavirus disease 2019 (COVID-19) and pneumonia of other diseases share similar CT characteristics, which contributes to the challenges in differentiating them with high accuracy. Purpose To establish and evaluate an artificial intelligence (AI) system for differentiating COVID-19 and other pneumonia at chest CT and assessing radiologist performance without and with AI assistance. Materials and Methods A total of 521 patients with positive reverse transcription polymerase chain reaction results for COVID-19 and abnormal chest CT findings were retrospectively identified from 10 hospitals from January 2020 to April 2020. A total of 665 patients with non-COVID-19 pneumonia and definite evidence of pneumonia at chest CT were retrospectively selected from three hospitals between 2017 and 2019. To classify COVID-19 versus other pneumonia for each patient, abnormal CT slices were input into the EfficientNet B4 deep neural network architecture after lung segmentation, followed by a two-layer fully connected neural network to pool slices together. The final cohort of 1186 patients (132 583 CT slices) was divided into training, validation, and test sets in a 7:2:1 and equal ratio. Independent testing was performed by evaluating model performance in separate hospitals. Studies were blindly reviewed by six radiologists without and then with AI assistance. Results The final model achieved a test accuracy of 96% (95% confidence interval [CI]: 90%, 98%), a sensitivity of 95% (95% CI: 83%, 100%), and a specificity of 96% (95% CI: 88%, 99%) with area under the receiver operating characteristic curve of 0.95 and area under the precision-recall curve of 0.90. On independent testing, this model achieved an accuracy of 87% (95% CI: 82%, 90%), a sensitivity of 89% (95% CI: 81%, 94%), and a specificity of 86% (95% CI: 80%, 90%) with area under the receiver operating characteristic curve of 0.90 and area under the precision-recall curve of 0.87. Assisted by the probabilities of the model, the radiologists achieved a higher average test accuracy (90% vs 85%, Δ = 5, P < .001), sensitivity (88% vs 79%, Δ = 9, P < .001), and specificity (91% vs 88%, Δ = 3, P = .001). Conclusion Artificial intelligence assistance improved radiologists' performance in distinguishing coronavirus disease 2019 pneumonia from non-coronavirus disease 2019 pneumonia at chest CT. © RSNA, 2020 Online supplemental material is available for this article.

Performance of Radiologists in Differentiating COVID-19 from Non-COVID-19 Viral Pneumonia at Chest CT.

Background Despite its high sensitivity in diagnosing coronavirus disease 2019 (COVID-19) in a screening population, the chest CT appearance of COVID-19 pneumonia is thought to be nonspecific. Purpose To assess the performance of radiologists in the United States and China in differentiating COVID-19 from viral pneumonia at chest CT. Materials and Methods In this study, 219 patients with positive COVID-19, as determined with reverse-transcription polymerase chain reaction (RT-PCR) and abnormal chest CT findings, were retrospectively identified from seven Chinese hospitals in Hunan Province, China, from January 6 to February 20, 2020. Two hundred five patients with positive respiratory pathogen panel results for viral pneumonia and CT findings consistent with or highly suspicious for pneumonia, according to original radiologic interpretation within 7 days of each other, were identified from Rhode Island Hospital in Providence, RI. Three radiologists from China reviewed all chest CT scans (n = 424) blinded to RT-PCR findings to differentiate COVID-19 from viral pneumonia. A sample of 58 age-matched patients was randomly selected and evaluated by four radiologists from the United States in a similar fashion. Different CT features were recorded and compared between the two groups. Results For all chest CT scans (n = 424), the accuracy of the three radiologists from China in differentiating COVID-19 from non-COVID-19 viral pneumonia was 83% (350 of 424), 80% (338 of 424), and 60% (255 of 424). In the randomly selected sample (n = 58), the sensitivities of three radiologists from China and four radiologists from the United States were 80%, 67%, 97%, 93%, 83%, 73%, and 70%, respectively. The corresponding specificities of the same readers were 100%, 93%, 7%, 100%, 93%, 93%, and 100%, respectively. Compared with non-COVID-19 pneumonia, COVID-19 pneumonia was more likely to have a peripheral distribution (80% vs 57%, P < .001), ground-glass opacity (91% vs 68%, P < .001), fine reticular opacity (56% vs 22%, P < .001), and vascular thickening (59% vs 22%, P < .001), but it was less likely to have a central and peripheral distribution (14% vs 35%, P < .001), pleural effusion (4% vs 39%, P < .001), or lymphadenopathy (3% vs 10%, P = .002). Conclusion Radiologists in China and in the United States distinguished coronavirus disease 2019 from viral pneumonia at chest CT with moderate to high accuracy. © RSNA, 2020 Online supplemental material is available for this article. A translation of this abstract in Farsi is available in the supplement. ترجمه چکیده این مقاله به فارسی، در ضمیمه موجود است.

[Clinical efficacy of Matrine and Sodium Chloride Injection in treatment of 40 cases of COVID-19].

In this paper, we analyzed medical records of 40 patients with coronavirus disease 2019(COVID-19), in order to explore the clinical efficacy of Matrine and Sodium Chloride Injection in the treatment of COVID-19. The investigation was based on the results of a previous animal test, which was aimed to investigate and confirme the clinical efficacy of Matrine and Sodium Chloride Injection in the treatment of COVID-19. The animal test demonstrated that Matrine and Sodium Chloride Injection has a significant therapeutic effect on the human coronavirus pneumonia for the model mice. The lung inhibition index reached up to 86.86%. The evaluation was conducted on 40 confirmed cases of COVID-19 treated at Jingzhou Hospital of Infectious Disease(Chest Hospital) of Hubei Pro-vince from January 30~(th) to March 21~(th), 2020. In these cases, patients were treated with other integrated Chinese and Western medicines regimens in the recommended Matrine and Sodium Chloride Injection diagnosis and treatment regimen. The clinical manifestations, laboratory data, nucleic acid clearance time, and imaging data were compared and analyzed before and after treatment. After administration with Matrine and Sodium Chloride Injection, the clinical symptoms of 40 cases were alleviated markedly, and their blood analysis and biochemical indexes returned to normal. The lung CT showed more than 50% of lesion absorption rate, and the viral nucleic acid test showed the average clearance time of patients was 16.6 days, and the average length of hospital stay was 25.9 days. After administration with Matrine and Sodium Chloride Injection, the symptoms of cough and fatigue were alleviated significantly, and the appetite was significantly improved compared with before, especially for patients with gastrointestinal symptoms. Additionally, laboratory indicators, especially absolute value and ratio of lymphocytes and CRP were significantly alleviated. According to the chest CT for short-term review, the absorption of lung lesions was faster than before, especially for grid-like and fibrotic lesions. Compared with antiviral drugs, such as Abidol and Kriging, the nucleic acid clearance time was significantly shorter than the cases treated with Matrine and Sodium Chloride Injection. The clinical effective rate of 40 cases was 100.0%. We believed that Matrine and Sodium Chloride Injection have a good clinical effect in the treatment of COVID-19, and suggested increasing the clinical application and further conducting large-sample-size cli-nical verification.