Dermatomyositis Flare After a COVID-19 Infection Successfully Treated with Rituximab: A Case Report and Literature Review.

Introduction: Since the beginning of the coronavirus disease 2019 (COVID-19) pandemic, there has been a sudden surge in the incidence of several immune-mediated diseases, including dermatomyositis. The reported cases of COVID-19-related dermatomyositis are heterogeneous in their clinical presentation and implemented therapies. Case Study: We report a 23-year-old female patient diagnosed with a 3-year history of dermatomyositis. She has been well-controlled on maintenance therapy. However, 6 weeks after a mild COVID-19 infection, she developed a dermatomyositis flare. She improved only after aggressive treatment with pulse steroids, intravenous immunoglobulin, and rituximab. Conclusion: Exacerbation of dermatomyositis can be encountered following a COVID-19 infection, even if the infection is mild. Aggressive therapy should be considered in such cases. The prognosis, however, is generally favorable.

A report on virtual 'Can't intubate, can't oxygenate' conference workshops at the 2021 Annual Scientific Meeting of the Australian and New Zealand College of Anaesthetists.

The COVID-19 pandemic has had profound implications for continuing medical education. Travel restrictions, lockdowns and social distancing in an effort to curb spread have meant that medical conferences have been postponed or cancelled. When the Australian and New Zealand College of Anaesthetists made the decision to commit to a fully virtual 2021 Annual Scientific Meeting, the organising committee investigated the viability of presenting a virtual 'Can't intubate, can't oxygenate' workshop. A workshop was designed comprising a lecture, case scenario discussion and demonstration of emergency front-of-neck access techniques broadcast from a central hub before participants separated into Zoom® (Zoom Video Communications, San Jose, CA, USA) breakout rooms for hands-on practice, guided by facilitators working virtually from their own home studios. Kits containing equipment including a 3D printed larynx, cannula, scalpel and bougie were sent to workshop participants in the weeks before the meeting. Participants were asked to complete pre- and post-workshop surveys. Of 42 participants, 32 responded, with the majority rating the workshop 'better than expected'. All except two respondents felt the workshop met learning objectives. Themes of positive feedback included being impressed with the airway model, the small group size, content and delivery. Feedback focused on previously unperceived advantages of virtual technical skills workshops, including convenience, equitable access and the reusable airway model. Disadvantages noted by respondents included lack of social interaction, inability to trial more expensive airway equipment, and some limitations of the ability of facilitators to review participants' technique. Despite limitations, in our experience, virtual workshops can be planned with innovative solutions to deliver technical skills education successfully.

No evidence of SARS-CoV-2 infection in Rousettus aegyptiacus bat in Egypt.

Bats are considered ideal reservoirs for zoonotic viruses with emerging capabilities over the past two decades and spotted evidence points out that they may play a role as a reservoir host for SARS-CoV-2. To investigate the possible role of bats as part of SARS-CoV-2 anthropozoonotic spill-over infections in Egypt, a total of 800 samples obtained from 200 Egyptian fruit bats (Rousettus aegyptiacus) were tested for SARS-CoV-2 using quantitative RT-PCR assay (RT-qPCR). RT-qPCR analysis of RNA extracted from bat tissues showed no positive results for SARS-CoV-2 nucleic acid. These findings suggest that during the study period, the Rousettus aegyptiacus bat was not a reservoir or amplifying host for SARS-CoV-2 infection in Egypt. The lack of SARS-CoV-2 nucleic acid in Egyptian fruit bats is thought to make a significant contribution to SARS-CoV-2 epidemiology.

SARS-CoV-2 and pediatric encephalopathy: Google analytics and predictive modeling

Background: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is rare in children and possesses distinctive clinical features. Aims and Objectives: The primary objective is to bring clinicians,' researchers,' and epidemiologists' attention to pediatric encephalopathy as part of the clinical manifestations of SARS-CoV-2 in children. Materials and Methods: Google analytics aimed to explore the spatial-temporal (geographicchronological) mapping of SARS-CoV-2 in conjunction with pediatric encephalopathy and encephalitis. We retrieved longitudinal data from Google Trends, for one year starting from December 2019, by deploying five search topics;"SARS-CoV-2," "Coronavirus disease 2019, COVID-19" "Pediatric Encephalopathy," "Pediatric Encephalitis," and "Encephalitis in Children." Results: Spatio-temporal mapping was most conclusive for "COVID-19" and "Severe acute respiratory syndrome coronavirus 2." Internet users were least interested in topics related to pediatric encephalopathy and encephalitis in children;potentially, reflecting the rarity of these entities in SARS-CoV-2 infections in children. We are also reporting a case of atypical SARS-CoV-2 in an 8-year-old child, in which pediatric encephalopathy occurred in a PCR-confirmed COVID-19 case. Conclusion: Google analytics reconciled with the case report. SARS-CoV-2 in children may present with neurological rather than respiratory manifestations, which is atypical and rare. We are conveying two key messages;(1) pediatricians can collaborate with data scientists to realize evidence-based pediatric medicine and (2) digital data are worthy of exploration to guide subsequent rigor research, including randomized controlled trials and meta-analytics. [ABSTRACT FROM AUTHOR] Copyright of Asian Journal of Medical Sciences is the property of Manipal Colleges of Medical Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Modeling and Simulation: A study on predicting the outbreak of COVID- 19 in Saudi Arabia (preprint)

The novel coronavirus (Covid-19) infection has resulted in an ongoing pandemic affecting health system and economy of more than 200 countries around the world. Mathematical models are used to predict the biological and epidemiological trends of an epidemic and develop methods for controlling it. In this work, we use mathematical model perspective to study the role of behavior change in slowing the spread of the COVID-19 disease in Saudi Arabia. The real-time updated data from 1st May 2020 to 8th January 2021 is collected from Saudi Ministry of Health, aiming to provide dynamic behaviors of the pandemic in Saudi Arabia. During this period, it has infected 297,205 people, resulting in 6124 deaths with the mortality rate 2.06 %. There is weak positive relationship between the spread of the infection and mortality (R^2=0.412). We use Susceptible-Exposed-Infection-Recovered (SEIR) mode, the logistic growth model and with special focus on the exposed, infection and recovery individuals to simulate the final phase of the outbreak. The results indicate that social distancing, good hygienic conditions, and travel limitation are the crucial measures to prevent further spreading of the epidemic.