Watch out for neuromyelitis optica spectrum disorder onset or clinical relapse after COVID-19 vaccination: What neurologists need to know?

INTRODUCTION: The ongoing global COVID-19 pandemic has dramatically impacted our lives. We conducted this systematic review to investigate the safety of the COVID-19 vaccines in NMOSD patients. METHODS: We systematically searched PubMed, Scopus, Web of Science, and Embase from the beginning of the COVID-19 vaccination to March 1, 2022. Except for the letters, posters, and reviews, we included all related articles to answer two main questions. Our first question examined the occurrence of NMOSD onset as an adverse effect of the COVID-19 vaccine. Our second question investigated the safety of the COVID-19 vaccines in NMOSD patients. RESULTS: Out of 262 records, nine studies, including five studies for the first question and four studies for the second question, met the inclusion criteria. Out of the six patients with NMOSD onset after COVID-19 vaccination, five (83.3%) were female. The median time to NMOSD onset was 6.5 days, and the frequency of the COVID-19 vaccine type was identical in all patients. The most common presentation was longitudinally extensive transverse myelitis, significantly improved by pulse methylprednisolone with or without plasma exchange. The maintenance therapy was described only in three patients: rituximab (n=2) and azathioprine (n=1). Regarding the second question, out of 67 patients, 77.61% were female, with a mean age of 54.75 years old, a mean EDSS of 2.83, and a mean disease duration of 9.5 years. 77% reported at least one preexisting comorbidity. 88.05% were under treatment, most of which were rituximab and azathioprine. 98.50% received two doses of the COVID-19 vaccine. mRNA vaccines were the most commonly used vaccine(86.56%), which were well tolerated. No significant adverse event was reported, and local pain was the most frequently reported. 4.67% of the patients experienced a clinical relapse after a mean interval of 49.75 days, which was mainly mild to moderate in severity. Unfortunately, the data on the COVID-19 vaccines were missing. CONCLUSION: The analysis suggests the safety profile of the COVID-19 vaccines. All NMOSD patients are strongly recommended to vaccinate for COVID-19. To maximize the effectiveness of the COVID-19 vaccines, further studies are needed to draw the best practice for vaccination.

Detection of COVID-19 in X-ray images by classification of bag of visual words using neural networks.

Coronavirus disease 2019 (COVID-19) was classified as a pandemic by the World Health Organization in March 2020. Given that this novel virus most notably affects the human respiratory system, early detection may help prevent severe lung damage, save lives, and help prevent further disease spread. Given the constraints on the healthcare facilities and staff, the role of artificial intelligence for automatic diagnosis is critical. The automatic diagnosis of COVID-19 based on medical images is, however, not straightforward. Due to the novelty of the disease, available X-ray datasets are very limited. Furthermore, there is a significant similarity between COVID-19 X-rays and other lung infections. In this paper, these challenges are addressed by proposing an approach consisting of a bag of visual words and a neural network classifier. The proposed method can classify X-ray chest images into non-COVID-19 and COVID-19 with high performance. Three public datasets are used to evaluate the proposed approach. Our best accuracy on the first, second, and third datasets is 96.1, 99.84, and 98 percent. Since detection of COVID-19 is important, sensitivity is used as a criterion. The proposed method's best sensitivities are 90.32, 99.65, and 91 percent on these datasets, respectively. The experimental results show that extracting features with the bag of visual words results in better classification accuracy than the state-of-the-art techniques.

The Anxiety Disorder Among the Healthcare Providers During The COVID-19 Infection Pandemic: A Systematic Review

Background: The outbreak of the novel coronavirus disease (COVID-19) imposes a considerable psychological burden on the medical staff working in central hospitals for COVID-19. In this systematic review, we will discuss the prevalence and the risk factors of anxiety disorder among the frontline medical staff dealing with COVID-19 patients. Methods: PubMed, Scopus, Embase, Web of Science data bases were systematically searched from December 01, 2019 to April 30, 2020 for related published articles. In all electronic databases, the following search strategy was implemented and these key words (in the title/abstract) were used: “COVID-19” OR “novel Coronavirus” AND “anxiety” OR “psychology” OR “psychiatry” OR “psychological distress” AND “nurses” or “clinicians”. We included only the cross sectional studies. Results: Through the search strategy, we could identify eight related cross sectional articles about anxiety among the healthcare workers in central hospitals for COVID-19 infection. However, the authors scanned the reference lists of the included studies and identified multiple references. According to our findings, the frontline medical staff are at risk developing anxiety disorder which is mainly mild. Additionally, the female nurses are more susceptible to experience anxiety during the COVID-19 pandemic. Conclusion:Regarding to the outbreak of COVID-19 worldwide and the workload of the frontline medical staff dealing with COVID-19 patients, a particular attention should be given on the mental health of the healthcare provides.

Novel Coronavirus Disease (COVID-19) and Central Nervous System Complications: What Neurologist Need to Know.

The novel coronavirus (Covid-19) is a family of large enveloped non-segmented positive-sense RNA viruses which has been considered as a global health concern as it has a very high transmissibility potential. Regarding to the similarity of the virus to SARS-CoV, it is postulated that the Covid-19 accumulates mainly in the nasal epithelia and lower respiratory airways. However, there is evidence suggesting the Covid-19 neurotropism which might contribute to respiratory failure. Here in we aim to review the central nervous system complications of the Covid-19 CoV since the emergence of the virus. Keywords: Novel Coronavirus, Covid19-Cov, CNS Complication, Nervous System.