The Implications of SARS-CoV-2 Infection in a Series of Neuro-Ophthalmological Manifestations-Case Series and Literature Review.

The global pandemic impact of the COVID-19 infection included clinical manifestations that affected several organs and systems, with various neuro-ophthalmological manifestations associated with the infection. These are rare and occur either secondary to the presence of the virus or by an autoimmune mechanism secondary to viral antigens. The manifestations are atypical, being present even in the absence of the systemic symptoms typical of a SARS-CoV-2 infection. In this article, we introduce a series of three clinical cases with neuro-ophthalmological manifestations associated with COVID infection that were shown in Ophthalmology Clinic of St. Spiridon Emergency Hospital. Case 1 is that of a 45-year-old male patient with no personal history of general pathology or ophthalmology, with binocular diplopia, painful red eyes, and lacrimal hypersecretion with a sudden onset of about 4 days. Based on the evaluations, a positive diagnosis of orbital cellulitis in both eyes is made. Case 2 is that of a 52-year-old female patient with general PPA (personal pathological antecedents) of SARS-CoV-2 infection 1 month prior to presentation with decreased visual acuity in the right eye and a positive central scotoma, preceded by photopsia and vertigo with balance disorders. The diagnosis is made at the right eye for retrobulbar optic neuritis and post-SARS-CoV-2 infection status. The last clinical case is that of a 55-year-old male patient known to have high blood pressure (HBP) with a sudden, painless decrease in VARE approximately 3 weeks post-SARS-CoV-2 immunization (Pfizer vaccine first dose). The diagnosis is made after consulting all the RE results for central retinal vein thrombosis. Conclusions: Although the cases were quickly and efficiently investigated and the treatment was administered adequately by a multidisciplinary team (cases 1 and 3), the evolution was not favorable in all three situations. Atypical neuro-ophthalmological manifestations can also be present in the absence of systemic symptoms typical of SARS-CoV-2 infection.

Mathematical Modeling to Predict COVID-19 Infection and Vaccination Trends.

BACKGROUND: COVID-19 caused by the Severe Acute Respiratory Syndrome Coronavirus 2 placed the health systems around the entire world in a battle against the clock. While most of the existing studies aimed at forecasting the infections trends, our study focuses on vaccination trend(s). MATERIAL AND METHODS: Based on these considerations, we used standard analyses and ARIMA modeling to predict possible scenarios in Romania, the second-lowest country regarding vaccinations from the entire European Union. RESULTS: With approximately 16 million doses of vaccine against COVID-19 administered, 7,791,250 individuals had completed the vaccination scheme. From the total, 5,058,908 choose Pfizer-BioNTech, 399,327 Moderna, 419,037 AstraZeneca, and 1,913,978 Johnson & Johnson. With a cumulative 2147 local and 17,542 general adverse reactions, the most numerous were reported in recipients of Pfizer-BioNTech (1581 vs. 8451), followed by AstraZeneca (138 vs. 6033), Moderna (332 vs. 1936), and Johnson & Johnson (96 vs. 1122). On three distinct occasions have been reported >50,000 individuals who received the first or second dose of a vaccine and >30,000 of a booster dose in a single day. Due to high reactogenicity in case of AZD1222, and time of launching between the Pfizer-BioNTech and Moderna vaccine could be explained differences in terms doses administered. Furthermore, ARIMA(1,1,0), ARIMA(1,1,1), ARIMA(0,2,0), ARIMA(2,1,0), ARIMA(1,2,2), ARI-MA(2,2,2), ARIMA(0,2,2), ARIMA(2,2,2), ARIMA(1,1,2), ARIMA(2,2,2), ARIMA(2,1,1), ARIMA(2,2,1), and ARIMA (2,0,2) for all twelve months and in total fitted the best models. These were regarded according to the lowest MAPE, p-value (p < 0.05, p < 0.01, and p < 0.001) and through the Ljung-Box test (p < 0.05, p < 0.01, and p < 0.001) for autocorrelations. CONCLUSIONS: Statistical modeling and mathematical analyses are suitable not only for forecasting the infection trends but the course of a vaccination rate as well.

Preliminary Data on Gastrointestinal Deficiencies Incidence and the Prevalence of Anxiety During the COVID-19 Pandemic Among the Medical Workers.

ABSTRACT: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly contagious new ß-coronavirus that primarily affects the lungs. Because of its unprecedented spread, in a relatively short interval, it is declared a global pandemic. Binding to the angiotensin-converting enzyme 2 receptors, SARS-CoV-2 is easily disseminated through air. Apart from the established clinical panel, individuals exposed to prolonged chronic stress also manifest gastrointestinal (GI) symptoms similar to those exhibited by SARS-CoV-2-infected patients.The present study aims to assess the incidence of GI deficiencies and prevalence of anxiety among healthy medical staff by applying the Visual Analog Scale for Irritable Bowel Syndrome (VAS-IBS) and Hamilton Anxiety Rating Scale (HAM-A) during this global crisis.We found significant differences on several items of the VAS-IBS: regarding the incidence of diarrhea (p = 0.04), bloating/gases (p = 0.02), and nausea/vomiting (p = 0.01) from the physical spectrum. After stratification based on age of the participants and after we applied Kruskal-Wallis test because of heterogeneity between groups, we noted two situations in which the null hypothesis is rejected: nausea/vomiting in women between 20 and 30 years, and between 30 and 40, and between 40 and 50 years, respectively (p = 0.026/0.029). Anxiety was prevalent among young and middle-class people after the centralization of HAM-A data, where 40.4% of the participants had various forms of anxiety: mild (n = 13; 13.82%), severe (n = 13; 13.82%), and moderate (n = 12; 12.76%).This study demonstrates that VAS-IBS is a reliable tool for assessing the incidence of GI deficiencies, as well as HAM-A for anxiety.

Mini-Review Discussing the Reliability and Efficiency of COVID-19 Vaccines.

Severe Acute Respiratory Syndrome Coronavirus 2 is a novel strain of human beta-coronavirus that has produced over two million deaths and affected one hundred million individuals worldwide. As all the proposed drugs proved to be unstable, inducing side effects, the need to develop a vaccine crystallized in a short time. As a result, we searched the databases for articles in which the authors reported the efficacy and safety of the use of several vaccines vaccines by sex, age group, and frequency of adverse reactions. We identified a total of 19 relevant articles that were discussed throughout this manuscript. We concluded that from all eleven vaccines, three had an efficacy >90% (Pfizer-BioNTech (~95%), Moderna (~94%), and Sputnik V (~92%)) except for Oxford-AstraZeneca (~81%). However, Moderna, Sputnik V, and Oxford-AstraZeneca also alleviate severe adverse reactions, whereas in Pfizer-BioNTech this was not revealed. The remaining five (Convidicea (AD5-nCOV); Johnson & Johnson (Ad26.COV2.S); Sinopharm (BBIBP-CorV); Covaxin (BBV152), and Sinovac (CoronaVac)) were discussed based on their immunogenicity, and safety reported by the recipients since only phases 1 and 2 were conducted without clear evidence published regarding their efficacy. CoviVac and EpiVacCorona have just been approved, which is why no published article could be found. All adverse events reported following the administration of one of the four vaccines ranged from mild to moderate; limited exceptions in which the patients either developed severe forms or died, because most effects were dose-dependent. It can be concluded that aforementioned vaccines are efficient and safe, regardless of age and sex, being well-tolerated by the recipients.

Testing the Accuracy of the ARIMA Models in Forecasting the Spreading of COVID-19 and the Associated Mortality Rate.

Background and objectives: The current pandemic of SARS-CoV-2 has not only changed, but also affected the lives of tens of millions of people around the world in these last nine to ten months. Although the situation is stable to some extent within the developed countries, approximately one million have already died as a consequence of the unique symptomatology that these people displayed. Thus, the need to develop an effective strategy for monitoring, restricting, but especially for predicting the evolution of COVID-19 is urgent, especially in middle-class countries such as Romania. Material and Methods: Therefore, autoregressive integrated moving average (ARIMA) models have been created, aiming to predict the epidemiological course of COVID-19 in Romania by using two statistical software (STATGRAPHICS Centurion (v.18.1.13) and IBM SPSS (v.20.0.0)). To increase the accuracy, we collected data between the established interval (1 March, 31 August) from the official website of the Romanian Government and the World Health Organization. Results: Several ARIMA models were generated from which ARIMA (1,2,1), ARIMA (3,2,2), ARIMA (3,1,3), ARIMA (3,2,2), ARIMA (3,1,3), ARIMA (2,2,2) and ARIMA (1,2,1) were considered the best models. For this, we took into account the lowest value of mean absolute percentage error (MAPE) for March, April, May, June, July, and August (MAPEMarch = 9.3225, MAPEApril = 0.975287, MAPEMay = 0.227675, MAPEJune = 0.161412, MAPEJuly = 0.243285, MAPEAugust = 0.163873, MAPEMarch - August = 2.29175 for STATGRAPHICS Centurion (v.18.1.13) and MAPEMarch = 57.505, MAPEApril = 1.152, MAPEMay = 0.259, MAPEJune = 0.185, MAPEJuly = 0.307, MAPEAugust = 0.194, and MAPEMarch - August = 6.013 for IBM SPSS (v.20.0.0) respectively. Conclusions: This study demonstrates that ARIMA is a useful statistical model for making predictions and provides an idea of the epidemiological status of the country of interest.

Forecasting the Spreading of COVID-19 across Nine Countries from Europe, Asia, and the American Continents Using the ARIMA Models.

Since mid-November 2019, when the first SARS-CoV-2-infected patient was officially reported, the new coronavirus has affected over 10 million people from which half a million died during this short period. There is an urgent need to monitor, predict, and restrict COVID-19 in a more efficient manner. This is why Auto-Regressive Integrated Moving Average (ARIMA) models have been developed and used to predict the epidemiological trend of COVID-19 in Ukraine, Romania, the Republic of Moldova, Serbia, Bulgaria, Hungary, USA, Brazil, and India, these last three countries being otherwise the most affected presently. To increase accuracy, the daily prevalence data of COVID-19 from 10 March 2020 to 10 July 2020 were collected from the official website of the Romanian Government GOV.RO, World Health Organization (WHO), and European Centre for Disease Prevention and Control (ECDC) websites. Several ARIMA models were formulated with different ARIMA parameters. ARIMA (1, 1, 0), ARIMA (3, 2, 2), ARIMA (3, 2, 2), ARIMA (3, 1, 1), ARIMA (1, 0, 3), ARIMA (1, 2, 0), ARIMA (1, 1, 0), ARIMA (0, 2, 1), and ARIMA (0, 2, 0) models were chosen as the best models, depending on their lowest Mean Absolute Percentage Error (MAPE) values for Ukraine, Romania, the Republic of Moldova, Serbia, Bulgaria, Hungary, USA, Brazil, and India (4.70244, 1.40016, 2.76751, 2.16733, 2.98154, 2.11239, 3.21569, 4.10596, 2.78051). This study demonstrates that ARIMA models are suitable for making predictions during the current crisis and offers an idea of the epidemiological stage of these regions.

Minireview Exploring the Biological Cycle of Vitamin B3 and Its Influence on Oxidative Stress: Further Molecular and Clinical Aspects.

Vitamin B3, or niacin, is one of the most important compounds of the B-vitamin complex. Recent reports have demonstrated the involvement of vitamin B3 in a number of pivotal functions which ensure that homeostasis is maintained. In addition, the intriguing nature of its synthesis and the underlying mechanism of action of vitamin B3 have encouraged further studies aimed at deepening our understanding of the close link between the exogenous supply of B3 and how it activates dependent enzymes. This crucial role can be attributed to the gut microflora and its ability to shape human behavior and development by mediating the bioavailability of metabolites. Recent studies have indicated a possible interconnection between the novel coronavirus and commensal bacteria. As such, we have attempted to explain how the gastrointestinal deficiencies displayed by SARS-CoV-2-infected patients arise. It seems that the stimulation of a proinflammatory cascade and the production of large amounts of reactive oxygen species culminates in the subsequent loss of host eubiosis. Studies of the relationhip between ROS, SARS-CoV-2, and gut flora are sparse in the current literature. As an integrated component, oxidative stress (OS) has been found to negatively influence host eubiosis, in vitro fertilization outcomes, and oocyte quality, but to act as a sentinel against infections. In conclusion, research suggests that in the future, a healthy diet may be considered a reliable tool for maintaining and optimizing our key internal parameters.