Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorder: Onset Following Acute COVID-19 Infection, a Case Series.

BACKGROUND AND OBJECTIVES: Acute COVID-19 infection has been associated with neurological involvement. We report a case series of newly diagnosed patients with multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) developed in a short period of time after acute COVID-19 infection. METHODS: New MS patients developing initial symptoms shortly after an acute COVID-19 infection were diagnosed based on the 2017 McDonald Criteria [Garcia-Ramos et al. in Cells, 2021]. The patients diagnosed with NMOSD met the 2015 International Panel criteria for the diagnosis of NMOSD (IPDN) [Thompson et al. in Lancet Neurol 17:162-173, 2018]. RESULTS FROM THE MS PATIENT GROUP: Ten patients were included who had developed initial MS symptoms after COVID-19 infection. Gender distribution was equal (50% male). The mean age was 28 (range 17-39) years. Average time to neurological presentation was between 2 and 6 weeks following acute COVID-19 infection. Partial transverse myelitis was the initial presentation in 40% of the cases, and 60% of patients had spinal cord lesions present at the moment of diagnosis. All patients showed enhancing lesions on brain magnetic resonance imaging (MRI). The presence of cerebrospinal fluid (CSF) oligoclonal bands was found in all six tested cases. The majority of patients (80%) were unvaccinated for COVID-19. The two vaccinated patients had received two doses of the monovalent COVID-19 messenger ribonucleic acid (mRNA) (Pfizer Biotech) vaccine and no booster, a year prior to contracting COVID-19. RESULTS FROM THE NMOSD GROUP: Two patients with NMOSD were included. Positive aquoporin-4 protein antibody (AQP-4 Ab) was detected in serum in both cases [one Enzyme Linked immunosorbent assay (ELISA) and one cell based]. Both patients had mild COVID-19 infection prior to presentation, initial neurologic symptoms presented between 3 and 6 weeks after COVID-19 infection. Neither patients were vaccinated. Both responded partially to steroids, one developed a relapse 40 days after diagnosis. CONCLUSION: COVID-19 infection has been linked to several neurological and immune-driven conditions. This study suggests that in susceptible individuals, acute COVID-19 infection may act as a trigger for developing MS and NMOSD.

Association between Sleep Quality and Physical Activity in Physical Education Students in Chile in the Pandemic Context: A Cross-Sectional Study.

Background: Due to the health restrictions put in place to face the pandemic, a decrease in the levels of physical activity and an alteration in the quality of sleep have been observed. One group susceptible to these changes is represented by students of physical education pedagogy, who, under normal conditions, present high levels of physical activity. However, the correlation between these variables has not been studied in the context of a pandemic lockdown. Objective: The aim of this study was to determine the prevalence of the quality of sleep and physical activity level as a function of gender and evaluate the association between quality of sleep and physical activity level in physical education pedagogy students during the COVID-19 pandemic considering sociodemographic and health characteristics. Methods: This was a cross-sectional study. An online questionnaire was applied to 280 Chilean university students of physical education pedagogy. The survey considered sociodemographic information, healthy habits, and self-reported health and included the International Physical Activity Questionnaire (IPAQ) for physical activity levels and the Pittsburgh Sleep Quality Index (PSQI) for sleep quality. Results: The prevalence of good sleep quality was 20.4%. Furthermore, 52.9% of students had a high level of physical activity. Regression analysis between PSQI global score and age-adjusted physical activity levels indicated that being male and presenting a high level of physical activity favored a better PSQI global score. Conclusions: The prevalence of good sleep quality was low in general and significantly lower in women. Being male and having a high level of physical activity during quarantine benefits good sleep quality, regardless of age.

Longwise Cluster Analysis for the Prediction of COVID-19 Severity within 72 h of Admission: COVID-DATA-SAVE-LIFES Cohort.

The use of routine laboratory biomarkers plays a key role in decision making in the clinical practice of COVID-19, allowing the development of clinical screening tools for personalized treatments. This study performed a short-term longitudinal cluster from patients with COVID-19 based on biochemical measurements for the first 72 h after hospitalization. Clinical and biochemical variables from 1039 confirmed COVID-19 patients framed on the "COVID Data Save Lives" were grouped in 24-h blocks to perform a longitudinal k-means clustering algorithm to the trajectories. The final solution of the three clusters showed a strong association with different clinical severity outcomes (OR for death: Cluster A reference, Cluster B 12.83 CI: 6.11-30.54, and Cluster C 14.29 CI: 6.66-34.43; OR for ventilation: Cluster-B 2.22 CI: 1.64-3.01, and Cluster-C 1.71 CI: 1.08-2.76), improving the AUC of the models in terms of age, sex, oxygen concentration, and the Charlson Comorbidities Index (0.810 vs. 0.871 with p < 0.001 and 0.749 vs. 0.807 with p < 0.001, respectively). Patient diagnoses and prognoses remarkably diverged between the three clusters obtained, evidencing that data-driven technologies devised for the screening, analysis, prediction, and tracking of patients play a key role in the application of individualized management of the COVID-19 pandemics.

A Proposed Framework for Developing FMEA Method Using Pythagorean Fuzzy CODAS

The purpose of this research article is to develop a hybridization between the Failure Mode and Effect Analysis (FMEA) method and the Combinative Distance-Based Assessment (CODAS) method under Pythagorean Fuzzy environment. The traditional FMEA procedure is based on the multiplication between the parameters of severity, occurrence, and detectability where everyone has equal relative importance;therefore, different combinations of these parameters can generate the same result creating uncertainty in the analysis. In this mode, the hybridization proposed in this research deal with relative importance of each parameter;in the fact to have a more suitable combination which consider the level of knowledge of the experts in the assessment. Finally, a numerical case was carried out concerning the public transportation service to validate our proposal;the results show that 31 failure modes and potential risks can be evaluated using user perceptions, a dominant with high level of knowledge about the public transportation service and an apprentice or common user, as team of experts and exploiting the subjectivity of the information in a mathematical model. Also, we compare the results with a variation of the proposed model with the multi-criteria method multi-objective optimization method by relationship analysis (MOORA);it was observed that the convergence of the failure modes depends on the nature of the mathematical model even under the same conditions at the start.