Background: There is mixed evidence on increasing rates of psychiatric disorders and symptoms during the COVID-19 pandemic in 2020. We evaluated pandemic-related psychopathology and psychiatry diagnoses and their determinants in the Brazilian Longitudinal Study of Health (ELSA-Brasil) São Paulo Research Center.

Objective The present study aims to investigate the occurrence of psychiatric and cognitive impairments in a cohort of survivors of moderate or severe forms of COVID-19. Method 425 adults were assessed 6 to 9 months after hospital discharge with a structured psychiatric interview, psychometric tests and a cognitive battery. A large, multidisciplinary, set of clinical data depicting the acute phase of the disease, along with relevant psychosocial variables, were used to predict psychiatric and cognitive outcomes using the ‘Least Absolute Shrinkage and Selection Operator’ (LASSO) method. Results Diagnoses of ‘depression’, ‘generalized anxiety disorder’ and ‘post-traumatic stress disorder’ were established respectively in 8%, 15.5% and 13.6% of the sample. After pandemic onset (i.e., within the previous year), the prevalence of ‘depression’ and ‘generalized anxiety disorder’ were 2.56% and 8.14%, respectively. Memory decline was subjectively reported by 51.1% of the patients. Psychiatric or cognitive outcomes were not associated with any clinical variables related to the severity of acute-phase disease, nor by disease-related psychosocial stressors. Conclusions This is the first study to access rates of psychiatric and cognitive morbidity in the long-term outcome after moderate or severe forms of COVID-19 using standardized measures. As a key finding, there was no significant association between clinical severity in the acute-phase of SARS-CoV-2 infection and the neuropsychiatric impairment 6 to 9 months thereafter.

Metabolomics has proven an useful tool for systems biology. Here we have used a metabolomics approach to identify conditions in which de novo expression of an established tumor marker, galectin-3, would confer a potential selective advantage for melanoma growth and survival. A murine melanoma cell line (Tm1) that lacks galectin-3 was modified to express it or not (Tm1.G2 and Tm1.N3, respectively). These variant cell line were then exposed to conditions of controlled oxygen tensions and glucose levels. Metabolic profiling of intracellular metabolites of cells exposed to these conditions was obtained in steady state using high resolution 1H Magnetic Resonance Spectroscopy (1H-MRS) and multivariate statistical analysis. The Nuclear Magnetic Resonance (NMR) spectra contained a large number of absorption lines from which we were able to distinguish 20 metabolites, 3 fatty acids and some absorption lines and clusters were not identified. Principal Components Analysis (PCA) allowed for the discrimination of 2 experimental conditions in which expression of the tumor marker galectin-3 may play a significant role, namely exposure of cells to hypoxia under high glucose. Interestingly, under all other experimental conditions tested, the cellular system was quite robust. Our results suggest that the Metabolomics approach can be used to access information about changes in many metabolic pathways induced in tumorigenic cells and to allow the evaluation of their behavior in controlled environmental conditions or selective pressures.

This study assessed the disinfection using 70% ethanol; H 2 O 2 -quaternary ammonium salt mixture; 0.1% sodium hypochlorite and autoclaving of four 3D-printed face shields with different designs, visor materials; and visor thickness (0.5-0.75 mm). We also investigated their clinical suitability by applying a questionnaire to health workers (HW) who used them. Each type of disinfection was done 40 times on each type of mask without physical damage. In contrast, autoclaving led to appreciable damage.

Cohort studies have displayed mixed findings on changes in mental symptoms severity in 2020, when the COVID-19 pandemic outbreak started. Network approaches can provide additional insights by analyzing the connectivity of such symptoms. We assessed the network structure of mental symptoms in the Brazilian Longitudinal Study of Health (ELSA-Brasil) in 3 waves: 2008-2010, 2017-2019, and 2020, and hypothesized that the 2020 network would present connectivity changes. We used the Clinical Interview Scheduled-Revised (CIS-R) questionnaire to evaluates the severity of 14 common mental symptoms. Networks were graphed using unregularized Gaussian models and compared using centrality and connectivity measures. The predictive power of centrality measures and individual symptoms were also estimated. Among 2,011 participants (mean age: 62.1 years, 58% females), the pandemic symptom 2020 network displayed higher overall connectivity, especially among symptoms that were related to general worries, with increased local connectivity between general worries and worries about health, as well as between anxiety and phobia symptoms. There was no difference between 2008-2010 and 2017-2019 networks. According to the network theory of mental disorders, external factors could explain why the network structure became more densely connected in 2020 compared to previous observations. We speculate that the COVID-19 pandemic and its innumerous social, economical, and political consequences were prominent external factors driving such changes; although further assessments are warranted.

Aim Evidence indicates most people were resilient to the impact of the COVID-19 pandemic on mental health. However, evidence also suggests the pandemic effect on mental health may be heterogeneous. Therefore, we aimed to identify groups of trajectories of common mental disorders’ (CMD) symptoms assessed before (2017–19) and during the COVID-19 pandemic (2020–2021), and to investigate predictors of trajectories. Methods We assessed 2,705 participants of the ELSA-Brasil COVID-19 Mental Health Cohort study who reported Clinical Interview Scheduled-Revised (CIS-R) data in 2017–19 and Depression Anxiety Stress Scale-21 (DASS-21) data in May–July 2020, July–September 2020, October–December 2020, and April–June 2021. We used an equi-percentile approach to link the CIS-R total score in 2017–19 with the DASS-21 total score. Group-based trajectory modeling was used to identify CMD trajectories and adjusted multinomial logistic regression was used to investigate predictors of trajectories. Results Six groups of CMD symptoms trajectories were identified: low symptoms (17.6%), low-decreasing symptoms (13.7%), low-increasing symptoms (23.9%), moderate-decreasing symptoms (16.8%), low-increasing symptoms (23.3%), severe-decreasing symptoms (4.7%). The severe-decreasing trajectory was characterized by age < 60 years, female sex, low family income, sedentary behavior, previous mental disorders, and the experience of adverse events in life. Limitations Pre-pandemic characteristics were associated with lack of response to assessments. Our occupational cohort sample is not representative. Conclusion More than half of the sample presented low levels of CMD symptoms. Predictors of trajectories could be used to detect individuals at-risk for presenting CMD symptoms in the context of global adverse events. Supplementary Information The online version contains supplementary material available at 10.1007/s00127-022-02365-0.

Background: Healthcare workers (HW) are a vulnerable group to develop burnout during the COVID-19 pandemic. The aims of this study were to evaluate the perception of HW about the antibody test, and, secondarily, the prevalence of burnout and factors associated with burnout among HW who took the test. Methods: In this cross-sectional study, we evaluated burnout among HW in a 600-bed building entirely dedicated to COVID-19 inpatients care at Hospital das Clinicas (HC), located in São Paulo, Brazil. The HW answered an online questionnaire that included questions on burnout, a single-item scale based on the Maslach Burnout Inventory; demographic data, professional category, type of Protective Personal Equipment (PPE) used, distancing from social support; and emotional reactions to their serology result. Bivariate and multivariate analyses were done to evaluate the risk of burnout. Outcomes: Among 4,417 HW tested, 528 (12.0%) were positive for SARS-CoV-2 and 1,945 answered the questionnaire. Burnout was reported by 308 (15.8%); anxiety, tenseness, and depression associated with COVID-19 were reported by 344 (17.7%); 292 (15.1%); and 181(9.3%) of the participants, respectively. The risk factors for burnout were: being a physician [adjOR:1.

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