Perspectives on a psychiatric outpatient service for immigrants and refugees in São Paulo, Brazil over a 15-year period.

BACKGROUND: Immigrants and refugees have specific mental health needs. Studies of immigrant/refugee psychiatric patients in Latin America are scarce. AIMS: Present the profile of patients from an outpatient psychiatric service in Sao Paulo (Brazil) to better inform mental health service planning for immigrants and refugees in the Global South. METHODS: Exploratory study to characterize the sociodemographic and mental health profile of refugees and immigrants attending outpatient psychiatric service from 2003 to 2018. Chi-square tests and logistic regressions were used to examine the association of demographic variables, exposure to violence, and immigrant status with psychiatric diagnosis. Cluster analysis was used to identify subgroups within the sample. RESULTS: A total of 162 immigrants and refugees referred to the service obtained treatment. Of these patients, 57.4% were men, 59.8% were refugees/asylum seekers, 51.9% were Black, 48.8% were single, 64.2% had 10 years of education, and 57.4% were unemployed; the mean age of the sample was 35.9. Half of the sample (52.5%) was exposed to violence. The most common diagnosis was depression (54.2%), followed by PTSD (16.6%). Approximately 34% of the participants sought psychiatric care within 6 months of arrival. Logistic regressions showed that men had lower odds of presenting with depression (OR = 0.34). Patients with PTSD were more likely to be refugees (OR = 3.9) and not have a university degree (OR = 3.1).In the cluster analysis, a cluster of patients with PTSD included almost all Black refugee men exposed to violence. Most patients diagnosed with psychotic disorders were also Black refugee men. CONCLUSION: Immigrants and refugees represent a vulnerable group. The majority of the sample was Black, refugee men, who were also more likely to present with PTSD. Future studies are needed to better understand issues in treatment adherence in relation to socioeconomic characteristics

Identification of individual subjects on the basis of their brain anatomical features

Abstract We examined whether it is possible to identify individual subjects on the basis of brain anatomical features. For this, we analyzed a dataset comprising 191 subjects who were scanned three times over a period of two years. Based on FreeSurfer routines, we generated three datasets covering 148 anatomical regions (cortical thickness, area, volume). These three datasets were also combined to a dataset containing all of these three measures. In addition, we used a dataset comprising 11 composite anatomical measures for which we used larger brain regions (11LBR). These datasets were subjected to a linear discriminant analysis (LDA) and a weighted K-nearest neighbors approach (WKNN) to identify single subjects. For this, we randomly chose a data subset (training set) with which we calculated the individual identification. The obtained results were applied to the remaining sample (test data). In general, we obtained excellent identification results (reasonably good results were obtained for 11LBR using WKNN). Using different data manipulation techniques (adding white Gaussian noise to the test data and changing sample sizes) still revealed very good identification results, particularly for the LDA technique. Interestingly, using the small 11LBR dataset also revealed very good results indicating that the human brain is highly individual