Psychiatric and psychological follow-up of undergraduate and postgraduate medical students: prevalence and associated factors. Results from the national BOURBON study. Running title: mental health and addictive behavior of medical students

International audienceBackground. Physicians are at risk of burnout, anxiety and depression. Prevention i

Relationship Between Anti-DFS70 Autoantibodies and Oxidative Stress

Background: The anti-DFS70 autoantibodies are one of the most commonly and widely described agent of unknown clinical significance, frequently detected in healthy individuals. It is not known whether the DFS70 autoantibodies are protective or pathogenic. One of the factors suspected of inducing the formation of anti-DFS70 antibodies is increased oxidative stress. We evaluated the coexistence of anti-DFS70 antibodies with selected markers of oxidative stress and investigated whether these antibodies could be considered as indirect markers of oxidative stress. Methods: The intensity of oxidative stress was measured in all samples via indices of free-radical damage to lipids and proteins such as total oxidant status (TOS), concentrations of lipid hydroperoxides (LPH), lipofuscin (LPS), and malondialdehyde (MDA). The parameters of the non-enzymatic antioxidant system, such as total antioxidant status (TAS) and uric acid concentration (UA), were also measured, as well as the activity of superoxide dismutase (SOD). Based on TOS and TAS values, the oxidative stress index (OSI) was calculated. All samples were also tested with indirect immunofluorescence assay (IFA) and 357 samples were selected for direct monospecific anti DFS70 enzyme-linked immunosorbent assay (ELISA) testing. Results: The anti-DFS70 antibodies were confirmed by ELISA test in 21.29% of samples. Compared with anti-DFS70 negative samples we observed 23% lower concentration of LPH (P =.038) and 11% lower concentration of UA (P =.005). TOS was 20% lower (P =.014). The activity of SOD was up to 5% higher (P =.037). The Pearson correlation showed weak negative correlation for LPH, UA, and TOS and a weak positive correlation for SOD activity. Conclusion: In samples positive for the anti-DFS70 antibody a decreased level of oxidative stress was observed, especially in the case of samples with a high antibody titer. Anti-DFS70 antibodies can be considered as an indirect marker of reduced oxidative stress or a marker indicating the recent intensification of antioxidant processes

Mémoire de source – présentation générale et revue des études dans la schizophrénie. [Source monitoring: general presentation and review of literature in schizophrenia]

International audienceSOURCE MONITORING FRAMEWORK: Source monitoring refers to the ability to remember the origin of information. Three source monitoring processes can be distinguished: external source monitoring, internal or self-monitoring and reality monitoring (i.e. discrimination between internal and external sources of information). Source monitoring decisions are based on memory characteristics recorded such as perceptions, contextual information or emotional reactions and heuristic or more controlled judgement processes. BRAIN STRUCTURES: Several studies suggested that specific structures in the prefrontal and the mediotemporal lobes are the main areas implicated in source monitoring. ASSESSMENT: A typical source monitoring paradigm includes an items generation stage and a second stage of recognition of items (old versus new) and identification of their sources: external (usually the examiner) or internal (the subject). Several indices can be calculated based on the raw data such as the number of false alarms, attribution biases or discrimination indexes. To date, there is no standardized source monitoring task and differences in the type of items used (words, pictures), in the cognitive or emotional effort involved or in the delay between the two test stages, contribute to the heterogeneity of results. FACTORS INFLUENCING SOURCE MONITORING: Factors such as age (either very young or very old) and emotions influence source monitoring performances. Influence of gender was not properly explored, whereas the role of IQ and selective attention is still debated. SOURCE MONITORING DEFICITS IN NEUROLOGICAL DISORDERS: Source monitoring deficits are observed mainly in disorders affecting frontotemporal areas, such as frontal trauma, Alzheimer's disease or frontotemporal dementia. SOURCE MONITORING AND SCHIZOPHRENIA: Source monitoring errors (e.g. external misattribution of self-generated information) are observed in schizophrenia and seem to correlate with positive symptomatology, in particular auditory hallucinations, thought intrusion and alien control symptoms. These results are of particular interest in clinical research because source monitoring is one of the rare cognitive tests showing a correlation with the positive dimension. Source monitoring deficits have been proposed as a potential explanation for the positive symptoms and some, but not all studies lent support to this hypothesis. Heterogeneity of studied samples, in particular different criteria to define hallucinating subjects (e.g. currently versus anytime during their lives), could explain the discordant results. SOURCE MONITORING IN PSYCHIATRIC DISORDERS WITHIN THE SCHIZOPHRENIC SPECTRUM: Source monitoring impairments were observed in pharmacological models of psychosis, in first degree relatives of schizophrenic patients, and also in the general population associated with schizotypal dimensions. These results support a relationship between source monitoring deficits and some of the symptomatic dimensions of the schizophrenic spectrum but still await replication. SOURCE MONITORING AND OTHER PSYCHIATRIC DISORDERS: Some studies found source monitoring deficits in other psychiatric conditions such as mania or obsessive-compulsive disorder. Thus, those studies suggest that source monitoring deficits may be not specific to schizophrenia. CONCLUSION: Source monitoring competencies are critical for good (i.e. adapted) everyday functioning. Source monitoring deficits have been suggested as a potential explanation for some (or all) positive psychotic symptoms. However, to date, methodological inconsistencies (especially with regard to test design and choice of subjects' samples) have precluded firm, definite conclusions

A National network of schizophrenia expert centres: An innovative tool to bridge the research-practice gap

International audienceSchizophrenia is probably the most severe psychiatric disorder with much suffering for the patients and huge costs for the society. Efforts to provide optimal care by general practitioners and psychiatrists are undermined by the complexity of the disorder and difficulties in applying clinical practice guidelines and new research findings to the spectrum of cases seen in day-today practice. An innovative model of assessment aimed at improving global care of people with schizophrenia provided by the French national network of schizophrenia expert centres is being described. Each centre has established strong links to local health services and provides support to clinicians in delivering personalized care plans. A common set of assessment tools has been adopted by the ten centres spread over the whole French territory. A web application, e-schizo ß has been created to record data in a common computerized medical file. This network offers systematic, comprehensive, longitudinal, and multi-dimensional assessments of cases including a medical workup and an exhaustive neuropsychological evaluation. This strategy offers an effective way to transfer knowledge and share expertise. This network is a great opportunity to improve the global patient care and is conceived as being an infrastructure for research from observational cohort to translational research

Machine learning for predicting psychotic relapse at 2 years in schizophrenia in the national FACE-SZ cohort

International audienceBackground Predicting psychotic relapse is one of the major challenges in the daily care of schizophrenia. Objectives To determine the predictors of psychotic relapse and follow-up withdrawal in a non-selected national sample of stabilized community-dwelling SZ subjects with a machine learning approach. Methods Participants were consecutively included in the network of the FondaMental Expert Centers for Schizophrenia and received a thorough clinical and cognitive assessment, including recording of current treatment. Relapse was defined by at least one acute psychotic episode of at least 7 days, reported by the patient, her/his relatives or by the treating psychiatrist, within the 2-year follow-up. A classification and regression tree (CART) was used to construct a predictive decision tree of relapse and follow-up withdrawal. Results Overall, 549 patients were evaluated in the expert centers at baseline and 315 (57.4%) (mean age = 32.6 years, 24% female gender) were followed-up at 2 years. On the 315 patients who received a visit at 2 years, 125(39.7%) patients had experienced psychotic relapse at least once within the 2 years of follow-up. High anger (Buss&Perry subscore), high physical aggressiveness (Buss&Perry scale subscore), high lifetime number of hospitalization in psychiatry, low education level, and high positive symptomatology at baseline (PANSS positive subscore) were found to be the best predictors of relapse at 2 years, with a percentage of correct prediction of 63.8%, sensitivity 71.0% and specificity 44.8%. High PANSS excited score, illness duration Conclusion Machine learning can help constructing predictive score. In the present sample, aggressiveness appears to be a good early warning sign of psychotic relapse and follow-up withdrawal and should be systematically assessed in SZ subjects. The other above-mentioned clinical variables may help clinicians to improve the prediction of psychotic relapse at 2 years

Hypovitaminosis D is associated with depression and anxiety in schizophrenia: Results from the national FACE-SZ cohort.

Objective: Hypovitaminosis D has been associated with respectively major depressive disorder, schizophrenia (SZ) and cognitive disorders in the general population, and with positive and negative symptoms and metabolic syndrome in schizophrenia. The objectives were (i) to determine the prevalence of hypovitaminosis D and associated factors (with a focus on depression and cognition) in a national non-selected multicentric sample of community-dwelling SZ subjects (ii) to determine the rate of SZ patients being administered vitamin D supplementation and associated factors. Methods: A comprehensive 2 daylong clinical and neuropsychological battery was administered in 140 SZ subjects included between 2015 and 2017 in the national FondaMental Expert Center (FACE-SZ) Cohort. Hypovitaminosis D was defined by blood vitamin D level Results: Hypovitaminosis D has been found in 21.4% of the subjects and none of them had received vitamin D supplementation in the previous 12 months. In multivariate analysis, hypovitaminosis D has been significantly associated with respectively higher depressive symptoms (aOR = 1.18 [1.03-1.35], p = 0.02) and current anxiety disorder (aOR = 6.18 [2.15-17.75], p = 0.001), independently of age and gender. No association of hypovitaminosis D with respectively positive and negative symptoms, cognitive scores or other biological variables has been found (all p > 0.05), however, a trend toward significance has been found for metabolic syndrome (p = 0.06). Vitamin D supplementation has been administered during the previous 12 months in only 8.5% of the subjects but was associated with lower depressive symptoms (aOR = 0.67 [0.46-0.98], p = 0.04) and lower rate of current anxiety disorder (aOR = 0.06 [0.01-0.66],p = 0.02) compared to patients with hypovitaminosis D. Conclusion: Hypovitaminosis D is frequent and associated with depressive symptoms and anxiety disorders in schizophrenia. Vitamin D supplementation is associated with lower depressive and anxiety symptoms, however patients with hypovitaminosis D remain insufficiently treated