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Valproate is associated with teratogenic and neurodevelopmental effects. Several agencies have restricted the conditions of its prescription in bipolar disorders (BD). We aimed to assess the evolution of valproate prescription and the clinical profile of BD women of childbearing age receiving valproate.

Based on a large national cohort, we included all BD women 16-50 years old. Sociodemographic, clinical and pharmacological data were recorded. Logistic regression analyses were used to describe variables associated with valproate prescription.

Of the 1018 included women 16-50 years old, 26.9% were treated with valproate with a mean daily dosage of 968 mg. The prevalence of BD women using valproate was 32.6% before May 2015 and 17.3% after May 2015 (p<0.001), the date of French regulatory publication of restriction of valproate prescription. The multivariate analysis revealed that the inclusion period after May 2015 (OR=0.54, CI 95% 0.37-0.78, p=0.001), the age lower than 40 years (OR=0.65, CI 95% 0.43-0.98, p=0.040) and the number of lifetime mood episodes (OR=0.98, CI 95% 0.95-0.99, p=0.040) were the variables negatively associated with the use of valproate.

Study could be underpowered to determine a clinical profile associated with valproate prescription.

The regulatory change in BD women of childbearing age had a significant impact on valproate prescription, even if the prescription rate remains high. Important efforts are needed to help clinicians and patients to improve quality of care in BD women of childbearing age.

The regulatory change in BD women of childbearing age had a significant impact on valproate prescription, even if the prescription rate remains high. Important efforts are needed to help clinicians and patients to improve quality of care in BD women of childbearing age.

Suicidal thoughts and behaviors have been studied in association with a variety of risk factors. The aim of the present study was to determine if levels of child/adolescent aggression and/or variation in candidate genes previously associated with suicidal behaviors in adults would influence the presence of suicidal ideation in childhood/adolescence, and to determine if ideation was associated with young adult depression.

A longitudinal study of children, adolescents and young adults who were at high or low risk for alcohol and other substance use disorders by familial background were assessed. The Child Behavior Checklist (CBCL) aggression scale scores with derived subtypes (physical and relational) and genetic variation (ANKK1, DRD2, COMT, SLC6A4, HTR2C) were used as predictors of the presence and onset of suicidal ideation in childhood using survival analysis. Structural equation models (SEM) were fit to determine the relative importance of the predictors controlling for background variables.

CBCL aggression was significantly associated with child/adolescent suicidal ideation. One SNP in the ANKK1 gene (rs1800497), one in the HTR2C gene (rs6318), and two haplotypes, AAAC in the ANKK1-DRD2 complex and the CCC haplotype of the HTR2C gene, were significantly associated with the presence and onset of child/adolescent suicidal ideation. Follow up in young adulthood showed a significant relationship between suicidal ideation in childhood/adolescence and young adult depression.

Genetic variation and presence of elevated aggression scores from the childhood CBCL are significant predictors of childhood suicidal ideation. Suicidal ideation in childhood and being female are predictors of young adult depression.

Genetic variation and presence of elevated aggression scores from the childhood CBCL are significant predictors of childhood suicidal ideation. Suicidal ideation in childhood and being female are predictors of young adult depression.

Course of illness in major depression (MD) is highly varied, which might lead to both under- and overtreatment if clinicians adhere to a 'one-size-fits-all' approach. Novel opportunities in data mining could lead to prediction models that can assist clinicians in treatment decisions tailored to the individual patient. This study assesses the performance of a previously developed data mining algorithm to predict future episodes of MD based on clinical information in new data.

We applied a prediction model utilizing baseline clinical characteristics in subjects who reported lifetime MD to two independent test samples (total n=4226). We assessed the model's performance to predict future episodes of MD, anxiety disorders, and disability during follow-up (1-9 years after baseline). In addition, we compared its prediction performance with well-known risk factors for a severe course of illness.

Our model consistently predicted future episodes of MD in both test samples (AUC 0.68-0.73, modest prediction). Equally accurately, it predicted episodes of generalized anxiety disorder, panic disorder and disability (AUC 0.65-0.78). Our model predicted these outcomes more accurately than risk factors for a severe course of illness such as family history of MD and lifetime traumas.

Prediction accuracy might be different for specific subgroups, such as hospitalized patients or patients with a different cultural background.

Our prediction model consistently predicted a range of adverse outcomes in MD across two independent test samples derived from studies in different subpopulations, countries, using different measurement procedures. This replication study holds promise for application in clinical practice.

Our prediction model consistently predicted a range of adverse outcomes in MD across two independent test samples derived from studies in different subpopulations, countries, using different measurement procedures. This replication study holds promise for application in clinical practice.

Acceptance/mindfulness-based interventions often focus on (a) developing dispositional mindfulness and (b) pursuing personally meaningful and valued activities. Acceptance/mindfulness-based interventions can reduce depression, but little is known about the combined effects of components or the influence of baseline variables on outcomes. This study tested whether practicing a brief (10-min) mindfulness meditation over a 2-week period followed by a single values session (mindfulness+values) was more effective than values alone (values only) in reducing symptoms of depression. selleck chemical The study was delivered online and modules were fully self-help (i.e., no therapist contact).

206 participants (M

=23.4 years, SD=6.53) with elevated depression scores (DASS-depression ≥ 10) were randomised to mindfulness+values condition or a 2-week wait period followed by the values session (i.e., values only condition). Symptoms of depression were assessed at baseline, after the 2-week mindfulness practice/wait period, and 1-week following the values session.