European Psychiatry最新文献

Background: Acute health and social services for children and adolescents often struggle with youth aggression and violence. Early identification of violence risk during institutional stay can help prevent violent incidents. As such, this study assessed the predictive accuracy of the Violence Risk Assessment Checklist for Youth (V-RISK-Y) aged 12-18 in two different juvenile settings providing 24-hour services for youth. Institutions were included from child and adolescent inpatient psychiatry and residential youth care under child protective services.

Methods: A prospective, naturalistic observational study design was employed. V-RISK-Y was administered for youth admitted to four acute inpatient psychiatric units and four acute residential youth care institutions. Incidents of violence and threats during the youth's stay were registered by institutional staff. In total, 517 youth were included in analyses, 59 of whom were registered with at least one incident of violence or threats during their stay. Area under curve (AUC) and logistic regression analyses were used to assess predictive accuracy and validity of V-RISK-Y.

Results: For the overall sample, V-RISK-Y had good predictive accuracy, and the sum score of V-RISK-Y significantly predicted registered violent incidents. Stratified analyses indicated good predictive accuracy of V-RISK-Y for the inpatient units, but not for the residential youth care institutions.

Conclusions: Findings imply that V-RISK-Y is accurate in identifying violence risk for youth admitted to inpatient psychiatric units but has limited predictive accuracy in residential youth care institutions. Future research should explore approaches to correctly identify violence risk in residential care settings.

Background: Recent years show an exponential increased interest ("renaissance") in the use of psychedelics for the treatment of mental disorders and broader. Some of these treatments, such as psilocybin for depression, are in the process of formal regulation by regulatory bodies in the US (FDA) and Europe (EMA), and as such on the brink of real-world implementation. In the slipstream of these developments increasing commercial initiatives are taking shape. The European Psychiatric Association (EPA) acknowledges both the therapeutic potential of psychedelic substances and the challenges for both research and clinical implementation. Steps need to be taken toward a well-balanced policy based upon sound scientific evidence and research, aiming at safe, ethical responsible integration of psychedelic therapy available for all patients who can potentially benefit.

Methods: In this EPA policy paper, we highlight the potential benefits, and also the challenges of psychedelic treatments, which can be relevant for the future real-world implementation of these treatments.

Results: In addition to an overview of the current evidence and hypotheses of working mechanisms of psychedelic treatment, this policy paper specifically highlights the importance of the psychosocial components of the treatment as well as the ethical and professional aspects playing a role in real-world implementation.

Conclusions: Four recommendations are formulated for further research and clinical implementation.

Background: Temperature increases in the context of climate change affect numerous mental health outcomes. One such relevant outcome is involuntary admissions as these often relate to severe (life)threatening psychiatric conditions. Due to a shortage of studies into this topic, relationships between mean ambient temperature and involuntary admissions have remained largely elusive.

Aims: To examine associations between involuntary admissions to psychiatric institutions and various meteorological variables.

Methods: Involuntary admissions data from 23 psychiatric institutions in the Netherlands were linked to meteorological data from their respective weather stations. Generalized additive models were used, integrating a restricted maximum likelihood method and thin plate regression splines to preserve generalizability and minimize the risk of overfitting. We thus conducted univariable, seasonally stratified, multivariable, and lagged analyses.

Results: A total of 13,746 involuntary admissions were included over 21,549 days. In univariable and multivariable models, we found significant positive associations with involuntary admissions for ambient temperature and windspeed, with projected increases of up to 0.94% in involuntary admissions per degree Celsius temperature elevation. In the univariable analyses using all data, the strongest associations in terms of significance and explained variance were found for mean ambient temperature (p = 2.5 × 10^-6, Variance Explained [r²] = 0.096%) and maximum ambient temperature (p = 8.65 × 10^-4, r² = 0.072%). We did not find evidence that the lagged associations explain the associations for ambient temperature better than the direct associations.

Conclusion: Mean ambient temperature is consistently but weakly associated with involuntary psychiatric admissions. Our findings set the stage for further epidemiological and mechanistic studies into this topic, as well as for modeling studies examining future involuntary psychiatric admissions.

The European Clozapine Task Force is a group of psychiatrists and pharmacologists practicing in 18 countries under European Medicines Agency (EMA) regulation, who are deeply concerned about the underuse of clozapine in European countries. Although clozapine is the most effective antipsychotic for people with treatment-resistant schizophrenia, a large proportion of them do not have access to this treatment. Concerns about clozapine-induced agranulocytosis and stringent blood monitoring rules are major barriers to clozapine prescribing and use. There is a growing body of evidence that the incidence of clozapine-induced agranulocytosis is very low after the first year of treatment. Maintaining lifelong monthly blood monitoring after this period contributes to unjustified discontinuation of clozapine. We leverage recent and replicated evidence on the long-term safety of clozapine to call for the revision and updating of the EMA's blood monitoring rules, thus aiming to overcome this major barrier to clozapine prescribing and use. We believe the time has come for relaxing the rules without increasing the risks for people using clozapine in Europe.

Background: One of the most relevant risk factors for suicide is the presence of previous attempts. The symptomatic profile of people who reattempt suicide deserves attention. Network analysis is a promising tool to study this field.

Objective: To analyze the symptomatic network of patients who have attempted suicide recently and compare networks of people with several attempts and people with just one at baseline.

Methods: 1043 adult participants from the Spanish cohort "SURVIVE" were part of this study. Participants were classified into two groups: single attempt group (n = 390) and reattempt group (n = 653). Different network analyses were carried out to study the relationships between suicidal ideation, behavior, psychiatric symptoms, diagnoses, childhood trauma, and impulsivity. A general network and one for each subgroup were estimated.

Results: People with several suicide attempts at baseline scored significantly higher across all clinical scales. The symptomatic networks were equivalent in both groups of patients (p > .05). Although there were no overall differences between the networks, some nodes were more relevant according to group belonging.

Conclusions: People with a history of previous attempts have greater psychiatric symptom severity but the relationships between risk factors show the same structure when compared with the single attempt group. All risk factors deserve attention regardless of the number of attempts, but assessments can be adjusted to better monitor the occurrence of reattempts.

On January 9, 2022, Belgian pop singer Stromae performed his new hit "L'enfer" live on French TV. The song addresses his personal struggles with suicidal ideation. To evaluate the impact of Stromae's performance, we modeled the evolution of hospital admission rates for suicide attempts (SAs) in France, calls to the national suicide prevention helpline (3114), and Twitter publications mentioning the singer or the helpline. We employed the Gombay test to identify change points within each time series. We identified a significant increase in mean SA rates among women aged 20-24 years 6 days after the singer's performance. No similar effect was observed in the general population or other young age groups. The show was immediately followed by a peak in tweets referring to the singer, while Twitter activity related to the 3114 remained modest. We did not observe any increase in calls to the helpline. Celebrity testimonies about suicidal experiences can help alleviate stigma but should be accompanied by prevention messages to reduce the risk of contagion.

Background: Estimating the risk of developing bipolar disorder (BD) in children and adolescents (C&A) with depressive disorders is important to optimize prevention and early intervention efforts. We aimed to quantitatively examine the risk of developing BD from depressive disorders and identify factors which moderate this development.

Methods: In this systematic review and meta-analysis (PROSPERO:CRD42023431301), PubMed and Web-of-Science databases were searched for longitudinal studies reporting the percentage of C&A with ICD/DSM-defined depressive disorders who developed BD during follow-up. Data extraction, random-effects meta-analysis, between-study heterogeneity analysis, quality assessment, sub-group analyses, and meta-regressions were conducted.

Results: Thirty-nine studies were included, including 72,371 individuals (mean age=13.9 years, 57.1% females); 14.7% of C&A with a depressive disorder developed BD after 20.4-288 months: 9.5% developed BD-I (95% CI=4.7 to 18.1); 7.7% developed BD-II (95% CI=3.2% to 17.3%); 19.8% (95% CI=9.9% to 35.6%) of C&A admitted into the hospital with a depressive disorder developed BD. Studies using the DSM (21.6%, 95% CI=20.2% to 23.1%) and studies evaluating C&A with a major depressive disorder only (19.8%, 95% CI=16.8% to 23.1%) found higher rates of development of BD. Younger age at baseline, a history of hospitalization and recruitment from specialized clinics were associated with an increased risk of developing BD at follow-up. Quality of included studies was good in 76.9% of studies.

Conclusions: There is a substantial risk of developing BD in C&A with depressive disorders. This is particularly the case for C&A with MDD, DSM-diagnosed depressive disorders, and C&A admitted into the hospital. Research exploring additional predictors and preventive interventions is crucial.

Background: Cardiovascular disease (CVD) is twice as prevalent among individuals with mental illness compared to the general population. Prevention strategies exist but require accurate risk prediction. This study aimed to develop and validate a machine learning model for predicting incident CVD among patients with mental illness using routine clinical data from electronic health records.

Methods: A cohort study was conducted using data from 74,880 patients with 1.6 million psychiatric service contacts in the Central Denmark Region from 2013 to 2021. Two machine learning models (XGBoost and regularised logistic regression) were trained on 85% of the data from six hospitals using 234 potential predictors. The best-performing model was externally validated on the remaining 15% of patients from another three hospitals. CVD was defined as myocardial infarction, stroke, or peripheral arterial disease.

Results: The best-performing model (hyperparameter-tuned XGBoost) demonstrated acceptable discrimination, with an area under the receiver operating characteristic curve of 0.84 on the training set and 0.74 on the validation set. It identified high-risk individuals 2.5 years before CVD events. For the psychiatric service contacts in the top 5% of predicted risk, the positive predictive value was 5%, and the negative predictive value was 99%. The model issued at least one positive prediction for 39% of patients who developed CVD.

Conclusions: A machine learning model can accurately predict CVD risk among patients with mental illness using routinely collected electronic health record data. A decision support system building on this approach may aid primary CVD prevention in this high-risk population.

Background: Postpartum anxiety (PPA) symptoms have harmful effects on child development and mother-infant interactions. Accordingly, in-depth knowledge of associated risk factors is crucial for prevention policies. This study aimed to estimate PPA symptom prevalence at 2 months and to identify associated risk factors in a representative sample of all women who gave birth in France in 2021, and in two subgroups: women with no postpartum depression (PPD) symptoms, and those with no history of mental health care.

Methods: Among the 12,723 women included in the representative French national perinatal survey 2021ENP, 7,133 completed the Edinburgh Postnatal Depression Scale (EPDS) self-administered questionnaire - including three anxiety-specific items (EPDS-3A) - at 2 months postpartum. We estimated the adjusted prevalence ratios (aPR) of PPA symptoms using Poisson regression models with robust variance.

Results: PPA symptom prevalence at 2 months was 27.6% (95% CI [26.5-28.8]). Associated risk factors were: age ≤ 34 years (maximum aPR = 1.38 [1.22-1.58] obtained for persons aged 25-29 years vs. 35-39 years), poorer health literacy (1.15 [1.07-1.23]), a history of medical termination of pregnancy (1.32 [1.05-1.68]), psychological (1.31 [1.17-1.47]) or psychiatric (1.42 [1.24-1.63]) care history since adolescence, nulliparity (1.23 [1.12-1.35]), no weight gain or loss (1.29 [1.03-1.61] vs. 9-15 kg gain) or gain ≥23 kg (1.20 [1.00-1.43]) during pregnancy, ≥3 pregnancy-related emergency consultations (1.16 [1.03-1.31] vs. none), poor/good support during pregnancy, (1.16 [1.00-1.34] and 1.15 [1.05-1.26], respectively, vs. very good), sadness (1.52 [1.36-1.69]), anhedonia (1.48 [1.27-1.72]), or both (1.99 [1.79-2.21]) during pregnancy, not at all/not very satisfied with pain management during childbirth (1.16 [1.01-1.32] vs. quite/very satisfied). Similar risk factors were found in the 'no PPD symptoms' and 'no history of mental health care' subgroups.

Conclusions: Estimated PPA symptom prevalence at 2 months in our study sample was 27.6%. The risk factors we identified may guide future prevention policies.