Acta Psychiatrica Scandinavica最新文献

Background

Functional recovery remains a core clinical objective for patients with bipolar disorder (BD). Sociodemographic, clinical, and neurocognitive variables are associated with long-term functional impairment, yet the impact of sex differences is unclear. Functional remediation (FR) is a validated intervention aimed at achieving functional recovery in BD. The present study assessed the effect of sex differences of FR on psychosocial functioning at post-treatment (6-months) and 12-month follow-up (FUP). To the best of our knowledge, this is the first study to explore the role of sex as a factor in the efficacy of FR.

Methods

157 participants with BD were randomly assigned to either FR (N = 77) or treatment as usual group (80). Clinical, sociodemographic, neuropsychological, and functional data were obtained using a comprehensive assessment battery. Sex differences were explored via a general linear model (GLM) for repeated measures to compare the effect of sex on the intervention over time (6 months and FUP).

Results

Results demonstrated that FR benefits both sexes, males (p = 0.001; d’ = 0.88) and females (p = 0.04; d’ = 0.57), at 6 months suggesting a generalized functional improvement. Conversely, at 12-month FUP sex differences were observed only in males (p = 0.005; d’ = 0.68).

Conclusions

FR is a beneficial intervention for males and females after treatment, suggesting that there are no relevant distinct needs. Females may benefit from ongoing psychosocial functioning booster sessions after the intervention to maintain original improvements. Future research exploring sex differences could help to identify strategies to offer personalized FR intervention approaches in individuals with BD.

Objective

Childhood maltreatment is associated with less favourable treatment outcomes with pharmacotherapy and psychotherapy for depression. It is unknown whether this increased risk of treatment resistance in maltreated individuals extends to electroconvulsive therapy (ECT).

Methods

This retrospective cohort study included 501 consecutive adult referrals for an acute course of twice-weekly ECT for unipolar or bipolar depression at an academic inpatient centre in Ireland between 2016 and 2024. Retrospectively reported physical and sexual childhood maltreatment were assessed on hospital admission. Response was defined as a score of 1 or 2 and remission was defined as a score of 1 on the Clinical Global Impression – Improvement scale 1–3 days after final ECT session. Logistic regression analyses were used to examine the associations between childhood maltreatment and ECT nonresponse and nonremission, adjusting for covariates. Mediation analyses were conducted to explore the role of psychiatric comorbidities, persistent depressive symptoms lasting 2 years or more in the current episode, and baseline depression severity.

Results

Compared to the group with no childhood maltreatment, the childhood maltreatment group had similar odds of ECT nonresponse (adjusted odds ratio = 1.47, 95% CI = 0.85–2.53) but significantly elevated odds of ECT nonremission (adjusted odds ratio = 3.75, 95% CI = 1.80–7.81). In a mediation analysis, presence of persistent depressive symptoms mediated 7.4% of the total effect of childhood maltreatment on ECT nonremission.

Conclusion

Individuals with exposure to childhood maltreatment may be less likely to achieve full remission following a course of ECT.

Objective

To evaluate the association between exposure to atypical antipsychotics during pregnancy and risk of miscarriage.

Material and Methods

This nested case–control study used a large Japanese administrative database. Pregnancy onset and outcomes were estimated using previously reported algorithms, classifying cases as women becoming pregnant between 2013 and 2022 and ending in a miscarriage. Controls were randomly selected from the entire pregnancy cohort by risk-set sampling with replacement and were individually matched to the cases (3:1). The association between exposure to atypical antipsychotics and risk of miscarriage was assessed using conditional logistic regression adjusted for confounders. The association between benzodiazepine exposure and the risk of miscarriage was assessed as a positive control.

Results

In the cohort, 44,118 patients were matched with 132,317 controls. The mean ages (standard deviations) of the case and control groups were 33.3 (5.7) and 33.2 (5.5) years, respectively. The prevalence of atypical antipsychotics was 0.5% in both groups. Aripiprazole is an individual antipsychotic with the highest prescription prevalence. The adjusted odds ratios (aOR) for miscarriage were 0.966 (95% confidence interval [CI], 0.796–1.173) for atypical antipsychotics and 0.998 (0.784–1.269) for aripiprazole. A higher aOR (1.431, 95% CI 1.303–1.573) suggested an association with benzodiazepines. A sensitivity analysis that limited the population to women diagnosed with schizophrenia alone did not suggest an association between atypical antipsychotics and the risk of miscarriage.

Conclusions

The results of this study do not suggest an association between exposure to atypical antipsychotics during pregnancy and the risk of miscarriage.

Introduction

Peripartum depression is common and treatment with mirtazapine may be indicated. However, evidence on its safety in pregnancy and lactation is fragmented.

The objective of this systematic review was to evaluate the literature on the safety of mirtazapine in pregnancy and lactation.

Methods

PubMed, Embase, Medline, PsycInfo, and clinicaltrials.gov were searched for ‘antidepressants’ or ‘mirtazapine’ in combination with ‘pregnancy’, ‘lactation’ or ‘offspring’.

No restrictions on type of study were applied and selection was performed by two independent reviewers using Covidence. Two reviewers extracted data and performed risk of bias assessment and evidence synthesis was performed for each outcome individually.

The protocol was registered at PROSPERO (registration number CRD42021275127).

Results

The initial search yielded 15,380 articles after removal of duplicates. After screening based on title and abstract, 431 articles remained for full text review. Of these, 41 studies were included (15 cohort studies, one case–control study, 11 case series, and 14 case reports). In most studies, the outcomes in mirtazapine-exposed pregnancies were comparable to controls. However, results on congenital malformations and spontaneous abortion were conflicting. Neonatal adaptation syndrome was reported after mirtazapine exposure in late pregnancy. Data on mirtazapine exposure during lactation were scarce.

Conclusions

We identified no substantial evidence indicating that mirtazapine exposure is associated with adverse outcomes in pregnancy or in offspring, other than neonatal adaptation syndrome. However, overall quality of evidence was low, and results on congenital malformations and spontaneous abortions were conflicting. Data on mirtazapine exposure through breastfeeding were limited and did not allow for conclusions.

Introduction

Accurate detection of cardiometabolic risk in early psychosis is crucial to reducing somatic morbidity and mortality in people with psychotic disorders. We conducted an external validation of the psychosis metabolic risk calculator (PsyMetRiC), a cardiometabolic risk prediction tool developed in the UK and tailored for young people with psychosis. We compared the predictive accuracy and clinical usefulness of PsyMetRiC and a general population-based risk prediction tool for type 2 diabetes, the Finnish Diabetes Risk Score (FINDRISC).

Methods

We included first-episode psychosis and ultra-high-risk for psychosis patients without metabolic syndrome aged 18–35 years from the Helsinki Early Psychosis and Turku Early Psychosis Study cohorts. We tested two versions of PsyMetRiC: the full model including age, sex, ethnicity, body-mass index, smoking status, prescription of metabolically-active antipsychotic medication, high-density lipoprotein, and triglyceride concentrations, and the partial-model excluding biochemical predictors, and the simplified FINDRISC including BMI, sex, systolic blood pressure, and fasting glucose. Discrimination, calibration, and decision curve analyses were used to assess the predictive performance and clinical usefulness of both PsyMetRiC and FINDRISC. We performed a site-specific re-calibration of PsyMetRiC (PsyMetRiC-Fi).

Results

The study sample consisted of 278 individuals (all White European ethnicity, 58.6% male, mean age 24.8 years, 37.8% smoking, mean BMI 23.5). Discrimination was marginally better in the PsyMetRiC full model (C = 0.72, 95% CI, 0.59–0.82) compared with partial model (C = 0.70, 95% CI 0.59–0.80) or FINDRISC (C = 0.63, 95% CI 0.54–0.71). Calibration plots displayed evidence of minor miscalibration for PsyMetRiC, which corrected following recalibration. Miscalibration was more pronounced for FINDRISC. Decision curve analysis showed that PsyMetRiC offers likely clinical usefulness in improving cardiometabolic risk management in early psychosis compared with giving everyone or no one an intervention.

Conclusion

PsyMetRiC has utility in predicting cardiometabolic risk in Finnish patients with early psychosis. It has better discriminatory accuracy and offers more accurate risk prediction compared to other available strategies.

Introduction

Suicidal ideation variability refers to within-day fluctuations in suicidal ideation, and has recently been proposed as an indicator of suicide risk. However, not much is known yet about its correlates and clinical relevance.

Methods

We examined characteristics of real-time suicidal ideation using Ecological Momentary Assessment in 82 individuals with current active suicidal ideation. Data were collected four times daily over 21 days. Latent profile analysis was used to identify subtypes of suicidal ideation. We further examined sociodemographic and clinical correlates of the profiles, and their association with the occurrence of suicide attempts during a 1-year follow-up.

Results

We identified three “digital” phenotypes of suicidal ideation that differed on the frequency, intensity and variability of ideation. The profiles were: high frequency, high intensity, moderate variability (Phenotype 1), moderate/high frequency, moderate intensity, high variability (Phenotype 2), and moderate frequency, low intensity, low variability (Phenotype 3). Phenotypes 1 and 2 were associated with a worse clinical profile at baseline (higher suicidal ideation and depressive symptom severity), and increased odds of suicide attempt during follow-up, compared to Phenotype 3. Phenotype 1 was further characterized by repeated suicidal behavior.

Conclusions

Two phenotypes of real-time suicidal ideation were identified that appear to confer a higher risk of suicidal behavior in the near future (12 months). These phenotypes were characterized by higher variability of suicidal ideation—and also higher intensity and frequency of ideation. Considering the small sample size, the clinical usefulness of the profiles remains to be demonstrated.

Objectives

Schizophrenia is associated with an increased risk of suicide. Few studies have investigated the risk of suicide across different ages, likely due to limitations around sample size.

Methods

From the National Health Insurance Research Database in Taiwan, this study identified 195,787 patients with schizophrenia from January 1, 2000, to December 31, 2019. During the study period, 3848 patients died from suicide. We calculated the standardized mortality ratio (SMR) for suicide stratified by age. In this age-stratified, nested case–control study, risk set sampling was used to match each case with 4 living controls by age, sex, and the year of the first diagnosis with schizophrenia. Conditional logistic regression was used for estimating age-stratified risk profiles.

Results

The SMR was the highest in the <25 years age group (52.8) and inversely correlated with age. Unemployment was associated with an increased risk of suicide in the 25 to 34, 35 to 44, 45 to 54, and 55 to 64 years age groups. Depressive and sleep disorders before suicide were more common among suicide cases with schizophrenia than among controls across all age groups. Drug-induced and alcohol-induced mental disorders were significantly associated with suicide but were observed only in the age group younger than 54. Heart disease, pneumonia, and moderate or severe renal disease were risk factors for suicide in the age groups less than 65.

Conclusions

The risk factors for suicide differ by age. This study's findings can be used to optimize health-care interventions for preventing suicide in patients with schizophrenia.

Introduction

The aim of this systematic review is to assess the functional magnetic resonance imaging (fMRI) studies of bipolar disorder (BD) patients that characterize differences in terms of structural, functional, and effective connectivity between the patients with BD, patients with other psychiatric disorders and healthy controls as possible biomarkers for diagnosing the disorder using neuroimaging.

Methods

Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), guidelines a systematic search for recent (since 2015) original studies on connectivity in bipolar disorder was conducted in PUBMED and SCOPUS.

Results

A total of 60 studies were included in this systematic review: 20 of the structural connectivity, 33 of the functional connectivity, and only 7 of the studies focused on effective connectivity complied with the inclusion and exclusion criteria.

Discussion

Despite the great heterogeneity in the findings, there are several trends that emerge. In structural connectivity studies, the main abnormalities in bipolar disorder patients were in the frontal gyrus, anterior, as well as posterior cingulate cortex and differences in emotion and reward-related networks. Cerebellum (vermis) to cerebrum functional connectivity was found to be the most common finding in BD. Moreover, prefrontal cortex and amygdala connectivity as part of the rich-club hubs were often reported to be disrupted. The most common findings based on effective connectivity were alterations in salience network, default mode network and executive control network.

Although more studies with larger sample sizes are needed to ascertain altered brain connectivity as diagnostic biomarker, there is a perspective that the method could be used as a single marker of diagnosis in the future, and the process of adoption could be accelerated by using approaches such as semiunsupervised machine learning.