Psychological Medicine最新文献

Background: Involuntary admissions to psychiatric hospitals are on the rise. If patients at elevated risk of involuntary admission could be identified, prevention may be possible. Our aim was to develop and validate a prediction model for involuntary admission of patients receiving care within a psychiatric service system using machine learning trained on routine clinical data from electronic health records (EHRs).

Methods: EHR data from all adult patients who had been in contact with the Psychiatric Services of the Central Denmark Region between 2013 and 2021 were retrieved. We derived 694 patient predictors (covering e.g. diagnoses, medication, and coercive measures) and 1134 predictors from free text using term frequency-inverse document frequency and sentence transformers. At every voluntary inpatient discharge (prediction time), without an involuntary admission in the 2 years prior, we predicted involuntary admission 180 days ahead. XGBoost and elastic net models were trained on 85% of the dataset. The models with the highest area under the receiver operating characteristic curve (AUROC) were tested on the remaining 15% of the data.

Results: The model was trained on 50 634 voluntary inpatient discharges among 17 968 patients. The cohort comprised of 1672 voluntary inpatient discharges followed by an involuntary admission. The best XGBoost and elastic net model from the training phase obtained an AUROC of 0.84 and 0.83, respectively, in the test phase.

Conclusion: A machine learning model using routine clinical EHR data can accurately predict involuntary admission. If implemented as a clinical decision support tool, this model may guide interventions aimed at reducing the risk of involuntary admission.

Background: Genetic vulnerability to mental disorders has been associated with coronavirus disease-19 (COVID-19) outcomes. We explored whether polygenic risk scores (PRSs) for several mental disorders predicted poorer clinical and psychological COVID-19 outcomes in people with pre-existing depression.

Methods: Data from three assessments of the Australian Genetics of Depression Study (N = 4405; 52.2 years ± 14.9; 76.2% females) were analyzed. Outcomes included COVID-19 clinical outcomes (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2] infection and long COVID, noting the low incidence of COVID-19 cases in Australia at that time) and COVID-19 psychological outcomes (COVID-related stress and COVID-19 burnout). Predictors included PRS for depression, bipolar disorder, schizophrenia, and anxiety. The associations between these PRSs and the outcomes were assessed with adjusted linear/logistic/multinomial regressions. Mediation (N = 4338) and moderation (N = 3326) analyses were performed to explore the potential influence of anxiety symptoms and resilience on the identified associations between the PRSs and COVID-19 psychological outcomes.

Results: None of the selected PRS predicted SARS-CoV-2 infection or long COVID. In contrast, the depression PRS predicted higher levels of COVID-19 burnout. Anxiety symptoms fully mediated the association between the depression PRS and COVID-19 burnout. Resilience did not moderate this association.

Conclusions: A higher genetic risk for depression predicted higher COVID-19 burnout and this association was fully mediated by anxiety symptoms. Interventions targeting anxiety symptoms may be effective in mitigating the psychological effects of a pandemic among people with depression.

The impact of vitamin D supplementation on depressive symptoms remains uncertain. This study aimed to investigate the dose-dependent effects of vitamin D supplementation on depressive and anxiety symptoms in adults. We systematically searched PubMed, Scopus, and Web of Science up to December 2022 to identify randomized controlled trials evaluating the effects of vitamin D₃ supplementation on depression and anxiety symptoms in adults. Using a random-effects model, we calculated the standardized mean difference (SMD) for each 1000 IU/day vitamin D₃ supplementation. The GRADE tool assessed the certainty of evidence. Our analysis included 31 trials with 24189 participants. Each 1000 IU/day vitamin D₃ supplementation slightly reduced depressive symptoms in individuals with and without depression (SMD: -0.32, 95% CI -0.43 to -0.22; GEADE = moderate). The effect was more pronounced in those with depressive symptoms (SMD: -0.57, 95% CI -0.69 to -0.44; n = 15). The greatest reduction occurred at 8000 IU/day (SMD: -2.04, 95% CI -3.77 to -0.31). Trials with follow-up ⩽8 weeks (SMD: -0.45, 95% CI -0.70 to -0.20; n = 8) and 8 to ⩽24 weeks (SMD: -0.47, 95% CI -0.70 to -0.24; n = 15) showed stronger effects compared to those lasting 24 to ⩽52 weeks (SMD: -0.13, 95% CI -0.28 to 0.02; n = 5) or longer than 52 weeks (SMD: 0.14, 95% CI -0.16 to 0.44; n = 3) (p group difference <0.001). Vitamin D₃ supplementation had no significant effects on anxiety symptoms. In summary, this study suggests that vitamin D₃ supplementation may effectively reduce depressive symptoms in short term. Further high-quality trials are warranted for a conclusive assessment of its impact on anxiety.

Background: We aimed to identify the common types of outcome trajectories for patients with psychosis who take up specialist psychological therapy for persecutory delusions. Knowing the different potential responses to therapy can inform expectations. Further, determining predictors of different outcomes may help in understanding who may benefit.

Methods: We analyzed delusion conviction data from 767 therapy sessions with 64 patients with persistent persecutory delusions (held with at least 60% conviction) who received a six-month psychological intervention (Feeling Safe) during a clinical trial. Latent class trajectory analysis was conducted to identify groups with distinct outcome profiles. The trajectories were validated against independent assessments, including a longer-term follow-up six months after the end of therapy. We also tested potential predictors of the trajectories.

Results: There were four outcome trajectories: (1) Very high delusion conviction/Little improvement (n = 14, 25%), (2) Very high delusion conviction/Large improvement (n = 9, 16%), (3) High delusion conviction/Moderate improvement (n = 17, 31%) and (4) High delusion conviction/Large improvement (n = 15, 27%). The groups did not differ in initial overall delusion severity. The trajectories were consistent with the independent assessments and sustained over time. Three factors predicted trajectories: persecutory delusion conviction, therapy expectations, and positive beliefs about other people.

Conclusions: There are variable responses to psychological therapy for persecutory delusions. Patients with very high delusion conviction can have excellent responses to therapy, though this may take a little longer to observe and such high conviction reduces the likelihood of positive responses. A trajectory approach requires testing in larger datasets but may prove highly informative.

Introduction: Short-term exposure to antipsychotics has proven to be beneficial. However, naturalistic studies are lacking regarding the long-term use of antipsychotics. This study aimed to investigate changes in use of antipsychotics over 20 years after a first-episode schizophrenia.

Methods: This study is part of the Danish OPUS trial (1998-2000), including 496 participants with first-episode schizophrenia. Participants were reassessed four times over 20 years. The main outcomes were days on medication, redeemed prescriptions of clozapine, psychiatric hospitalizations, and employment.

Results: At the 20-year follow-up, an attrition of 71% was detected. In total, 143 out of 496 participated, with 36% (n = 51) in remission-of-psychotic-symptoms-off-medication. The lowest number of days on medication (mean [s.d.], 339 [538] days) was observed in this group over 20 years. Register data on redeemed antipsychotics were available for all trial participants (n = 416). Individuals in treatment with antipsychotics (n = 120) at the 20-year follow-up had spent significantly more days in treatment (5405 [1857] v. 1434 [1819] mean days, p = 0.00) and more had ever redeemed a prescription of clozapine (25% v. 7.8%, p = 0.00) than individuals who had discontinued antipsychotics (n = 296). Further, discontinuers had significantly higher employment at the 20-year follow-up (28.4% v. 12.5%, p = 0.00).

Conclusion: In a cohort of individuals with first-episode schizophrenia, 36% were in remission-of-psychotic-symptoms-off-medication. However, high attrition was detected, potentially affecting study results by inflating results from individuals with favorable outcomes. From register data, free from attrition, approximately 30% were in treatment with antipsychotics, and 70% had discontinued antipsychotics. Individuals in treatment had the least favorable outcomes, implying greater illness severity.

Background: To explore the association of cardiovascular-kidney-metabolic (CKM) health with the risk of depression and anxiety and to investigate the joint association of CKM health and social connection with depression and anxiety.

Methods: This prospective cohort study included 344 956 participants from the UK Biobank. CKM syndrome was identified as a medical condition with the presence of metabolic risk factors, cardiovascular disease, and chronic kidney disease, and was classified into five stages (stage 0-4) in this study. Loneliness and social isolation status were determined by self-reported questionnaires. Cox proportional hazards models were applied for analyses.

Results: Compared with participants in stage 0, the HRs for depression were 1.17 (95% CI 1.10-1.25), 1.40 (95% CI 1.33-1.48), and 2.14 (95% CI 1.98-2.31) for participants in stage 1, 2-3, and 4, respectively. Similarly, participants in stage 2-3 (HR = 1.20, 95% CI 1.14-1.26) and stage 4 (HR = 1.63, 95% CI 1.51-1.75) had greater risks of incident anxiety. We found additive interactions between loneliness and CKM health on the risk of depression and anxiety. Participants simultaneously reported being lonely and in stage 4 had the greatest risk of depression (HR = 4.44, 95% CI 3.89-5.07) and anxiety (HR = 2.58, 95% CI 2.21-3.01) compared with those without loneliness and in stage 0. We also observed an additive interaction between social isolation and CKM health on the risk of depression.

Conclusions: Our findings suggest the importance of comprehensive interventions to improve CKM health and social connection to reduce the disease burden of depression and anxiety.

Background: ADHD symptoms are associated with emotional problems such as depressive and anxiety symptoms from early childhood to adulthood, with the association increasing with age. A shared aetiology and/or a causal relationship could explain their correlation. In the current study, we explore these explanations for the association between ADHD symptoms and emotional problems from childhood to adulthood.

Methods: Data were drawn from the Twins Early Development Study (TEDS), including 3675 identical and 7063 non-identical twin pairs. ADHD symptoms and emotional symptoms were reported by parents from childhood to adulthood. Self-report scales were included from early adolescence. Five direction of causation (DoC) twin models were fitted to distinguish whether associations were better explained by shared aetiology and/or causal relationships in early childhood, mid-childhood, early adolescence, late adolescence, and early adulthood. Follow-up analyses explored associations for the two subdomains of ADHD symptoms, hyperactivity-impulsivity and inattention, separately.

Results: The association between ADHD symptoms and emotional problems increased in magnitude from early childhood to adulthood. In the best-fitting models, positive genetic overlap played an important role in this association at all stages. A negative causal effect running from ADHD symptoms to emotional problems was also detected in early childhood and mid-childhood. When distinguishing ADHD subdomains, the apparent protective effect of ADHD symptoms on emotional problems in childhood was mostly driven by hyperactivity-impulsivity.

Conclusions: Genetic overlap plays an important role in the association between ADHD symptoms and emotional problems. Hyperactivity-impulsivity may protect children from emotional problems in childhood, but this protective effect diminishes after adolescence.

Background: First-episode schizophrenia (FES) is a progressive psychiatric disorder influenced by genetics, environmental factors, and brain function. The functional gradient deficits of drug-naïve FES and its relationship to gene expression profiles and treatment outcomes are unknown.

Methods: In this study, we engaged a cohort of 116 FES and 100 healthy controls (HC), aged 7 to 30 years, including 15 FES over an 8-week antipsychotic medication regimen. Our examination focused on primary-to-transmodal alterations in voxel-based connection gradients in FES. Then, we employed network topology, Neurosynth, postmortem gene expression, and support vector regression to evaluate integration and segregation functions, meta-analytic cognitive terms, transcriptional patterns, and treatment predictions.

Results: FES displayed diminished global connectome gradients (Cohen's d = 0.32-0.57) correlated with compensatory integration and segregation functions (Cohen's d = 0.31-0.36). Predominant alterations were observed in the default (67.6%) and sensorimotor (21.9%) network, related to high-order cognitive functions. Furthermore, we identified notable overlaps between partial least squares (PLS1) weighted genes and dysregulated genes in other psychiatric conditions. Genes linked with gradient alterations were enriched in synaptic signaling, neurodevelopment process, specific astrocytes, cortical layers (layer II and IV), and developmental phases from late/mid fetal to young adulthood. Additionally, the onset age influenced the severity of FES, with discernible differences in connection gradients between minor- and adult-FES. Moreover, the connectivity gradients of FES at baseline significantly predicted treatment outcomes.

Conclusions: These results offer significant theoretical foundations for elucidating the intricate interplay between macroscopic functional connection gradient changes and microscopic transcriptional patterns during the onset and progression of FES.

Background: Machine learning (ML) has developed classifiers differentiating patient groups despite concerns regarding diagnostic reliability. An alternative strategy, used here, is to develop a functional classifier (hyperplane) (e.g. distinguishing the neural responses to received reward v. received punishment in typically developing (TD) adolescents) and then determine the functional integrity of the response (reward response distance from the hyperplane) in adolescents with externalizing and internalizing conditions and its associations with symptom clusters.

Methods: Two hundred and ninety nine adolescents (mean age = 15.07 ± 2.30 years, 117 females) were divided into three groups: a training sample of TD adolescents where the Support Vector Machine (SVM) algorithm was applied (N = 65; 32 females), and two test groups- an independent sample of TD adolescents (N = 39; 14 females) and adolescents with a psychiatric diagnosis (major depressive disorder (MDD), generalized anxiety disorder (GAD), attention deficit hyperactivity disorder (ADHD) & conduct disorder (CD); N = 195, 71 females).

Results: SVM ML analysis identified a hyperplane with accuracy = 80.77%, sensitivity = 78.38% and specificity = 88.99% that implicated feature neural regions associated with reward v. punishment (e.g. nucleus accumbens v. anterior insula cortices). Adolescents with externalizing diagnoses were significantly less likely to show a normative and significantly more likely to show a deficient reward response than the TD samples. Deficient reward response was associated with elevated CD, MDD, and ADHD symptoms.

Conclusions: Distinguishing the response to reward relative to punishment in TD adolescents via ML indicated notable disruptions in this response in patients with CD and ADHD and associations between reward responsiveness and CD, MDD, and ADHD symptom severity.

Background: Unpredictability is a core but understudied dimension of adversities and has been receiving increasing attention recently. The effects of unpredictability on psychopathology and the underlying neural mechanisms, however, remain unclear. It is also unknown how unpredictability interacts with other dimensions of adversities in predicting brain development and psychopathology of youth.

Methods: We applied cluster robust standard errors to examine how unpredictability was associated with the developmental changes in resting-state functional connectivity (rsFC) of large-scale brain networks implicated in psychopathology, as well as the moderating role of deprivation, using data from the Adolescent Brain Cognitive Development (ABCD) study, which included four measurements from baseline (mean ± s.d. age, 119.13 ± 7.51 months; 2815 females) to 3-year follow-up (N = 5885).

Results: After controlling for threat, unpredictability was associated with a smaller increase in rsFC within default mode network (DMN) and a smaller decrease in rsFC between cingulo-opercular network (CON) and DMN. Neighborhood educational deprivation moderated the associations between unpredictability and changes in rsFC within DMN and fronto-parietal network (FPN), as well as between CON and DMN. A smaller decrease in rsFC between CON and DMN mediated the association between unpredictability and externalizing problems. Neighborhood educational deprivation moderated the indirect pathway from unpredictability to externalizing problems via a smaller decrease in CON-DMN rsFC.

Conclusions: Our findings shed light on the neural mechanisms underlying the associations between unpredictability and adolescents' psychopathology and the moderating role of deprivation, highlighting the significance of providing stable environment and abundant educational opportunities to facilitate optimal development.