Journal of Clinical Psychiatry最新文献

Objectives: Recent studies report a fluctuating course of attention-deficit/ hyperactivity disorder (ADHD) across development characterized by intermittent periods of remission and recurrence. In the Multimodal Treatment of ADHD (MTA) study, we investigated fluctuating ADHD including clinical expression over time, childhood predictors, and between- and within-person associations with factors hypothesized as relevant to remission and recurrence.

Methods: Children with DSM-5 ADHD, combined type (N = 483), participating in the MTA adult follow-up were assessed 9 times from baseline (mean age = 8.46) to 16-year follow-up (mean age = 25.12). The fluctuating subgroup (63.8% of sample) was compared to other MTA subgroups on variables of interest over time.

Results: The fluctuating subgroup experienced multiple fluctuations over 16 years (mean = 3.58, SD = 1.36) with a 6- to 7-symptom within-person difference between peaks and troughs. Remission periods typically first occurred in adolescence and were associated with higher environmental demands (both between- and within-person), particularly at younger ages. Compared to other groups, the fluctuating subgroup demonstrated moderate clinical severity. In contrast, the stable persistent group (10.8%) was specifically associated with early and lasting risk for mood disorders, substance use problems in adolescence/ young adulthood, low medication utilization, and poorer response to childhood treatment. Protective factors were detected in the recovery group (9.1%; very low parental psychopathology) and the partial remission group (15.6%; higher rates of comorbid anxiety).

Conclusions: In the absence of specific risk or protective factors, individuals with ADHD demonstrated meaningful within-individual fluctuations across development. Clinicians should communicate this expectation and monitor fluctuations to trigger as-needed return to care. During remission periods, individuals with ADHD successfully manage increased demands and responsibilities.

Trial Registration: ClinicalTrials.gov identifier: NCT00000388.

Background: Bipolar disorder represents a significant source of morbidity and elevated mortality risk. Ketamine has emerged as a powerful antidepressant; however, there have been few trials of ketamine in bipolar depression and no trials with esketamine in bipolar depression, and few data exist from real-world settings. Here, we report outcomes from a cohort of patients with bipolar depression treated with ketamine/ esketamine in a real-world setting.

Methods: Patients with treatment refractory bipolar depression were referred to Yale Psychiatric Hospital Interventional Services for treatment from October 2014 to November 2023. Appropriate patients were treated with intravenous (IV) ketamine (0.5 mg/kg over 40 minutes) or intranasal esketamine (56 or 84 mg). Diagnosis of bipolar depression was done by clinical evaluation by an attending psychiatrist, based on DSM criteria. Clinical outcomes were tabulated from medical records.

Results: Overall, 45 patients with bipolar depression were treated with IV ketamine or intranasal (IN) esketamine during the time period specified. Depression severity outcomes were available for 38 patients that completed an acute series, defined as treatment twice weekly for up to 4 weeks. Overall, 15/38 (39%) achieved clinical response (≥50% improvement on the Montgomery-Asberg Depression Rating Scale [MADRS]) and 5/38 (13.2%) achieved remission (≤10 on MADRS) following the acute series. Mean MADRS scores decreased from 31.1 to 19.2 (38.3% mean improvement). Safety data (hypomania/manic symptoms) were available for all 45 patients (518 patient-months of follow-up). No patients experienced any mania/hypomania during the acute series phase (when treatments are given twice weekly). However, 13/45 (28.9%) patients experienced symptoms consistent with a hypomanic or manic episode at some point following the acute phase while continuing to receive ketamine or esketamine during a maintenance phase. There were 16 manic/hypomanic events, indicating 1 event for every 2.7 patient-years. Only 1 event was severe and resulted in hospitalization.

Conclusion: In a small sample of patients with bipolar depression treated with ketamine/esketamine, no evidence of mania/hypomania was seen during the acute phase of treatment. Further research is needed to evaluate whether ketamine or esketamine confers heightened risk of affective switch during maintenance treatment.

Objective: Suicide is a critical global health concern. Research indicates that generative artificial intelligence (GenAI) and large language models, such as generative pretrained transformer-3 (GPT-3) and GPT-4, can evaluate suicide risk comparably to experts, yet the criteria these models use are unclear. This study explores how variations in prompts, specifically regarding past suicide attempts, gender, and age, influence the risk assessments provided by ChatGPT-3 and ChatGPT-4.

Methods: Using a controlled scenario based approach, 8 vignettes were created. Both ChatGPT-3.5 and ChatGPT 4 were used to predict the likelihood of serious suicide attempts, suicide attempts, and suicidal thoughts. A univariate 3-way analysis of variance was conducted to analyze the effects of the independent variables (previous suicide attempts, gender, and age) on the dependent variables (likelihood of serious suicide attempts, suicide attempts, and suicidal thoughts).

Results: Both ChatGPT-3.5 and ChatGPT-4 recognized the importance of previous suicide attempts in predicting severe suicide risks and suicidal thoughts. ChatGPT-4 also identified gender differences, associating men with a higher risk, while both models disregarded age as a risk factor. Interaction analysis revealed that ChatGPT-3.5 associated past attempts with a higher likelihood of suicidal thoughts in men, whereas ChatGPT-4 showed an increased risk for women.

Conclusions: The study highlights ChatGPT-3.5 and ChatGPT-4's potential in suicide risk evaluation, emphasizing the importance of prior attempts and gender, while noting differences in their handling of interactive effects and the negligible role of age. These findings reflect the complexity of GenAI decision-making. While promising for suicide risk assessment, these models require careful application due to limitations and real-world complexities.

Objective: In this meta-analysis, we evaluated changes in cognition for patients with schizophrenia spectrum disorders (SSD) with different durations of illness (DOIs).

Data Sources: Records were identified through searches in PubMed, PsycINFO, CINAHL, and Cochrane until December 2021. We used terms related to SSDs, chronicity, course, and recovery.

Study Selection and Data Extraction: We included 57 longitudinal studies, with a follow-up length of at least 1 year, investigating changes in 10 domains of cognition of patients who are all diagnosed with SSD. Changes in cognition were analyzed through effect sizes of change between baseline and follow-up assessments within each study. These changes were evaluated in different subgroups of studies including patients with a DOI <5 years, 5-10 years, or >10 years. We also investigated the influence of 19 potential moderators on these changes in cognition.

Results: We found marginal improvements in overall cognition (d =0.13), small improvements in verbal memory (d = 0.21), processing speed (d = 0.32), marginal improvements in visual memory (d = 0.17), executive functioning (d = 0.19), and language skills (d = 0.13), and no significant improvements in the other cognitive domains. The largest improvements were achieved for patients with a DOI <10 years. Changes are more favorable for patients with a younger age, no schizophrenia diagnosis, female gender, higher education level, and low negative symptom severity.

Conclusions: We observed only modest cognitive improvement in SSD almost exclusively in patients with early psychosis. Future research should focus on optimizing interventions targeting cognition in specific subgroups and the interrelationships with other life domains.

The use of regression analysis is common in research. This article presents an introductory section that explains basic terms and concepts such as independent and dependent variables (IVs and DVs), covariates and confounds, zero-order correlations and multiple correlations, variance explained by variables and shared variance, bivariate and multivariable linear regression, line of least squares and residuals, unadjusted and adjusted analyses, unstandardized (b) and standardized (β) coefficients, adjusted R², interaction terms, and others. Next, this article presents a more advanced section with the help of 3 examples; the raw data files for these examples are included in supplementary materials, and readers are encouraged to download the data files and run the regressions on their own in order to better follow what is explained in the text (this, however, is not mandatory, and readers who do not do so can also follow the discussions in the text). The 3 examples illustrate many points. When important covariates are not included in regressions, the included IVs explain a smaller proportion of the variance in the DV, and the relationships between the included IVs and the DV may not be correctly understood. Including interaction terms between IVs can improve the explanatory value of the model whether the IVs are intercorrelated or not. When IVs are intercorrelated (such as when one is a confound), although their net effect in multivariable regression may explain a greater proportion of the variance in the DV, their individual b and β coefficients decrease in proportion to the shared variance that is removed. Thus, variables that were found statistically significant in unadjusted analyses may lose statistical significance in fully adjusted analyses. Readers may find it useful to keep these points in mind when running regressions on their data or when reading studies that present their results through regressions.

Objective: To determine the validity of telephone or video interviews, compared to face-to-face, for psychiatric diagnosis.

Data Sources: We searched MEDLINE, Embase, and PsycINFO from inception to June 22, 2023, and performed backward and forward citation analysis on all included studies on August 3, 2023.

Study Selection: We included primary studies comparing live telehealth (via telephone or videoconferencing) with face-to-face interviews using the same standardized diagnostic criteria for a mental health condition. Each patient had to undergo both modes of interviewing. Risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies-2.

Results: This review included 35 studies. Seven are clinical studies that compare telehealth with face-to-face consultations for initial psychiatric diagnosis; telehealth via video or telephone is a reliable alternative for some specific disorders or for use in some specific populations that were studied. The other 28 studies compared telehealth to face-to-face interviews for the use of mental health standardized diagnostic instruments for a broad range of conditions, including depression, bipolar disorder, posttraumatic stress disorder, social anxiety disorder, and autism spectrum disorder, demonstrating good agreement and reliability. Telehealth holds promise for psychiatric assessments, especially when in-person evaluations are not feasible.

Conclusions: From the limited studies primarily conducted before the expansion of telehealth during the COVID-19 pandemic, several small studies suggest that telehealth's psychiatric diagnoses or assessments of various psychiatric conditions seem to be a viable option and should be considered for certain patients during situations, settings, or environments. More research is needed, as telehealth has become more broadly utilized.

Objective: While collaborative care is known to improve depressive and anxiety symptoms in primary care, comparative effectiveness studies of virtual collaborative care versus virtual specialty psychiatry treatment in real world settings are lacking. This study examined patient depressive and anxiety symptoms over 6 months in collaborative care versus specialty psychiatry.

Methods: This was an observational study with target trial emulation in a large, community-based, integrated health care system. Participants were ≥18 years old with mild-moderate depressive or anxiety symptoms measured by the Patient Health Questionnaire-9 or Generalized Anxiety Disorder-7 Scale. Exclusion criteria included acute suicide risk. Patients were assigned to collaborative care or specialty psychiatry, and symptoms were measured 6 months after treatment initiation using linear mixed-effects regression with inverse probability of treatment weighting.

Results: There were N = 10,380 patients (n = 1,607 in collaborative care; n = 8,773 in specialty psychiatry) with depressive disorders and N = 2,935 (n = 570 in collaborative care; n = 2,365 in specialty psychiatry) with anxiety disorders. Model effects at 6 months showed significant symptom improvement for patients in collaborative care (adjusted mean difference [AMD] = -9.0, 95% CI, -9.7, -8.4 for depression; -5.4, 95% CI, -6.2, -4.7 for anxiety) and in specialty psychiatry (AMD = -5.0, 95% CI, -5.6, -4.5 for depression; -2.8, 95% CI, -3.6, -2.1 for anxiety), with patients in collaborative care showing significantly greater improvement compared to those in specialty psychiatry (AMD = -4.0, 95% CI, -4.7, -3.3, P < .0001 for depression; AMD = -2.6, 95% CI, -3.4, -1.8, P < .0001 for anxiety).

Conclusions: Virtual collaborative care was at least as effective as specialty psychiatry for depression and anxiety. Collaborative care implementation can support national guidelines regarding depression and anxiety screening and treatment.

Objective: Major depressive disorder (MDD) is a common psychiatric disorder for which pharmacologic standard-of-care treatments have limited efficacy, particularly among individuals with cognitive dysfunction. Cognitive dysfunction is observed in approximately 25%-50% of those with MDD, wherein response to standard-of-care medications is reduced. Vortioxetine is an approved antidepressant that has shown evidence of procognitive effects in patients. It is not known if it has greater clinical efficacy in MDD patients with cognitive dysfunction, a more difficult to treat population, than other antidepressants.

Methods: This study was a reanalysis of 1,812 subjects with MDD across 4 placebo controlled trials. Baseline cognition was measured by the Digit Symbol Substitution Test (DSST), the primary measure used to demonstrate vortioxetine's procognitive effects in clinical studies. Analyses examined whether baseline cognitive function was associated with differences in treatment outcomes.

Results: Baseline DSST did not predict placebo-adjusted treatment effects of vortioxetine on depressive symptoms (pooled Cohen d = -0.02, 95% CI = -0.12 to 0.07). Analyses of additional cognitive measures similarly did not predict placebo-adjusted treatment effects on depression (all 95% CI contained zero). Finally, analyses of trials with selective serotonin reuptake inhibitors (SSRIs)/serotonin and norepinephrine reuptake inhibitors (SNRIs) as active comparators also revealed no prediction of SSRI/SNRI adjusted treatment effects of vortioxetine on depression.

Conclusions: These findings, taken together, suggest that cognitive function does not moderate depression outcomes in vortioxetine, with results comparable to other antidepressants.