Pharmacopsychiatry最新文献

Fear and anxiety perform essential protective roles, yet when they become dysregulated, they can trap trauma survivors in persistent hypervigilance and distress. Post-traumatic stress disorder (PTSD) manifests as intrusive memories, avoidance, and heightened arousal long after the precipitating event. Although current pharmacotherapies - including selective serotonin reuptake inhibitors, adrenergic blockers, benzodiazepines, and atypical antipsychotics - provide relief for some, many patients contend with residual symptoms or intolerable adverse effects. Recent discoveries position the endocannabinoid system as a pivotal regulator of fear acquisition, consolidation, and extinction. Clinical observations of altered anandamide levels and cannabinoid receptor CB₁ upregulation in individuals with severe PTSD underscore the therapeutic potential of restoring endocannabinoid tone. Preclinical studies demonstrate that direct CB₁ agonists, fatty acid amide hydrolase (FAAH) inhibitors, and phytocannabinoids such as tetrahydrocannabinol (THC) and cannabidiol (CBD) can facilitate extinction learning and attenuate anxiety-like behaviours. Preliminary human trials report that nabilone alleviates trauma-related nightmares and that acute cannabinoid administration modulates amygdala reactivity to a threat. Yet optimal dosing strategies, sex-specific responses, and ideal THC:CBD ratios remain to be defined. Self-medication with cannabis can offer transient relief but carries a risk of cannabis use disorder and potential worsening of PTSD symptoms. By elucidating molecular targets - including CB₁, CB₂, FAAH, and monoacylglycerol lipase - this review outlines a strategic framework for next-generation cannabinoid-based interventions. Harnessing the endocannabinoid system promises to expand the therapeutic arsenal for PTSD, offering hope for more effective and better-tolerated treatments.

Background: Continuous antipsychotic (AP) therapy is crucial for managing psychotic disorders, and its early interruption reflects the drug's failure. Real-world epidemiological research is essential for confirming experimental data and generating new research hypotheses.

Methods: The persistence of oral APs in a large population sample from 2000 to 2021 was analyzed by comparing AP prescriptions over this period across four Italian provinces, using dispensing data linked via a record-linkage procedure among regional healthcare utilization databases. We calculated personalized daily dosages and assessed time-to-treatment discontinuation over a 3-month period for patients initiating AP treatment. Treatment persistence was evaluated using Kaplan-Meier curves and Cox regression, with adjustments for age and sex.

Results: Second-generation antipsychotics (SGAs) were favored over first-generation antipsychotics (FGAs), with olanzapine as the most prescribed. Within the study time frame, 42,434 individuals were prescribed a new continuous AP regimen. The analysis revealed 24 significant differences within 28 comparisons. As a class, SGAs demonstrated better treatment persistence than FGAs (HR: 0.76; 95%CI: 0.73, 0.79). Clozapine stood out for its superior persistence, surpassing all other SGAs, notably olanzapine (HR: 0.85; 95%CI: 0.79-0.91) and risperidone (HR: 0.80; 95%CI: 0.74-0.87). Olanzapine and aripiprazole showed better results than both risperidone and quetiapine. Quetiapine showed inferior 3-month persistence in all pairwise comparisons.

Conclusion: The study results provide insight into the performance dynamics among SGAs: clozapine, despite being one of the less frequently dispensed APs in our sample, emerged as a significant prescription choice. The significance of pharmacoepidemiological studies in complementing experimental findings is also underscored.

This systematic review investigates the instruments measuring medication literacy (ML) in psychiatric patients and their caregivers. Despite the critical role of ML in ensuring adherence to medication regimens, especially in populations with mental health conditions, existing instruments lack comprehensive validation of their measurement properties. This review identifies and assesses four instruments designed for psychiatric populations based on COSMIN guidelines. The findings reveal significant gaps in the validity and reliability of these tools. The review underscores the necessity for developing new, robust ML instruments tailored to people with mental illnesses and their caregivers to enhance clinical practice and patient outcomes. The results help to inform future psychiatry research and its clinical applications, promoting better medication management and improving adherence towards overall management in psychiatric care settings.

Regulatory compliance is crucial in the clinical development of psychedelic substances, including psilocybin. This study aimed to examine the alignment of clinical trial protocols for psilocybin in the treatment of major depressive disorder (MDD) and treatment-resistant depression (TRD) with established regulatory requirements.A cross-sectional investigation was conducted on ClinicalTrials.gov using the keywords: "Psilocybin" and "Psilocin" to identify interventional studies with posted trial protocols. Only protocols for MDD and TRD were included. Data extraction focused on key regulatory aspects, including safety, functional unblinding, expectancy bias, and the distribution of investigational medical products.Eleven psilocybin trial protocols were identified, with four meeting the inclusion criteria. The most commonly studied psilocybin dose was 25 mg. Two trials were double-blind. Although the analyzed protocols superficially adhered to regulatory requirements, there were gaps in addressing potential drug interactions, the acute and chronic concurrent use of antidepressants, and prohibited medications. Certain aspects, such as functional unblinding or expectancy bias, did not share all pathways. Risk mitigation strategies were primarily based on external criteria. Patients with bipolar spectrum disorders or schizoaffective disorders were excluded.This study underscores the importance of conducting clinical trials on psychedelics in strict adherence to regulatory standards. Future research should focus on improving regulatory compliance and exploring the efficacy of psychedelics in broader patient populations.

Measurement-based care (MBC) involves systematically assessing patients' symptoms and adverse events using standardized scales to guide treatment. While MBC has been shown to enhance the quality of care and outcomes in the pharmacotherapy of major depressive disorder (MDD), it is still rarely used in clinical practice. In this study, the feasibility of implementing MBC was assessed for patients with MDD seen in a large outpatient psychiatry clinic.Adults diagnosed with MDD were assessed at baseline and during a 12-week follow-up by phone or via emailed links with: the 9-item Patient Health Questionnaire (PHQ-9), an adverse effect rating scale, and a published suicide risk management protocol (SRMP). Antidepressants were recommended based on preferences expressed by the participant and treating psychiatrist; dosages were adjusted by the treating psychiatrist based on symptomatic improvement and adverse events.Over 2 years, 52 (21.2%) of 246 patients referred to the study were enrolled, 28 (53.8%) completed all assessments at all follow-up visits, 45 (87.0%) participants were prescribed one of the recommended antidepressants, and 22 (42.3%) remitted. Of the 27 participants presenting with suicidal ideation, 18 (66.6%) experienced a full resolution of these ideations.These findings highlight the challenges in implementing MBC for the pharmacotherapy of MDD and confirm some barriers to its broad adoption in clinical practice. The study also highlights its benefits in the selected group of patients who engage in MBC. Future studies need to continue to explore innovative ways to facilitate its broader implementation.

To develop an optimal model to predict valproic acid (VPA) concentrations by machine learning, ensuring that the VPA plasma concentration is in the effective treatment range, and thus effectively control the patient's epilepsy.This single-center, retrospective study included patients diagnosed with epilepsy from January 2014 to January 2022. Patients receiving VPA and having undergone therapeutic drug monitoring were enrolled. Top three algorithms exhibiting superior model performance were selected to establish the ensemble prediction model, with Shapley Additive exPlanations (SHAP) employed for model interpretation. An independent dataset was collected as a clinical validation group to verify the prediction model performance.The algorithms chosen for the ensemble model-Light Gradient Boosting, Categorical Boosting, and Gradient Boosted Regression Trees-demonstrated high R ² (0.549, 0.515, and 0.503, respectively). Post-feature selection, the final model incorporated 20 variables, proving superior in predictive performance compared to models considering all 24 variables. The R ² , mean absolute error, mean square error, absolute accuracy (±20 mg/L), and relative accuracy (±20%) of external validation were 0.621, 10.67, 221.50, 78.98%, and 66.48%, respectively. The importance and direction of each variable were visually represented using SHAP values, with VPA administration and liver function emerging as the most significant factors.The innovative application harnesses advanced multi-algorithm mining methodologies to forecast VPA concentrations in adult epileptic patients. Furthermore, it employs SHAP to elucidate the nuanced influence of each feature within the integrated prediction model, thereby providing a robust and plausible explanation for the determinants affecting VPA concentration predictions.

Both patients and physicians are routinely exposed to the corporate promotion of artificial intelligence (AI) for healthcare products. Hype for AI products may impact both patient behavior and attitudes about healthcare. Corporate AI hype may intentionally overlook the known limitations associated with AI products and focus solely on potential benefits. As AI is increasingly integrated into medicine, physicians are also routinely subject to AI hype. As the promotion and use of AI products have grown dramatically in recent years, physicians should be aware of the potential benefits and risks of AI products despite the hype.

Dose-related reference ranges can be used in therapeutic drug monitoring to monitor pharmacotherapy. The deviation of a measured serum concentration from the expected serum concentration at the corresponding dose can thus be identified early and responded to appropriately. The serum concentrations of patients treated with cariprazine regularly deviated from this dose-related reference range. As this is a relatively new drug with only one recommendation on values for a dose-related reference range, the values were tested for validity using real-world data.Serum concentrations of 24 patients receiving cariprazine once daily were analyzed retrospectively. Only patients without pharmacokinetic abnormalities were included. The measured serum concentrations were compared with the values of the dose-related reference range in the guidelines of the Arbeitsgemeinschaft für Neuropsychopharmakologie und Pharmakopsychiatrie consensus guidelines of 2017 and checked whether a sufficient number of serum concentrations were within the dose-related reference range.Only 45.8% of the measured serum concentrations were within the dose-related reference range. The C/D ratio was 1.58±0.73. Accordingly, a lower value of 0.85 and an upper value of 2.31 were calculated for the updated dose-related reference range, which is below the currently recommended values.The results suggest that the current values for the dose-related reference range are too high and require adjustment. The updated dose-related reference range lies between 0.85 and 2.31, with a mean of 1.58±0.73.

Background: Nicotinamide adenosine dinucleotide phosphate oxidases (NOX) play important roles in mediating stress-induced depression. Three NOX isotypes are expressed mainly in the brain: NOX2, NOX3 and NOX4. In this study, the expression and cellular sources of these NOX isoforms was investigated in the context of stress-induced depression.

Methods: Chronic restraint stress (CRS)-induced depressive-like behaviour and cognitive deficits were evaluated by tail suspension tests, forced swimming tests and the Morris water maze test. Hippocampal NOX expression was determined by immunofluorescence staining and western blotting. The hippocampal levels of the brain-derived neurotrophic factor (BDNF) mRNA were determined via quantitative real-time -polymerase chain reaction. Glucocorticoid levels in the hippocampus were measured using ELISA kits.

Results: In the mouse CRS model, a significant increase in NOX2 expression was observed in the hippocampus, whereas no significant changes in NOX3 and NOX4 expression were detected. Next, NOX2 expression was primarily localised to neurons (NeuN⁺) but not microglia (Iba-1⁺) or astrocytes (GFAP⁺). Treatment with gp91ds-tat, a specific NOX2 inhibitor, effectively mitigated the behavioural deficits induced by CRS. The decreased expression of the BDNF mRNA in the hippocampus of CRS mice was restored upon gp91ds-tat treatment. A positive correlation was identified between neuronal NOX2 expression and serum glucocorticoid levels.

Conclusions: Our study indicated that neuronal NOX2 may be a critical mediator of depression-like behaviours and spatial cognitive deficits in mice subjected to CRS. Blockade of NOX2 signalling may be a promising therapeutic strategy for depression.