AIMS: The efficacy of cariprazine for major depressive disorder (MDD) (adjunctive therapy) and bipolar I (BP-I) depression has been demonstrated in clinical trials. This study evaluated the real-world effectiveness of cariprazine in reducing depressi...
Tardive dyskinesia (TD) is a late-onset adverse effect of dopamine receptor-blocking medications, characterized by involuntary movements primarily affecting the mouth, though other body parts may be involved. Severity of TD varies from mild to debil...
European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology
Apr 13, 2025
It is unclear if lithium and quetiapine have neuroprotective effects, especially in early stages of bipolar and schizoaffective disorders. Here, an age-related multivariate brain structural measure (i.e., brain-PAD) at baseline and changes in respons...
Clinical pharmacology and therapeutics
Apr 8, 2025
Measuring medication discontinuation in claims data primarily relies on the gaps between prescription fills, but such definitions are rarely validated. This study aimed to establish a natural language processing (NLP)-based validation framework to ev...
BACKGROUND: The combination of antidepressant and antipsychotic medication is an effective treatment for major depressive disorder with psychotic features ('psychotic depression'). The present study aims to identify sociodemographic and clinical pred...
Clozapine is widely regarded as one of the most effective therapeutics for treatment-resistant schizophrenia. Despite its proven efficacy, the therapeutic use of clozapine is complicated by its narrow therapeutic index, which necessitates rapid and p...
International journal of molecular sciences
Feb 14, 2025
Approximately 50% of Alzheimer's disease (AD) patients develop psychotic symptoms, leading to a subtype known as psychosis in AD (AD + P), which is associated with accelerated cognitive decline compared to AD without psychosis. Currently, no FDA-appr...
We apply machine learning techniques to navigate the multifaceted landscape of schizophrenia. Our method entails the development of predictive models, emphasizing peripheral inflammatory biomarkers, which are classified into treatment response subgro...
Predicting early treatment response in schizophrenia is pivotal for selecting the best therapeutic approach. Utilizing machine learning (ML) technique, we aimed to formulate a model predicting antipsychotic treatment outcomes. Data were obtained from...
OBJECTIVE: The capacity of machine-learning algorithms to predict medication adherence was assessed using data from AiCure, a computer vision-assisted smartphone application, which records the medication ingestion event.
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