Efficacy and safety of adjunctive therapy to lamotrigine, lithium, or valproate monotherapy in bipolar depression: a systematic review and meta-analysis of randomized controlled trials

Practice Guidelines for Bipolar Disorder by the JSMD (Japanese Society of Mood Disorders)

The Japanese Society of Mood Disorders (JSMD) published treatment guidelines of bipolar disorder in 2011. The present guidelines incorporating new findings were developed to comply to the guidelines of the National Academy of Medicine (NAM) by utilizing systematic reviews and meta-analysis and taking patient and family opinions as well as insights from multiple professional fields into account. They support combination therapy using mood stabilizers and second-generation antipsychotics in many aspects. They also have limitations, including the grouping of mood stabilizers and second-generation antipsychotics when meta-analysis was performed despite their distinct properties, due to the scarcity of drug-specific evidence. Despite the limitations, these guidelines provide clinical decision support for psychiatrists in Japan.

Human-Comparable Sensitivity of Large Language Models in Identifying Eligible Studies Through Title and Abstract Screening: 3-Layer Strategy Using GPT-3.5 and GPT-4 for Systematic Reviews

BACKGROUND

The screening process for systematic reviews is resource-intensive. Although previous machine learning solutions have reported reductions in workload, they risked excluding relevant papers.

OBJECTIVE

We evaluated the performance of a 3-layer screening method using GPT-3.5 and GPT-4 to streamline the title and abstract-screening process for systematic reviews. Our goal is to develop a screening method that maximizes sensitivity for identifying relevant records.

METHODS

We conducted screenings on 2 of our previous systematic reviews related to the treatment of bipolar disorder, with 1381 records from the first review and 3146 from the second. Screenings were conducted using GPT-3.5 (gpt-3.5-turbo-0125) and GPT-4 (gpt-4-0125-preview) across three layers: (1) research design, (2) target patients, and (3) interventions and controls. The 3-layer screening was conducted using prompts tailored to each study. During this process, information extraction according to each study's inclusion criteria and optimization for screening were carried out using a GPT-4-based flow without manual adjustments. Records were evaluated at each layer, and those meeting the inclusion criteria at all layers were subsequently judged as included.

RESULTS

On each layer, both GPT-3.5 and GPT-4 were able to process about 110 records per minute, and the total time required for screening the first and second studies was approximately 1 hour and 2 hours, respectively. In the first study, the sensitivities/specificities of the GPT-3.5 and GPT-4 were 0.900/0.709 and 0.806/0.996, respectively. Both screenings by GPT-3.5 and GPT-4 judged all 6 records used for the meta-analysis as included. In the second study, the sensitivities/specificities of the GPT-3.5 and GPT-4 were 0.958/0.116 and 0.875/0.855, respectively. The sensitivities for the relevant records align with those of human evaluators: 0.867-1.000 for the first study and 0.776-0.979 for the second study. Both screenings by GPT-3.5 and GPT-4 judged all 9 records used for the meta-analysis as included. After accounting for justifiably excluded records by GPT-4, the sensitivities/specificities of the GPT-4 screening were 0.962/0.996 in the first study and 0.943/0.855 in the second study. Further investigation indicated that the cases incorrectly excluded by GPT-3.5 were due to a lack of domain knowledge, while the cases incorrectly excluded by GPT-4 were due to misinterpretations of the inclusion criteria.

CONCLUSIONS

Our 3-layer screening method with GPT-4 demonstrated acceptable level of sensitivity and specificity that supports its practical application in systematic review screenings. Future research should aim to generalize this approach and explore its effectiveness in diverse settings, both medical and nonmedical, to fully establish its use and operational feasibility.

International Trends in Lithium Use for Pharmacotherapy and Clinical Correlates in Bipolar Disorder: A Scoping Review

Lithium remains an effective option in the treatment of bipolar disorder (BD). Thus, we aim to characterize the pharmaco-epidemiological patterns of lithium use internationally over time and elucidate clinical correlates associated with BD using a scoping review, which was conducted using the methodological framework by Arksey and O'Malley (2005). We searched several databases for studies that examined the prescriptions for lithium and clinical associations in BD from inception until December 2023. This review included 55 articles from 1967 to 2023, which collected data from North America (n = 24, 43.6%), Europe (n = 20, 36.4%), and Asia (n = 11, 20.0%). The overall prescription rates ranged from 3.3% to 84% (33.4% before and 30.6% after the median year cutoffs). Over time, there was a decline in lithium use in North America (27.7% before 2010 to 17.1% after 2010) and Europe (36.7% before 2003 to 35.7% after 2003), and a mild increase in Asia (25.0% before 2003 to 26.2% after 2003). Lithium use was associated with specific demographic (e.g., age, male gender) and clinical factors (e.g., lower suicide risk). Overall, we found a trend of declining lithium use internationally, particularly in the West. Specific clinical correlates can support clinical decision-making for continued lithium use.

Appropriate Macronutrients or Mineral Elements Are Beneficial to Improve Depression and Reduce the Risk of Depression

Depression is a common mental disorder that seriously affects the quality of life and leads to an increasing global suicide rate. Macro, micro, and trace elements are the main components that maintain normal physiological functions of the brain. Depression is manifested in abnormal brain functions, which are considered to be tightly related to the imbalance of elements. Elements associated with depression include glucose, fatty acids, amino acids, and mineral elements such as lithium, zinc, magnesium, copper, iron, and selenium. To explore the relationship between these elements and depression, the main literature in the last decade was mainly searched and summarized on PubMed, Google Scholar, Scopus, Web of Science, and other electronic databases with the keywords "depression, sugar, fat, protein, lithium, zinc, magnesium, copper, iron, and selenium". These elements aggravate or alleviate depression by regulating a series of physiological processes, including the transmission of neural signals, inflammation, oxidative stress, neurogenesis, and synaptic plasticity, which thus affect the expression or activity of physiological components such as neurotransmitters, neurotrophic factors, receptors, cytokines, and ion-binding proteins in the body. For example, excessive fat intake can lead to depression, with possible mechanisms including inflammation, increased oxidative stress, reduced synaptic plasticity, and decreased expression of 5-Hydroxytryptamine (5-HT), Brain Derived Neurotrophic Factor (BDNF), Postsynaptic density protein 95(PSD-95), etc. Supplementing mineral elements, such as selenium, zinc, magnesium, or lithium as a psychotropic medication is mostly used as an auxiliary method to improve depression with other antidepressants. In general, appropriate nutritional elements are essential to treat depression and prevent the risk of depression.