Gentry, Melanie T.

Since the discovery of the first psychoactive medications, their psychiatric and medical uses have overlapped. Designating a medication psychiatric or psychotropic is thus arbitrary, based on its most common usage, but labeling it so obscures the full range of its pharmacologic activity and clinical utility. Psychotropic medications (PMs) are frequently used to treat medical conditions or symptoms in the areas of neurology (e.g., migraine, seizure disorder), dermatology (e.g., itching), gastroenterology, and chronic pain, among many others. It is important for both primary care and specialty physicians to be aware of the potential non-psychiatric indications for the use of common PMs such as antidepressants, antipsychotics, and anxiolytics. This review examines the potential benefits and risks of PMs when used for non-psychiatric indications, highlighting how their pharmacologic effects on neurotransmitters contribute to both therapeutic outcomes and adverse effects. It also provides guiding principles for prescribers, including the importance of adjusting doses based on the specific indication, monitoring for harmful side effects, considering age-related factors, and addressing the risks associated with polypharmacy.

ABSTRACT Major depressive disorder (MDD) is a substantial public health challenge. Pharmacogenomics (PGx), which identifies genetic variations that predict drug treatment outcomes, may have utility for clinical practice, but adequate representation of all populations is needed. As precision medicine in psychiatry moves towards the use of Artificial Intelligence (AI) and Machine Learning (ML) to predict treatment outcomes using PGx data, representation of diverse populations will be especially important in order to mitigate algorithmic bias and achieve equitable and generalizable findings. This work sought to quantify population diversity in pharmacogenomic studies of MDD through a systematic review. Data from 390 MDD antidepressant PGx studies were extracted from 5739 articles screened. Studies summarized were predominantly conducted in Europe, East Asia, and North America. Across all global studies, the study population comprised 57.3% White, 36.4% Asian, 1.7% Black, 3.5% Hispanic/Latino, and 0.1% Native American or Indigenous participants. Only sixty‐three (16.2%) studies included Black or Latino/Hispanic patients. Additionally, Black, Asian, Hispanic/Latino, and American Indian/Alaska Native populations were statistically underrepresented in U.S. study populations when compared to national census data, while Asian and Black populations were underrepresented in the United Kingdom. The overrepresentation of participants from a limited number of countries combined with the underrepresentation of Black and Hispanic/Latino populations could impact the extent to which pharmacogenomic testing and associated AI/ML‐based PGx tools could individualize antidepressant medication regimens for treating MDD.

Background: During the COVID-19 pandemic, increased use of telehealth expanded access to health care for older adults. Many clinicians and health systems adjusted workflows and realized that certain competencies are needed to fully engage older adults in telehealth services. This scoping review evaluates the approaches needed to educate clinicians about providing telehealth services to older adults. Methods: We conducted a review of studies published from January 2000 through February 2024 by using the 6-stage scoping review process. Searches of PubMed/MEDLINE and five other databases included the concept areas of competencies, telehealth delivery of mental health services, and older adults. Results: We initially identified 813 articles, of which 89 were eligible for full-text review and 15 met our inclusion criteria. Most studies included training participants about the use of telehealth but without formal curricular interventions or evaluations and lacked details about topics, materials, methods, or outcomes. Telehealth training was general and focused primarily on the use of technology and telepresence, although not specifically for older adults. Three themes were identified from the studies: the role of teams and interprofessional education, the importance of training for clinicians and older patients, and adaptations to improve telehealth delivery for older adults. Conclusions: Individual and institutional competencies are needed to guide educational goals and outcome measures related to telehealth services for older adults. The use of telehealth specifically for older adults may require adaptation to clinical practice and delivery, adjustments to workflow, development of clinician skills, and promotion of interprofessional teamwork.

ABSTRACTPharmacogenetics is a promising strategy to facilitate individualized care for patients with Major Depressive Disorder (MDD). Research is ongoing to identify the optimal genetic markers for predicting outcomes to antidepressant therapies. The primary aim of this systematic review was to summarize antidepressant pharmacogenetic studies to enhance understanding of the genes, variants, datatypes/methodologies, and outcomes investigated in the context of MDD. The secondary aim was to identify clinical genetic panels indicated for antidepressant prescribing and summarize their genes and variants. Screening of N = 5793 articles yielded N = 390 for inclusion, largely comprising adult (≥ 18 years) populations. Top‐studied variants identified in the search were discussed and compared with those represented on the N = 34 clinical genetic panels that were identified. Summarization of articles revealed sources of heterogeneity across studies and low rates of replicability of pharmacogenetic associations. Heterogeneity was present in outcome definitions, treatment regimens, and differential inclusion of mediating variables in analyses. Efficacy outcomes (i.e., response, remission) were studied at greater frequency than adverse‐event outcomes. Studies that used advanced analytical approaches, such as machine learning, to integrate variants with complimentary biological datatypes were fewer in number but achieved higher rates of significant associations with treatment outcomes than candidate variant approaches. As large biological datasets become more prevalent, machine learning will be an increasingly valuable tool for parsing the complexity of antidepressant response. This review provides valuable context and considerations surrounding pharmacogenetic associations in MDD which will help inform future research and translation efforts for guiding antidepressant care.

AbstractObjectiveThe Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects evaluates familial frontotemporal lobar degeneration (FTLD) kindreds with MAPT, GRN, or C9orf72 mutations. Objectives were to examine whether health‐related quality of life (HRQoL) correlates with clinical symptoms and caregiver burden, and whether self‐rated and informant‐rated HRQoL would correlate with each other.MethodsIndividuals were classified using the Clinical Dementia Rating (CDR®) Scale plus National Alzheimer's Coordinating Center (NACC) FTLD. HRQoL was measured with DEMQOL and DEMQOL‐proxy; caregiver burden with the Zarit Burden Interview (ZBI). For analysis, Pearson correlations and weighted kappa statistics were calculated.ResultsThe cohort of 312 individuals included symptomatic and asymptomatic individuals. CDR® plus NACC FTLD was negatively correlated with DEMQOL (r = −0.20, P = .001), as were ZBI and DEMQOL (r = −0.22, P = .0009). There was fair agreement between subject and informant DEMQOL (κ = 0.36, P <.0001).ConclusionLower HRQoL was associated with higher cognitive/behavior impairment and higher caregiver burden. These findings demonstrate the negative impact of FTLD on individuals and caregivers.

AbstractPurposeWe explored the feasibility of a clinical pathway to identify hospitalized patients with dementia who would benefit from a palliative intervention.Design and MethodsConsecutive geropsychiatric admissions were screened for terminal dementia to be randomized to a palliative consultation vs usual care.FindingsA total of 43 of the 188 patients (23%) had dementia; however, dementia stages were severe but not terminal. The pathway was not feasible because of the lack of the target population in the inpatient setting for the intervention.Practice ImplicationsNew clinical pathways are needed to identify patients with dementia who would benefit from palliative care.