Christine Leong

Introduction Acute methamphetamine intoxication is a common presentation in emergency departments (EDs). Empowering paramedics to treat methamphetamine intoxication in the prehospital setting could help to improve patient and system outcomes. This study evaluated the impact of a 2018 policy allowing paramedics to administer olanzapine for methamphetamine intoxication in the prehospital setting on patient and system outcomes. Methods Retrospective pre-post analysis of population-based health administrative data and qualitative paramedic reports. Individuals with a methamphetamine-related health system contact between 2016–2020 in Winnipeg, Canada, who were eligible for pre-hospital olanzapine were included. The exposure was the administration of olanzapine in the pre-hospital setting by paramedics. Individuals who received prehospital olanzapine were compared with those who did not, prior to (2016–2018) and after (2018–2020) the policy change. Primary outcomes included physical or chemical restraint prior to ED, transport to ED and leaving from the ED prior to being seen or against medical advice. Outcomes were modelled using logistic (binary outcomes) and Cox proportional hazard (temporal outcomes) models adjusted for covariates using inverse probability of treatment weighting. Results The cohort included 1041 individuals, of which 222 received the intervention. Among individuals receiving olanzapine, the median age was 31 years, 58.1% were male, 56.8% were in the lowest income quintile and a high prevalence of mental health disorders and legal system involvement were observed. After adjusting for covariates, individuals receiving olanzapine in the prehospital setting were more likely to be transported to ED by paramedics (adjusted OR (aOR): 11.83, 95% CI 3.19 to 43.80) and less likely to leave the ED without being seen by a doctor (aOR: 0.56, 95% CI 0.32 to 0.97) compared with individuals who did not. Conclusions Prehospital administration of olanzapine among individuals experiencing methamphetamine intoxication was associated with a higher likelihood of transport to the ED and being seen by a physician.

Objective: To examine changes in the prevalence and incidence of attention deficit/hyperactivity disorder (ADHD) medication dispensations in individuals 24 years and younger in Manitoba, Canada. Design, setting and participants: This was a retrospective repeated cross-sectional study of community-based Manitoba children, adolescents and young adults 24 years and younger using administrative prescription dispensing data from the Manitoba Centre for Health Policy. Primary and secondary outcome measures: Quarterly prevalence and incidence of prescription medications dispensed for ADHD were reported by calendar year from 2015 to 2023. Findings were stratified by age, sex and drug. Results: The study population changed from 445 058 (2015) to 467 591 (2023). A greater than 80% increase in the prevalence (183.64–337.99 per 10 000; p<0.001) and incidence (12.76–23.95 per 10 000; p<0.001) of stimulants was observed during this period. An approximate threefold increase in the prevalence (7.32 per 10 000 to 26.52 per 10 000; p<0.001) and incidence (1.17–3.17 per 10 000; p<0.001) of non-stimulants was also observed. The increase in stimulant dispensations was most pronounced among those 19–24 years (incidence 6.81–34.65 per 10 000, p<0.001) and females (incidence 8.56 per 10 000 to 27.39 per 10 000, p<0.001). The prevalence increased markedly for lixdexamphetamine (12.65–105.39 per 10 000, p<0.001) and guanfacine (1.91–18.93 per 10 000). Conclusions: Stimulant and non-stimulant dispensations for ADHD increased from 2015 to 2023, consistent with international findings. The increase was observed to be the greatest in the population 19 to 24 years of age and females. While there was a significant increase in most ADHD medications, there was a pronounced increase in lisdexamphetamine and guanfacine, specifically.

Background Over the last decade, gabapentin has become one of the most utilized antiseizure medications during pregnancy, but association between gabapentin use during pregnancy and adverse neonatal outcomes among pregnant people with epilepsy (PPWE), and pregnant people without epilepsy (PPWOE) is not clear. Methods We conducted a retrospective population-based cohort study among pregnant people in Manitoba, between 1998 to 2021 to examine the association between gabapentin exposure in-utero and the risk of low birth weight (LBW), preterm birth, NICU admissions, maternal length of hospital stays (LOS), infants LOS, infant mortality, neonatal mortality, neonatal readmissions, neonatal respiratory distress syndrome, and severe neonatal morbidity. We performed crude, adjusted and high dimensional propensity scores (HDPS) analysis using generalised estimating equations with exchangeable matrix. Results Among 1057 pregnant people exposed to gabapentin, we found a significant increased risk of LBW (aOR 1.95, 95% CI 1.58-2.41), preterm birth (aOR 1.68, 95% CI 1.39-2.03), NICU admissions (aOR 2.04, 95% CI 1.71-2.42), pregnant peoples LOS (aOR 1.33, 95% CI 1.15-1.54), infant LOS (aOR 2.09, 95% CI 1.81-2.41) and neonatal respiratory distress syndrome (aOR 3.36, 95% CI 1.16-9.71). In exposed PPWE and PPWOE we found a significant increased risk of infant mortality aOR 5.39 (95% CI 1.11-26.2). The results from HDPS models showed attenuated estimates and non-significant results, suggesting strong unmeasured confounding among adjusted regression models. Conclusion We observed potential risk for specific neonatal outcomes, however unmeasured confounding can not be dismissed. Future studies on the effect of gabapentin during pregnancy are warranted.

Background: Health care systems generate vast amounts of unstructured text, such as clinical notes, which capture nuanced patient experiences, clinical reasoning, and subtle indicators of health status. While health system research has traditionally relied upon structured data, natural language processing (NLP) enables the extraction of this rich textual information. Leveraging NLP could improve the identification and characterization of underreported adverse drug events (ADEs). Objective: The primary objective of this study was to train and evaluate multiple NLP models, including both previously published architectures and a novel model, for the identification of ADEs from clinical notes. Methods: Electronic medical records from the Manitoba Primary Care Research Network (MaPCReN) were used in this study. Clinical notes were annotated to indicate the presence of a possible ADE, the associated words or phrases, and the corresponding drug. A subselection algorithm was applied to ensure sufficient representation of notes containing ADEs for training a robust classifier. The cohort was restricted to patients aged 55 years and older and was annotated in 2 waves: Wave 1 comprised primary care encounter notes selected for a temporally linked emergency department (ED) visit, enriching it for acute presentations, while Wave 2 relaxed this requirement, and its acuity composition was uncharacterized. The annotated data were split into training and test sets. NLP models—including BioBERT, BlueBERT, a large language model (LLM) classifier, and an LLM embeddings–based classifier—were trained on both original clinical notes and notes reformatted into Subjective-Objective-Assessment-Plan (SOAP) structure. To approximate a clinician-inspired reasoning workflow, Mistral-7b-Instruct was used to extract presenting symptoms and generate a ranked list of potential etiologies. Model performance was evaluated using precision, recall, and F ₁ -score. Results: Of the 1085 annotated encounter notes, 355 included ADEs. Across 9 modeling approaches evaluated over 5 random seeds, models trained on SOAP-rewritten notes generally outperformed those trained on original notes. The SOAP Rewrite+ LLM Embeddings Classifier (GritLM-SOAP) achieved the highest mean F ₁ -score (72.53%; 95% CI 62.40%‐81.82%), while BioBERT-SOAP weighted achieved the highest mean recall (76.34%; 95% CI 62.69%‐89.66%). End-to-end span-level extraction (named entity recognition+relation extraction) on ADE-positive test notes achieved a mean relaxed F ₁ -score of 0.455, with relation extraction identified as the bottleneck. Conclusions: Effective detection of ADEs in clinical notes may benefit from NLP models that approximate the clinical reasoning of health care providers. While the SOAP Rewrite+ LLM Embeddings Classifier demonstrated a reasonable balance of precision and recall, there is room for improvement as models evolve.

Purpose: Early discontinuation of antidepressants continues to be a major challenge in treating mood and anxiety disorders, despite strong evidence supporting ongoing pharmacotherapy to prevent relapse and enhance long-term outcomes. This narrative review aimed to identify potential patient-level, medication-level, prescriber-level, and system-level factors of early discontinuation and to highlight strategies to improve long-term adherence. Methods: First, guideline recommendations from Canada, the United States, the United Kingdom, Europe, and international bodies were reviewed to contextualize recommended treatment durations. Then, a literature search was performed, including studies published from 2000 to 2025. We used PubMed, Google Scholar, PsycINFO, and Web of Science databases. Findings from observational studies, clinical guidelines, and qualitative research were synthesized to identify key factors contributing to early discontinuation and to outline strategies to improve adherence. Results: Early antidepressant discontinuation was often associated with low socioeconomic status, immigrant background, older age, prior substance use, comorbid psychiatric conditions, and misconceptions about treatment, although findings varied depending on the operational definition and study settings. Medication‑related contributors included adverse effect burden, initiation on tricyclic antidepressants, and cost‑related non-adherence. Prescriber‑level and system‑level contributors included limited follow‑up, high workload, variability in prescribing practices, and communication barriers. Several strategies to improve adherence can be adopted, including patient-centered communication, culturally competent care, selecting well‑tolerated first‑line agents, structured follow‑up, pharmacist‑led support, and digital/telehealth‑based interventions. Conclusions: Early antidepressant discontinuation is common and influenced by intersecting social, clinical, and structural factors, including equity-related determinants. Multifaceted, coordinated approaches, including effective communication, appropriate medication selection, and strengthened follow‑up processes, are needed to improve adherence.

Decision-making around medication use during lactation is often challenging for both parents and healthcare providers. The purpose of this study is to unde

To investigate the public’s perception of pharmacists trained in Mental Health First Aid (MHFA) and to describe their encounters with pharmacists addressing mental health concerns. An online survey was disseminated to Canadian adults 18 years and older over a 3-month period (September–December 2022) to describe their views on the value of pharmacists trained in MHFA and their pharmacist encounters related to addressing mental health concerns. Descriptive statistics was used to describe survey responses. Chi square test was used to determine the difference in the level of comfort in discussing mental health concerns between pharmacists with and without MHFA training. There were 228 participants included in the study. The proportion of respondents who agreed, either somewhat or strongly, that they ‘would be comfortable talking to a pharmacist about mental health problems’ was 53.5% for non-MHFA-trained pharmacists and 61.8% for MHFA-trained pharmacists (P = .0366). Approximately two-thirds (64.8%) of survey respondents agreed that ‘pharmacists should be trained in MHFA’. Approximately one-third (n = 75) of participants met with a pharmacist to discuss their mental health once a month and 36.4% (n = 83) indicated they received help from a pharmacist when they were experiencing a deterioration in mental health. More participants reported feeling comfortable discussing their mental health concerns with a pharmacist trained in MHFA compared with non-trained pharmacists. Pharmacists trained in MHFA may be perceived by the public to be better equipped to discuss mental health in the pharmacy setting.