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Development and preclinical testing of a naloxone prodrug depot for extended protection against opioid overdose.
Nat Commun
January 2025
Department of Pharmaceutical Sciences, Thomas J. Long School of Pharmacy, University of the Pacific, Stockton, CA, US.
The opioid crisis, driven by synthetic opioids like fentanyl, demands innovative solutions. The opioid antidote naloxone has a short action ( ~ 1 hour), requiring repeated doses. To address this, we present a new and simple naloxone prodrug delivery system repurposing a hydrophilic derivative of acoramidis, a potent transthyretin ligand.
View Article and Find Full Text PDFAssessing the "Reach" of a Fire-Based Mobile Integrated Health Buprenorphine Induction Program through an Implementation Science Lens.
Prehosp Emerg Care
January 2025
Medical College of Wisconsin, Department of Emergency Medicine.
Objectives: Medication for opioid use disorder (MOUD) reduces morbidity and mortality for patients with opioid use disorder (OUD). Recent administrative and legislative changes have made MOUD possible in the prehospital setting. We use an implementation science framework to outline the Reach of a fire department EMS-based Mobile Integrated Health (MIH) prehospital MOUD program.
View Article and Find Full Text PDFA Review of Leveraging Artificial Intelligence to Predict Persistent Postoperative Opioid Use and Opioid Use Disorder and its Ethical Considerations.
Curr Pain Headache Rep
January 2025
Division of Perioperative Informatics, Department of Anesthesiology, University of California, San Diego, La Jolla, CA, USA.
Purpose Of Review: Artificial intelligence (AI) offers a new frontier for aiding in the management of both acute and chronic pain, which may potentially transform opioid prescribing practices and addiction prevention strategies. In this review paper, not only do we discuss some of the current literature around predicting various opioid-related outcomes, but we also briefly point out the next steps to improve trustworthiness of these AI models prior to real-time use in clinical workflow.
Recent Findings: Machine learning-based predictive models for identifying risk for persistent postoperative opioid use have been reported for spine surgery, knee arthroplasty, hip arthroplasty, arthroscopic joint surgery, outpatient surgery, and mixed surgical populations.
Mortality risk among individuals who smoke opioids compared with those who inject: A propensity score-matched cohort analysis of United States national treatment data.
Addiction
January 2025
Family and Community Medicine, University of California San Francisco, San Francisco, CA, USA.
Background And Aims: Opioid smoking is becoming more common in the United States. The aim of this analysis was to estimate relative mortality risk among those who primarily smoke opioids compared with those who inject.
Design: Retrospective propensity score-matched cohort analysis.
Characteristics of supervised injection site clients and factors associated with requiring overdose intervention, Montreal, Canada, 2018-2022.
Int J Drug Policy
January 2025
Centre de recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), 900 rue St-Denis, Montréal, Québec H2X 0A9, Canada; Department of Emergency and Family Medicine, Université de Montréal, 2900 blvd Edouard Montpetit, Montréal, Québec H3T 1J4, Canada; National Drug and Alcohol Research Centre, UNSW Sydney, Anzac Parade, Kensington NSW 2052, Australia. Electronic address:
Background: Supervised injection sites (SIS) offer a hygienic environment in which people can inject drugs under observation; as such, these harm reduction services have been on the forefront of the overdose epidemic. We sought to understand factors predictive of an overdose requiring an emergency response intervention at SIS in Montréal, Canada.
Methods: We used administrative data from all four Montréal SIS from 1 March 2018 - 31 October 2022 to first calculate the rate of onsite overdose requiring intervention (e.
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