Introduction: Acetaminophen is the most involved active substance in both unintentional and intentional drug poisoning. However, its availability outside community pharmacies is being debated in France.
Methods: We made, via a self-administered questionnaire, a prospective assessment of knowledge, use and acetaminophen overdose risk in patients consulting their general practitioner, in the Metz Métropole urban area, between May 2015 and February 2016. We estimated the prevalence of potential unintentional overdosage by capture-recapture method.
Results: Among 819 responding patients, only 17.9 % had a sufficient knowledge and 20.3 % were at risk for potential unintentional overdose. The risk was higher for patients aged over 55 years or belonging to socioprofessional categories of laborers and inactive. A good knowledge score was a protective factor for overdose risk (P<0.0001). The liver toxicity of acetaminophen was particularly unknown. The prevalence of potential unintentional acetaminophen overdose was estimated at 1 to2 % of the population.
Conclusion: Proposing acetaminophen outside of pharmacies cannot be recommended in France in such conditions. Information campaigns are needed to limit the risk of unintentional overdose and its consequences on liver toxicity.
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http://dx.doi.org/10.1016/j.therap.2016.12.012 | DOI Listing |
Stat Med
February 2025
MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
There is a growing number of Phase I dose-finding studies that use a model-based approach, such as the CRM or the EWOC method to estimate the dose-toxicity relationship. It is common to assume that all patients will have similar toxicity risk given the dose regardless of patients' individual characteristics. In many trials, however, some patients' covariates (e.
View Article and Find Full Text PDFEur J Clin Pharmacol
January 2025
Department of the Acute Pain Service, St. Luke's University Health Network, 801 Ostrum St, Bethlehem, PA, 18015, USA.
Purpose: Opioid medications remain a common treatment for acute pain in hospitalized patients. This study aims to identify factors contributing to opioid overdose in the inpatient population, addressing the gap in data on which patients are at higher risk for opioid-related adverse events in the hospital setting.
Methods: A retrospective chart review of inpatients receiving at least one opioid medication was performed at a large academic medical center from January 1, 2022, through December 31, 2022.
Int J Drug Policy
January 2025
Center for Opioid Epidemiology and Policy, Department of Population Health, NYU Grossman School of Medicine, New York University, New York City, NY, USA. Electronic address:
Background: Identifying the most effective state laws and provisions to reduce opioid overdose deaths remains critical.
Methods: Using expert ratings of opioid laws, we developed annual state scores for three domains: opioid prescribing restrictions, harm reduction, and Medicaid treatment coverage. We modeled associations of state opioid policy domain scores with opioid-involved overdose death counts in 3133 counties, and among racial/ethnic subgroups in 1485 counties (2013-2020).
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.
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