18 research outputs found

    Cannabinoid hyperemesis syndrome and cannabis withdrawal syndrome: a review of the management of cannabis-related syndrome in the emergency department.

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    BACKGROUND Cannabis-related medical consultations are increasing worldwide, a non-negligible public health issue; patients presenting to acute care traditionally complain of abdominal pain and vomiting. Often recurrent, these frequent consultations add to the congestion of already chronically saturated emergency department(s) (ED). In order to curb this phenomenon, a specific approach for these patients is key, to enable appropriate treatment and long-term follow-up. OBJECTIVES This study reviews cannabinoid hyperemesis syndrome (CHS) and cannabis withdrawal syndrome (CWS), in a bid to help promote better understanding and handling of pathologies associated with chronic cannabis use. Following a literature review, we present a novel therapeutic algorithm aimed at guiding clinicians, in a bid to improve long-term outcomes and prevent recurrences. METHODS Using the keywords "Cannabis," "Hyperemesis," "Syndrome," "Withdrawal," and "Emergency Medicine," we completed a literature review of three different electronic databases (PubMed®, Google scholar®, and Cochrane®), up to November 2021. RESULTS Although often presenting with similar symptoms such as abdominal pain and vomiting, cannabinoid hyperemesis syndrome (CHS) and cannabis withdrawal syndrome (CWS) are the result of two differing pathophysiological processes. Distinguishing between these two syndromes is essential to provide appropriate symptomatic options. CONCLUSION The correct identification of the underlying cannabis-related syndrome, and subsequent therapeutic choice, may help decrease ED presentations. Our study emphasizes the importance of both acute care and long-term outpatient follow-up, as key processes in cannabis-related disorder treatment

    [Ketamine for medically-delegated analgesia in the Emergency Department].

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    Ketamine has the optimal characteristics for use in an Emergency Department. Added in 2020 to the Emergency Department's medically delegated analgesia protocol of the Cantonal Hospital of Neuchâtel (RHNe), it has become a valuable ally for the management of acute pain. The purpose of this article is to present the advantages of its use in an Emergency Department by means of a review of evidence and experience

    PLUS-IS-LESS project: Procalcitonin and Lung UltraSonography-based antibiotherapy in patients with Lower rESpiratory tract infection in Swiss Emergency Departments: study protocol for a pragmatic stepped-wedge cluster-randomized trial

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    Abstract Background Lower respiratory tract infections (LRTIs) are among the most frequent infections and a significant contributor to inappropriate antibiotic prescription. Currently, no single diagnostic tool can reliably identify bacterial pneumonia. We thus evaluate a multimodal approach based on a clinical score, lung ultrasound (LUS), and the inflammatory biomarker, procalcitonin (PCT) to guide prescription of antibiotics. LUS outperforms chest X-ray in the identification of pneumonia, while PCT is known to be elevated in bacterial and/or severe infections. We propose a trial to test their synergistic potential in reducing antibiotic prescription while preserving patient safety in emergency departments (ED). Methods The PLUS-IS-LESS study is a pragmatic, stepped-wedge cluster-randomized, clinical trial conducted in 10 Swiss EDs. It assesses the PLUS algorithm, which combines a clinical prediction score, LUS, PCT, and a clinical severity score to guide antibiotics among adults with LRTIs, compared with usual care. The co-primary endpoints are the proportion of patients prescribed antibiotics and the proportion of patients with clinical failure by day 28. Secondary endpoints include measurement of change in quality of life, length of hospital stay, antibiotic-related side effects, barriers and facilitators to the implementation of the algorithm, cost-effectiveness of the intervention, and identification of patterns of pneumonia in LUS using machine learning. Discussion The PLUS algorithm aims to optimize prescription of antibiotics through improved diagnostic performance and maximization of physician adherence, while ensuring safety. It is based on previously validated tests and does therefore not expose participants to unforeseeable risks. Cluster randomization prevents cross-contamination between study groups, as physicians are not exposed to the intervention during or before the control period. The stepped-wedge implementation of the intervention allows effect calculation from both between- and within-cluster comparisons, which enhances statistical power and allows smaller sample size than a parallel cluster design. Moreover, it enables the training of all centers for the intervention, simplifying implementation if the results prove successful. The PLUS algorithm has the potential to improve the identification of LRTIs that would benefit from antibiotics. When scaled, the expected reduction in the proportion of antibiotics prescribed has the potential to not only decrease side effects and costs but also mitigate antibiotic resistance. Trial registration This study was registered on July 19, 2022, on the ClinicalTrials.gov registry using reference number: NCT05463406. Trial status Recruitment started on December 5, 2022, and will be completed on November 3, 2024. Current protocol version is version 3.0, dated April 3, 2023
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