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Anesthesia depth monitoring during opioid free anesthesia - a prospective observational study.

BMC Anesthesiol

January 2025

Department of Anesthesiology and Intensive Care Medicine, Halland Hospital Halmstad, Lasarettsvägen, Halmstad, SE-30581, Sweden.

Background: Patients undergoing general anesthesia are more frequently monitored for depth of anesthesia using processed electroencephalography. Opioid-free anesthesia is nowadays an accepted modality for general anesthesia, however it is unclear how to interpret data from processed electroencephalography when using a mixture of non-opioid anesthetic drugs. Our objective was to describe density spectral array patterns and compare processed encephalographic data indices between opioid-free and routine opioid based anesthesia.

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Background: Preclinical studies and anecdotal case reports support the potential therapeutic benefit of low-dose oral ketamine as a treatment of clinical symptoms in Rett syndrome (RTT); however, no controlled studies have been conducted in RTT to evaluate safety, tolerability and efficacy.

Design: This was a sequentially initiated, dose-escalating cohort, placebo-controlled, double blind, randomized sequence, cross-over study of oral ketamine in 6-12-year-old girls with RTT to evaluate short-term safety and tolerability and explore efficacy.

Methods: Participants were randomized to either five days treatment with oral ketamine or matched placebo, followed by a nine-day wash-out period and then crossed-over to the opposite treatment.

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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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Importance: During buprenorphine treatment for opioid use disorder (OUD), risk factors for opioid relapse or treatment dropout include comorbid substance use disorder, anxiety, or residual opioid craving. There is a need for a well-powered trial to evaluate virtually delivered groups, including both mindfulness and evidence-based approaches, to address these comorbidities during buprenorphine treatment.

Objective: To compare the effects of the Mindful Recovery Opioid Use Disorder Care Continuum (M-ROCC) vs active control among adults receiving buprenorphine for OUD.

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Background: Using an analogue-based drug design approach, a number of novel 2-substituted-1,3-thiazolone derivatives (3-10) have been produced and given permission to proceed for their anti-inflammatory properties. In the present paper, the new thiazole derivatives were designed, synthesized, and tested for their alpha-glucosidase, alpha-amylase, and COX-inhibitory activities. Approving the anti-diabetic activity.

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