Current opinion in anaesthesiology
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Curr Opin Anaesthesiol · Aug 2024
ReviewRemimazolam: its clinical pharmacology and evolving role in anesthesia and sedation practice.
Remimazolam is a novel benzodiazepine anesthetic/sedative, designed as a rapidly metabolized carboxylic acid. Since its recent launch, the role of remimazolam in modern anesthesia and sedation practice is still evolving. This review aims to outline the clinical pharmacology and clinical utility of remimazolam to elucidate its potential advantages and limitations. ⋯ Remimazolam may be beneficial to use in procedural sedation and general anesthesia for patients with difficult airways or hemodynamic instability. Further clinical studies with remimazolam are warranted to identify the potential benefits in other settings and patient populations.
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Curr Opin Anaesthesiol · Aug 2024
ReviewThe drug titration paradox: a control engineering perspective.
The drug titration paradox describes that, from a population standpoint, drug doses appear to have a negative correlation with its clinical effect. This paradox is a relatively modern discovery in anesthetic pharmacology derived from large clinical data sets. This review will interpret the paradox using a control engineering perspective. ⋯ This drug titration paradox describes the constraints of how the average clinician will dose a patient with an unknown clinical response. While our understanding of the paradox is still in its infancy, it remains unclear how alternative dosing schemes, such as through automation, may exceed the boundaries of the paradox and potentially affect its conclusions.
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Curr Opin Anaesthesiol · Aug 2024
ReviewRemifentanil-induced hyperalgesia: the current state of affairs.
Remifentanil-induced hyperalgesia (RIH) is a part of a general opioid-induced hyperalgesia (OIH) syndrome, seemingly resulting from abrupt cessation of continuous remifentanil infusion at rates equal or exceeding 0.3 mcg/kg/min. The intricate mechanisms of its development are still not completely understood. ⋯ Several ways of prevention and management have been suggested, such as slow withdrawal of remifentanil infusion, the addition of propofol, pretreatment with or concomitant administration of ketamine, buprenorphine, cyclooxygenase-2 inhibitors (NSAIDs), methadone, dexmedetomidine. In clinical and animal studies, these strategies exhibited varying success, and many are still being investigated.
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Given the rapid growth of nonoperating room anesthesia (NORA) in recent years, it is essential to review its unique challenges as well as strategies for patient selection and care optimization. ⋯ Considering the unique challenges of NORA settings, meticulous patient selection, risk stratification, and preoperative optimization are crucial. Embracing data-driven strategies and leveraging technological innovations (such as artificial intelligence) is imperative to refine quality control methods in targeted areas. Collaborative efforts led by anesthesia providers will ensure personalized, well tolerated, and improved patient outcomes across all phases of NORA care.
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The integration of artificial intelligence (AI) in nonoperating room anesthesia (NORA) represents a timely and significant advancement. As the demand for NORA services expands, the application of AI is poised to improve patient selection, perioperative care, and anesthesia delivery. This review examines AI's growing impact on NORA and how it can optimize our clinical practice in the near future. ⋯ The findings underscore the substantial benefits of AI in NORA, which include improved safety, efficiency, and personalized care. AI's predictive capabilities in assessing hypoxemia risk and other perioperative events, have demonstrated potential to exceed human prognostic accuracy. The implications of these findings advocate for a careful yet progressive adoption of AI in clinical practice, encouraging the development of robust ethical guidelines, continual professional training, and comprehensive data management strategies. Furthermore, AI's role in anesthesia underscores the need for multidisciplinary research to address the limitations and fully leverage AI's capabilities for patient-centered anesthesia care.