Anesthesia and analgesia
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Anesthesia and analgesia · Sep 2024
Randomized Controlled Trial Multicenter StudyImpact on Anesthetic Agent Consumption After Autonomic Neural Blockade as Part of a Combined Anesthesia Protocol: A Randomized Clinical Trial.
The intraoperative autonomic neural blockade (ANB) was found safe and effective in controlling pain and associated symptoms and reducing analgesic consumption after laparoscopic sleeve gastrectomy (LSG). This study evaluated whether ANB performed at the outset of LSG reduces anesthetic consumption and promotes hemodynamic stability. ⋯ Performing ANB at the onset of LSG is a safe and effective approach that reduces remifentanil consumption and promotes hemodynamic stability during the procedure. This technique holds promise for optimizing anesthesia management in LSG and other minimally invasive surgeries.
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Anesthesia and analgesia · Sep 2024
Review Practice GuidelineCare of the Pediatric Patient for Ambulatory Tonsillectomy With or Without Adenoidectomy: The Society for Ambulatory Anesthesia Position Statement.
The landscape of ambulatory surgery is changing, and tonsillectomy with or without adenoidectomy is one of the most common pediatric surgical procedures performed nationally. The number of children undergoing tonsillectomy on an ambulatory basis continues to increase. The 2 most common indications for tonsillectomy are recurrent throat infections and obstructive sleep-disordered breathing. ⋯ The aim is to provide health care professionals with practical criteria and suggestions based on the best available evidence. When high-quality evidence is unavailable, we relied on group consensus from pediatric ambulatory specialists in the SAMBA Pediatric Committee. Consensus recommendations were presented to the Pediatric Committee of SAMBA.
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Anesthesia and analgesia · Sep 2024
Tranexamic Acid Administration During Liver Transplantation Is Not Associated With Lower Blood Loss or With Reduced Utilization of Red Blood Cell Transfusion.
Current clinical guidelines recommend antifibrinolytic treatment for liver transplantation to reduce blood loss and transfusion utilization. However, the clinical relevance of fibrinolysis during liver transplantation is questionable, a benefit of tranexamic acid (TXA) in this context is not supported by sufficient evidence, and adverse effects are also conceivable. Therefore, we tested the hypothesis that use of TXA is associated with reduced blood loss. ⋯ Our data do not support the use of TXA during liver transplantation. Physicians should exercise caution and consider individual factors when deciding whether or not to administer TXA.
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Anesthesia and analgesia · Sep 2024
Decision Curve Analysis of In-Hospital Mortality Prediction Models: The Relative Value of Pre- and Intraoperative Data For Decision-Making.
Clinical prediction modeling plays a pivotal part in modern clinical care, particularly in predicting the risk of in-hospital mortality. Recent modeling efforts have focused on leveraging intraoperative data sources to improve model performance. However, the individual and collective benefit of pre- and intraoperative data for clinical decision-making remains unknown. We hypothesized that pre- and intraoperative predictors contribute equally to the net benefit in a decision curve analysis (DCA) of in-hospital mortality prediction models that include pre- and intraoperative predictors. ⋯ When it comes to predicting in-hospital mortality and subsequent decision-making, preoperative demographics, comorbidities, and surgery-related data provide the largest benefit for clinicians with risk-averse preferences, whereas preoperative laboratory values provide the largest benefit for decision-makers with more moderate risk preferences. Our decision-analytic investigation of different predictor categories moves beyond the question of whether certain predictors provide a benefit in traditional performance metrics (eg, AUROC). It offers a nuanced perspective on for whom these predictors might be beneficial in clinical decision-making. Follow-up studies requiring larger datasets and dedicated deep-learning models to handle continuous intraoperative data are essential to examine the robustness of our results.