BMC anesthesiology
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This study aimed to compile data on the effectiveness of music therapy for patients undergoing cardiothoracic surgery. ⋯ Music therapy can significantly reduce anxiety, pain, HR, SBP, and postoperative opioid use and even improve SpO2 in patients who undergo cardiothoracic surgery. Music therapy has a positive effect on patients after cardiothoracic surgery with few side effects, so it is promising for use in clinics.
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The purpose of this network meta-analysis was to assess the impact of different protective ventilatory strategies on postoperative pulmonary complications (PPCs). ⋯ LTVs combined with iPEEP and RM decreased the incidence of PPCs, postoperative atelectasis, and pneumonia in noncardiac surgery patients. Individual PEEP-guided ventilation was the optimal lung protection ventilation strategy. The quality of evidence is moderate.
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Dexmedetomidine is considered to have neuroprotective effects and may reduce postoperative delirium in both cardiac and major non-cardiac surgeries. Compared with non-cardiac surgery, the delirium incidence is extremely high after cardiac surgery, which could be caused by neuroinflammation induced by surgical stress and CPB. Thus, it is essential to explore the potential benefits of dexmedetomidine on the incidence of delirium in cardiac surgery under CPB. ⋯ CRD42023452410.
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Sepsis is associated with a high incidence and mortality and poses a significant challenge to the treatment. Although esmolol has shown promise in sepsis treatment, its efficacy and safety remain contentious. This meta-analysis aims to clarify the role of esmolol in sepsis management. ⋯ Esmolol reduces 28-day mortality, length of ICU stay and duration of mechanical ventilation in sepsis patients. Furthermore, esmolol improves oxygen metabolism, mitigates myocardial injury and decreases heart rate without significantly affecting hemodynamic parameters.
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Meta Analysis
Artificial intelligence-assisted interventions for perioperative anesthetic management: a systematic review and meta-analysis.
Integration of artificial intelligence (AI) into medical practice has increased recently. Numerous AI models have been developed in the field of anesthesiology; however, their use in clinical settings remains limited. This study aimed to identify the gap between AI research and its implementation in anesthesiology via a systematic review of randomized controlled trials with meta-analysis (CRD42022353727). ⋯ This systematic review and meta-analysis revealed that randomized controlled trials on AI-assisted interventions in anesthesiology are in their infancy, and approaches that take into account complex clinical practice should be investigated in the future.