Articles: anesthesia.
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Multicenter Study
The association between intraoperative low driving pressure ventilation and perioperative healthcare-associated costs: A retrospective multicenter cohort study.
A low dynamic driving pressure during mechanical ventilation for general anesthesia has been associated with a lower risk of postoperative respiratory complications (PRC), a key driver of healthcare costs. It is, however, unclear whether maintaining low driving pressure is clinically relevant to measure and contain costs. We hypothesized that a lower dynamic driving pressure is associated with lower costs. ⋯ Intraoperative mechanical ventilation targeting low dynamic driving pressures could be a relevant measure to reduce perioperative healthcare-associated costs in high-risk patients.
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Multicenter Study
A first assessment of the safe brain initiative care bundle for addressing postoperative delirium in the postanesthesia care unit.
Postoperative delirium (POD) following surgery is a prevalent and distressing condition associated with adverse patient outcomes and an increased healthcare burden. ⋯ The presented pragmatic implementation of a multidisciplinary care bundle, encompassing pre-, intra-, and postoperative measures alongside outcome monitoring, has the potential to significantly reduce the incidence of POD in the PACU. Improved patient outcomes may be achieved for general surgical departments with patient cohorts not typically considered at risk for developing POD.
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Anesthesia and analgesia · Oct 2024
Randomized Controlled Trial Multicenter Study Comparative StudyEnd-Tidal Control Versus Manual Control of Inhalational Anesthesia Delivery: A Randomized Controlled Noninferiority Trial.
Anaesthetic machine End-Tidal Control of ET-agent & ET-oxygen concentrations achieves and maintains desired targets at least as well as manual control.
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Randomized Controlled Trial Multicenter Study
Effects of different forced-air warming systems on the core temperature of patients: a manikin and multi-center clinical study.
The use of forced-air warming (FAW) blankets is widely recognized for preventing shivering and hypothermia in patients under general anesthesia. Various types of products are currently available for hospitals, and we have conducted a preliminary evaluation of insulation equipment based on expert opinions and initial parameters. However, we lack real-world experiments and accurate clinical data to validate these parameters and the accuracy of our decision-making results. This study aims to confirm the effectiveness of different FAW systems by assessing the thermal protection and operational characteristics of the equipment in both experimental and clinical settings, thereby enhancing our evaluation database. ⋯ Among patients undergoing laparoscopic radical resection of colorectal cancer with general anesthesia, all four FAW systems effectively prevented perioperative hypothermia. However, the system in Group A minimized heat loss more effectively than the others, providing superior thermal protection.
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Multicenter Study
Evaluating the accuracy of ChatGPT-4 in predicting ASA scores: A prospective multicentric study ChatGPT-4 in ASA score prediction.
This study investigates the potential of ChatGPT-4, developed by OpenAI, in enhancing medical decision-making processes, particularly in preoperative assessments using the American Society of Anesthesiologists (ASA) scoring system. The ASA score, a critical tool in evaluating patients' health status and anesthesia risks before surgery, categorizes patients from I to VI based on their overall health and risk factors. Despite its widespread use, determining accurate ASA scores remains a subjective process that may benefit from AI-supported assessments. This research aims to evaluate ChatGPT-4's capability to predict ASA scores accurately compared to expert anesthesiologists' assessments. ⋯ The findings suggest that ChatGPT-4 can significantly contribute to the medical field by supporting anesthesiologists in preoperative assessments. This study not only demonstrates ChatGPT-4's efficacy in medical data analysis and decision-making but also opens new avenues for AI applications in healthcare, particularly in enhancing patient safety and optimizing surgical outcomes. Further research is needed to refine AI models for complex case assessments and integrate them seamlessly into clinical workflows.