British journal of anaesthesia
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Review Meta Analysis
The impact of perioperative ketamine or esketamine on the subjective quality of recovery after surgery: a meta-analysis of randomised controlled trials.
This meta-analysis aimed to evaluate the impact of ketamine/esketamine on postoperative subjective quality of recovery (QoR). ⋯ PROSPERO (CRD42023477580).
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Editorial Review
Perioperative anaphylaxis and the principle of primum non nocere.
Perioperative anaphylaxis is a rare and unpredictable event that continues to cause patient harm. More work is needed to decrease the risk to patients through measures to limit sensitisation, optimise management and investigation, and ensure that patients are not inadvertently re-exposed to allergens. Robust epidemiological data such as that provided by the consecutive GERAP surveys over the past 30 yr have been invaluable in defining the problem, identifying emerging allergens, acting as a catalyst for change, and stimulating research.
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Multicenter Study
Multicentre validation of a machine learning model for predicting respiratory failure after noncardiac surgery.
Postoperative respiratory failure is a serious complication that could benefit from early accurate identification of high-risk patients. We developed and validated a machine learning model to predict postoperative respiratory failure, defined as prolonged (>48 h) mechanical ventilation or reintubation after surgery. ⋯ Utilising just eight easily extractable variables, this machine learning model demonstrated excellent discrimination in both internal and external validation for predicting postoperative respiratory failure. The model enables personalised risk stratification and facilitates data-driven clinical decision-making.
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Multicenter Study
Association of preoperative beta-blocker use and cardiac complications after major noncardiac surgery: a prospective cohort study.
Cardiac complications after major noncardiac surgery are common and associated with high morbidity and mortality. How preoperative use of beta-blockers may impact perioperative cardiac complications remains unclear. ⋯ NCT02573532.
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Timely detection of modifiable risk factors for postoperative pulmonary complications (PPCs) could inform ventilation strategies that attenuate lung injury. We sought to develop, validate, and internally test machine learning models that use intraoperative respiratory features to predict PPCs. ⋯ These findings suggest that real-time identification of surgical patients' risk of postoperative pulmonary complications could help personalise intraoperative ventilatory strategies and reduce postoperative pulmonary complications.