British journal of anaesthesia
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Observational Study
Residual neuromuscular block in the postanaesthesia care unit: a single-centre prospective observational study and systematic review.
Concerns regarding residual neuromuscular block (RNMB) have persisted since the introduction of neuromuscular blocking agents, with reported incidences in the 21st century up to 50%. Advances in neuromuscular transmission (NMT) monitoring and the introduction of sugammadex have addressed this issue, but the impact of these developments remains unclear. ⋯ The incidence of residual neuromuscular block in the PACU was 2.2%. This suggests significant improvement in the prevention of residual neuromuscular block and stresses the importance of rigorous neuromuscular transmission monitoring and adequate use of reversal agents.
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We investigated the intraneural spread of injected fluid in brachial plexus nerve roots, examining the potential for intrafascicular spread and identifying influencing factors. ⋯ In contrast with multifascicular peripheral nerves, intrafascicular spread was possible after deliberate intraneural injections near the neuroforaminal canal exit of the brachial plexus nerve roots in several monofascicular or bifascicular ventral rami if the fascicle diameter was more than twice the needle opening length and the entire opening was inside the fascicle.
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We explored how adult surgical patients perceived their risk of major postoperative complications, including neurological complications, and how much information they wanted to receive about such risks. ⋯ Many participants did not know the risks of major perioperative complications but based their risk perception on previous experiences and trust in health professionals. Participants focused on hope more than their concerns. Information provision should be personalised as patients expressed differences in the desired amount of information on risks.
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Hypotension is associated with organ injury and death in surgical and critically ill patients. In clinical practice, treating hypotension remains challenging because it can be caused by various underlying haemodynamic alterations. We aimed to identify and independently validate endotypes of hypotension in big datasets of surgical and critically ill patients using unsupervised deep learning. ⋯ Unsupervised deep learning identified four endotypes of hypotension in surgical and critically ill patients: vasodilation, hypovolaemia, myocardial depression, and bradycardia. The algorithm provides the probability of each endotype for each hypotensive data point. Identifying hypotensive endotypes could guide clinicians to causal treatments for hypotension.