Annals of emergency medicine
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To use artificial intelligence (AI) to predict billing code levels for emergency department (ED) encounters. ⋯ Currently available AI models accurately predict billing code levels for ED encounters based on clinical notes, clinical characteristics, and orders. This has the potential to automate coding of ED encounters and save administrative costs and time.
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Multicenter Study
Association Between Neuromuscular Blocking Agents and Outcomes of Emergency Tracheal Intubation: A Secondary Analysis of Randomized Trials.
To examine the association between the neuromuscular blocking agent received (succinylcholine versus rocuronium) and the incidences of successful intubation on the first attempt and severe complications during tracheal intubation of critically ill adults in an emergency department (ED) or ICU. ⋯ Among critically ill adults undergoing tracheal intubation, the incidences of successful intubation on the first attempt and severe complications were not significantly different between patients who received succinylcholine and patients who received rocuronium.