The American journal of emergency medicine
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To develop and externally validate models based on neural networks and natural language processing (NLP) to identify suspected serious infections in emergency department (ED) patients afebrile at initial presentation. ⋯ We developed and validated models to identify suspected serious infection in the ED. Extracted information from initial ED physician notes using NLP contributed to increased model performance, permitting identification of suspected serious infection at early stages of ED visits.
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Most children receive emergency care by general emergency physicians and not in designated children's hospitals. There are unique considerations in the care of children that differ from the care of adults. ⋯ These studies address pediatric resuscitation, traumatic arrest, septic shock, airway management, nailbed injuries, bronchiolitis, infant fever, cervical spine injuries, and cancer risk from radiation (Table 1). The findings in these articles have the potential to impact the evaluation and management of children (Table 2).
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Epidemiology and patterns of gymnastics-related head & neck trauma injuries: A NEISS database study.
To describe the epidemiology and patterns of gymnastics-related Head & Neck trauma injuries using the NEISS database from 2001 to 2020. ⋯ This study characterizes gymnastics-related head and neck injuries which is a topic that is under-studied. The findings from this study are helpful for gymnasts and those who care for them including providers, coaches and guardians, and this data may help inform future guidelines for treatment and injury prevention.
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ChatGPT, developed by OpenAI, represents the cutting-edge in its field with its latest model, GPT-4. Extensive research is currently being conducted in various domains, including cardiovascular diseases, using ChatGPT. Nevertheless, there is a lack of studies addressing the proficiency of GPT-4 in diagnosing conditions based on Electrocardiography (ECG) data. The goal of this study is to evaluate the diagnostic accuracy of GPT-4 when provided with ECG data, and to compare its performance with that of emergency medicine specialists and cardiologists. ⋯ Our study has shown that GPT-4 is more successful than emergency medicine specialists in evaluating both everyday and more challenging ECG questions. It performed better compared to cardiologists on everyday questions, but its performance aligned closely with that of the cardiologists as the difficulty of the questions increased.
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Epinephrine is recommended without an apparent ceiling dosage during cardiac arrest. However, excessive alpha- and beta-adrenergic stimulation may contribute to unnecessarily high aortic afterload, promote post-arrest myocardial dysfunction, and result in cerebral microvascular insufficiency in patients receiving extracorporeal cardiopulmonary resuscitation (ECPR). ⋯ After adjusting for age, cumulative epinephrine doses above 3 mg during cardiac arrest may be associated with unfavorable neurologic outcomes after ECPR and require further investigation.