Articles: emergency-medicine.
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Artificial Intelligence (AI) models like GPT-3.5 and GPT-4 have shown promise across various domains but remain underexplored in healthcare. Emergency Departments (ED) rely on established scoring systems, such as NIHSS and HEART score, to guide clinical decision-making. This study aims to evaluate the proficiency of GPT-3.5 and GPT-4 against experienced ED physicians in calculating five commonly used medical scores. ⋯ While AI models demonstrated some level of concordance with human expertise, they fell short in emulating the complex clinical judgments that physicians make. The study suggests that current AI models may serve as supplementary tools but are not ready to replace human expertise in high-stakes settings like the ED. Further research is needed to explore the capabilities and limitations of AI in emergency medicine.
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The Clinical Emergency Data Registry (CEDR) is a qualified clinical data registry that collects data from participating emergency departments (EDs) in the United States for quality measurement, improvement, and reporting purposes. This article aims to provide an overview of the data collection and validation process, describe the existing data structure and elements, and explain the potential opportunities and limitations for ongoing and future research use. CEDR data are primarily collected for quality reporting purposes and are obtained from diverse sources, including electronic health records and billing data that are de-identified and stored in a secure, centralized database. ⋯ Key limitations include the limited generalizability due to the selective nature of participating EDs and the limited validation and completeness of data elements not currently used for quality reporting purposes, including demographic data. Nonetheless, CEDR holds great potential for ongoing and future research in emergency medicine due to its large-volume, longitudinal, near real-time, clinical data. In 2021, the American College of Emergency Physicians authorized the transition from CEDR to the Emergency Medicine Data Institute, which will catalyze investments in improved data quality and completeness for research to advance emergency care.
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Whole-Body CT (WBCT) is frequently used in emergency situations for promptly diagnosing paediatric polytrauma patients, given the challenges associated with obtaining precise details about the mechanism and progression of trauma. However, WBCT does not lead to reduced mortality in paediatric patients, but is associated with high radiation exposure. We therefore wanted to develop a screening tool for CT demand-driven emergency room (ER)-trauma diagnostic to reduce radiation exposure in paediatric patients. ⋯ With the newly developed PePCI-Score, the frequency of WBCT in a paediatric emergency patients collective can be significantly reduced according to our data. After prospective validation, the initial assessment of paediatric trauma patients in the future could be made not only by the mechanism of injury, but also by the new PePCI-Score, deriving on clinical findings after thorough clinical assessment and the discretion of the trauma team.
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Yonsei medical journal · May 2024
Interrupting Effect of Social Distancing on Ischemic Heart Disease, Asthma, Stroke, and Suicide Attempt Patients by PM2.5 Exposure.
This study aimed to examine the interrupting effect of social distancing (SD) on emergency department (ED) patients with ischemic heart disease (IHD), stroke, asthma, and suicide attempts by PM2.5 exposure in eight Korean megacities from 2017 to 2020. ⋯ While the interrupting effect of SD was not as pronounced as anticipated, this study did validate the effectiveness of SD in modifying health behaviors and minimizing avoidable visits to EDs in addition to curtailing the occurrence of infectious diseases.