The American journal of emergency medicine
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A nomogram is a visualized clinical prediction models, which offer a scientific basis for clinical decision-making. There is a lack of reports on its use in predicting the risk of arrhythmias in trauma patients. This study aims to develop and validate a straightforward nomogram for predicting the risk of arrhythmias in trauma patients. ⋯ The nomogram developed in this study is a valuable tool for accurately predicting the risk of post-traumatic arrhythmias, offering a novel approach for physicians to tailor risk assessments to individual patients.
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This study analyzes the trajectory of youth emergency department or inpatient hospital visits for depression or anxiety in Illinois before and during the COVID-19 pandemic. ⋯ llinois youth depression and anxiety hospital visit rates declined significantly after the pandemic shutdown and remained stable into 2023 at levels below 2016-2019 rates. Further progress will require both clinical innovations and effective prevention grounded in a better understanding of the cultural roots of youth mental health.
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Hydrodissection is becoming increasingly recognized as a treatment for nerve entrapment syndromes in the orthopedic and rehabilitation world. Carpal Tunnel Syndrome (CTS) is the most prevalent nerve entrapment neuropathy, characterized by compression of the median nerve as it passes through the carpal tunnel. ⋯ This case report demonstrates the potential for an alternative approach to analgesia in the Emergency Department (ED) for patients presenting with pain related to CTS. Here we discuss a case of a 26-year-old female presenting with CTS symptoms and her successful treatment with ultrasound-guided hydrodissection in the ED.
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The Emergency Severity Index (ESI) is the most commonly used system in over 70% of all U.S. emergency departments (ED) that uses predicted resource utilization as a means to triage [1], Mistriage, which includes both undertriage and overtriage has been a persistent issue, affecting 32.2% of total ED visits [2]. Our goal is to develop a machine learning framework that predicts patients' resource needs, thereby improving resource allocation during triage. ⋯ This study shows the high accuracy in predicting resource needs for patients in the ED using a machine learning model. This can greatly improve patient flow and resource allocation in already resource limited emergency departments.
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Observational Study
The benefits of a virtual emergency department observation unit for hospital observation patients.
The benefit of virtual emergency department observation unit (EDOU) care relative to traditional observation care in an inpatient bed is unknown. ⋯ Management of observation patients in a virtual-EDOU setting is superior to care in a traditional inpatient setting in terms of costs, length of stays, inpatient admission and adverse events rates.