The American journal of emergency medicine
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Randomized Controlled Trial
Isotonic balanced fluid versus 0.9% saline in patients with moderate to severe traumatic brain injury: A double-blinded randomised controlled trial.
Traumatic brain injury (TBI) is a global health concern with significant economic impact. Optimal fluid therapy aims to restore intravascular volume, maintain cerebral perfusion pressure and blood flow, thus preventing secondary brain injury. While 0.9% saline (NS) is commonly used, concerns about acid-base and electrolyte imbalance and development of acute kidney injury (AKI) lead to consideration of balanced fluids as an alternative. ⋯ In patients with moderate to severe TBI, the use of SF was not associated with reduced in-hospital mortality, development of AKI, or improved 6-month GOS-E when compared to NS.
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Observational Study
The TriAGe + score for vertigo or dizziness: A validation study in a university hospital emergency department in Hong Kong.
Patients with dizziness commonly present to Emergency Departments (ED) and 6% of these patients will be diagnosed with acute stroke. The TriAGe+ score comprises of eight clinical parameters and stratifies patients into four risk groups. The Japanese authors reported that the tool performed well, so our aim was to validate this diagnostic tool in our ED in Hong Kong. ⋯ The TriAGe+ score is an efficient stroke prediction score for patients presenting to the ED with dizziness.
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>50,000 people died in the February 2023 earthquakes in Türkiye. The aim of this study was to identify the factors affecting mortality rates of the trauma patients who were presented to the emergency department (ED) after the earthquake and provide suggestions for better preparedness strategies for future natural disasters. ⋯ In the aftermath of a devastating earthquake, this study underscores the formidable challenges faced by healthcare systems during natural disasters. To prepare for future disasters, healthcare systems must enhance resilience, develop rapid identification techniques, and adopt a holistic patient care approach.
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The manual recording of electronic health records (EHRs) by clinicians in the emergency department (ED) is time-consuming and challenging. In light of recent advancements in large language models (LLMs) such as GPT and BERT, this study aimed to design and validate LLMs for automatic clinical diagnoses. The models were designed to identify 12 medical symptoms and 2 patient histories from simulated clinician-patient conversations within 6 primary symptom scenarios in emergency triage rooms. ⋯ This paper highlights the potential of LLMs for automatic EHR recording in Korean EDs. The KLUE-RoBERTa-based model demonstrated superior classification performance. Furthermore, XAI using SHAP provided reliable explanations for model outputs. The reliability of these explanations was confirmed by a Turing test.
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Timely hospital presentation and treatment are critical for recovery from coronavirus disease (COVID-19). However, the relationship between symptom onset-to-door time and key clinical outcomes, such as inpatient mortality, has been poorly understood due to the difficulty of retrospectively measuring symptom onset in observational data. This study examines the association between patient-reported symptom onset-to-door time (ODT) and mortality among patients hospitalized and treated for COVID-19 disease. ⋯ More days between symptom onset and hospital arrival were associated with lower mortality among hospitalized patients treated for COVID-19 disease, particularly if they did not have severe illness at ED presentation. However, onset-to-door time was not associated with mortality among hospitalized patients with severe illness at ED presentation. Collectively, these results suggest that non-severely ill COVID-19 patients who require hospitalization are less likely to decompensate with each passing day without severe illness. These findings may continue to guide clinical care delivery for hospitalized COVID-19 patients.