The American journal of emergency medicine
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The emergency department (ED) triage process serves as a crucial first step for patients seeking acute care, This initial assessment holds crucial implications for patient survival and prognosis. In this study, a systematic review of the existing literature was performed to investigate the performance of machine learning (ML) models in recognizing and predicting the need for intensive care among ED patients. ⋯ ML models have demonstrated good performance in identifying and predicting critically ill patients in ED triage. However, because of the limited number of studies on each model, further high-quality prospective research is needed to validate these findings.
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To examine whether a fluid resuscitation strategy based on guidelines (at least 30 mL/kg IV crystalloids) vs. a restrictive approach with <30 mL/kg within three hours affects in-hospital mortality in patients with sepsis and a history of heart failure (HF). ⋯ Restrictive fluid resuscitation increased the risk of in-hospital mortality in HF patients with sepsis. More rigorous research is required to determine the optimal fluid resuscitation strategy for this population.
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To evaluate early measurement of the arterial to end-tidal carbon dioxide (PaCO2-PetCO2) gap, a surrogate for physiologic dead space, and its association with clinical outcomes in intubated adults in the emergency department (ED). ⋯ An elevated PaCO2-PetCO2 gap is common in the post-intubation period in the ED, but not significantly associated with clinical outcomes.
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Accurate, reliable, and sufficient data is required to reduce the burden of drowning by targeting preventive measures and improving treatment. Today's drowning statistics are informed by various methods sometimes based on data sources with questionable reliability. These methods are likely responsible for a systematic and significant underreporting of drowning. This study's aim was to assess the 30-day survival of patients with out-of-hospital cardiac arrest (OHCA) identified in the Danish Cardiac Arrest Registry (DCAR) after applying the Danish Drowning Formula. ⋯ This study was registered at ClinicalTrials.gov before analyses (NCT05323097).
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Previous studies have shown that an elevated prehospital National Early Warning Score (preNEWS) is associated with increased levels of adverse outcomes in patients with trauma. However, whether preNEWS is a predictor of massive transfusion (MT) in patients with trauma is currently unknown. This study investigated the accuracy of preNEWS in predicting MT and hospital mortality among trauma patients. ⋯ preNEWS is a useful, rapid predictor for MT and 24 h mortality. Calculation of preNEWS would be helpful for making the decision at the scene such as transfer straightforward to trauma center and advanced treatment.