J Emerg Med
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Armed conflicts constitute a significant public health problem, and the advent of asymmetric warfare tactics creates unique and new challenges to health care organizations providing trauma care in conflicts. ⋯ The study demonstrated a cyclical burden of conflict-related injuries and extensive medical needs, which increased over time. Among conflict-related injuries, explosive etiology predominated and was likely to result in mass casualty incidents. The low mortality might be due to critical but potentially salvageable patients not reaching the hospital in time, owing to the adverse context.
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The ideal way to make a connection with patients and their families is well studied. Despite these prescriptive measures, communication in emergency medicine is never easy. This past year and a half with restrictions imposed by coronavirus, all levels of communication have been made more difficult. This humanities in medicine essay uses patient examples to illustrate the challenges and pitfalls encountered when family and friends are no longer able to participate in history taking.
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Machine learning (ML) is an emerging tool for predicting need of end-of-life discussion and palliative care, by using mortality as a proxy. But deaths, unforeseen by emergency physicians at time of the emergency department (ED) visit, might have a weaker association with the ED visit. ⋯ In patients discharged to home from the ED, three-quarters of all 30-day deaths did not surprise an adjudicating committee with emergency medicine specialists. When only unsurprising deaths were included, ML mortality prediction improved significantly.