Scand J Trauma Resus
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Scand J Trauma Resus · Sep 2020
Multicenter StudyPre-hospital care & interfacility transport of 385 COVID-19 emergency patients: an air ambulance perspective.
COVID-19, the pandemic caused by the severe acute respiratory syndrome coronavirus-2, is challenging healthcare systems worldwide. Little is known about problems faced by emergency medical services-particularly helicopter services-caring for suspected or confirmed COVID-19 patients. We aimed to describe the issues faced by air ambulance services in Europe as they transport potential COVID-19 patients. ⋯ All participating air ambulance providers were prepared for COVID-19. Safe care and transport of suspected or confirmed COVID-19 patients is achievable. Most patients on primary missions were transported by ground. These patients were less sick than interfacility transport patients, for whom air transport was the preferred method.
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Scand J Trauma Resus · Sep 2020
Multicenter StudyReal-time AI prediction for major adverse cardiac events in emergency department patients with chest pain.
A big-data-driven and artificial intelligence (AI) with machine learning (ML) approach has never been integrated with the hospital information system (HIS) for predicting major adverse cardiac events (MACE) in patients with chest pain in the emergency department (ED). Therefore, we conducted the present study to clarify it. ⋯ An AI real-time prediction model is a promising method for assisting physicians in predicting MACE in ED patients with chest pain. Further studies to evaluate the impact on clinical practice are warranted.