Resuscitation
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A machine-learning model trained to recognize emergency calls regarding Out-of-Hospital Cardiac Arrest (OHCA) was tested in clinical practice at Copenhagen Emergency Medical Services (EMS) from September 2018 to December 2019. We aimed to investigate emergency call characteristics where the machine-learning model failed to recognize OHCA or misinterpreted a call as being OHCA. ⋯ Continuous optimization of the language model is needed to improve the prediction of OHCA and thereby improve sensitivity and specificity of the machine-learning model on recognising OHCA in emergency telephone calls.
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This study aimed to describe the characteristics of cases of out-of-hospital cardiac arrest (OHCA) with an initial asystole rhythm in which extracorporeal cardiopulmonary resuscitation (ECPR) was introduced and discuss the clinical indications for ECPR in such patients. ⋯ A total of 202 ECPR cases with an initial asystole rhythm, including 12 patients with favourable neurological outcomes, were described. Even if the initial cardiac rhythm is asystole, ECPR could be considered if certain conditions are met.
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Observational Study
Annual improvement trends in resuscitation outcome of patients defibrillated by laypersons after out-of-hospital cardiac arrests and compression-only resuscitation of laypersons.
We aimed to investigate the effect of compression-only cardiopulmonary resuscitation (CPR) with conventional CPR in patients who were defibrillated by laypersons. ⋯ In Japan, the outcomes of out-of-hospital cardiac arrest patients who were defibrillated by laypersons were considerably better in compression-only resuscitation of laypersons every year.