Prehospital emergency care : official journal of the National Association of EMS Physicians and the National Association of State EMS Directors
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Evidence suggests that Extracorporeal Cardiopulmonary Resuscitation (ECPR) can improve survival rates for nontraumatic out-of-hospital cardiac arrest (OHCA). However, when ECPR is indicated over 50% of potential candidates are unable to qualify in the current hospital-based system due to geographic limitations. This study employs a Geographic Information System (GIS) model to estimate the number of ECPR eligible patients within the United States in the current hospital-based system, a prehospital ECPR ground-based system, and a prehospital ECPR Helicopter Emergency Medical Services (HEMS)-based system. ⋯ The study demonstrates a two-fold increase in ECPR eligibility for a prehospital ECPR ground-based system and a four-fold increase for a prehospital ECPR HEMS-based system compared to the current hospital-based ECPR system. This novel GIS model can inform future ECPR implementation strategies, optimizing systems of care.
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Telephone instructions are commonly used to improve cardiopulmonary resuscitation (CPR) by lay bystanders. This usually implies an audio but no visual connection between the provider and the emergency medical telecommunicator. We aimed to investigate whether video-guided feedback via a camera drone enhances the quality of CPR. ⋯ Video-guided feedback via drones might be a helpful tool to enhance the quality of telephone-assisted CPR in lay bystanders.
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A single dose epinephrine protocol (SDEP) for out-of-hospital cardiac arrest (OHCA) achieves similar survival to hospital discharge (SHD) rates as a multidose epinephrine protocol (MDEP). However, it is unknown if a SDEP improves SHD rates among patients with a shockable rhythm or those receiving bystander cardiopulmonary resuscitation (CPR). ⋯ Adjusting for confounders, the SDEP increased SHD in patients who received bystander CPR and there was a significant interaction between SDEP and bystander CPR. Single dose epinephrine protocol and MDEP had similar SHD rates regardless of rhythm type.
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The prehospital treatment for stable patients with atrial fibrillation with rapid ventricular response is rate-controlling agents such as calcium channel blockers, often diltiazem given as a bolus. At our agency we encourage the use of a bolus given via the infusion pump over two to four minutes immediately followed by a maintenance infusion, given concerns of recurrent tachycardia or hypotension secondary to rapid bolus administration. We examined if administering a bolus and infusion via an infusion pump shows better heart rate (HR) control at arrival to the emergency department (ED) compared with administration of a bolus only, while maintaining hemodynamic stability during transport. We also analyzed if a patient received a second bolus within 60 min of arrival to the ED. ⋯ Our results show no significant differences in HR control or need for repeat bolus at the ED with the use of a diltiazem infusion following a diltiazem bolus. However, even when administering larger boluses, the use of an infusion pump resulted in less hypotension.
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Asthma exacerbations are a common cause of pediatric Emergency Medical Services (EMS) encounters. Accordingly, prehospital management of pediatric asthma exacerbations has been designated an EMS research priority. However, accurate identification of pediatric asthma exacerbations from the prehospital record is nuanced and difficult due to the heterogeneity of asthma symptoms, especially in children. Therefore, this study's objective was to develop a prehospital-specific pediatric asthma computable phenotype (CP) that could accurately identify prehospital encounters for pediatric asthma exacerbations. ⋯ We modified existing and developed new pediatric asthma CPs to retrospectively identify prehospital pediatric asthma exacerbation encounters. We found that machine learning-based models greatly outperformed rule-based models. Given the high performance of the machine-learning models, the development and application of machine learning-based CPs for other conditions and diseases could help accelerate EMS research and ultimately enhance clinical care by accurately identifying patients with conditions of interest.