Prehospital emergency care : official journal of the National Association of EMS Physicians and the National Association of State EMS Directors
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Pediatric out-of-hospital cardiac arrest (OHCA) impacts 15,000-25,000 children annually in the U.S. The objective of this study was to determine if specific Emergency Medical Services (EMS) agency factors such as pediatric volume and preparedness factors, including hours of required pediatric training, pediatric emergency care coordinator (PECC), or pediatric informational resources are associated with improved quality of care or adverse events for pediatric OHCA. ⋯ In this large medical record review of EMS-treated pediatric OHCA cases, pediatric training, pediatric care coordination, and conducting pediatric quality reviews were not associated with reduced ASEs. Additional research is needed to understand how EMS agencies can improve the quality of care for pediatric OHCA, especially for infants.
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Motorcycle helmets save lives and reduce serious injury after motorcycle collisions (MCC). In 2022, 18 states had laws requiring helmet use by motorcyclists aged ≥21 years. Our objective was to compare helmet use and head trauma in emergency medical services (EMS) patients involved in MCC in states with and without helmet use laws. ⋯ In this retrospective cross-sectional study, a higher proportion of patients involved in MCCs in states without helmet laws were not wearing helmets at the time of injury, and unhelemted patients had increased likelihood of sustaining a head injury. EMS agencies in states without helmet laws should prepare their systems and clinicians for an increased incidence of head injuries after MCCs.
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While epinephrine is widely used for medical cardiac arrests, there is a knowledge gap regarding its utility for traumatic arrests. Traumatic arrests result from hypovolemia, hypoxia, or anatomic impairment of cardiac function such that the inotropic and vasoconstrictive effects of epinephrine may be ineffective or harmful. We hypothesized that epinephrine does not improve survival among patients with traumatic cardiac arrest. ⋯ Epinephrine was not associated with improved survival following traumatic cardiac arrest, and in multiple subanalyses, it was associated with inferior outcomes. These results may inform prehospital traumatic arrest protocols.
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Opioids kill tens of thousands of patients each year. While only a fraction of people with opioid use disorder (OUD) have accessed treatment in the last year, 30% of people who died from an overdose had an Emergency Medical Services (EMS) encounter within a year of their death. Prehospital buprenorphine represents an important emerging OUD treatment, yet limited data describe barriers to this treatment. Our objectives were to quantify the number of patients encountered by EMS who were eligible for prehospital buprenorphine, and to examine characteristics of patients who did or did not receive treatment. ⋯ One-in-three EMS patients with suspected opioid use disorder were ineligible for treatment with buprenorphine due to altered mental status. The second largest group consisted of patients who were eligible but not offered buprenorphine, highlighting potential gaps in paramedic training, logistical challenges in field administrations, and other factors that warrant further exploration.
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While ambulance transport decisions guided by artificial intelligence (AI) could be useful, little is known of the accuracy of AI in making patient diagnoses based on the pre-hospital patient care report (PCR). The primary objective of this study was to assess the accuracy of ChatGPT (OpenAI, Inc., San Francisco, CA, USA) to predict a patient's diagnosis using the PCR by comparing to a reference standard assigned by experienced paramedics. The secondary objective was to classify cases where the AI diagnosis did not agree with the reference standard as paramedic correct, ChatGPT correct, or equally correct. ⋯ In this study, overall accuracy of ChatGPT to diagnose patients based on their emergency medical services PCR was 75.0%. In cases where the ChatGPT diagnosis was considered less likely than paramedic diagnosis, most commonly the AI diagnosis was more critical than the paramedic diagnosis - potentially leading to over-triage. The under-triage rate was less than 1%.