EMS and DNAR directives among patients with OHCA

Background: Emergency Medical Services (EMS) are often involved in end-of-life circumstances, yet little is known about how EMS interfaces with advance directives to forego unwanted resuscitation (Do Not Attempt Resuscitation (DNAR)). We evaluated the frequency of these directives involved in out-of-hospital cardiac arrest (OHCA) and how they impact care. Methods: We conducted a cohort investigation of adult, EMS-attended OHCA from January 1 to December 31, 2018 in … Continue reading EMS and DNAR directives among patients with OHCA

Clinical Characteristics of Patients With COVID-19 Receiving EMS

Question  What is the clinical presentation to emergency medical services among persons with coronavirus disease 2019 (COVID-19)? Findings  This cohort study of 124 patients with COVID-19 revealed that most patients with COVID-19 presenting to emergency medical services were older and had multiple chronic health conditions. Initial concern, symptoms, and examination findings were heterogeneous and not consistently characterized as febrile respiratory illness. Meaning  The findings of this study suggest … Continue reading Clinical Characteristics of Patients With COVID-19 Receiving EMS

Prevalence of COVID-19 in OHCA: Implications for Bystander CPR

We undertook a cohort investigation of OHCA attended by emergency medical services (EMS) in Seattle and King County, WA from January 1 to April 15, 2020. Patients where EMS attempted resuscitation (EMS treated) and where EMS responded but did not provide resuscitation because of signs of irreversible death (dead on EMS arrival) were included. Our population-based OHCA registry systematically abstracts information about OHCA presentation, treatment, and outcome from dispatch audio recordings, defibrillator electronic data, prehospital … Continue reading Prevalence of COVID-19 in OHCA: Implications for Bystander CPR

Occupational Exposures and Programmatic Response to COVID-19 Pandemic: An EMS Experience

Abstract Background: Rigorous assessment of occupational COVID-19 risk and personal protective equipment (PPE) use are not well-described. We evaluated 9-1-1 emergency medical services (EMS) encounters for patients with COVID-19 to assess occupational exposure, programmatic strategies to reduce exposure, and PPE use. Methods: We conducted a retrospective cohort investigation of lab-confirmed COVID-19 patients in King County, WA who received 9-1-1 EMS responses from February 14, 2020 … Continue reading Occupational Exposures and Programmatic Response to COVID-19 Pandemic: An EMS Experience

Causes of Chest Compression Interruptions During OHCA

Abstract Background Interruptions in chest compressions contribute to poor outcomes in out‐of‐hospital cardiac arrest. The objective of this retrospective observational cohort study was to characterize the frequency, reasons, and duration of interruptions in chest compressions and to determine if interruptions changed over time. Methods and Results All out‐of‐hospital cardiac arrests treated by the Seattle Fire Department (Seattle, WA, United States) from 2007 to 2016 with … Continue reading Causes of Chest Compression Interruptions During OHCA

Targeted Temperature Management at 33 Versus 36 Degrees: A Retrospective Cohort Study

Abstract Objectives: To determine the association between targeted temperature managementgoal temperature of 33°C versus 36°C and neurologic outcome after out-of-hospital cardiac arrest. Design: This was a retrospective, before-and-after, cohort study. Setting: Urban, academic, level 1 trauma center from 2010 to 2017. Patients: Adults with nontraumatic out-of-hospital cardiac arrest who received targeted temperature management. Interventions: Our primary exposure was targeted temperature management goal temperature, which was changed from 33°C to 36°C in April of 2014 at the study hospital. Primary … Continue reading Targeted Temperature Management at 33 Versus 36 Degrees: A Retrospective Cohort Study

Machine learning as a supportive tool to recognize cardiac arrest in emergency calls

Background Emergency medical dispatchers fail to identify approximately 25% of cases of out of hospital cardiac arrest, thus lose the opportunity to provide the caller instructions in cardiopulmonary resuscitation. We examined whether a machine learning framework could recognize out-of-hospital cardiac arrest from audio files of calls to the emergency medical dispatch center. Methods For all incidents responded to by Emergency Medical Dispatch Center Copenhagen in … Continue reading Machine learning as a supportive tool to recognize cardiac arrest in emergency calls