RESUMO
Out-of-hospital cardiac arrest (OHCA) occurs in nearly 350,000 people each year in the United States (US). Despite advances in pre- and in-hospital care, OHCA survival remains low and is highly variable across systems and regions. The critical barrier to improving cardiac arrest outcomes is not a lack of knowledge about effective interventions, but rather the widespread lack of systems of care to deliver interventions known to be successful. The RAndomized Cluster Evaluation of Cardiac ARrest Systems (RACE-CARS) trial is a 7-year pragmatic, cluster-randomized trial of 60 counties (57 clusters) in North Carolina using an established registry and is testing whether implementation of a customized set of strategically targeted community-based interventions improves survival to hospital discharge with good neurologic function in OHCA relative to control/standard care. The multi-faceted intervention comprises rapid cardiac arrest recognition and systematic bystander CPR instructions by 9-1-1 telecommunicators, comprehensive community CPR training and enhanced early automated external defibrillator (AED) use prior to emergency medical systems (EMS) arrival. Approximately 20,000 patients are expected to be enrolled in the RACE CARS Trial over 4 years of the assessment period. The primary endpoint is survival to hospital discharge with good neurologic outcome defined as a cerebral performance category (CPC) of 1 or 2. Secondary outcomes include the rate of bystander CPR, defibrillation prior to arrival of EMS, and quality of life. We aim to identify successful community- and systems-based strategies to improve outcomes of OHCA using a cluster randomized-controlled trial design that aims to provide a high level of evidence for future application.
RESUMO
BACKGROUND: Drone-delivered automated external defibrillators (AEDs) hold promises in the treatment of out-of-hospital cardiac arrest. Our objective was to estimate the time needed to perform resuscitation with a drone-delivered AED and to measure cardiopulmonary resuscitation (CPR) quality. METHODS: Mock out-of-hospital cardiac arrest simulations that included a 9-1-1 call, CPR, and drone-delivered AED were conducted. Each simulation was timed and video-recorded. CPR performance metrics were recorded by a Laerdal Resusci Anne Quality Feedback System. Multivariable regression modeling examined factors associated with time from 9-1-1 call to AED shock and CPR quality metrics (compression rate, depth, recoil, and chest compression fraction). Comparisons were made among those with recent CPR training (≤2 years) versus no recent (>2 years) or prior CPR training. RESULTS: We recruited 51 research participants between September 2019 and March 2020. The median age was 34 (Q1-Q3, 23-54) years, 56.9% were female, and 41.2% had recent CPR training. The median time from 9-1-1 call to initiation of CPR was 1:19 (Q1-Q3, 1:06-1:26) minutes. A median time of 1:59 (Q1-Q3, 01:50-02:20) minutes was needed to retrieve a drone-delivered AED and deliver a shock. The median CPR compression rate was 115 (Q1-Q3, 109-124) beats per minute, the correct compression depth percentage was 92% (Q1-Q3, 25-98), and the chest compression fraction was 46.7% (Q1-Q3, 39.9%-50.6%). Recent CPR training was not associated with CPR quality or time from 9-1-1 call to AED shock. Younger age (per 10-year increase; ß, 9.97 [95% CI, 4.63-15.31] s; P<0.001) and prior experience with AED (ß, -30.0 [95% CI, -50.1 to -10.0] s; P=0.004) were associated with more rapid time from 9-1-1 call to AED shock. Prior AED use (ß, 6.71 [95% CI, 1.62-11.79]; P=0.011) was associated with improved chest compression fraction percentage. CONCLUSION: Research participants were able to rapidly retrieve an AED from a drone while largely maintaining CPR quality according to American Heart Association guidelines. Chest compression fraction was lower than expected.