Background: : Drones are able to deliver automated external defibrillators in cases of out-of-hospital cardiac arrest (OHCA) but can be deployed for other purposes. Our aim was to evaluate the feasibility of sending live photos to dispatch centres before arrival of other units during time-critical incidents. Methods: : In this retrospective observational study, the regional dispatch centre implemented a new service using five existing AED-drone systems covering an estimated 200 000 inhabitants in Sweden. Drones were deployed automatically over a 4-month study period (December 2022-April 2023) in emergency calls involving suspected OHCAs, traffic accidents and fires in buildings. Upon arrival at the scene, an overhead photo was taken and transmitted to the dispatch centre. Feasibility of providing photos in real time, and time delays intervals were examined. Results: : Overall, drones were deployed in 59/440 (13%) of all emergency calls: 26/59 (44%) of suspected OHCAs, 20/59 (34%) of traffic accidents, and 13/59 (22%) of fires in buildings. The main reasons for non-deployment were closed airspace and unfavourable weather conditions (68%). Drones arrived safely at the exact location in 58/59 cases (98%). Their overall median response time was 3:49 min, (IQR 3:18-4:26) vs. emergency medical services (EMS), 05:51 (IQR: 04:29-08:04) p-value for time difference between drone and EMS = 0,05. Drones arrived first on scene in 47/52 cases (90%) and the largest median time difference was found in suspected OHCAs 4:10 min, (IQR: 02:57-05:28). The time difference in the 5/52 (10%) cases when EMS arrived first the time difference was 5:18 min (IQR 2:19-7:38), p = NA. Photos were transmitted correctly in all 59 alerts. No adverse events occurred. Conclusion: : In a newly implemented drone dispatch service, drones were dispatched to 13% of relevant EMS calls. When drones were dispatched, they arrived at scene earlier than EMS services in 90% of cases. Drones were able to relay photos to the dispatch centre in all cases. Although severely affected by closed airspace and weather conditions, this novel method may facilitate additional decision-making information during time-critical incidents.

BACKGROUND:Reducing the time to treatment by means of cardiopulmonary resuscitation (CPR) and defibrillation is essential to increasing survival after cardiac arrest. A novel method of dispatching drones for delivery of automated external defibrillators (AEDs) to the site of a suspected out-of-hospital cardiac arrest (OHCA) has been shown to be feasible, with the potential to shorten response times compared with the emergency medical services. However, little is known of dispatchers' experiences of using this novel methodology. METHODS:A qualitative semi-structured interview study with a phenomenological approach was used. Ten registered nurses employed at an emergency medical dispatch centre in Gothenburg, Sweden, were interviewed and the data was analysed by qualitative content analysis. The purpose was to explore dispatcher nurses' experiences of deliveries of AEDs by drones in cases of suspected OHCA. RESULTS:Three categories were formed. Nurses expressed varying compliance to the telephone-assisted protocol for dispatch of AED-equipped drones. They experienced uncertainty as to how long would be an acceptable interruption from the CPR protocol in order to retrieve a drone-delivered AED. The majority experienced that collegial support was important. Technical support, routines and training need to be improved to further optimise action in cases of drone-delivered AEDs handled by dispatcher nurses. CONCLUSIONS:Although telephone-assisted routines for drone dispatch in cases of OHCA were available, their use was rare. Registered nurses showed variable degrees of understanding of how to comply with these protocols. Collegial and technical support was considered important, alongside routines and training, which need to be improved to further support bystander use of drone-delivered AEDs. As the possibilities of using drones to deliver AEDs in cases of OHCA are explored more extensively globally, there is a good possibility that this study could be of benefit to other nations implementing similar methods. We present concrete aspects that are important to take into consideration when implementing this kind of methodology at dispatch centres.

Importance: Out-of-hospital cardiac arrest (OHCA) is a leading cause of morbidity and mortality in the US and Europe (∼600,000 incident events annually) and around the world (∼3.8 million). With every minute that passes without cardiopulmonary resuscitation or defibrillation, the probability of survival decreases by 10%. Preliminary studies suggest that uncrewed aircraft systems, also known as drones, can deliver automated external defibrillators (AEDs) to OHCA victims faster than ground transport and potentially save lives. Objective: To date, the United States (US), Sweden, and Canada have made significant contributions to the knowledge base regarding AED-equipped drones. The purpose of this Special Communication is to explore the challenges and facilitators impacting the progress of AED-equipped drone integration into emergency medicine research and applications in the US, Sweden, and Canada. We also explore opportunities to propel this innovative and important research forward. Evidence review: In this narrative review, we summarize the AED-drone research to date from the US, Sweden, and Canada, including the first drone-assisted delivery of an AED to an OHCA. Further, we compare the research environment, emergency medical systems, and aviation regulatory environment in each country as they apply to OHCA, AEDs, and drones. Finally, we provide recommendations for advancing research and implementation of AED-drone technology into emergency care. Findings: The rates that drone technologies have been integrated into both research and real-life emergency care in each country varies considerably. Based on current research, there is significant potential in incorporating AED-equipped drones into the chain of survival for OHCA emergency response. Comparing the different environments and systems in each country revealed ways that each can serve as a facilitator or barrier to future AED-drone research. Conclusions and relevance: The US, Sweden, and Canada each offers different challenges and opportunities in this field of research. Together, the international community can learn from one another to optimize integration of AED-equipped drones into emergency systems of care.

BACKGROUND:A novel approach to improve bystander defibrillation for out-of-hospital cardiac arrests is to dispatch and deliver an automated external defibrillator (AED) directly to the suspected cardiac arrest location by drone. The aim of this study was to investigate how often a drone could deliver an AED before ambulance arrival and to measure the median time benefit achieved by drone deliveries. METHODS:In this prospective observational study, five AED-equipped drones were placed within two separate controlled airspaces in Sweden, covering approximately 200 000 inhabitants. Drones were dispatched in addition to standard emergency medical services for suspected out-of-hospital cardiac arrests and flight was autonomous. Alerts concerning children younger than 8 years, trauma, and emergency medical services-witnessed cases were not included. Exclusion criteria were air traffic control non-approval of flight, unfavourable weather conditions, no-delivery zones, and darkness. Data were collected from the dispatch centres, ambulance organisations, Swedish Registry for Cardiopulmonary Resuscitation, and the drone operator. Core outcomes were the percentage of cases for which an AED was delivered by a drone before ambulance arrival, and the median time difference (minutes and seconds) between AED delivery by drone and ambulance arrival. Explorative outcomes were percentage of attached drone-delivered AEDs before ambulance arrival and the percentage of cases defibrillated by a drone-delivered AED when it was used before ambulance arrival. FINDINGS:During the study period (from April 21, 2021 to May 31, 2022), 211 suspected out-of-hospital cardiac arrest alerts occurred, and in 72 (34%) of those a drone was deployed. Among those, an AED was successfully delivered in 58 (81%) cases, and the major reason for non-delivery was cancellation by dispatch centre because the case was not an out-of-hospital cardiac arrest. In cases for which arrival times for both drone and ambulance were available (n=55), AED delivery by drone occurred before ambulance arrival in 37 cases (67%), with a median time benefit of 3 min and 14 s. Among these cases, 18 (49%) were true out-of-hospital cardiac arrests and a drone-delivered AED was attached in six cases (33%). Two (33%) had a shockable first rhythm and were defibrillated by a drone-delivered AED before ambulance arrival, with one person achieving 30-day survival. No adverse events occurred. AED delivery (not landing) was made within 15 m from the patient or building in 91% of the cases. INTERPRETATION:AED-equipped drones dispatched in cases of suspected out-of-hospital cardiac arrests delivered AEDs before ambulance arrival in two thirds of cases, with a clinically relevant median time benefit of more than 3 min. This intervention could potentially decrease time to attachment of an AED, before ambulance arrival. FUNDING:Swedish Heart Lung Foundation.

AIMS:Early defibrillation is critical for the chance of survival in out-of-hospital cardiac arrest (OHCA). Drones, used to deliver automated external defibrillators (AEDs), may shorten time to defibrillation, but this has never been evaluated in real-life emergencies. The aim of this study was to investigate the feasibility of AED delivery by drones in real-life cases of OHCA.METHODS AND RESULTS:In this prospective clinical trial, three AED-equipped drones were placed within controlled airspace in Sweden, covering approximately 80 000 inhabitants (125 km2). Drones were integrated in the emergency medical services for automated deployment in beyond-visual-line-of-sight flights: (i) test flights from 1 June to 30 September 2020 and (ii) consecutive real-life suspected OHCAs. Primary outcome was the proportion of successful AED deliveries when drones were dispatched in cases of suspected OHCA. Among secondary outcomes was the proportion of cases where AED drones arrived prior to ambulance and time benefit vs. ambulance. Totally, 14 cases were eligible for dispatch during the study period in which AED drones took off in 12 alerts to suspected OHCA, with a median distance to location of 3.1 km [interquartile range (IQR) 2.8-3.4). AED delivery was feasible within 9 m (IQR 7.5-10.5) from the location and successful in 11 alerts (92%). AED drones arrived prior to ambulances in 64%, with a median time benefit of 01:52 min (IQR 01:35-04:54) when drone arrived first. In an additional 61 test flights, the AED delivery success rate was 90% (55/61).CONCLUSION:In this pilot study, we have shown that AEDs can be carried by drones to real-life cases of OHCA with a successful AED delivery rate of 92%. There was a time benefit as compared to emergency medical services in cases where the drone arrived first. However, further improvements are needed to increase dispatch rate and time benefits.TRIAL REGISTRATION NUMBER:ClinicalTrials.gov Identifier: NCT04415398.

Introduction: Early defibrillation is essential for increasing survival in out-of-hospital-cardiac-arrest (OHCA). Previous studies on AED-delivery using drones have shown that the method is feasible and has potential to shorten time to defibrillation. However, it is still unclear if drones can deliver AEDs before ambulance arrival with clinically relevant time benefits in real-life suspected OHCA. Our aim was to investigate if drones, used as a complement to standard care, can deliver AEDs before ambulance arrival in real-life suspected OHCA in Sweden. Method: Five AED-equipped drones were placed in separate sectors within two controlled airspaces around Gothenburg, Sweden. In cases of suspected OHCA during a study period of 11 months, a drone was dispatched by the dispatch center. A drone operator deployed and remotely surveilled the autonomously responding drone (beyond visual line of sight), which on arrival winched down an AED. The dispatchers then instructed the callers to retrieve the AED. The drone range one-way was 6 kilometers and the drone had a velocity of approximately 60 km/h. Alerts to no-fly zones and alerts in rain and wind > 8 m/s were excluded. Time to AED delivery was compared to standard of care ambulance delay in each case. Results: A total of 223 suspected OHCA were observed in the study areas. In 72 (32%) cases a drone took off, out of these an AED was delivered in 58 (81%) cases. In 56 cases, arrival times for both drone and ambulance were available. The AED-delivery occurred prior to ambulance arrival in 36 of these cases (64%) with a median time benefit of 3 min and 14 sec. Totally 6 patients (11%) had an AED attached, amongst them two were defibrillated and one patient survived 30 days. The main reasons for non-flights were weather conditions (16%), cancelled by dispatch center (17%) and service offline (13%). Conclusion: The use of AED-equipped drones has potential to enable AED delivery prior to ambulance arrival in many cases of suspected OHCA and the time benefit seen in this study indicates potential to facilitate defibrillation before ambulance arrival. However, more improvements and studies are needed to further increase time benefits and the proportion of cases where an AED is attached and used before ambulance arrival.

Drone-Delivered AED in Cardiac Arrest This case report describes a patient in Sweden who had an out-of-hospital cardiac arrest and received defibrillation with an automated external defibrillator delivered by a drone (shown in a video).

BACKGROUND:Early defibrillation is essential for increasing the chance of survival in out-of-hospital-cardiac-arrest (OHCA). Automated external defibrillator (AED)-equipped drones have a substantial potential to shorten times to defibrillation in OHCA patients. However, optimal locations for drone deployment are unknown. Our aims were to find areas of high incidence of OHCA on a national level for placement of AED-drones, and to quantify the number of drones needed to reach 50, 80, 90 and 100% of the target population within eight minutes.METHODS:This is a retrospective observational study of OHCAs reported to the Swedish Registry for Cardiopulmonary Resuscitation between 2010-2018. Spatial analyses of optimal drone placement were performed using geographical information system (GIS)-analyses covering high-incidence areas (>100 OHCAs in 2010-2018) and response times.RESULTS:39,246 OHCAs were included. To reach all OHCAs in high-incidence areas with AEDs delivered by drone or ambulance within eight minutes, 61 drone systems would be needed, resulting in overall OHCA coverage of 58.2%, and median timesaving of 05:01 (min:sec) [IQR 03:22-06:19]. To reach 50% of the historically reported OHCAs in <8 min, 21 drone systems would be needed; for 80%, 366; for 90%, 784, and for 100%, 2408.CONCLUSIONS:At a national level, GIS-analyses can identify high incidence areas of OHCA and serve as tools to quantify the need of AED-equipped drones. Use of only a small number of drone systems can increase national coverage of OHCA substantially. Prospective real-life studies are needed to evaluate theoretically optimized suggestions for drone placement.

Background: Submersion time is a strong predictor for death in drowning, already 10 min after submersion, survival is poor. Traditional search efforts are time-consuming and demand a large number of rescuers and resources. We aim to investigate the feasibility and effectiveness of using drones combined with an online machine learning (ML) model for automated recognition of simulated drowning victims. Methods: This feasibility study used photos taken by a drone hovering at 40 m altitude over an estimated 3000 m(2) surf area with individuals simulating drowning. Photos from 2 ocean beaches in the south of Sweden were used to (a) train an online ML model (b) test the model for recognition of a drowning victim. Results: The model was tested for recognition on n = 100 photos with one victim and n = 100 photos with no victims. In drone photos containing one victim (n = 100) the ML model sensitivity for drowning victim recognition was 91% (95%CI 84.9%-96.2%) with a median probability score that the finding was human of 66% (IQR 52-71). In photos with no victim (n = 100) the ML model specificity was 90% (95%CI: 83.9%-95.6%). False positives were present in 17.5% of all n = 200 photos but could all be ruled out manually as false objects. Conclusions: The use of a drone and a ML model was feasible and showed satisfying effectiveness in identifying a submerged static human simulating drowning in open water and favorable environmental conditions. The ML algorithm and methodology should be further optimized, again tested and validated in a real-life clinical study.

Background Guidelines emphasize the clinician to consider the use of ultrasound to determine the cause of cardiac arrest. In this study we aimed to investigate how focused cardiac ultrasound (FOCUS) shortly after return of spontaneously circulation (ROSC) was associated with the use of further diagnostic measures and if the detection of pulmonary embolism, cardiac tamponade and acute myocardial infarction could be improved. Methods A retrospective, single-center, observational study at a tertiary hospital to evaluate FOCUS performed by cardiologists within 60 min after ROSC. Included were adult cardiac-arrest patients with ROSC, without restrictions in care. Excluded were patients with ECGs demonstrating ST elevation, patients with an obvious non-cardiac cause of cardiac arrest and patients where FOCUS was not performed. Results Between January 2012 and December 2017, FOCUS was performed in 237 (182 OHCA and 55 IHCA) patients. FOCUS findings influenced management and led to further immediate diagnostic measures in 52 (21.9%) patients. Left-ventricular regional wall motion abnormalities influenced the decision to perform emergency coronary angiography in 17 (7.2%) patients, of which nine were treated with PCI. Right-ventricular dilatation and/or pressure overload influenced a decision to perform computerized tomography of the thorax in 21 (8.9%) patients, of which 11 were diagnosed with pulmonary embolism. Cardiac tamponade was found in three patients (1.2%). Conclusion The retrospective data on this cardiac-arrest population supports that ALS-conformed post-resuscitation care could include FOCUS as an adjunctive diagnostic measure shortly after ROSC.