Functionality of Registered Automated External Defibrillators

We aimed to assess the functionality of all registered AEDs in a geographically selected area and calculate the proportion of historical out-of-hospital cardiac arrests (OHCAs) covered by non-functioning AEDs.

Methods: In this cross-sectional study we inspected all registered and available AEDs on the island of Bornholm in Denmark. We collected information on battery status (determined by AED self-test) and electrode status, as well as AED availability. We identified all historical OHCAs registered with the Danish Cardiac Arrest Registry on Bornholm during 2016-2019 and calculated the proportion of OHCAs covered by an AED (regardless of functionality status) within ≤100, ≤750, and ≤1800 meters and the proportion of OHCAs covered by non-functioning AEDs.

Results: Of 211 registered AEDs, 181 (81.9%) were publicly accessible and functional. The remaining 40 (18.1%) were not functional, primarily due to expired electrodes (42.5%, n=17), obstacles to AED retrieval (20.0%, n=8) or failed self-tests (17.5%, n=7). Of 197 historical OHCAs, non-functional AEDs resulted in an OHCA coverage loss of 5.6%, 4.1% and 1.0 % for ≤100 m, ≤750 m and ≤1800 m, respectively.

ConclusionAlmost one-fifth of all registered and publicly available AEDs were not functional, primarily due to expired electrodes, failed self-tests or obstacles to retrieving AEDs. One in twenty historical OHCA was covered by a non-functional AED. Although general AED functionality was high, this finding underlines the importance of regular AED maintenance.

https://pubmed.ncbi.nlm.nih.gov/35618078/

Human drone interaction in delivery of medical supplies: A scoping review of experimental studies

This German based study aims to perform a systematic scoping review on experimental studies examining the human drone interaction in deliveries of defibrillators.

Methods: Two databases (MEDLINE and CINAHL) and references of identified publications were searched without narrowing the year of publication or language. Studies that investigated the human drone interaction or medical delivery with drones in an experimental manner were included (research articles). All studies that only simulated the delivery process were excluded. Results: The search revealed 83 publications with four studies being included. Three categories of human drone interaction were identified: landing, handover, and communications. Regarding landing and handover, the most important issue was the direct physical contact with the drone while regarding communications users need clearer instructions about drone´s direction, sound and look like.

Discussion: The identified studies used technology-driven approaches by investigating human drone interaction in already existing technologies. Users must become integral part of the whole development process of medical drone services to reduce concerns, and to improve security, usability and usefulness of the system. Human drone interaction should be developed according to the identified categories of human drone interaction by using demand- and technology-driven approaches

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9049298/

Bystander-initiated cardiopulmonary resuscitation and automated external defibrillator use after out-of-hospital cardiac arrest: Uncovering disparities in care and survival across the urban-rural spectrum

Aim: To evaluate the association between bystander cardiopulmonary resuscitation (CPR), automated external defibrillator (AED) use, and survival after out-of-hospital cardiac arrest (OHCA) across the urban-rural spectrum in Canada. This was a retrospective cohort study of 325,477 adult OHCAs within the Cardiac Arrest Registry to Enhance Survival from 2013-2019. Bystander interventions were categorized into no bystander intervention, bystander CPR alone, and bystander AED use (with or without CPR). The primary outcome was survival to hospital discharge with good neurological outcome.

Results: Bystander CPR alone occurred most often in rural areas (50.8%), and least often in urban areas (35.4%). Bystander AED use in public settings was similar across the urban-rural spectrum (10.5%-13.1%). Survival with good neurological outcome varied for urban (8.1%), suburban (7.7%), large rural (9.1%), small town (7.1%), and rural areas (6.1%). In comparison to no bystander intervention, the adjusted odds ratios (95% confidence intervals) for bystander AED use and survival were 2.57 (2.37-2.79) in urban areas, 2.58 (1.81-3.67) in suburban areas, 1.99 (1.44-2.76) in large rural areas, 1.90 (1.27-2.86) in small towns, and 3.05 (1.99-4.68) in rural areas. Bystander CPR alone was also associated with survival in all areas (adjusted odds ratio range: 1.29-1.45). There was no strong evidence of interaction between bystander interventions and geographical status on the primary outcome (p=0.63).

ConclusionBystander CPR and AED use are associated with positive clinical outcomes after OHCA in all areas along the urban-rural spectrum.

https://pubmed.ncbi.nlm.nih.gov/35469933/

Strategic placement of automated external defibrillators (AEDs) for cardiac arrests in public locations and private residences

The aim of our study was to determine whether businesses can be identified that rank highly for their potential to improve coverage of out-of-hospital cardiac arrests (OHCAs) by automated external defibrillators (AEDs), both in public locations and private residences. The cohort comprised 10,422 non-traumatic OHCAs from 2014 to 2020 in Perth, Western Australia. We ranked 115 business brands (across 5,006 facilities) for their potential to supplement coverage by the 3,068 registered public-access AEDs in Perth, while accounting for AED access hours.

Results: Registered public-access AEDs provided 100 m coverage of 23% of public-location arrests, and 4% of arrests in private residences. Of the 10 business brands ranked highest for increasing the coverage of public OHCAs, six brands were ranked in the top 10 for increased coverage of OHCAs in private residences. A public phone brand stood out clearly as the highest-ranked of all brands, with more than double the coverage-increase of the second-ranked brand. If all 115 business brands hosted AEDs with 24-7 access, 57% of OHCAs would remain without 100 m coverage for public arrests, and 92% without 100 m coverage for arrests in private residences.

Conclusion: Many businesses that ranked highly for increased coverage of arrests in public locations also rank well for increasing coverage of arrests in private residences. However, even if the business landscape was highly saturated with AEDs, large gaps in coverage of OHCAs would remain, highlighting the importance of considering other modes of AED delivery in metropolitan landscapes.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9065707/

Application of Automated External Defibrillators in Motorcycle Ambulances in Thailand’s Emergency Medical Services

Access time to emergency patients is a critical factor that affects the outcomes of life-or-death situations, especially in the cases of out-of-hospital cardiac arrests (OHCA). This study focused on developing a new model of emergency medical services (EMS) using a motorcycle-based ambulance (motorlance) with an automated external defibrillator (AED). There are currently no studies regarding access time for this vehicle. This study aimed at utilization of an AED in conjunction with motorlance and comparing the response time between a traditional ambulance and a motorlance. This was a prospective study from September 2021 to January 2022. Data were recorded employing a national standard of operations record form used for Thailand EMS departments nationwide.

Results: The 891 cases were divided into two groups which were motorlance and ambulance. The activation times for motorlance and ambulance were 0.44 minutes and 1.42 minutes, respectively (p < 0.001) and the response time in the motorlance group was 7.20 minutes compared with 9.25 minutes in the ambulance group. In OHCA, the motorlance with AED arrived at patients location and assisted to continue resuscitation at the hospital 88.9% of the time.

Conclusion: AED used in conjunction with motorcycle ambulances had shorter periods of both activation time and response time compared to ambulances. The use of AEDs clearly increases the number of continuous resuscitations in out-of-hospital cardiac arrest patients.

https://pubmed.ncbi.nlm.nih.gov/35437357/

A review of progress and an advanced method for shock advice algorithms in automated external defibrillators

Shock advice algorithm plays a vital role in the detection of sudden cardiac arrests on electrocardiogram signals and hence, brings about survival improvement by delivering prompt defibrillation. The last decade has witnessed a surge of research efforts in racing for efficient shock advice algorithms, in this context. On one hand, it has been reported that the classification performance of traditional threshold-based methods has not complied with the American Heart Association recommendations. On the other hand, the rise of machine learning and deep learning-based counterparts is paving the new ways for the development of intelligent shock advice algorithms.

In this paper, we firstly provide a comprehensive survey on the development of shock advice algorithms for rhythm analysis in automated external defibrillators. Shock advice algorithms are categorized into three groups based on the classification methods in which the detection performance is significantly improved by the use of machine learning and/or deep learning techniques instead of threshold-based approaches. Indeed, in threshold-based shock advice algorithms, a parameter is calculated as a threshold to distinguish shockable rhythms from non-shockable ones. In contrast, machine learning-based methods combine multiple parameters of conventional threshold-based approaches as a set of features to recognize sudden cardiac arrest.

Noticeably, those features are possibly extracted from stand-alone ECGs, alternative signals using various decomposition techniques, or fully augmented ECG segments. Moreover, these signals can be also used directly as the input channels of deep learning-based shock advice algorithm designs. Then, we propose an advanced shock advice algorithm using a support vector machine classifier and a feature set extracted from a fully augmented ECG segment with its shockable and non-shockable signals. The relatively high detection performance of the proposed shock advice algorithm implies a potential application for the automated external defibrillator in the practical clinic environment. Finally, we outline several interesting yet challenging research problems for further investigation.

https://pubmed.ncbi.nlm.nih.gov/35366906/