AED applied, not recommending defibrillation - A validation study of the new variable “AED” in the Danish Cardiac Arrest Registry

Background: to design and implement a new variable, in accordance with the Utstein style – namely the variable “AED” - considering the challenges of reporting cases in which the AED did not recommend an electrical shock after analyzing cardiac arrhythmias, for use in the Danish Cardiac Arrest Registry.Participants: Patients with out-of-hospital cardiac arrest for which resuscitation was attempted between 2016 and 2019, identified in the nationwide Danish Cardiac Arrest Registry. Their medical records were reviewed to establish a positive variable in “AED”.Methods: Data from the national Danish Cardiac Arrest Registry were used to identify core features of out-of-hospital cardiac arrests medical recording in Denmark and its possible improvement. Results: Among n= 1080 cases, summary statistics on core recording variables of interest were collected. We found statistically significant differences in the two cohorts of cardiac arrests where an AED was present on the scene and recorded in the Danish Cardiac Arrest Registry, regarding age, location, emeregency medical service response time, witnesses, bystander cardiopulmonary resuscitation, first monitored rhythm, direct current cardioversion shock delivered by the medical staff and survival outcomes such as return of spontaneous circulation at any time, status at arrival at hospital and 30-day survival. Conclusions: This validation study showed an improved completeness of registration of out-of-hospital cardiac arrests when implementing the new AED-variable, in accordance with the Utstein style. Thus, the new AED-variable is a valid and substantial resource for future epidemiological studies. However, a future effort to improve registration completeness along with continuous improvement of the Danish Cardiac Arrest Registry is needed.

Research on Edge Service Composition Method Based on BAS Algorithm

Edge services are transferred data processing, application running, and implementation of some functional services from cloud central server to network edge server to provide services. Combined edge service can effectively reduce task computation in the cloud, shorten transmission distance of processing data, quickly decompose task of service request, and select the optimal edge service combination to provide service for users. BAS is an efficient intelligent optimization algorithm, which can achieve efficient optimization and neither need to know the specific form of function nor need gradient information. This paper designs an edge service composition model based on edge computing and proposes a method about edge service composition by BAS optimization algorithm. Our proposed method has obvious advantages in service composition efficiency compared with service composition method based on PSO or WPA heuristic algorithm. Compared with cloud service composition method, our proposed method has advantages of shorter service response time, low cost, and high quality of user experience.

Fog Enabled Cloud Based Intelligent Resource Management Approach Using Improved Grey Wolf Optimization Strategy and Kernel Support Vector Machine

Resource management is a significant task of scheduling and allocating resources to applications to meet the required Quality of Service (QoS) limitations by the minimization of overhead with an effective resource utilization. This paper presents a Fog-enabled Cloud computing resource management model for smart homes by the Improved Grey Wolf Optimization Strategy. Besides, Kernel Support Vector Machine (KSVM) model is applied for series forecasting of time and also of processing load of a distributed server and determine the proper resources which should be allocated for the optimization of the service response time. The presented IGWO-KSVM model has been simulated under several aspects and the outcome exhibited the outstanding performance of the presented model.

The Effect of Implementing Mechanical Cardiopulmonary Resuscitation Devices on Out-of-Hospital Cardiac Arrest Patients in an Urban City of Taiwan

High-quality cardiopulmonary resuscitation (CPR) is a key element in out-of-hospital cardiac arrest (OHCA) resuscitation. Mechanical CPR devices have been developed to provide uninterrupted and high-quality CPR. Although human studies have shown controversial results in favor of mechanical CPR devices, their application in pre-hospital settings continues to increase. There remains scant data on the pre-hospital use of mechanical CPR devices in Asia. Therefore, we conducted a retrospective cohort study between September 2018 and August 2020 in an urban city of Taiwan to analyze the effects of mechanical CPR devices on the outcomes of OHCA; the primary outcome was attainment of return of spontaneous circulation (ROSC). Of 552 patients with OHCA, 279 received mechanical CPR and 273 received manual CPR, before being transferred to the hospital. After multivariate adjustment for the influencing factors, mechanical CPR was independently associated with achievement of any ROSC (OR = 1.871; 95%CI:1.195–2.930) and sustained (≥24 h) ROSC (OR = 2.353; 95%CI:1.427–3.879). Subgroup analyses demonstrated that mechanical CPR is beneficial in shorter emergency medical service response time (≤4 min), witnessed cardiac arrest, and non-shockable cardiac rhythm. These findings support the importance of early EMS activation and high-quality CPR in OHCA resuscitation.

Daytime admission is associated with higher 1-month survival for pediatric out-of-hospital cardiac arrest: Analysis of a nationwide multicenter observational study in Japan

Objective Hospital characteristics, such as hospital type and admission time, have been reported to be associated with survival in adult out-of-hospital cardiac arrest (OHCA) patients. However, findings regarding the effects of hospital types on pediatric OHCA patients have been limited. The aim of this study was to analyze the relationship between the hospital characteristics and the outcomes of pediatric OHCA patients. Methods This study was a retrospective secondary analysis of the Japanese Association for Acute Medicine-out-of-hospital cardiac arrest registry. The period of this study was from 1 June 2014 to 31 December 2015. We enrolled all pediatric patients (those 0–17 years of age) experiencing OHCA in this study. We enrolled all types of OHCA. The primary outcome of this study was 1-month survival after the onset of cardiac arrest. Results We analyzed 310 pediatric patients (those 0–17 years of age) with OHCA. In survivors, the rate of witnessed arrest and daytime admission was significantly higher than nonsurvivors (56% vs. 28%, p < 0.001: 49% vs. 31%; p = 0.03, respectively). The multiple logistic regression model showed that daytime admission was related to 1-month survival (odds ratio, OR: 95% confidence interval, CI, 3.64: 1.23–10.80) (p = 0.02). OHCA of presumed cardiac etiology and witnessed OHCA were associated with higher 1-month survival. (OR: 95% CI, 3.92: 1.23–12.47, and 6.25: 1.98–19.74, respectively). Further analyses based on the time of admission showed that there were no significant differences in the proportions of patients with witnessed arrest and who received bystander cardiopulmonary resuscitation and emergency medical service response time by admission time. Conclusion Pediatric OHCA patients who were admitted during the day had a higher 1-month survival rate after cardiac arrest than patients who were admitted at night.

PrEstoCloud

Fog computing extends multi-cloud computing by enabling services or application functions to be hosted close to their data sources. To take advantage of the capabilities of fog computing, serverless and the function-as-a-service (FaaS) software engineering paradigms allow for the flexible deployment of applications on multi-cloud, fog, and edge resources. This article reviews prominent fog computing frameworks and discusses some of the challenges and requirements of FaaS-enabled applications. Moreover, it proposes a novel framework able to dynamically manage multi-cloud, fog, and edge resources and to deploy data-intensive applications developed using the FaaS paradigm. The proposed framework leverages the FaaS paradigm in a way that improves the average service response time of data-intensive applications by a factor of three regardless of the underlying multi-cloud, fog, and edge resource infrastructure.

Improving bystander defibrillation in out-of-hospital cardiac arrests at home

Aims: Most out-of-hospital cardiac arrests occur at home with dismal bystander defibrillation rates. We investigated automated external defibrillator coverage of home arrests, and the proportion potentially reachable with an automated external defibrillator before emergency medical service arrival according to different bystander activation strategies. Methods and results: Cardiac arrests in homes (private/nursing/senior homes) in Copenhagen, Denmark (2008–2016) and registered automated external defibrillators (2007–2016), were identified. Automated external defibrillator coverage (distance from arrest to automated external defibrillator) and accessibility at the time of arrest were examined according to route distance to nearest automated external defibrillator and emergency medical service response time. The proportion of arrests reachable with an automated external defibrillator by bystander was calculated using two-way (from patient to automated external defibrillator and back) and one-way (from automated external defibrillator to patient) potential activation strategies. Of 1879 home arrests, automated external defibrillator coverage ≤100 m was low (6.3%) and a two-way bystander could potentially only retrieve an accessible automated external defibrillator before emergency medical service in 31.1% ( n=37) of cases. If a bystander only needed to travel one-way to bring an automated external defibrillator (≤100 m, ≤250 m and ≤500 m), 45.4% ( n=54/119), 37.1% ( n=196/529) and 29.8% ( n=350/1174) could potentially be reached before the emergency medical service based on current automated external defibrillator accessibility. Conclusions: Few home arrests were reachable with an automated external defibrillator before emergency medical service if bystanders needed to travel from patient to automated external defibrillator and back. However, nearly one-third of arrests ≤500 m of an automated external defibrillator could be reached before emergency medical service arrival if the bystander only needed to travel one-way from the automated external defibrillator to the patient.

Load Balancing in the Presence of Services in Named-Data Networking

Load balancing is a mechanism to distribute client requests among several service instances. It enables resource utilization, lowers response time, and increases user satisfaction. In Named-Data Networking (NDN) and NDN-like architectures, load balancing becomes crucial when dynamic services are present, where relying solely on forwarding strategies can overload certain service instances while others are underutilized especially with the limited benefit of on-path caching when it comes to services. To understand the challenges and opportunities of load balancing in NDN, we analyze conventional load balancing in IP networks, and three closely related fields in NDN: congestion control, forwarding strategies, and data center management. We identify three possible scenarios for load balancing in NDN: facade load balancer, controller for Interest queues, and router-based load balancing. These different solutions use different metrics to identify the load on replicas, have different compliance levels with NDN, and place the load balancing functionality in different network components. From our findings, we propose and implement a new lightweight router-based load balancing approach called the communicating vessels and experimentally show how it reduces service response time and senses server capabilities without probing.

Multi-Objective Service Placement Scheme Based on Fuzzy-AHP System for Distributed Cloud Computing

With the rapid increase in the development of the cloud data centers, it is expected that massive data will be generated, which will decrease service response time for the cloud data centers. To improve the service response time, distributed cloud computing has been designed and researched for placement and migration from mobile devices close to edge servers that have secure resource computing. However, most of the related studies did not provide sufficient service efficiency for multi-objective factors such as energy efficiency, resource efficiency, and performance improvement. In addition, most of the existing approaches did not consider various metrics. Thus, to maximize energy efficiency, maximize performance, and reduce costs, we consider multi-metric factors by combining decision methods, according to user requirements. In order to satisfy the user’s requirements based on service, we propose an efficient service placement system named fuzzy- analytical hierarchical process and then analyze the metric that enables the decision and selection of a machine in the distributed cloud environment. Lastly, using different placement schemes, we demonstrate the performance of the proposed scheme.