Automated External Defibrillators and Survival After Nonresidential Out of Hospital Cardiac Arrest in a Small North American City

Lwanga, Anita; Garcia‐Sayan, Enrique; Lwanga, Steven; Karreman, Erwin; Mohamed, Amira

doi:10.1016/j.amjcard.2017.03.023

Cited by 6 publications

(5 citation statements)

References 16 publications

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“…Risk factors for OHCA deaths include elderly and female patients [ 21 ], non-public locations [ 22 ], and no witnesses [ 19 , 20 ]. On the other hand, factors that can reduce death include bystander CPR [ 17 , 22 , 23 ], shockable rhythm [ 17 , 23 ], and prehospital AED use [ 24 , 25 ].…”

Section: Discussionmentioning

confidence: 99%

Effects of Prehospital Factors on Survival of Out-Of-Hospital Cardiac Arrest Patients: Age-Dependent Patterns

Rhee

Kim

Lee

2020

IJERPH

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Many prehospital factors that are known to influence survival rates after out-of-hospital cardiac arrest (OHCA) have been rarely studied as to how their influence varies depending on the age. In this study, we tried to find out what prehospital factors affect the survival rate after OHCA by age groups and how large the effect size of those factors is in each age group. We used the South Korean OHCA registry, which includes information on various prehospital factors relating OHCA and final survival status. The association between prehospital factors and survival was explored through logistic regression analyses for each age group. The effects of prehospital factors vary depending on the patient’s age. Being witnessed was relatively more influential in younger patients and the presence of first responders became more important as patients became older. While bystander cardiopulmonary resuscitation (CPR) did not appear to significantly affect survival in younger people, use of an automated external defibrillator (AED) showed the largest effect size on the survival in all age groups. Since the pathophysiology and etiologies of OHCA vary according to age, more detailed information on life support by age is needed for the development and application of more specialized protocols for each age.

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Section: Discussionmentioning

confidence: 99%

Effects of Prehospital Factors on Survival of Out-Of-Hospital Cardiac Arrest Patients: Age-Dependent Patterns

Rhee

Kim

Lee

2020

IJERPH

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“…In the planning stage of AED facilities, most will give priority to residential areas in the center of the city where the population is concentrated. AED facility planning usually gives priority to residential areas in urban centers with a high concentration of residents [2,9,10,26]. In terms of WORK_DEN, the density of companies was the determinant with the second or third highest explanatory power ranking after LIVE_DEN, explaining 78.9% and 62.9% of the variance of AED equity in Guangzhou and Shenzhen, respectively.…”

Section: Individual Effect Of Each Determinant On Aed Equitymentioning

confidence: 99%

“…Due to its importance to human well-being and health, the study on spatial location of AEDs has become a research hotspot in geography, urban planning, emergency medicine, and other specialties [21][22][23][24][25][26][27]. The relevant literature mainly focused on spatial distribution, accessibility, and spatial optimization layout.…”

Section: Introductionmentioning

confidence: 99%

Observed Equity and Driving Factors of Automated External Defibrillators: A Case Study Using WeChat Applet Data

Liao,

Gao,

Feng

et al. 2023

IJGI

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Out-of-hospital cardiac arrest (OHCA) causes a high mortality rate each year, which is a threat to human well-being and health. An automated external defibrillator (AED) is an effective device for heart attack-related diseases and is a panacea to save OHCA. Most relevant literature focuses on the spatial distribution, accessibility, and configuration optimization of AED devices, which all belong to the characteristics of the spatial distribution of AED devices. Still, there is a lack of discussion on related potential influencing factors. In addition, analysis of AED facilities involving multiple city comparisons is less considered. In this study, data on AED facilities in two major cities in China were obtained through the WeChat applet. Then, the AED equity at the city and block scales and its socioeconomic factors were analyzed using the Gini coefficient, Lorenz curve, and optimal parameters-based geo-graphical detector (OPGD) model. Results show that the number of AEDs in Shenzhen was about eight-times that of in Guangzhou. The distribution of AEDs in Shenzhen was more equitable with a global Gini of 0.347, higher than that in Guangzhou with a global Gini of 0.504. As for the determinants of AED equity, residential density was the most significant determinant in both Guangzhou and Shenzhen from the perspective of individual effects on AED equity. Differently, due to the aging population in Guangzhou, the proportion of the elderly in blocks was influential to local AED equity. The local economic development level was crucial to local AED equity in Shenzhen. The results of the interaction detector model illustrate that relatively equitable AED distributions were found in the high-density residential areas with a balance of employment and housing, high-aging residential areas, and high-mobility residential areas in Guangzhou. The area with a high level of local economic development, dense population, and large mobility was the area with a relatively equitable distribution of AEDs in Shenzhen. The results of this paper are conducive to understanding the equity of AEDs and its socio-economic determinants, providing scientific reference for the optimization and management of AEDs.

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“…For instance, many reports emphasize the crucial role of bystanders in out-of-hospital cardiac arrests. These bystanders perform cardiopulmonary resuscitation or use automated external defibrillators [5][6][7][8][9][10][11][12][13][14][15]. When it comes to disaster medicine, the first witness usually initiates the systems of pre-hospital emergency medical services (EMS).…”

Section: What Are Witness Sensors?mentioning

confidence: 99%

The Significance of Witness Sensors for Mass Casualty Incidents and Epidemic Outbreaks (Preprint)

Pan¹,

Lin²,

Lin³

et al. 2017

Preprint

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UNSTRUCTURED Due to the increasing number of natural and man-made disasters, mass casualty incidents occur more often than ever before. As a result, health care providers need to adapt in order to cope with the overwhelming patient surge. To ensure quality and safety in health care, accurate information in pandemic disease control, death reduction, and health quality promotion should be highlighted. However, obtaining precise information in real time is an enormous challenge to all researchers of the field. In this paper, innovative strategies are presented to develop a sound information network using the concept of “witness sensors.” To overcome the reliability and quality limitations of information obtained through social media, researchers must focus on developing solutions that secure the authenticity of social media messages, especially for matters related to health. To address this challenge, we introduce a novel concept based on the two elements of “witness” and “sensor.” Witness sensors can be key players designated to minimize limitations to quality of information and to distinguish fact from fiction during critical events. In order to enhance health communication practices and deliver valid information to end users, the education and management of witness sensors should be further investigated, especially for implementation during mass casualty incidents and epidemic outbreaks.

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Automated External Defibrillators and Survival After Nonresidential Out of Hospital Cardiac Arrest in a Small North American City

Cited by 6 publications

References 16 publications

Effects of Prehospital Factors on Survival of Out-Of-Hospital Cardiac Arrest Patients: Age-Dependent Patterns

Effects of Prehospital Factors on Survival of Out-Of-Hospital Cardiac Arrest Patients: Age-Dependent Patterns

Observed Equity and Driving Factors of Automated External Defibrillators: A Case Study Using WeChat Applet Data

The Significance of Witness Sensors for Mass Casualty Incidents and Epidemic Outbreaks (Preprint)

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