Implementation of an Off-Hospital Rural and Urban Public Access Defibrillator
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Abstract:
The occurrence of out-of-hospital cardiac arrest (OHCA) is a critical life-threatening event that often warrants initial defibrillation with a semi-automated external defibrillator (SAED). In INDIA, about 4280 deaths in 1Lakh are due to SCA. The optimization of allocating a limited number of SAEDs in various types of communities is challenging. Hence this paper presents the implementation of an off-hospital rural and urban public access defibrillators. This defibrillator is a semi-automated defibrillator, a medical device which analyse the patient’s electrocardiogram in order to establish whether he/she is suffering from ventricular fibrillation and if necessary, delivers an electric shock, or defibrillation, to help the heart re-establish an effective rhythm.Keywords:
Automated external defibrillator
Heart Rhythm
Automated external defibrillator
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The American Heart Association has included the use of automated external defibrillators (AEDs) for early defibrillation by first responders as a standard of care for in-hospital ventricular fibrillation (VF). However, there are as yet no reports on the in-hospital early defibrillation program in Japan. To make the program successful, an early defibrillation capability by all nurses is essential. Recent studies have indicated that hospital nurses can easily use AEDs, because AEDs preclude the need for extensive training on ECG recognition, and there is also no fear of delivering shocks to a patient. Therefore, the use of AEDs can facilitate the introduction of the in-hospital early defibrillation program. Here, we report the case of a 70-year-old hospitalized man who developed an episode of VF outside our critical care area. Using AED, a nurse delivered shock to revert the VF, and succeeded in restoring the patient's circulation before the arrival of a physician. The delay between recognition of the VF and the delivery of the first shock was under 2 minutes. The physician arrived in the ward 74 seconds after the delivery of the shock. This case highlights the importance of the ability of nurses to successfully use defibrillation to strengthen the in-hospital chain-of-survival. The use of AEDs may thus promote the in-hospital chain-of-survival.
Chain of survival
Automated external defibrillator
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The automated external defibrillator (AED) appears to be an effective device for the treatment of cardiac arrest in an environment remote from medical care, where contributing factors (stress of travel, reduced oxygen tension in flight, and disruption of circadian rhythms) may exacerbate underlying pathology.Reassuringly, its specificity was 100% in those conscious patients whose rhythm was not ventricular fibrillation (VF) and where the AED was being used as a monitoring device.Interestingly, another paper in the same issue of the journal (see Additional information), reports the experiences of security guards using the device in casinos.Presumably, enthusiasts would like to see AEDs in all public places in the future, enabling successful defibrillation to become routinely performed by the public.Perhaps a convenient location for AEDs would be alongside cash-point machines in the high street, which may also become a high-stress environment following a review of one's bank-balance!
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Automated external defibrillators (AEDs) as we now know them have had a rapid and interesting evolution. The first report of an “automatic cardiac resuscitator” was made by Diack et al. in 1979, who had developed the defibrillator, the Heart-Aid. A first clinical report on successful ambulance use was published in 1982. The design of this defibrillator was unusual for several reasons. First, it used a tongue electrode together with a chest electrode for defibrillation. Second, the tongue blade also contained a sensor for respiration, which prevented the defibrillator from delivering a shock as long as an air stream was detected over the tongue. Confidence in the algorithm to detect ventricular fibrillation (VF) by the ECG was not sufficient: a second independent sign of circulatory arrest was desired. Further automated analysis of the ECG and defibrillation in cardiac arrest was investigated first in defibrillators that were used by traditional responders such as Emergency Medical Technicians. Then, when safety and efficacy were confirmed, the use was extended to fire fighters who were already part of the Emergency Medical Services (EMS) and to police squads who had never been part of the EMS. It became clear that the future of automated defibrillation was with lay rescuers with limited training, without the ability to interpret ECGs. Ease of use was paramount.
Automated external defibrillator
First aid
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Background Mathematical optimization of automated external defibrillator (AED) placement may improve AED accessibility and out-of-hospital cardiac arrest (OHCA) outcomes compared with American Heart Association (AHA) and European Resuscitation Council (ERC) placement guidelines. We conducted an in silico trial (simulated prospective cohort study) comparing mathematically optimized placements with placements derived from current AHA and ERC guidelines, which recommend placement in locations where OHCAs are usually witnessed. Methods and Results We identified all public OHCAs of presumed cardiac cause from 2008 to 2016 in Copenhagen, Denmark. For the control, we computationally simulated placing 24/7-accessible AEDs at every unique, public, witnessed OHCA location at monthly intervals over the study period. The intervention consisted of an equal number of simulated AEDs placements, deployed monthly, at mathematically optimized locations, using a model that analyzed historical OHCAs before that month. For each approach, we calculated the number of OHCAs in the study period that occurred within a 100-m route distance based on Copenhagen's road network of an available AED after it was placed ("OHCA coverage"). Estimated impact on bystander defibrillation and 30-day survival was calculated by multivariate logistic regression. The control scenario involved 393 AEDs at historical, public, witnessed OHCA locations, covering 15.8% of the 653 public OHCAs from 2008 to 2016. The optimized locations provided significantly higher coverage (24.2%; P<0.001). Estimated bystander defibrillation and 30-day survival rates increased from 15.6% to 18.2% (P<0.05) and from 32.6% to 34.0% (P<0.05), respectively. As a baseline, the 1573 real AEDs in Copenhagen covered 14.4% of the OHCAs. Conclusions Mathematical optimization can significantly improve OHCA coverage and estimated clinical outcomes compared with a guidelines-based approach to AED placement.
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