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• W2079457527 abstract "HomeCirculationVol. 130, No. 21Initiatives for Improving Out-of-Hospital Cardiac Arrest Outcomes Free AccessEditorialPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessEditorialPDF/EPUBInitiatives for Improving Out-of-Hospital Cardiac Arrest Outcomes Robert J. Myerburg, MD Robert J. MyerburgRobert J. Myerburg From the Division of Cardiology, University of Miami Miller School of Medicine, Miami, FL. Search for more papers by this author Originally published1 Oct 2014https://doi.org/10.1161/CIRCULATIONAHA.114.013047Circulation. 2014;130:1840–1843Other version(s) of this articleYou are viewing the most recent version of this article. Previous versions: November 18, 2014: Previous Version 1 Out-of-hospital cardiac arrest (OHCA) leading to sudden cardiac death (SCD) remains a huge public health burden, accounting for >350 000 deaths in the United States each year1 and an equivalent number in Europe. The societal impact is evident from the fact that as many as 50% of all cardiac deaths are SCDs,1 with many of the affected individuals in their productive years. One cost estimate places the financial burden on society at $33 billion per year in the United States,2 including the cost of response systems, post–cardiac arrest hospitalizations, and long-term care of survivors. Long-term care includes rehabilitation, disability expenses, and medical costs specific to survivors such as implantable cardioverter-defibrillators.Article see p 1859Prediction, Prevention, and InterventionAttempts to address the OHCA/SCD challenge encompass 3 basic strategies: prediction, prevention, and intervention. Prediction remains a daunting challenge because 50% of SCDs are first cardiac events without specific forewarnings of unrecognized disease.1,3,4 Data on familial clustering of SCD as first cardiac events4 suggest the possibility of genetic profiling of individual risk. However, other than the rare inherited arrhythmia syndromes, identification of genetic SCD risk markers with a large effect size remains a hope for the future. The numerically large problem associated with the common cardiac disorders dominates the public health burden. Atherosclerosis risk scoring methods provide some profiling capability for this most common cause, but they are largely not specific for cardiac arrest itself and have limitations for individual risk prediction.3Prevention is equally challenging. It depends on unrealized strategies for developing individual risk prediction models having small denominators and proportionally large numerators, in addition to cost-effective preventive therapies that provide high levels of efficiency. The latter is defined as high absolute risk reduction in an identified population subset that encompasses a substantial proportion of the event burden.4–6 Only a small part of the prevention strategy is addressed by use of implantable cardioverter-defibrillators and other therapies in the identified high-risk subgroups such as the primary prevention of SCD in patients with low ejection fractions or heart failure and the rare inherited arrhythmogenic syndromes. However, the majority of OHCAs and SCDs occur among 3 lower-risk groups: the apparently normal general population, those with risk factors for atherosclerosis in the absence of recognized disease, and those with known disease that is profiled to be at low risk. Risk factor modification and treatment have had an impact on the expression of disease prevalence, but less so for SCD than other expressions of atherosclerosis.The third leg of this tripod, intervention, has provided benefits but requires additional attention to achieve better outcomes. The evolution of hospital- and community-based responses to cardiac arrest is a fascinating piece of medical history,7 but outcomes from responses to OHCA, measured as survival free of significant neurological deficits, remain disappointingly low. Overall survival is in the range of ≤10%, with some exceptions based on locations and response times. Private homes are the most common sites of OHCAs and have the worst outcomes; public locations have better outcomes, with airports, airliners, casinos, and a few other public locations among the best reported. The optimist in me believes that over time society will come forth with resources for research leading to greater progress in prediction and prevention, but while we wait, we need to seek new strategies that will improve intervention outcomes.Emerging Strategies in Community Response Designs: The Copenhagen InitiativeA great deal of effort has been expended in attempts to improve outcomes from responses to OHCA, with various levels of success. The 2 major areas of focus have included response times and intra-arrest and postarrest management strategies. In this issue of the Circulation, Hansen and coworkers8 report a network of voluntarily deployed automated external defibrillators (AEDs) in Copenhagen, Denmark, along with its methodology and observations of coverage of cardiac arrests in the city. The foundation for this program resides in a publically accessible grid system that permits geocoding of precise location coordinates for various public benefit purposes.9 The basis for this is a standardized European grid system. The specific feature of interest for this project was the development of an integrated, Internet-accessible, actively managed network providing information on locations of all registered AEDs in the community, analogous to initiatives such as crowd-sourcing strategies10 and other initiatives with similar goals.11–14 Features of the Copenhagen model include the capability to update the data on a continuous basis and the ability of both emergency medical services and lay responders to access the information online to identify the closest AED during a response. The result is coordination among victim location, first responder, AED location, and emergency medical services call center.With the network in place, it was feasible to collect data tracking and linking the locations of OHCAs and AEDs, with changes in patterns over time from 2007 through 2011, and to create a map of the distributions of OHCAs in the community from 1994 to 2011. The investigators defined the term accessible AEDs as those devices within 100 m of an event and analyzed for coverage of cardiac arrest on that basis. This is the recommended distance based on a reasonable estimate to achieve a 1½-minute AED-to-victim access time. They further separated their community into high-risk areas, defined as ≥1 cardiac arrests every 2 years in a 100-m area; low-risk areas based on fewer numbers of events; and those areas with no cardiac arrests for the duration of the observation. High-risk areas accounted for only 1% of the city area but contained 18% of the cardiac arrests. During the study period, AED coverage of cardiac arrest, as defined above, increased from 2.7% to 32.6% overall and from 5.7% to 51.3% in the high-risk areas. Although the match between AED deployment sites and high-risk areas was not optimal during this observation period, with only 55 cardiac arrests occurring within 100 m of an AED, the change in coverage over time in the high-risk areas and the ability to identify changes in risk patterns for specific areas over time suggest a methodology that offers an opportunity to continuously improve this pattern as the network matures.There are 2 major points of interest associated with the network development and the analysis of related data reported in this article. The most obvious is the practical concept of an active, coordinated, frequently updated system of information from which both lay responders and emergency medical personnel can draw while responding to emergency calls. This offers hope for improving coverage and reducing time to defibrillation as more data are collected and the system becomes more sophisticated. As an example, the most pessimistic outcomes data are derived from the facts that ≈80% of OHCAs occur in private homes and that survival rates in the United States are no better than 6%. Although this may relate in part to medical circumstances in that population subset, delays in activation and response times may also be important factors. The potential for benefit of a neighborhood-based (rather than home-based) AED deployment system was suggested on a hypothetical basis by Zipes in 200115 but never gained attention or testing because of feasibility questions, in addition to data suggesting that a home AED strategy was not effective.16 With the development of accessible, integrated, high-resolution mapping of locations of victims, AEDs, and lay responders, perhaps this is a notion worth revisiting, given the magnitude of the problem.From Copenhagen to ChicagoThe second point of interest, much broader in nature, is the potential for mapping historical locations of cardiac arrest and AED locations as part of a generalizable methodology for response planning in other communities of various sizes and the generation of other data of strategic value. By extrapolating from the design of the Copenhagen study, one can envision the development of registries of information on cardiac arrest, including its frequency and related distributions of response resources. This might provide unique response assistance in many different geographic patterns while providing a continuous source of information on the evolution of those response patterns that are most effective for increasing survival. For this to occur beyond the limits of a single moderate-sized city such as Copenhagen (population, ≈600 000; area, 97 km2 or 60 sq miles), methods and strategies suited to data collection and analysis for specific locations and circumstances will be necessary.In the United States, we are in desperate need of uniform access to OHCA data across a country that is heterogeneous in respect to local population numbers and densities, population origins, and basic geography. One of the major limitations in dealing with the geographic epidemiology of OHCA and SCD is the lack of uniform reporting systems for planning purposes. Geographic epidemiology of OHCA can be analyzed in terms of population density and geographic dispersion. Approximately one half of the US population is located within the 13% of all metropolitan statistical areas with populations of ≥1 million and ≈10% of the population is distributed in the 50% of metropolitan statistical areas with populations <250 000. There is a general relationship between population size and population density, with a tendency for areas of smaller populations to be distributed over larger geographic areas. For both extremely dense populations in major cities such as Chicago and New York and sparsely populated regions, the relationship between population density and population size affects response times. In fact, data from very densely populated areas that include vertical development such as high-rise living and working sites and from areas that are very sparsely populated demonstrate worse outcomes for survival, in part on the basis of an impaired ability to respond timely. If we can gain greater specific insight into the geographic distribution of cardiac arrests and design systems that are best suited to specific population density patterns, response times to sites of OHCA may improve.From Integrating AED Access to Integrating Hospital TransportAn additional potential benefit of a grid-based tracking and linking method is extension to strategies for transport from sites of OHCA to receiving hospitals. The standard principle of transport to the nearest facility appropriately equipped for handling cardiac arrest victims is being challenged by the concept of emergency medical services bypass on the basis of the notion that cardiac arrest victims with major post–cardiac arrest complications will have better outcomes in regional centers capable of advanced support. Although still debated, some recent data support this concept,17 but the questions of when and how to make the decision to bypass to a regional advance care facility remain. Admission to the nearest facility with subsequent transport to an advanced facility is one approach, but another might be to use geocoded grids, as suggested in the Figure, to integrate hospitals capable of various levels of care with on-site postarrest status of the victim.Download figureDownload PowerPointFigure. Targeted urgency scale. A 4-tiered model aligning immediate post–cardiac arrest status and level of required care is illustrated to reflect a priority-based hospital bypass system. The Copenhagen model provides a foundation for this additional level of coordination. Patients can be transported to the closest facility appropriate to the optimal or minimal care requirements. Color-coded symbols link level of patient urgency to recommended hospital resources on community grid maps. CCU indicates coronary care unit; ED, emergency department; ICU, intensive care unit; NICU, neurological intensive care unit; PCI, percutaneous coronary intervention; and ROSC, return of spontaneous circulation.The Copenhagen model provides a foundation for this additional level of coordination. With the addition of information on the capabilities and locations of local and regional hospitals on a Copenhagen-style grid, a mathematical integral of OHCA location, initial postarrest status, level of care required, distance, and transport time (even including instantaneous traffic conditions) could be generated. The 4-tiered model of postarrest status and level of care required (Figure) reflects such a priority-based bypass system. On the basis of the updating component of the Copenhagen model, this can include prospective measures of outcomes and subsequent remodeling when indicated.Geocoding for Data SourcingAddressing the problem of SCD in its broadest perspectives will require greater insights into numbers, regions, specific locations, circumstances, disease prevalence, population characteristics, and response systems than are currently available. The Copenhagen model provides a foundation for providing a database on OHCAs that can ultimately expand to include data for addressing these broader epidemiological issues. Uniform identification and logging of most, if not all, OHCA/SCDs is the first step in the creation of a comprehensive database that can lead to such analyses. In fact, the Copenhagen methodology became national in Denmark in 2010, suggesting the feasibility of developing national reporting systems. It would be naive to think that a method that appears to have been relatively easily developed in a small country could be developed as easily in United States. Nevertheless, there is great potential value to the accumulation of data on cardiac arrest on a nationwide basis. To achieve this, the first step is the identification of OHCAs in centrally accessible databases, allowing the user to evaluate local, regional, or national questions, patterns of events, and outcomes. Beyond that, however, is the even greater value of a national database on cardiac arrest, which might ultimately provide access to data on causes, outcomes, and even potentially genetic characterization of regional populations, given the heterogeneity of the US population. To achieve this, OHCA/SCD would have to be declared a reportable event. This differs from the voluntary Copenhagen program for AED tracking.ConclusionsThe Copenhagen report provides a description and analysis of a practical and important system for tracking cardiac arrests and improving lay responders’ access to AEDs. It also integrates emergency medical services calls with responders and AED locations. However, the components provide a foundation with potential to extend far beyond the initial intent and design. Extrapolation and development of the methodology for broader uses offer an opportunity for advances in the interventional approaches to OHCA and perhaps contribute new knowledge about SCD prediction and prevention.Source of FundingDr Myerburg is supported in part by the American Heart Association Chair in Cardiovascular Research at the University of Miami Miller School of Medicine.DisclosuresNone.FootnotesThe opinions expressed in this article are not necessarily those of the editors or of the American Heart Association.Correspondence to Robert J. Myerburg, MD, Division of Cardiology (D-39), University of Miami Miller School of Medicine, PO Box 016960, Miami, FL 33101. E-mail [email protected]References1. Fishman GI, Chugh SS, Dimarco JP, Albert CM, Anderson ME, Bonow RO, Buxton AE, Chen PS, Estes M, Jouven X, Kwong R, Lathrop DA, Mascette AM, Nerbonne JM, O’Rourke B, Page RL, Roden DM, Rosenbaum DS, Sotoodehnia N, Trayanova NA, Zheng ZJ. 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Accessed October 15, 2014.Google Scholar Previous Back to top Next FiguresReferencesRelatedDetailsCited By Paratz E, Semsarian C and La Gerche A (2020) Mind the gap: Knowledge deficits in evaluating young sudden cardiac death, Heart Rhythm, 10.1016/j.hrthm.2020.07.029, 17:12, (2208-2214), Online publication date: 1-Dec-2020. Cassina T, Clivio S, Putzu A, Villa M, Moccetti T, Fortuna D and Casso G (2020) Neurological outcome and modifiable events after out-of-hospital cardiac arrest in patients managed in a tertiary cardiac centre: A ten years register, Medicina Intensiva (English Edition), 10.1016/j.medine.2019.05.015, 44:7, (409-419), Online publication date: 1-Oct-2020. Cassina T, Clivio S, Putzu A, Villa M, Moccetti T, Fortuna D and Casso G (2020) Neurological outcome and modifiable events after out-of-hospital cardiac arrest in patients managed in a tertiary cardiac centre: A ten years register, Medicina Intensiva, 10.1016/j.medin.2019.05.006, 44:7, (409-419), Online publication date: 1-Oct-2020. 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Wellens H, Lindemans F, Houben R, Gorgels A, Volders P, ter Bekke R and Crijns H (2015) Improving survival after out-of-hospital cardiac arrest requires new tools, European Heart Journal, 10.1093/eurheartj/ehv485, 37:19, (1499-1503), Online publication date: 14-May-2016. November 18, 2014Vol 130, Issue 21 Advertisement Article InformationMetrics © 2014 American Heart Association, Inc.https://doi.org/10.1161/CIRCULATIONAHA.114.013047PMID: 25274001 Originally publishedOctober 1, 2014 Keywordsdeath, sudden, cardiacEditorialsemergency medical servicesatherosclerosisheart arrestPDF download Advertisement SubjectsArrhythmiasEpidemiologyTreatment" @default.
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