Skip to main content
×
Home
    • Aa
    • Aa

Do neighbourhoods in Vancouver and surrounding areas demonstrate different rates of bystander CPR and survival for out-of-hospital cardiac arrest?

  • David Barbic (a1), Brian Klinkenberg (a2), Brian Grunau (a1) and Jim Christenson (a1)
Abstract
Abstract Objective

No prior work exists examining the relation between the geographic distribution of out-of-hospital cardiac arrest (OHCA) in the city of Vancouver and surrounding areas that may exhibit a clustering of cases. The primary objective of this study was to describe the distribution of OHCA within the Vancouver Coastal Health region using a geographic information system (GIS) analysis and appropriate statistical analyses.

Methods

This study was a post-hoc GIS-based analysis of OHCA patients in the city of Vancouver and surrounding areas, using data collected by the Resuscitation Outcomes Consortium between September 2007 and December 2011. The kernel density techniques and regression tree analysis using binary recursive partitioning were used.

Results

We examined 1617 cases of OHCA with a mortality rate of 86.5% (95% CI 84.8-88.2). The mean age of OHCA cases was 66.6 years (95% CI 65.7-67.5), and 33.6% (95% CI 31.3-35.9) were female. The proportion with an initial shockable rhythm (VF or pulseless VT) was 22.2% (95% CI 20.2-24.2); 42.3% (95% CI 39.9-44.7) of all cases received bystander CPR, and 49.7% (95% CI 47.3-52.1) were transported to the hospital by paramedics. The rate of survival to hospital discharge with favourable neurological status (FNS) Cerebral Performance Category (CPC) 1 or 2 was 10.4% (8.9-11.9). Distance of transport to the hospital (less than 2.7 km) was a significant predictor of survival with FNS, but income did not predict survival with FNS. Areas with higher proportions of commuters by car demonstrated lower rates of survival with FNS.

Conclusion

This is the first GIS-based study to examine OHCA in a single large Canadian centre. Clustering of OHCA consistent with areas of high population density was observed. Distance of transport was a significant predictor of survival with FNS for patients with OHCA. This may have important implications for future emergency medical services deployment and dispatch decision-making, and public policy initiatives.

RÉSUMÉ Objectif

Aucune étude n’a porté jusqu’à maintenant sur la relation entre la répartition géographique des arrêts cardiaques extra-hospitaliers (ACEH) à Vancouver et dans les régions voisines, et de possibles concentrations de cas. L’étude avait pour objectif principal de décrire la répartition des ACEH au sein de la région sanitaire Vancouver Coastal, à l’aide d’une analyse fondée sur des systèmes d’information géographique (SIG) et d’analyses statistiques appropriées.

Méthode

Il s’agit d’une étude analytique, postérieure aux faits et fondée sur des SIG, de patients ayant subi un ACEH à Vancouver et dans les régions voisines; les données ont été recueillies par le Resuscitation Outcomes Consortium, entre septembre 2007 et décembre 2011. Les auteurs ont eu recours à des techniques de densité par noyau et à une analyse de régression arborescente à l’aide d’un compartimentage récursif binaire.

Résultats

Ont été recensés 1617 cas d’ACEH; le taux de mortalité s’élevait à 86,5 % (IC à 95 % : 84,8-88,2), l’âge moyen des patients était de 66,6 ans (IC à 95 % :65,7-67,5) et 33,6 % (IC à 95 % : 31,3-35,9) des personnes touchées étaient des femmes. Dans 22,2 % (IC à 95 % : 20,2-24,2) des cas, le rythme initial (fibrillation ventriculaire ou tachycardie ventriculaire sans pouls) se prêtait au traitement par décharge électrique; dans 42,3 % (IC à 95 % : 39,9-44,7) des cas, des manœuvres de réanimation ont été effectuées par des passants et dans 49,7 % (IC à 95 % : 47,3-52,1) des cas, il y a eu transport à l’hôpital par des ambulanciers paramédicaux. Le taux de survie avec un état neurologique satisfaisant ([ENS]; CPC [Cerebral Performance Category] : 1 ou 2) au moment du congé de l’hôpital atteignait 10,4 % (8,9-11,9). La distance de transport vers l’hôpital (moins de 2,7 km) s’est révélé un facteur prévisionnel important de survie avec un ENS, contrairement aux revenus. Enfin, dans les régions où la proportion de navetteurs utilisant une automobile était élevée, le taux de survie avec un ENS était plus faible qu’ailleurs.

Conclusions

Il s’agit de la première étude reposant sur des SIG et visant à examiner les cas d’ACEH survenus dans un seul centre urbain d’importance au Canada. Des concentrations d’ACEH ont été observées dans les régions densément peuplées. Par ailleurs, la distance de transport s’est révélée un facteur prévisionnel important de survie avec un ENS chez les patients ayant subi un ACEH. Les résultats de l’étude peuvent avoir une incidence importante sur la distribution future des services médicaux d’urgence et les prises de décision relatives à la répartition des ressources ainsi que sur des initiatives en matière de politique publique.

  • View HTML
    • Send article to Kindle

      To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle.

      Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

      Find out more about the Kindle Personal Document Service.

      Do neighbourhoods in Vancouver and surrounding areas demonstrate different rates of bystander CPR and survival for out-of-hospital cardiac arrest?
      Available formats
      ×
      Send article to Dropbox

      To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your Dropbox account. Find out more about sending content to Dropbox.

      Do neighbourhoods in Vancouver and surrounding areas demonstrate different rates of bystander CPR and survival for out-of-hospital cardiac arrest?
      Available formats
      ×
      Send article to Google Drive

      To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your Google Drive account. Find out more about sending content to Google Drive.

      Do neighbourhoods in Vancouver and surrounding areas demonstrate different rates of bystander CPR and survival for out-of-hospital cardiac arrest?
      Available formats
      ×
Copyright
Corresponding author
Correspondence to: Dr. David Barbic, Department of Emergency Medicine, University of British Columbia, 1081 Burrard Street, Vancouver, BC V6Y 1YZ; Email: David.barbic@ubc.ca
References
Hide All
1. NicholG, ThomasE, CallawayCW, et al. Regional variation in out-of-hospital cardiac arrest incidence and outcome. JAMA 2008;300(12):1423-1431.
2. LarsenMP, EisenbergMS, CumminsRO, et al. Predicting survival from out-of-hospital cardiac arrest: a graphic model. Ann Emerg Med 1993;22(11):1652-1658.
3. ValenzuelaTD, RoeDJ, CretinS, et al. Estimating effectiveness of cardiac arrest interventions: a logistic regression survival model. Circulation 1997;96(10):3308-3313.
4. DayaMR, SchmickerRH, ZiveDM, et al. Out-of-hospital cardiac arrest survival improving over time: results from the Resuscitation Outcomes Consortium (ROC). Resuscitation 2015;91:108-115.
5. FieldJM, HazinskiMF, SayreMR, et al. Part 1: executive summary: 2010 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care. Circulation 2010;122(18 Suppl 3):S640-S656.
6. SempleHM, CudnikMT, SayreM, et al. Identification of high-risk communities for unattended out-of-hospital cardiac arrests using GIS. J Community Health 2013;38(2):277-284.
7. YasunagaH, MiyataH, HoriguchiH, et al. Population density, call-response interval, and survival of out-of-hospital cardiac arrest. Int J Health Geogr BioMed Central 2011;10(1):26.
8. OngMEH, TanEH, YanX, et al. An observational study describing the geographic-time distribution of cardiac arrests in Singapore: what is the utility of geographic information systems for planning public access defibrillation? (PADS Phase I). Resuscitation 2008;76(3):388-396.
9. MorrisonLJ, NicholG, ReaTD, et al. Rationale, development and implementation of the Resuscitation Outcomes Consortium Epistry-Cardiac Arrest. Resuscitation 2008;78(2):161-169.
10. LernerEB, FairbanksRJ, ShahMN. Identification of out-of-hospital cardiac arrest clusters using a geographic information system. Acad Emerg Med 2005;12(1):81-84.
11. EdgrenE, HedstrandU, KelseyS, et al. Assessment of neurological prognosis in comatose survivors of cardiac arrest. BRCT I Study Group. Lancet 1994;343(8905):1055-1059.
12. WardenCR, DayaM, LeGradyLA. Using geographic information systems to evaluate cardiac arrest survival. Prehosp Emerg Care 2007;11(1):19-24.
13. OngMEH, WahW, HsuLY, et al. Geographic factors are associated with increased risk for out-of hospital cardiac arrests and provision of bystander cardio-pulmonary resuscitation in Singapore. Resuscitation 2014;85(9):1153-1160.
14. BeyerHL. Spatial Ecology. Geospatial Modelling Environment (Version 0.7.3.0) (Software); 2012. Available at: http://www.spatialecology.com/gme (accessed October 1, 2015).
15. R Core Team. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria; 2015. Available at: http://www.R-project.org/ (accessed October 1, 2015).
16. LyonRM, CobbeSM, BradleyJM, et al. Surviving out of hospital cardiac arrest at home: a postcode lottery? Emerg Med J 2004;21(5):619-624.
17. VaillancourtC, LuiA, De MaioVJ, et al. Socioeconomic status influences bystander CPR and survival rates for out-of-hospital cardiac arrest victims. Resuscitation 2008;79(3):417-423.
18. ReinierK, ThomasE, AndrusiekDL, et al. Socioeconomic status and incidence of sudden cardiac arrest. Can Med Assoc J 2011;183(15):1705-1712.
19. NasselAF, RootED, HaukoosJS, et al. Multiple cluster analysis for the identification of high-risk census tracts for out-of-hospital cardiac arrest (OHCA) in Denver, Colorado. Resuscitation 2014;85(12):1667-1673.
20. KajiAH, HanifAM, BossonN, et al. Predictors of neurologic outcome in patients resuscitated from out-of-hospital cardiac arrest using classification and regression tree analysis. Am J Cardiol 2014;114(7):1024-1028.
21. TherneauTM, AtkinsonEJ. An introduction to recursive partitioning using the RPART routines; 2014. Available at: https://cran.r-project.org/web/packages/rpart/vignettes/longintro.pdf (accessed October 1, 2015).
22. TherneauTM, AtkinsonB, RipleyB. RPART: recursive partitioning and regression trees. R package version 4.1-9; 2015. Available at: http://CRAN.R-project.org/package=rpart (accessed October 1, 2015).
23. RootED, GonzalesL, PersseDE, et al. A tale of two cities: the role of neighborhood socioeconomic status in spatial clustering of bystander CPR in Austin and Houston. Resuscitation 2013;84(6):752-759.
24. CudnikMT, SchmickerRH, VaillancourtC, et al. A geospatial assessment of transport distance and survival to discharge in out of hospital cardiac arrest patients: implications for resuscitation centers. Resuscitation 2010;81(5):518-523.
25. SpaiteDW, StiellIG, BobrowBJ, et al. Effect of transport interval on out-of-hospital cardiac arrest survival in the OPALS study: implications for triaging patients to specialized cardiac arrest centers. Ann Emerg Med 2009;54(2):248-255.
26. SassonC, MagidDJ, ChanP, et al. Association of neighbourhood characteristics with bystander-initiated CPR. N Engl J Med 2012;367(17):1607-1615.
27. ShahAS, BhopalR, GaddS, et al. Out-of-hospital cardiac arrest in South Asian and white populations in London: database evaluation of characteristics and outcome. Heart 2010;96(1):27-29.
28. FosbolEL, DupreME, StraussB, et al. Association of neighbourhood characteristics with incidence of out-of-hospital cardiac arrest and rates of bystander-initiated CPR: implications for community-based education intervention. Resuscitation 2014;85(11):1512-1517.
29. MoonS, BobrowBJ, VadeboncoeurTF, et al. Disparities in bystander CPR provision and survival from out-of-hospital cardiac arrest according to neighbourhood ethnicity. Am J Emerg Med 2014;32(9):1041-1045.
30. FlintE, CumminsS. Active commuting and obestiy in mid-life: cross-sectional, observational evidence from UK Biobank. Lancet Diabetes Endocrinol 2016;4(5):420-435.
31. FlintE, CumminsS, SackerA. Associations between active commuting, body fat, and body mass index: population based, cross sectional study in the United Kingdom. BMJ 2014;349:g4887, doi:10.1136/bmj.g4887.
32. BuickJE, AllanKS, RayJG, et al. Does location matter? A proposed methodology to evaluate neighbourhood effects on cardiac arrest survival and bystander CPR. Can J Emerg Med 2015;17(3):286-294.
33. RaunLH, JeffersonLS, PersseD, et al. Geospatial analysis for targeting out-of-hospital cardiac arrest intervention. Am J Prev Med 2013;45(2):137-142.
34. ChanTC, LiH, LebovicG, et al. Identifying locations for public access defibrillators using mathematical optimization. Circulation 2013;127(17):1801-1809.
35. GrunauB, ReynoldsJC, ScheuermeyerFX, et al. Comparing the prognosis of those with initial shockable and non-shockable rhythms with increasing durations of CPR: informing minimum durations of resuscitation. Resuscitation 2016;101:50-56, doi:10.1016/j.resuscitation.2016.01.021.
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Canadian Journal of Emergency Medicine
  • ISSN: -
  • EISSN: 1481-8035
  • URL: /core/journals/canadian-journal-of-emergency-medicine
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×

Keywords:

Type Description Title
UNKNOWN
Supplementary Materials

Barbic supplementary material
Barbic supplementary material 5

 Unknown (28 KB)
28 KB
UNKNOWN
Supplementary Materials

Barbic supplementary material
Barbic supplementary material 4

 Unknown (42 KB)
42 KB
UNKNOWN
Supplementary Materials

Barbic supplementary material
Barbic supplementary material 3

 Unknown (39 KB)
39 KB
UNKNOWN
Supplementary Materials

Barbic supplementary material
Barbic supplementary material 6

 Unknown (43 KB)
43 KB
UNKNOWN
Supplementary Materials

Barbic supplementary material
Barbic supplementary material 1

 Unknown (45 KB)
45 KB
UNKNOWN
Supplementary Materials

Barbic supplementary material
Barbic supplementary material 7

 Unknown (39 KB)
39 KB
UNKNOWN
Supplementary Materials

Barbic supplementary material
Barbic supplementary material 2

 Unknown (40 KB)
40 KB

Metrics

Altmetric attention score

Full text views

Total number of HTML views: 6
Total number of PDF views: 39 *
Loading metrics...

Abstract views

Total abstract views: 566 *
Loading metrics...

* Views captured on Cambridge Core between 17th October 2016 - 24th October 2017. This data will be updated every 24 hours.