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Association between population density and reported incidence, characteristics and outcome after out-of-hospital cardiac arrest in Sweden
Resuscitation 82 (2011) 1307–1313
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Resuscitation journal homepage: www.elsevier.com/locate/resuscitation
Clinical paper
Association between population density and reported incidence, characteristics and outcome after out-of-hospital cardiac arrest in Sweden夽 A. Strömsöe a,b,∗ , L. Svensson c , A. Claesson d , J. Lindkvist b , A. Lundström e , J. Herlitz b,f a
School of Health and Social Sciences, University of Dalarna, 791 88 Falun, Sweden Institute of Internal Medicine, Department of Metabolism and Cardiovascular Research, Sahlgrenska University Hospital, 413 45 Göteborg, Sweden Stockholm Prehospital Centre, South Hospital, 118 83 Stockholm, Sweden d Kungälv Ambulance Service, 442 40 Kungälv, Sweden e Lerum Ambulance Service, 443 61 Stenkullen, Sweden f The Prehospital Research Centre, University College of Borås, 501 90 Borås, Sweden b c
a r t i c l e
i n f o
Article history: Received 8 July 2010 Received in revised form 18 April 2011 Accepted 26 April 2011
Keywords: Cardiac arrest Population density Survival Characteristics
a b s t r a c t Aim: To describe the reported incidence of out of hospital cardiac arrest (OHCA) and the characteristics and outcome after OHCA in relation to population density in Sweden. Methods: All patients participating in the Swedish Cardiac Arrest Register between 2008 and 2009 in (a) 20 of 21 regions (n = 6457) and in (b) 165 of 292 municipalities (n = 3522) in Sweden, took part in the survey. Results: The regional population density varied between 3 and 310 inhabitants per km2 in 2009. In 2008–2009, the number of reported cardiac arrests varied between 13 and 52 per 100,000 inhabitants and year. Survival to 1 month varied between 2% and 14% during the same period in different regions. With regard to population density, based on municipalities, bystander CPR (p = 0.04) as well as cardiac etiology (p = 0.002) were more frequent in less populated areas. Ambulance response time was longer in less populated areas (p < 0.0001). There was no significant association between population density and survival to 1 month after OHCA or incidence (adjusted for age and gender) of OHCA. Conclusion: There was no significant association between population density and survival to 1 month after OHCA or incidence (adjusted for age and gender) of OHCA. However, bystander CPR, cardiac etiology and longer response times were more frequent in less populated areas. © 2011 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Survival after out-of-hospital cardiac arrest (OHCA) is still low and the variation is vast.1–6 Information is available about incidence and survival after OHCA, based first and foremost on data from the USA and Europe. The incidence of Emergency Medical Services (EMS)-treated all-rhythm and ventricular fibrillation (VF) OHCA and survival to hospital discharge has been established.4,5 The mechanisms behind the variability in outcome after OHCA between counties and municipalities have not been adequately explained.
夽 A Spanish translated version of the summary of this article appears as Appendix in the final online version at doi:10.1016/j.resuscitation.2011.04.025. ∗ Corresponding author at: Institute of Medicine, Department of Metabolism and Cardiovascular Research, Sahlgrenska University Hospital, SE-413 45 Göteborg, Sweden. Tel.: +46 23 778000. E-mail address: [email protected] (A. Strömsöe). 0300-9572/$ – see front matter © 2011 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.resuscitation.2011.04.025
A number of factors might play a role including municipality factors, patient factors, factors at resuscitation, treatment factors and post resuscitation care factors.7–14 In terms of municipality factors, a number of aspects might be importance. They include the population distribution of age, sex and co morbidity, the preparedness of optimal handling of OHCA (knowledge of cardiopulmonary resuscitation (CPR) among lay people in the municipality, automated external defibrillator (AED) programs etc.) and finally the structure and skillfulness of the EMS in the municipality.15–20 Another important municipality aspect is the geographical structure and the population density. Data from the Swedish Cardiac Arrest Register (SCAR) which are reported annually to the Swedish Resuscitation Council indicate a variability in terms of reported incidence of OHCA and furthermore the characteristics and outcome among patients who suffer from OHCA. The geographical structure in Sweden differs markedly between regions and thereby also the population density. The influence of population density on the incidence of OHCA and the outcome after OHCA is not known.
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Fig. 1. Population density in Sweden in 2009.
Fig. 2. Number of treated OHCA in Sweden, 2008–2009.
The aim of this study was to address the following two questions:
both types of registrations. Only a few EMS systems participated from the start. During the time of this survey, it was estimated that 70% of patients with OHCAs in whom CPR was started were included in the register. Treated OHCA refers to patients with cardiac arrest that occurred out of hospital who were treated with CPR, defibrillation or/and drugs. Treatments such as drugs were only given by EMS personnel. The investigation took place in the time period from 1 January 2008 to 31 December 2009. Survival was reported as alive to 1 month.
(1) Is population density related to OHCA outcome (survival) and what are the covariates and how do they affect an eventual association? (2) Is population density related to OHCA occurrence (incidence) and what are the eventual covariates and how do they affect the incidence? 2. Methods 2.1. Study population Sweden is divided into three large areas Norrland (the north), Svealand (the centre) and Götaland (the south). Furthermore, there are 21 counties, including urban and rural areas, and of these 20 counties were included in this investigation. The one remaining county was not included as a result of no reporting to SCAR. The collected data related to persons with cardiac arrest independent of causes, and all the age groups with both genders were included. This study is based on all OHCAs treated by EMS crews or/and initiated bystander CPR and registered in the SCAR, which was introduced in 1990. The OHCA were documented in report forms which then were submitted by mail. From the end of 2007 registration via web was initiated. There are still EMS systems which report both as manual registration and web. In this study Figs. 1–4 were based on both manual- and web-registrations but not duplicated. The first part in Table 1 (counties) was based on both manual and webregistrations and the second part (municipalities) was only based on web registrations. Figs. 2 and 3 and Tables 2 and 3 are based on
2.2. Study design This study is a retrospective ecological observational study. The register includes information on age, gender, etiology, witnessed status, bystander CPR (according to the Utstein style, a person regardless of profession who starts CPR before the arrival of the EMS21 ), initial rhythm, delay between calling for the EMS and the arrival of the EMS, delay between calling for the EMS and first defibrillation and survival. 2.2.1. EMS structure and treatment The structure of the EMS system appears to differ between various countries. In Sweden the EMS organization and steering varies between counties and municipalities. The staffs on board the vehicles are mostly nurses and paramedics. Since 2005 there is a requirement from the National Board of Health and Welfare that there must be a nurse on board each EMS vehicle. In a few cities the EMS have physicians on board in order to give prescriptions and treatment and sometimes to decide whether a patient should be transported to hospital or not. Furthermore some EMS systems are
Table 1 Age, gender, cardiac etiology, place, witnessed status, bystander CPR, VF/VT, interval call-EMS arrival and alive at 1 month of the OHCA register data and data based on population area according inhabitant per km2 and age. The data is presented per county and in quartiles (municipality) in Sweden for time period 2008–2009. County
OHCA register data Cardiac etiology (%)
Place – at home (%)
Witnessed %
Bystander CPR (%)
VF/VT (%)
Interval call-EMS arrival Median (min)
Alive 1 month (%)
28 – 25 31 21 34 25 27 31 34 32 25 41 29 27 35 26 33 32
83 – 72 69 74 61 75 93 70 74 72 66 64 58 66 67 70 67 67
64 – 57 68 73 66 57 73 62 66 63 60 64 63 70 58 67 56 65
64 – 70 69 69 70 79 100 74 75 68 74 69 65 69 69 70 71 73
79 – 74 74 49 60 70 69 62 66 53 52 60 65 57 55 63 61 68
32 – 33 21 36 28 34 60 27 30 30 36 21 17 29 32 27 34 25
8 – 9 11 9 8 8 9 9 8 8 7 8 9 9 6 10 8 9
14 – 11 11 8 8 10 0 8 13 12 9 2 6 10 7 8 13 10
69
28
70
69
63
71
28
9
8
70
33
43
64
66
61
21
9
8
70 72 70 70 NS
29 30 31 30 NS
73 70 69 65 0.0015
60 68 63 66 NS
68 71 69 71 NS
73 67 67 64 0.038
30 27 30 27 NS
10 9 9 8 <.0001
11 10 9 10 NS
Age
Age
Gender
Inhabitant per km2
Average
Median (year)
Female (%)
3 3 5 10 11 15 16 18 21 22 32 33 40 40 44 49 52 54 66
43 43 41 43 43 43 43 43 44 42 41 42 41 40 42 42 43 42 41 39 41 39 39 39
69 – 69 71 69 72 70 77 72 73 70 69 72 72 70 67 73 70 71
112 310 0.2–12 12–26 27–73 74–4410
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Norrbotten Jämtland Västerbotten Dalarna Västernorrland Gävleborg Värmland Gotland Kalmar Kronoberg Jönköping Örebro Östergötland Uppsala Södermanland Västmanland Blekinge Halland Västra Götaland Gothenburg** Skåne Malmoe** Stockholm Stockholm** Municipality class A Municipality class B Municipality class C Municipality class D P-value*
Population area data
VF/VT = ventricular fibrillation/ventricular tachycardia. NS = non-significant. * P-value refers only to municipalities. ** Most populated cities in Sweden.
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Table 2 The counties are analyzed for reported incidence of out of cardiac arrest in relation to population density. The counties are divided into quartiles according to population density during period 2008–2009. Counties in class A (lowest quartile i.e. lowest population density) are reference counties. Reported incidence of out of hospital cardiac arrest in quartiles 2–4 (class B–D) is expressed as odds ratio (OR) and 95% confidence intervals (95% CI). Inhabitant per km2
Incidence
N County class A County class B County class C County class D P-value
3–15 16–32 33–50 52–310
Adjusted*
Unadjusted
2,386,606 2,861,575 6,572,401
OR (95% CI)
N
1.04 (0.92–1.17) 0.84 (0.75–0.95) 0.87 (0.79–0.95) 0.0002
OR (95%)
2,386,595 2,861,561 6,572,395
1.07 (0.94-1.21) 1.02 (0.86–1.20) 0.80 (0.70–0.92) 0.10
N = number. * Adjusted OR for age and gender.
Table 3 The counties are analyzed for outcome (survival to 1 month) in relation to population density. The counties are divided into quartiles according to population density during period 2008–2009. Counties in class A (lowest quartile i.e. lowest population density) are reference counties. Outcome (survival to 1 month) in quartiles 2–4(class B–D) is expressed as odds ratio (OR) and 95% confidence intervals (95% CI). Survival
County class A County class B County class C County class D P-value
Inhabitant per km2
Unadjusted
Adjusted*
Adjusted**
N
OR (95% CI)
N
OR (95% CI)
N
OR (95% CI)
3–15 16–32 33–50 52–310
1614 1957 4463
0.99 (0.72–1.37) 0.63 (0.46–0.87) 0.84 (0.66–1.09) 0.94
1475 1756 3893
0.93 (0.66–1.32) 0.67 (0.47–0.94) 0.99 (0.76–1.30) 0.84
1129 1400 2994
0.99 (0.60–1.65) 0.70 (0.44–1.11) 1.02 (0.71–1.48) 0.80
N = number. * Adjusted OR for age, gender, place, cardiac etiology and witnessed status. ** Adjusted OR for age, gender, cardiac etiology, place, witnessed status, bystander CPR, initial rhythm and EMS response time.
Fig. 3. Number of reported survivors of OHCA, 2008–2009.
Fig. 4. Proportion of survivors in Sweden, 2008–2009.
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steered by county councils whereas others are steered by private companies. During the study time there were 241 EMS systems which reported OHCA events to SCAR. The nurses administrate drugs (adrenaline and amiodarone) which are reported to SCAR and both nurses and paramedics defibrillate. In some cases the fire brigade or other first responders were first in place to give CPR and defibrillation with AED while waiting for EMS which is also reported to SCAR. 2.2.2. Epidemiology of OHCA in Sweden From 2008 to 2009 there were 6457 OHCA reported to SCAR. Survival to 1 month was 9%, 71% were witnessed (either by bystander or crew) and bystander CPR was initiated in 63% of cases. The EMS crew classified the cause of the OHCA. Witnessed status was established in the form of yes or no and also whether it was witnessed by a bystander or ambulance crew. The time of cardiac arrest was determined in witnessed cases. Ventricular fibrillation and ventricular tachycardia without a pulse were together defined as a shockable rhythm. Survival was determined from the national state administrative authority. All analyses were performed in a central database in Gothenburg. In 2009, all OHCA cases in Western Sweden (1.5 million inhabitants) a central region in Sweden – Dalarna (279,000 inhabitants) and Stockholm (2 million inhabitants) which were reported to SCAR, were cross checked against all OHCA documented in respective ambulance register in the same region to which all ambulance missions were reported. The proportion of OHCA cases not reported to SCAR was found to be 23%, 30% and 15% respectively. This cross checking covered about 45% of the study population. 2.3. Statistical methods Descriptive statistics and correlation analyses were used in this study. The variables were presented as percentages, mean and median. For comparison of dichotomous variables Wilcoxon score and Kruskal–Wallis test were used and Spearman’s rank statistics for continuous variables. In the evaluation of the association between population density and the reported incidence of OHCA respective outcome after OHCA logistic regression was used. When adjusting for initial rhythm, place and etiology patients were divided as follows: ventricular fibrillation versus no ventricular fibrillation (initial rhythm), home versus not at home (place) and cardiac versus non-cardiac (etiology). 3. Results 3.1. Population density and incidence of OHCA In Sweden, the total number of OHCA patients recorded in the register from 1 January 2008 to 31 December 2009 was 6457 based on manual and web registrations Furthermore treated OHCAs from period 1, 1 January 2008 to 31 December 2009 based on web registrations, consisted of 3522 cases. In Sweden, the regional density of the population varied from 3 to 310 inhabitants per km2 in 2009 (Fig. 1).22 In the time period 2008–2009, the regional incidence of all-rhythm OHCA varied from 13 to 52 per 100,000 inhabitants and year, based on data from 20 counties in Sweden (Fig. 1). 3.2. Characteristics (Table 1) 3.2.1. Counties The average age in the three largest cities in Sweden (Stockholm, Gothenburg and Malmoe) was lower than the average age in all
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counties (Stockholm excluded). The median age of cardiac arrest victims varied from 67 years to 77 years. Overall, one third was women. In one county (Östergötland), there was a marked increase in women, but otherwise differences between counties were small. The proportion of OHCA with a cardiac etiology varied from 43% to 93%. The proportion of OHCA that occurred at home varied from 56% to 73%. The proportion of witnessed OHCA varied from 63% to 100%. The county in which the proportion was 100% (Gotland) had a low reported incidence of OHCA per year. The proportion of witnessed cases which received bystander CPR varied between 49% and 79%. There was an increase in bystander CPR in low populated areas. The incidence of ventricular fibrillation/ventricular tachycardia varied between 17% and 60%. The median interval from dispatch of EMS until arrival of EMS varied between 6 min and 11 min. Survival to 1 month alive (all rhythm included) varied between 2% and 14%). 3.2.2. Municipalities There was no significant association between population density and age and gender. Bystander CPR (p = 0.04) and a cardiac etiology (p = 0.002) were more frequent in less populated areas. The interval between call for and arrival of EMS were longer in less populated areas (p < 0.0001). There was no significant association between population density and any other variable. 3.3. Association between population density and reported incidence of OHCA (Table 2) There was no linear association between population density and reported incidence of OHCA when adjusting for age and gender. However, the incidence of OHCA was lower in the quartile with the highest population density as compared with the quartile with the lowest population density. In non-adjusted analyses, the reported incidence of OHCA decreased with increasing population density. When dividing the various regions into quartiles according to population density the mean age (years) in the population successively decreased from 42.8 (1st), 42.4 (2nd), 41.2 (3rd) to 40.2 in the 4th quartile. 3.4. Association between population density and outcome after OHCA (Tables 1 and 3) There was no association between population density and outcome after OHCA. 4. Discussion The major finding in this survey was that there was no association between the population density and survival after OHCA regardless whether evaluated in a regional or municipality perspective. The numbers of inhabitants per km2 vary in different counties in Sweden. The northern part of Sweden is more sparsely populated than the southern part. There are several municipalities in each county in which population density differs. About 20–40% of all inhabitants are living in one municipality in a community. In Sweden, there are more populated, larger cities in the south than in the north which also might explain part of the difference in population density. Stockholm, the capital of Sweden, is located in the most populated county in Sweden. Cardiac etiology was associated with population density. Cardiac arrests caused by trauma and intoxication may be more common in more populated areas and this could explain the lower rate of cardiac etiology in these areas. There was no association between population density and the proportion of patients found in ventricular fibrillation. We had
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expected to find a lower proportion of patients found in ventricular fibrillation in more sparsely populated regions due to longer response times in these regions. This was not confirmed. However, there was an association between bystander CPR and population density. Jennings et al. found more bystander CPR in rural areas compared with urban ones.23 This was confirmed in our study based on municipality data. An increased incidence of ventricular fibrillation with a shorter EMS response time in more densely populated areas may be counteracted by a lower incidence of OHCA of a cardiac etiology in these areas. There was an association between population density and EMS response time. Previous studies have suggested a longer EMS response time in rural areas.23 However, urban areas which signify high population density versus rural areas which signify the opposite do not always imply the density of the population. In previous research, most studies indicate that mid-size cities have the best response times and survival rates.3,24–26 This is because response times are long in rural areas as well as in big cities (more than 1 million populations). This could not be clearly addressed in this article since in Sweden there is only 1 metropolitan area (Stockholm). The number of available ambulances per county might vary and this could be an important factor when it comes to ambulance response time. In Stockholm and Gothenburg, the two largest cities in Sweden, there are three ambulances per 100,000 inhabitants compared with a rural county Norrbotten, in the north, where there are 11 ambulances per 100,000 inhabitants. The use of geospatial time analysis of ambulance deployment has been reported to reduce the EMS response time.27 Furthermore, information about the dispatchers’ way of acting when confronted with a presumed OHCA is crucial. The patients and the bystanders are also of ultimate importance. Perhaps there are cultural differences in calling a dispatcher when an OHCA is suspected.4 There was no association between population density and survival to 1 month. Survival to 1 month has increased in Sweden in counties with both a low and a high population density during the last decade (unpublished data). Our hypothesis was that survival was associated with population density and that this is due in particular to a longer EMS response time in less populated areas. However, in rural areas, there may perhaps be other thresholds which signify the possibility of a successful resuscitation and other criteria for initiating bystander CPR might therefore exist.4,28 A previous study reported that a higher incidence of OHCA would result in lower survival when all cases regardless of rhythm, were assessed.4 Previous investigations have suggested that there is a high incidence of coronary occlusion among survivors of OHCA and that treatment with Percutaneous Coronary Intervention (PCI) might improve survival.29 Another study confirmed the importance of post-resuscitation care and the distance to an intervention hospital.30 The number of hospitals and their location should therefore be an important factor for survival after OHCA. In this study, we have not investigated these ideas. Furthermore, information about the number of EMS systems per county and the crews’ level of education is crucial. The etiology of OHCA was associated with population density and this could influence the association between age and survival. A previous study confirmed the variation in etiology in different age groups.31 Our result suggest a slightly lower mean age in more populated areas. Another investigation showed an increase in bystander CPR among OHCA cases with a higher socioeconomic status.12 Socioeconomic status might differ in relation to population density but this was not evaluated in our survey.
There are still some EMS systems which do not participate in SCAR. The participating EMS systems crews have directives, given by the steering committee – to follow when they document OHCAs. This is important as this investigation, like other studies, is based on the reported data.1,10 The classification has to be performed in the same way by all EMS systems crews. Previous studies have described different thresholds related to the delay from calling a dispatcher until treatment was initiated and this may explain various clinical ways of acting both by the EMS and by bystanders.4,32 There is no continuous check for disparities between the ambulance protocol and the SCAR. Since 2009, many OHCA cases are registered via the web, with the aim of making them more easily accessible and to avoid errors. 5. Implications Our findings suggest that there is a potential to increase survival particularly in areas with a higher population density. In these areas there should be a shorter distance for the EMS to reach the patient. Future education of lay persons in CPR might be particularly favorable in high populated areas since here bystander CPR occurred less often. Due to longer EMS response times in less populated areas new defibrillation strategies should be tested (for example use of fire brigade) with the aim to shorten delay to defibrillation). To improve the research in OHCA in Sweden the register data regarding SCAR has to be cross checked against source data more continuously. Furthermore the thresholds for OHCA treatment in each county have to be investigated to find out if they differ. Moreover, the distance to post resuscitation hospitals should be evaluated. The use of early defibrillation programs using fire brigade more frequently is now being introduced in various parts of the country. 6. Limitations Due to incomplete reporting of OHCAs by EMS systems participating in SCAR and incomplete covering by SCAR there might be some bias. We estimate that the proportion of cases not being reported to SCAR is in the range of 20–30%. We do not know how these patients differ as compared with those being reported to SCAR. In the current situation there is a lack of assistance to get an identical reporting to SCAR in each county. 7. Conclusion There was no significant association between population density and survival to 1 month after OHCA or incidence (adjusted for age and gender) of OHCA. However, bystander CPR, cardiac etiology and longer response times were more frequent in less populated areas. Conflicts of interest No conflict of interest has been declared by the authors. Acknowledgement This study was supported by grants from the Laerdal Foundation for Acute Medicine and the Swedish Association of Local Authorities and Regions and the Swedish Heart and Lung Association.
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Clinical paper
Association between population density and reported incidence, characteristics and outcome after out-of-hospital cardiac arrest in Sweden夽 A. Strömsöe a,b,∗ , L. Svensson c , A. Claesson d , J. Lindkvist b , A. Lundström e , J. Herlitz b,f a
School of Health and Social Sciences, University of Dalarna, 791 88 Falun, Sweden Institute of Internal Medicine, Department of Metabolism and Cardiovascular Research, Sahlgrenska University Hospital, 413 45 Göteborg, Sweden Stockholm Prehospital Centre, South Hospital, 118 83 Stockholm, Sweden d Kungälv Ambulance Service, 442 40 Kungälv, Sweden e Lerum Ambulance Service, 443 61 Stenkullen, Sweden f The Prehospital Research Centre, University College of Borås, 501 90 Borås, Sweden b c
a r t i c l e
i n f o
Article history: Received 8 July 2010 Received in revised form 18 April 2011 Accepted 26 April 2011
Keywords: Cardiac arrest Population density Survival Characteristics
a b s t r a c t Aim: To describe the reported incidence of out of hospital cardiac arrest (OHCA) and the characteristics and outcome after OHCA in relation to population density in Sweden. Methods: All patients participating in the Swedish Cardiac Arrest Register between 2008 and 2009 in (a) 20 of 21 regions (n = 6457) and in (b) 165 of 292 municipalities (n = 3522) in Sweden, took part in the survey. Results: The regional population density varied between 3 and 310 inhabitants per km2 in 2009. In 2008–2009, the number of reported cardiac arrests varied between 13 and 52 per 100,000 inhabitants and year. Survival to 1 month varied between 2% and 14% during the same period in different regions. With regard to population density, based on municipalities, bystander CPR (p = 0.04) as well as cardiac etiology (p = 0.002) were more frequent in less populated areas. Ambulance response time was longer in less populated areas (p < 0.0001). There was no significant association between population density and survival to 1 month after OHCA or incidence (adjusted for age and gender) of OHCA. Conclusion: There was no significant association between population density and survival to 1 month after OHCA or incidence (adjusted for age and gender) of OHCA. However, bystander CPR, cardiac etiology and longer response times were more frequent in less populated areas. © 2011 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Survival after out-of-hospital cardiac arrest (OHCA) is still low and the variation is vast.1–6 Information is available about incidence and survival after OHCA, based first and foremost on data from the USA and Europe. The incidence of Emergency Medical Services (EMS)-treated all-rhythm and ventricular fibrillation (VF) OHCA and survival to hospital discharge has been established.4,5 The mechanisms behind the variability in outcome after OHCA between counties and municipalities have not been adequately explained.
夽 A Spanish translated version of the summary of this article appears as Appendix in the final online version at doi:10.1016/j.resuscitation.2011.04.025. ∗ Corresponding author at: Institute of Medicine, Department of Metabolism and Cardiovascular Research, Sahlgrenska University Hospital, SE-413 45 Göteborg, Sweden. Tel.: +46 23 778000. E-mail address: [email protected] (A. Strömsöe). 0300-9572/$ – see front matter © 2011 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.resuscitation.2011.04.025
A number of factors might play a role including municipality factors, patient factors, factors at resuscitation, treatment factors and post resuscitation care factors.7–14 In terms of municipality factors, a number of aspects might be importance. They include the population distribution of age, sex and co morbidity, the preparedness of optimal handling of OHCA (knowledge of cardiopulmonary resuscitation (CPR) among lay people in the municipality, automated external defibrillator (AED) programs etc.) and finally the structure and skillfulness of the EMS in the municipality.15–20 Another important municipality aspect is the geographical structure and the population density. Data from the Swedish Cardiac Arrest Register (SCAR) which are reported annually to the Swedish Resuscitation Council indicate a variability in terms of reported incidence of OHCA and furthermore the characteristics and outcome among patients who suffer from OHCA. The geographical structure in Sweden differs markedly between regions and thereby also the population density. The influence of population density on the incidence of OHCA and the outcome after OHCA is not known.
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Fig. 1. Population density in Sweden in 2009.
Fig. 2. Number of treated OHCA in Sweden, 2008–2009.
The aim of this study was to address the following two questions:
both types of registrations. Only a few EMS systems participated from the start. During the time of this survey, it was estimated that 70% of patients with OHCAs in whom CPR was started were included in the register. Treated OHCA refers to patients with cardiac arrest that occurred out of hospital who were treated with CPR, defibrillation or/and drugs. Treatments such as drugs were only given by EMS personnel. The investigation took place in the time period from 1 January 2008 to 31 December 2009. Survival was reported as alive to 1 month.
(1) Is population density related to OHCA outcome (survival) and what are the covariates and how do they affect an eventual association? (2) Is population density related to OHCA occurrence (incidence) and what are the eventual covariates and how do they affect the incidence? 2. Methods 2.1. Study population Sweden is divided into three large areas Norrland (the north), Svealand (the centre) and Götaland (the south). Furthermore, there are 21 counties, including urban and rural areas, and of these 20 counties were included in this investigation. The one remaining county was not included as a result of no reporting to SCAR. The collected data related to persons with cardiac arrest independent of causes, and all the age groups with both genders were included. This study is based on all OHCAs treated by EMS crews or/and initiated bystander CPR and registered in the SCAR, which was introduced in 1990. The OHCA were documented in report forms which then were submitted by mail. From the end of 2007 registration via web was initiated. There are still EMS systems which report both as manual registration and web. In this study Figs. 1–4 were based on both manual- and web-registrations but not duplicated. The first part in Table 1 (counties) was based on both manual and webregistrations and the second part (municipalities) was only based on web registrations. Figs. 2 and 3 and Tables 2 and 3 are based on
2.2. Study design This study is a retrospective ecological observational study. The register includes information on age, gender, etiology, witnessed status, bystander CPR (according to the Utstein style, a person regardless of profession who starts CPR before the arrival of the EMS21 ), initial rhythm, delay between calling for the EMS and the arrival of the EMS, delay between calling for the EMS and first defibrillation and survival. 2.2.1. EMS structure and treatment The structure of the EMS system appears to differ between various countries. In Sweden the EMS organization and steering varies between counties and municipalities. The staffs on board the vehicles are mostly nurses and paramedics. Since 2005 there is a requirement from the National Board of Health and Welfare that there must be a nurse on board each EMS vehicle. In a few cities the EMS have physicians on board in order to give prescriptions and treatment and sometimes to decide whether a patient should be transported to hospital or not. Furthermore some EMS systems are
Table 1 Age, gender, cardiac etiology, place, witnessed status, bystander CPR, VF/VT, interval call-EMS arrival and alive at 1 month of the OHCA register data and data based on population area according inhabitant per km2 and age. The data is presented per county and in quartiles (municipality) in Sweden for time period 2008–2009. County
OHCA register data Cardiac etiology (%)
Place – at home (%)
Witnessed %
Bystander CPR (%)
VF/VT (%)
Interval call-EMS arrival Median (min)
Alive 1 month (%)
28 – 25 31 21 34 25 27 31 34 32 25 41 29 27 35 26 33 32
83 – 72 69 74 61 75 93 70 74 72 66 64 58 66 67 70 67 67
64 – 57 68 73 66 57 73 62 66 63 60 64 63 70 58 67 56 65
64 – 70 69 69 70 79 100 74 75 68 74 69 65 69 69 70 71 73
79 – 74 74 49 60 70 69 62 66 53 52 60 65 57 55 63 61 68
32 – 33 21 36 28 34 60 27 30 30 36 21 17 29 32 27 34 25
8 – 9 11 9 8 8 9 9 8 8 7 8 9 9 6 10 8 9
14 – 11 11 8 8 10 0 8 13 12 9 2 6 10 7 8 13 10
69
28
70
69
63
71
28
9
8
70
33
43
64
66
61
21
9
8
70 72 70 70 NS
29 30 31 30 NS
73 70 69 65 0.0015
60 68 63 66 NS
68 71 69 71 NS
73 67 67 64 0.038
30 27 30 27 NS
10 9 9 8 <.0001
11 10 9 10 NS
Age
Age
Gender
Inhabitant per km2
Average
Median (year)
Female (%)
3 3 5 10 11 15 16 18 21 22 32 33 40 40 44 49 52 54 66
43 43 41 43 43 43 43 43 44 42 41 42 41 40 42 42 43 42 41 39 41 39 39 39
69 – 69 71 69 72 70 77 72 73 70 69 72 72 70 67 73 70 71
112 310 0.2–12 12–26 27–73 74–4410
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Norrbotten Jämtland Västerbotten Dalarna Västernorrland Gävleborg Värmland Gotland Kalmar Kronoberg Jönköping Örebro Östergötland Uppsala Södermanland Västmanland Blekinge Halland Västra Götaland Gothenburg** Skåne Malmoe** Stockholm Stockholm** Municipality class A Municipality class B Municipality class C Municipality class D P-value*
Population area data
VF/VT = ventricular fibrillation/ventricular tachycardia. NS = non-significant. * P-value refers only to municipalities. ** Most populated cities in Sweden.
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Table 2 The counties are analyzed for reported incidence of out of cardiac arrest in relation to population density. The counties are divided into quartiles according to population density during period 2008–2009. Counties in class A (lowest quartile i.e. lowest population density) are reference counties. Reported incidence of out of hospital cardiac arrest in quartiles 2–4 (class B–D) is expressed as odds ratio (OR) and 95% confidence intervals (95% CI). Inhabitant per km2
Incidence
N County class A County class B County class C County class D P-value
3–15 16–32 33–50 52–310
Adjusted*
Unadjusted
2,386,606 2,861,575 6,572,401
OR (95% CI)
N
1.04 (0.92–1.17) 0.84 (0.75–0.95) 0.87 (0.79–0.95) 0.0002
OR (95%)
2,386,595 2,861,561 6,572,395
1.07 (0.94-1.21) 1.02 (0.86–1.20) 0.80 (0.70–0.92) 0.10
N = number. * Adjusted OR for age and gender.
Table 3 The counties are analyzed for outcome (survival to 1 month) in relation to population density. The counties are divided into quartiles according to population density during period 2008–2009. Counties in class A (lowest quartile i.e. lowest population density) are reference counties. Outcome (survival to 1 month) in quartiles 2–4(class B–D) is expressed as odds ratio (OR) and 95% confidence intervals (95% CI). Survival
County class A County class B County class C County class D P-value
Inhabitant per km2
Unadjusted
Adjusted*
Adjusted**
N
OR (95% CI)
N
OR (95% CI)
N
OR (95% CI)
3–15 16–32 33–50 52–310
1614 1957 4463
0.99 (0.72–1.37) 0.63 (0.46–0.87) 0.84 (0.66–1.09) 0.94
1475 1756 3893
0.93 (0.66–1.32) 0.67 (0.47–0.94) 0.99 (0.76–1.30) 0.84
1129 1400 2994
0.99 (0.60–1.65) 0.70 (0.44–1.11) 1.02 (0.71–1.48) 0.80
N = number. * Adjusted OR for age, gender, place, cardiac etiology and witnessed status. ** Adjusted OR for age, gender, cardiac etiology, place, witnessed status, bystander CPR, initial rhythm and EMS response time.
Fig. 3. Number of reported survivors of OHCA, 2008–2009.
Fig. 4. Proportion of survivors in Sweden, 2008–2009.
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steered by county councils whereas others are steered by private companies. During the study time there were 241 EMS systems which reported OHCA events to SCAR. The nurses administrate drugs (adrenaline and amiodarone) which are reported to SCAR and both nurses and paramedics defibrillate. In some cases the fire brigade or other first responders were first in place to give CPR and defibrillation with AED while waiting for EMS which is also reported to SCAR. 2.2.2. Epidemiology of OHCA in Sweden From 2008 to 2009 there were 6457 OHCA reported to SCAR. Survival to 1 month was 9%, 71% were witnessed (either by bystander or crew) and bystander CPR was initiated in 63% of cases. The EMS crew classified the cause of the OHCA. Witnessed status was established in the form of yes or no and also whether it was witnessed by a bystander or ambulance crew. The time of cardiac arrest was determined in witnessed cases. Ventricular fibrillation and ventricular tachycardia without a pulse were together defined as a shockable rhythm. Survival was determined from the national state administrative authority. All analyses were performed in a central database in Gothenburg. In 2009, all OHCA cases in Western Sweden (1.5 million inhabitants) a central region in Sweden – Dalarna (279,000 inhabitants) and Stockholm (2 million inhabitants) which were reported to SCAR, were cross checked against all OHCA documented in respective ambulance register in the same region to which all ambulance missions were reported. The proportion of OHCA cases not reported to SCAR was found to be 23%, 30% and 15% respectively. This cross checking covered about 45% of the study population. 2.3. Statistical methods Descriptive statistics and correlation analyses were used in this study. The variables were presented as percentages, mean and median. For comparison of dichotomous variables Wilcoxon score and Kruskal–Wallis test were used and Spearman’s rank statistics for continuous variables. In the evaluation of the association between population density and the reported incidence of OHCA respective outcome after OHCA logistic regression was used. When adjusting for initial rhythm, place and etiology patients were divided as follows: ventricular fibrillation versus no ventricular fibrillation (initial rhythm), home versus not at home (place) and cardiac versus non-cardiac (etiology). 3. Results 3.1. Population density and incidence of OHCA In Sweden, the total number of OHCA patients recorded in the register from 1 January 2008 to 31 December 2009 was 6457 based on manual and web registrations Furthermore treated OHCAs from period 1, 1 January 2008 to 31 December 2009 based on web registrations, consisted of 3522 cases. In Sweden, the regional density of the population varied from 3 to 310 inhabitants per km2 in 2009 (Fig. 1).22 In the time period 2008–2009, the regional incidence of all-rhythm OHCA varied from 13 to 52 per 100,000 inhabitants and year, based on data from 20 counties in Sweden (Fig. 1). 3.2. Characteristics (Table 1) 3.2.1. Counties The average age in the three largest cities in Sweden (Stockholm, Gothenburg and Malmoe) was lower than the average age in all
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counties (Stockholm excluded). The median age of cardiac arrest victims varied from 67 years to 77 years. Overall, one third was women. In one county (Östergötland), there was a marked increase in women, but otherwise differences between counties were small. The proportion of OHCA with a cardiac etiology varied from 43% to 93%. The proportion of OHCA that occurred at home varied from 56% to 73%. The proportion of witnessed OHCA varied from 63% to 100%. The county in which the proportion was 100% (Gotland) had a low reported incidence of OHCA per year. The proportion of witnessed cases which received bystander CPR varied between 49% and 79%. There was an increase in bystander CPR in low populated areas. The incidence of ventricular fibrillation/ventricular tachycardia varied between 17% and 60%. The median interval from dispatch of EMS until arrival of EMS varied between 6 min and 11 min. Survival to 1 month alive (all rhythm included) varied between 2% and 14%). 3.2.2. Municipalities There was no significant association between population density and age and gender. Bystander CPR (p = 0.04) and a cardiac etiology (p = 0.002) were more frequent in less populated areas. The interval between call for and arrival of EMS were longer in less populated areas (p < 0.0001). There was no significant association between population density and any other variable. 3.3. Association between population density and reported incidence of OHCA (Table 2) There was no linear association between population density and reported incidence of OHCA when adjusting for age and gender. However, the incidence of OHCA was lower in the quartile with the highest population density as compared with the quartile with the lowest population density. In non-adjusted analyses, the reported incidence of OHCA decreased with increasing population density. When dividing the various regions into quartiles according to population density the mean age (years) in the population successively decreased from 42.8 (1st), 42.4 (2nd), 41.2 (3rd) to 40.2 in the 4th quartile. 3.4. Association between population density and outcome after OHCA (Tables 1 and 3) There was no association between population density and outcome after OHCA. 4. Discussion The major finding in this survey was that there was no association between the population density and survival after OHCA regardless whether evaluated in a regional or municipality perspective. The numbers of inhabitants per km2 vary in different counties in Sweden. The northern part of Sweden is more sparsely populated than the southern part. There are several municipalities in each county in which population density differs. About 20–40% of all inhabitants are living in one municipality in a community. In Sweden, there are more populated, larger cities in the south than in the north which also might explain part of the difference in population density. Stockholm, the capital of Sweden, is located in the most populated county in Sweden. Cardiac etiology was associated with population density. Cardiac arrests caused by trauma and intoxication may be more common in more populated areas and this could explain the lower rate of cardiac etiology in these areas. There was no association between population density and the proportion of patients found in ventricular fibrillation. We had
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expected to find a lower proportion of patients found in ventricular fibrillation in more sparsely populated regions due to longer response times in these regions. This was not confirmed. However, there was an association between bystander CPR and population density. Jennings et al. found more bystander CPR in rural areas compared with urban ones.23 This was confirmed in our study based on municipality data. An increased incidence of ventricular fibrillation with a shorter EMS response time in more densely populated areas may be counteracted by a lower incidence of OHCA of a cardiac etiology in these areas. There was an association between population density and EMS response time. Previous studies have suggested a longer EMS response time in rural areas.23 However, urban areas which signify high population density versus rural areas which signify the opposite do not always imply the density of the population. In previous research, most studies indicate that mid-size cities have the best response times and survival rates.3,24–26 This is because response times are long in rural areas as well as in big cities (more than 1 million populations). This could not be clearly addressed in this article since in Sweden there is only 1 metropolitan area (Stockholm). The number of available ambulances per county might vary and this could be an important factor when it comes to ambulance response time. In Stockholm and Gothenburg, the two largest cities in Sweden, there are three ambulances per 100,000 inhabitants compared with a rural county Norrbotten, in the north, where there are 11 ambulances per 100,000 inhabitants. The use of geospatial time analysis of ambulance deployment has been reported to reduce the EMS response time.27 Furthermore, information about the dispatchers’ way of acting when confronted with a presumed OHCA is crucial. The patients and the bystanders are also of ultimate importance. Perhaps there are cultural differences in calling a dispatcher when an OHCA is suspected.4 There was no association between population density and survival to 1 month. Survival to 1 month has increased in Sweden in counties with both a low and a high population density during the last decade (unpublished data). Our hypothesis was that survival was associated with population density and that this is due in particular to a longer EMS response time in less populated areas. However, in rural areas, there may perhaps be other thresholds which signify the possibility of a successful resuscitation and other criteria for initiating bystander CPR might therefore exist.4,28 A previous study reported that a higher incidence of OHCA would result in lower survival when all cases regardless of rhythm, were assessed.4 Previous investigations have suggested that there is a high incidence of coronary occlusion among survivors of OHCA and that treatment with Percutaneous Coronary Intervention (PCI) might improve survival.29 Another study confirmed the importance of post-resuscitation care and the distance to an intervention hospital.30 The number of hospitals and their location should therefore be an important factor for survival after OHCA. In this study, we have not investigated these ideas. Furthermore, information about the number of EMS systems per county and the crews’ level of education is crucial. The etiology of OHCA was associated with population density and this could influence the association between age and survival. A previous study confirmed the variation in etiology in different age groups.31 Our result suggest a slightly lower mean age in more populated areas. Another investigation showed an increase in bystander CPR among OHCA cases with a higher socioeconomic status.12 Socioeconomic status might differ in relation to population density but this was not evaluated in our survey.
There are still some EMS systems which do not participate in SCAR. The participating EMS systems crews have directives, given by the steering committee – to follow when they document OHCAs. This is important as this investigation, like other studies, is based on the reported data.1,10 The classification has to be performed in the same way by all EMS systems crews. Previous studies have described different thresholds related to the delay from calling a dispatcher until treatment was initiated and this may explain various clinical ways of acting both by the EMS and by bystanders.4,32 There is no continuous check for disparities between the ambulance protocol and the SCAR. Since 2009, many OHCA cases are registered via the web, with the aim of making them more easily accessible and to avoid errors. 5. Implications Our findings suggest that there is a potential to increase survival particularly in areas with a higher population density. In these areas there should be a shorter distance for the EMS to reach the patient. Future education of lay persons in CPR might be particularly favorable in high populated areas since here bystander CPR occurred less often. Due to longer EMS response times in less populated areas new defibrillation strategies should be tested (for example use of fire brigade) with the aim to shorten delay to defibrillation). To improve the research in OHCA in Sweden the register data regarding SCAR has to be cross checked against source data more continuously. Furthermore the thresholds for OHCA treatment in each county have to be investigated to find out if they differ. Moreover, the distance to post resuscitation hospitals should be evaluated. The use of early defibrillation programs using fire brigade more frequently is now being introduced in various parts of the country. 6. Limitations Due to incomplete reporting of OHCAs by EMS systems participating in SCAR and incomplete covering by SCAR there might be some bias. We estimate that the proportion of cases not being reported to SCAR is in the range of 20–30%. We do not know how these patients differ as compared with those being reported to SCAR. In the current situation there is a lack of assistance to get an identical reporting to SCAR in each county. 7. Conclusion There was no significant association between population density and survival to 1 month after OHCA or incidence (adjusted for age and gender) of OHCA. However, bystander CPR, cardiac etiology and longer response times were more frequent in less populated areas. Conflicts of interest No conflict of interest has been declared by the authors. Acknowledgement This study was supported by grants from the Laerdal Foundation for Acute Medicine and the Swedish Association of Local Authorities and Regions and the Swedish Heart and Lung Association.
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