Characteristics and outcomes of out-of-hospital sudden cardiac arrest according to the time of occurrence

Accepted Manuscript Title: Characteristics and Outcomes of Out-of-Hospital Sudden Cardiac Arrest According to the Time of Occurrence Authors: Nicole Karam, Eloi Marijon, Florence Dumas, Lucile Offredo, Frankie Beganton, Wulfran Bougouin, Daniel Jost, Lionel Lamhaut, Jean-Philippe Empana, Alain Cariou, Christian Spaulding, Xavier Jouven PII: DOI: Reference:

S0300-9572(17)30177-6 http://dx.doi.org/doi:10.1016/j.resuscitation.2017.04.024 RESUS 7158

To appear in:

Resuscitation

Received date: Revised date: Accepted date:

21-1-2017 31-3-2017 23-4-2017

Please cite this article as: Karam Nicole, Marijon Eloi, Dumas Florence, Offredo Lucile, Beganton Frankie, Bougouin Wulfran, Jost Daniel, Lamhaut Lionel, Empana Jean-Philippe, Cariou Alain, Spaulding Christian, Jouven Xavier.Characteristics and Outcomes of Out-of-Hospital Sudden Cardiac Arrest According to the Time of Occurrence.Resuscitation http://dx.doi.org/10.1016/j.resuscitation.2017.04.024 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Characteristics and Outcomes of Out-of-Hospital Sudden Cardiac Arrest According to the Time of Occurrence Nicole Karam, MD, MPH1,2,3,4; Eloi Marijon, MD, PhD1,2,3,4; Florence Dumas, MD, PhD1,2,4,5; Lucile Offredo, MPH1,4; Frankie Beganton, MS1,4; Wulfran Bougouin, MD, MPH1,2,4; Daniel Jost, MD4,6; Lionel Lamhaut, MD1,4,7; Jean-Philippe Empana, MD, PhD2,4; Alain Cariou, MD, PhD1,2,4,8; Christian Spaulding, MD, PhD1,2,3,4; Xavier Jouven, MD, PhD1,2,3,4, for the Paris Sudden Death Expertise Center 1

Paris Cardiovascular Research Center, INSERM Unit 970, Paris, France

2

Université Paris Descartes, Sorbonne Paris Cité, Paris, France

3

Assistance Publique–Hôpitaux de Paris, Hôpital Européen Georges Pompidou, Cardiology department,

Paris, France 4

Sudden Death Expertise Center, Paris, France

5

Département des Urgences, Hôpital Cochin, Paris, France

6

Service Médical d’Urgence–Brigade de Sapeurs-Pompiers de Paris, France

7

Service d’Aide Médicale Urgente de Paris, Paris, France

8

Département de Réanimation Médicale, Hôpital Cochin, Paris, France

Corresponding author: Nicole Karam, MD, MPH European Georges Pompidou Hospital INSERM Unit 970, Team 4 Sudden Death Expertise Center 20-40 Rue Leblanc, 75908 Paris CEDEX 15, France Tel: 33 6 18 01 06 64 Fax: 33 1 56 09 26 64 E-mail: [email protected]

Abstract Purpose — The impact of time of occurrence has been extensively evaluated for in-hospital cardiac arrests but less for Out-of-Hospital Cardiac Arrests (OHCA). We assessed the impact of the time of occurrence on the characteristics and prognosis of OHCA. Methods — Using data from the Paris Sudden Cardiac Death Expertise Center prospective study that includes all OHCA in the Paris Area, we compared characteristics and outcomes of off-hours OHCA (nights and days off) to regular-hours OHCA between 2011 and 2014. Results — Among a total of 9,834 OHCA (70.0±17 years old, 62.1% males), off-hours OHCA accounted for 63.4%. Although bystanders were more often present (74.4 vs. 72.1%, P=0.01), rates of bystander CPR (46.7 vs. 50.6%, P=0.001) and AED use (1.0 vs. 1.9%, P=0.01) were lower during off-hours. While EMS arrival delays were similar, patients were less often in shockable rhythm (16.3 vs. 19.1%, P<0.0001), and return of spontaneous circulation was less frequent (27.5 vs. 31.1%, P<0.0001). There was no difference in rates of targeted temperature control (54.8 vs. 54.7%, P=0.75), coronary angiography (57.3 vs. 58.2%, P=0.68) and angioplasty use (32.2 vs. 35.6%, P=0.22). Survival at hospital discharge was lower (4.7 vs. 6.5%, P<0.0001) during off-hours. After adjusting for potential confounders, time of occurrence was not associated with worse outcome (OR 0.85, 95% CI 0.69-1.06, P=0.15), and bystanderinitiated CPR, shockable initial rhythm and AED use were the main survival predictors (P<0.0001). Conclusion — Off-hours OHCA have a 30% lower survival rate, mainly due to differences in initial management (bystander CPR and AED use), illustrating the need to improve bystanders' responsiveness in all circumstances. Keywords: Resuscitation; Sudden Death; Survival; Education; Community

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Introduction Sudden cardiac arrest is a major public health issue with approximately 400,000 cases per year in the United States and 300,000 cases in Europe, accounting for almost half of cardiovascular mortality.1,2,3 Survival remains extremely poor (less than 10%) and relatively stable over time, despite decades of research and major financial investments in resuscitation.4 The impact of time of occurrence has been extensively evaluated for cardiac arrests occurring in hospital: off-hours were independently associated with a lower survival rate.5,6 There is limited data published on the impact of time of occurrence on Out-of-Hospital Cardiac Arrest (OHCA).6,7,8,9 Studies suggested that differences in Emergency Medical Systems (EMS) and/or in-hospital management (including the use of coronary angiography and targeted temperature control) might explain a potential difference in off-hours OHCA survival. However, none of these studies provided data on in-hospital management to definitely conclude on this matter. A better understanding of the relationship between time of occurrence and survival after OHCA, especially the identification of the most influencing factors, would give the opportunity to improve OHCA prognosis, by highlighting the main gaps on which future efforts should be targeted. Using data from a large prospective study in the Paris area, we assessed the differences in OHCA characteristics, pre and in-hospital management, and outcomes according to their time of occurrence.

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Methods Study Setting The Sudden Death Expertise Center (SDEC) study was initiated in May 15, 2011.10 It includes all OHCA occurring in Paris and its suburbs, which accounts for a residential population of approximately 6.6 million (10% of the overall French population) and a total area of 762 km2 (294 square miles). In the Paris area, the EMS is a two-tiered response system: a Basic Life Support tier served by firefighters of the Brigade de Sapeurs Pompiers de Paris, who can apply Automated External Defibrillation (AED), and an advanced cardiac life support tier served by ambulance teams with an emergency physician, a nurse, and/or a paramedic (Service d’Aide Médicale Urgente).11 To ensure completeness of collection, the SDEC data is derived from intensive and prospective epidemiologic case-finding, combining “passive and active” attitudes. First, for every cardiac arrest assessed by EMS, two nominative report forms are sent by the two EMS tiers (source 1). Second, an electronic query algorithm is performed in the advanced cardiac life support computer system to identify every case of SCD (source 2). Finally, regular controls based on diagnostic codes are conducted in selected intensive care units (control). Thus, the method of collection involved every link of the chain of survival, to ensure completeness of the registry. With this meticulous data collection and verification, the exhaustiveness of the database is 98.6 %. We report the 3-year data, up toMay 2014. This prospective study was conducted according to the Declaration of Helsinki, with the approval of the Committee for the Protection of Human Subjects in Biomedical Research (CCPPRB) and the French data protection committee (Commission Nationale Informatique et Liberté, CNIL). All OHCA for whom the EMS were called were included in the study, after confirmation of the cardiac arrest by the EMS personal and systematic exclusion of cases with obvious extra-cardiac causes.12,13 Follow up was then performed until death or final hospital discharge. In 9,695 (98.6%) OHCA cases, a complete follow-up was eventually obtained. Exclusion criteria were age less than 18

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years, OHCA occurring outside the Paris Area, prior terminal condition (such as metastatic malignancy), or an obvious non-cardiac cause according to Utstein templates (trauma, drowning, respiratory, etc.).12,13 Recorded Variables Data were collected according to Utstein recommandations.14 Collected data included general information regarding demographic characteristics and location of the OHCA (street address, home, or public place), and pre-hospital care data such as bystander presence, bystander-initiated CPR or AED use before EMS arrival, presence of shockable rhythm at EMS arrival, and survival at hospital admission. For hospitalized patients, data on medical management, including the use of Extra-Corporeal Membrane Oxygenation (ECMO), targeted temperature control, coronary angiography and angioplasty, were prospectively collected. Outcomes, including vital, as well as neurological status at hospital discharge, were collected. Neurological status was evaluated with a systematic functional evaluation according to the Cerebral Performance Categories score (a CPC score of 1 or 2 was considered as a favorable outcome).15 Two investigators (and a third in case of disagreement) systematically reviewed each record in order to guarantee data completion and validity. Time definitions OHCA were classified and compared according to their time of occurrence. Regular-hours included weekdays, except public holidays, from 8:00am to 6:00pm, which are the official working-hours of hospitals in France. Off-hours included two components: weekdays between 6:00pm and 8:00am, and offdays (weekends and public holidays), during which medical and paramedical teams in hospitals are reduced. Statistical analysis This report was prepared in compliance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist for observational studies.16 Data were described in the entire population, and according to the timing to OHCA: off-hours or regular-hours. Continuous variables were reported as means (standard deviations), and compared according to their time of occurrence using the

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student t test. Categorical variables were reported as numbers and proportions, and compared using the Chi-square test for categorical variables. Logistic regression models were used to estimate the odds ratios (OR) and their 95% confidence interval (95% CI) for the association between the time of OHCA occurrence and the odds of being alive at hospital discharge. The log linearity was tested for continuous variables, and variables for which log linearity was not proven were converted into categorical variables. A univariate analysis was first performed with all the descriptive variables, and the association between these variables and the survival rate was tested using the Wald test. Stratification was then performed on OHCA characteristics with adjustment for age and sex. Multivariate analysis was performed with adjustment for all the variables that were significant in the univariate analysis. A sensitivity analysis was finally performed by separating off-hours OHCA into nighttime OHCA and weekend/holidays OHCA. All tests were two-tailed, and P values of less than 0.05 were considered to indicate statistical significance. All data were analyzed at INSERM, Unit 970, Cardiovascular Epidemiology and Sudden Death, Paris, using R software, version 3.1.2.

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Results Characteristics and Pre-Hospital OHCA Management Over the study period, 9,834 OHCA (mean age 70.3±17 years, 62.1% males) were recorded. Of those, 6,239 OHCA (63.4%) occurred during off-hours (Figure 1). Baseline characteristics of OHCA, according to the time of occurrence, are described in Table 1. Off-hours OHCA occurred more frequently at home (84.5% vs. 73.8%, P<0.0001); bystanders were more often present (74.4% vs. 72.1%, P=0.01), but were less likely to initiate CPR (48.4% vs. 52.1%, P=0.001), and to use AEDs prior to EMS arrival (1.6% vs. 2.9%, P=0.01), compared to regular hours OHCA. The rate of bystander CPR (47.0% vs. 59.3%, P=0.005), and AED use (0.6% vs. 6.1%, P=0.004) were particularly low in OHCA occurring at home compared to those occurring in public areas. Time delay between call to EMS and EMS arrival was similar in the two groups. The rate of shockable initial rhythm was lower during off-hours (16.3% vs. 19.1%, P<0.0001), return of spontaneous circulation (ROSC) was less frequently obtained (27.5% vs. 31.1%, P<0.0001), and survival to hospital admission was lower (21.0% vs. 24.5%, P<0.0001). In-Hospital OHCA Management and Survival to Hospital Discharge Among survivors to hospital admission, there were similar rates of ECMO, targeted temperature control, coronary angiography, and coronary angioplasty use during off-hours compared to regular-hours. At discharge, the survival rate was lower in the off-hours group (4.7% vs. 6.5%, P<0.0001). The neurological outcome among patients who were discharged alive was similar. In univariate analysis (Table 2), variables associated with a higher survival rate included public location (OR 6.33, 95% CI 5.28–7.59, P<0.0001), male sex (OR 1.88, 95% CI 1.54–2.31, P<0.0001), presence of bystanders (OR 7.97, 95% CI 5.40–12.37, P<0.0001), bystander-CPR (OR 13.01, 95% CI 8.78–20.27, P<0.0001), and AED use by bystander prior to EMS arrival (OR 47.65, 95% CI 26.32–87.25, P<0.0001), while advanced age (OR 0.96, 95% CI 0.95–0.96, P<0.0001) and off-hours OHCA (OR 0.71, 95% CI 0.60–0.85, P=0.0002) were associated with a lower survival rate.

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In order to identify the most influencing factors for survival, we performed an additional analysis with adjustment for age and sex and further stratification on OHCA characteristics (Figure 2). When bystanders were not available, the prognosis was extremely poor and did not statistically differ between off and regular-hours (OR 0.47, 95% CI 0.21–1.08, P=0.07). When bystanders were available, survival was lower during off-hours, unless they performed CPR (OR 0.89, 95% CI 0.71–1.13, P=0.33), or used AEDs (OR 0.74, 95% CI 0.28–1.95, P=0.55). In multivariate analysis (Table 3), after adjustment for time of occurrence, age, sex, shockable initial rhythm, bystander initiated CPR, and OHCA location, there was no survival rate difference between regular-hours and off-hours OHCA (OR 0.85, 95% CI 0.69–1.06, P=0.15). Shockable initial rhythm (OR 10.90, 95% CI 8.60–13.91, P<0.0001) and bystander-CPR (OR 5.22, 95% CI 3.38–8.46, P<0.0001) were the main predictors for survival. Sensitivity Analyses The survival rate was also lower compared to regular-hours OHCA in the subgroups of OHCA occurring during weekends and holidays (4.5% vs. 6.5%, P<0.0001) or nights (4.9% vs. 6.5%, P=0.008), with a similar call-to-EMS arrival delay and post-EMS arrival management in the three groups (Table 4). The only significant differences in characteristics and management between OHCA occurring during weekends and holidays (31.6% of OHCA) and regular-hours OHCA were the rate of OHCA occurrence at home, that was higher during weekends and holidays (83.7% vs. 73.8%, P<0.0001), and the rate of shockable initial rhythm that was lower (16.9% vs. 19.1%, P=0.029). The subgroup of OHCA occurring during nights, showed marked differences compared to regular-hours OHCA. Patients were younger, with a higher rate of male gender and bystanders' presence but with a lower rate of CPR and AED use before EMS arrival.

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Discussion In this study on 9,834 OHCA, off-hours OHCA accounted for two third of cases. We performed a comprehensive assessment of both pre and post EMS arrival, as well as in-hospital management of OHCA according to the time of occurrence. Pre- and in-hospital medical management were similar. In contrast, bystanders in the field were less likely to initiate CPR and use AED during off-hours, and survival rate at hospital discharge was 30% lower. Lower survival rates have been previously described in in-hospital cardiac arrests and ST elevation myocardial infarctions (STEMI) occurring during off-hours.5,6,17 For OHCA, previous studies have provided conflicting results.7,8,9,18 Lower survival rates were frequently noted and differences in inhospital management were suggested as a cause for this difference. However, data on in-hospital treatment was lacking. To the best of our knowledge, our study is the first to provide detailed information regarding in-hospital management. In-hospital management was similar regardless of the time of occurrence, and therefore cannot account for the worse survival rate in the off-hours group. Conversely, we noted major differences in bystanders’ response to OHCA according to the time of occurrence, with a lower rate of bystander CPR and AED use during off-hours, despite a more frequent bystander presence. The low rate of AED use might be explained by a lower availability during off-hours, partly because off-hours OHCA occur most often at home where AEDs are not available, but also because the majority of AEDs are deployed in schools and working areas that are usually closed during offhours.19 This issue has been previously reported in Copenhagen, Denmark, where a nearby AED was inaccessible in more than half of off-hours OHCA, even though it was located within walking distance of the OHCA20. Ahead of the unavailability of AEDs, the frequent occurrence of off-hours OHCA at home also leads to an infrequent AED use since bystanders are often family members, and known to be more likely reluctant to use AEDs.21,22,23,24 Family members' reluctance might also account for the low rate of CPR observed during offhours, especially at home.21,22,23,24 Furthermore, a difference in bystanders awareness has also been demonstrated between home and public locations, with home bystanders being less often trained in

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CPR.24 Most CPR training sessions are organized in high schools, universities, or working areas, and usually target young adults and the working population. Home bystanders are more likely to be very young children or elderly, two populations that are too often neglected in CPR trainings despite the evidence that children above 13 years of age can perform CPR with an efficacy similar to adults.25 A recent European initiative (Kids Save Lives) supported by the World Health Organization aims to implement CPR training for children above 12 years of age.26,27 Our findings emphasize the importance of extending CPR training programs to the elderly population in order to achieve a better survival rate for OHCA occurring those occurring during off-hours, especially at home. Our results illustrate the major impact of the early phase of OHCA management on outcomes; the association between time of occurrence and OHCA survival rate disappeared when bystanders performed CPR or used AEDs. Our data support recent observations demonstrating the importance of bystandersinitiated CPR and AED use.21,28,29,30 According to a recent national French study, major heterogeneities have been observed among districts in terms of survival after sports-related OHCA, and the rate of bystander-initiated CPR appeared to be the main reason behind those differences.31 Although this study is the first to provide information regarding both initial and post-EMS arrival management, including in-hospital data, we acknowledge several limitations. First, data on low-flow and no-flow delays were missing in a significant proportion of cases. However, in the subset of patients in whom the low-flow delay was available (1,842 patients), there was no significant difference between working and off-hours OHCA. Second, the available post-EMS management data only included ECMO, targeted temperature control, and coronary angiography, and other confounders may still persist. Finally, this study was conducted in Paris and its suburbs. The extent to which similar results could be obtained in countries with a different health care system needs further evaluations on a European32 or an international level. Conclusion In the Paris area, two thirds of OHCA occur during off-hours and their survival rate is 30% lower compared to OHCA occurring during regular-hours. This lower survival rate appears to be mainly related

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to bystanders' response to OHCA (CPR and AED use before EMS arrival), rather than to an EMS and inhospital management difference. Those findings highlight the need for more efforts in order to improve bystanders’ responsiveness in all settings, especially among family members, elderly and young children.

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Conflicts of interest: None

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27. Bohn A, Lukas RP, Breckwoldt J, Böttiger BW, Van Aken H. “Kids save lives”: why schoolchildren should train in cardiopulmonary resuscitation. Curr Opin Crit Care 2015;21(3):220–5. 28. Hasselqvist-Ax I, Riva G, Herlitz J, et al. Early Cardiopulmonary Resuscitation in Out-of-Hospital Cardiac Arrest. N Engl J Med 2015;372(24):2307–15. 29. Malta Hansen C, Kragholm K, Pearson DA, et al. Association of Bystander and First-Responder Intervention With Survival After Out-of-Hospital Cardiac Arrest in North Carolina, 2010-2013. JAMA 2015;314(3):255–64. 30. Nakahara S, Tomio J, Ichikawa M, et al. Association of Bystander Interventions With Neurologically Intact Survival Among Patients With Bystander-Witnessed Out-of-Hospital Cardiac Arrest in Japan. JAMA 2015;314(3):247–54. 31. Marijon E, Bougouin W, Celermajer DS, et al. Major regional disparities in outcomes after sudden cardiac arrest during sports. Eur Heart J 2013;34(47):3632–40. 32. Gräsner J-T, Lefering R, Koster RW, et al. EuReCa ONE-27 Nations, ONE Europe, ONE Registry: A prospective one month analysis of out-of-hospital cardiac arrest outcomes in 27 countries in Europe. Resuscitation 2016;105:188–95.

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Figure Legends: Figure 1: Study Flowchart between May 2011 and May 2014 Figure 2: Stratified Survival Analysis with Adjustment to Age and Sex. CPR indicates CardioPulmonary Resuscitation; AED, Automated External Defibrillator

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Figr-1

16

Figr-2

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Table 1: Characteristics and Outcomes of Patients According to the Time of OHCA Occurrence Regular-hours

Off-hours

N=3,595

N=6,239

N

P value

Characteristics Male gender, n (%)

9,817

2,184 (60.8)

3,908 (62.8)

0.059

Age, mean (SD)

9,789

70.9 (16.7)

69.9 (17.2)

0.005

Home location, n (%)

9,738

2,633 (73.8)

5,215 (84.5)

<0.001

Bystander presence, n (%)

9,365

2,478 (72.1)

4,412 (74.4)

0.015

1,152 (34.3)

2,198 (38.1)

1,253 (37.3)

2,061 (35.7)

1,622 (61.7)

2,729 (63.6)

48 (1.8)

45 (1.1)

10 (6)

Bystander management, n (%) Bystander / no CPR, 9,139 Bystander + CPR Bystander / no AED use

0.001

6,919 Bystander + AED use

0.012

EMS and In-Hospital Management Call-to-EMS arrival, mean (SD),min

9,406

10 (6)

Shockable initial rhythm, n (%)

8,910

628 (19.1)

ECMO, n (%)

9833

Hypothermia, n (%)

0.558

914 (16.3)*

<0.001

92 (2.6)

144 (2.3)

0.652

1,987

432 (54.1)

651 (54.8)

0.749

Coronary angiography, n (%)

2,053

482 (58.2)

702 (57.3)

0.683

Coronary angioplasty, n (%)

1,205

170 (35.6)

234 (32.2)

0.224

ROSC, n (%)

7,993

922 (31.1)

1,385 (27.5)

<0.001

Survival at hospital admission

9,834

881 (24.5)

1,309 (20.9)

<0.001

Survival at hospital discharge

9,695

230 (6.5)

291 (4.7)

<0.001

Survival with CPC 1 or 2

9,624

185 (5.3)

241 (3.9)

0.002

Outcomes, n (%)

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CPR indicates CardioPulmonary Resuscitation; AED, Automated External Defibrillator; EMS, Emergency Medical Service; ECMO, ExtraCorporeal Membrane Oxygenation; ROSC, Return of Spontaneous Circulation; and CPC, Cerebral Performance Category

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Table 2: Variables Associated with Improved Survival to Hospital Discharge (Univariate Analysis) N

OR (95%CI)

P Value

Global population Timing (ref: off-hours)

9,695

1.40 (1.17-1.67)

<0.001

Gender (ref: women)

9,679

1.88 (1.54-2.31)

<0.001

Age

9,652

0.96 (0.95-0.96)

<0.001

Location (ref: home)

9,609

6.33 (5.28-7.59)

<0.001

Bystander (ref: no bystander)

9,251

7.97 (5.40-12.37)

<0.001

1.00

<0.001

13.01 (8.78-20.27)

<0.001

3.85 (2.53-6.13)

<0.001

1.00

<0.001

47.65 (26.32-87.25)

<0.001

11.97 (8.10-18.59)

<0.001

Bystander and CPR (ref: no bystander) Bystander and CPR

9,031

Bystander without CPR AED use (ref: no bystander) Bystander and AED use

6,850

Bystander without AED use Shockable initial rhythm

8,815

21.71 (17.50-27.14)

<0.001

Call-to-EMS arrival delay (ref: <10 min)

9,282

0.83 (0.69-1.01)

0.061

Hypothermia (ref: no)

1,969

1.98 (1.60-2.46)

<0.001

Coronary angiography (ref: no)

2,031

4.53 (3.57-5.82)

<0.001

Coronary angioplasty (ref: no)

1,193

2.68 (2.07-3.45)

<0.001

Subgroup of patients alive at hospital admission

Ref indicates Reference, CPR, CardioPulmonary Resuscitation; AED, Automated External Defibrillator; and EMS, Emergency Medical Service

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Table 3: Variables Associated with Improved Survival to Hospital Discharge (Multivariate Analysis)

OR (95% CI)

P Value

Timing (ref: off-hours)

0.85 (0.69–1.06)

0.151

Age

0.97 (0.96–0.98)

<0.001

Gender (ref: women)

0.73 (0.57–0.94)

0.013

10.90 (8.60–13.91)

<0.001

Bystander and CPR

5.22 (3.38–8.46)

<0.001

Bystander without CPR

2.28 (1.44–3.77)

<0.001

2.45 (1.96–3.06)

<0.001

Shockable initial rhythm Bystander / CPR (ref: no bystander)

Location (ref: home)

CPR indicates CardioPulmonary Resuscitation

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Table 4: Characteristics and Outcomes of Patients According to the Time of OHCA Occurrence: subgroup analysis Regular-

Holidays and

hours

weekends

N

Nights

Characteristics N

9,834

3,595

3,108

3,131

Male gender, n (%)

9,817

2,184 (60.8)

1,902 (61.3)

2,006 (64.1)*

Age, mean (SD)

9,789

71.0 (16.7)

70.8 (17.1)

69.1 (17.2)*

Home location, n (%)

9,738

2,633 (73.8)

2,572 (83.7)*

2,643 (85.3)*

Bystander presence, n (%)

9,365

2478 (72.1)

2,184 (74.3)

2,228 (74.5)*

1,152 (34.3)

1,033 (36.1)

1,165 (40.0)*

Bystander + CPR

1,253 (37.3)

1,075 (37.5)

986 (33.9)*

Bystander / no AED use

1,622 (61.7)

1,371 (63.7)

1,358 (63.5) *

48 (1.8)

25 (1.2)

20 (0.9)*

Bystander management, n (%) Bystander / no CPR 9,139

6,919 Bystander + AED use EMS and In-Hospital management Call-to-EMS arrival, mean(SD), min

9,406

10 (6)

10 (6)

10 (6)

Shockable initial rhythm, n (%)

8,910

628 (19.1)

468 (16.9)*

446 (15.7)*

ECMO, n (%)

9833

92 (2.6)

64 (2.1)

80 (2.6)

Hypothermia, n (%)

1,987

432 (54.1)

321 (53.2)

330 (56.5)

Coronary angiography, n (%)

2,053

482 (58.2)

343 (55.3)

359 (59.3)

Coronary angioplasty, n (%)

1,205

170 (35.6)

111 (30.9)

123 (33.4)

ROSC

7,993

922 (31.1)

708 (28.2)*

677 (26.9)*

Survival at hospital admission

9,834

881 (24.5)

666 (21.4)*

643 (20.5)*

Outcomes, n (%)

22

Survival at hospital discharge

9,695

230 (6.5)

138 (4.5)*

153 (4.9)*

Survival with CPC 1 or 2

9,624

185 (5.3)

111 (3.6)*

130 (4.2)*

* P<0.05 CPR indicates CardioPulmonary Resuscitation; AED, Automated External Defibrillator; EMS, Emergency Medical Service; ECMO, ExtraCorporeal Membrane Oxygenation; ROSC, Return of Spontaneous Circulation; and CPC, Cerebral Performance Category

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