University of Southern Denmark

Socioeconomic differences in coronary procedures and survival after out-of-hospital cardiacarrestA nationwide Danish studyMøller, Sidsel; Wissenberg, Mads; Kragholm, Kristian; Folke, Fredrik; Hansen, CarolinaMalta; Ringgren, Kristian B.; Andersen, Julie; Barcella, Carlo; Lippert, Freddy; Køber, Lars;Gislason, Gunnar; Gerds, Thomas Alexander; Torp-Pedersen, Christian

Published in:Resuscitation

DOI:10.1016/j.resuscitation.2020.05.022

Publication date:2020

Document version:Accepted manuscript

Document license:CC BY-NC-ND

Citation for pulished version (APA):Møller, S., Wissenberg, M., Kragholm, K., Folke, F., Hansen, C. M., Ringgren, K. B., Andersen, J., Barcella, C.,Lippert, F., Køber, L., Gislason, G., Gerds, T. A., & Torp-Pedersen, C. (2020). Socioeconomic differences incoronary procedures and survival after out-of-hospital cardiac arrest: A nationwide Danish study. Resuscitation,153, 10-19. https://doi.org/10.1016/j.resuscitation.2020.05.022

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Socioeconomic differences in coronary procedures and survival afterout-of-hospital cardiac arrest: A nationwide Danish study

Sidsel Møller MD Mads Wissenberg Kristian Kragholm Fredrik FolkeCarolina Malta Hansen Kristian B. Ringgren Julie Andersen CarloBarcella Freddy Lippert Lars Køber Gunnar Gislason ThomasAlexander Gerds Christian Torp-Pedersen

PII: S0300-9572(20)30201-X

DOI: https://doi.org/doi:10.1016/j.resuscitation.2020.05.022

Reference: RESUS 8540

To appear in: Resuscitation

Received Date: 2 December 2019

Revised Date: 11 May 2020

Accepted Date: 14 May 2020

Please cite this article as: Moller S, Wissenberg M, Kragholm K, Folke F, Hansen CM,Ringgren KB, Andersen J, Barcella C, Lippert F, Kober L, Gislason G, Gerds TA,Torp-Pedersen C, Socioeconomic differences in coronary procedures and survival afterout-of-hospital cardiac arrest: a nationwide Danish study, Resuscitation (2020),doi: https://doi.org/10.1016/j.resuscitation.2020.05.022

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Socioeconomic differences in coronary procedures and survival after out-of-

hospital cardiac arrest: a nationwide Danish study

Sidsel Møller1, Mads Wissenberg

1,2, Kristian Kragholm

3, Fredrik Folke

1,2, Carolina Malta

Hansen1,2

, Kristian B. Ringgren3, Julie Andersen

4, Carlo Barcella

1, Freddy Lippert

2, Lars Køber

5,

Gunnar Gislason1,4,6

, Thomas Alexander Gerds7, Christian Torp-Pedersen

3,8

Affiliations:

1 Department of Cardiology, Copenhagen University Hospital Gentofte, Hellerup, Denmark

2 Copenhagen Emergency Medical Services, University of Copenhagen, Denmark

3 Department of Cardiology, North Denmark Regional Hospital & Aalborg University Hospital, Denmark

4 Danish Heart Foundation, department of research, Copenhagen, Denmark

5 The Heart Centre, Rigshospitalet, University of Copenhagen Copenhagen, Denmark

6 The National Institute of Public Health, University of Southern Denmark, Copenhagen Denmark

7 Section of Biostatistics, Department of Public Health, University of Copenhagen, Copenhagen, Denmark

8 Department of Cardiology, North Zealand Hospital, The Capital Region of Denmark,

Address for correspondence:

Sidsel Møller MD;

Department of Cardiology, Copenhagen University Hospital, Gentofte;

Kildegårdsvej 28, Post-635; 2900 Hellerup Denmark;

E-mail: Sidselgm@gmail.com

Word count: Abstract: 243 Manuscript: 2,999 References: 40

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Abstract

Aim: It remains unclear whether socioeconomic differences exist in post-resuscitation care in out-

of-hospital cardiac arrests (OHCA). We aimed to examine socioeconomic differences in coronary

procedures and survival after OHCA.

Methods: OHCA patients ≥30 years of cardiac cause with a hospital admission from the Danish

Cardiac Arrest Registry, 2001-2014, were divided according to quartiles of household income

(lowest, low, high, highest). Associations of income, coronary procedures and 30-day survival were

examined by age-standardized incidence rates and incidence rate ratios (IRR), and by logistic

regression.

Results: A total of 6,105 patients were included. Higher-income patients were younger, males and

had less comorbidity-burden. Higher-income patients had higher incidence rates for coronary

angiographies both day 0-1 and day 2-7 after OHCA (day 0-1: highest: IRR 1.79, 95%CI 1.46-2.21;

high: IRR 1.28, 95%CI 1.10-1.51; low: IRR 1.05, 95%CI 0.90-1.23), compared to lowest. Fifty-four

percentage of the patients undergoing a coronary angiography received percutaneous-coronary-

intervention or coronary-artery-bypass-grafting with no difference among three of the four groups,

but lower IRR in low-income patients (IRR 0.74, 95%CI 0.61-0.89) compared to lowest. Higher-

income patients had also higher odds for 30-day survival compared to lowest, both in patients with

(highest: OR 1.61, 95%CI 1.12−2.32; high: OR 1.13, 95%CI 0.80−1.60; low: OR 1.14, 95%CI

0.81−1.61) and without (highest: OR 2.54, 95%CI 1.83−3.53; high: OR 1.41, 95%CI 1.06−1.87;

low: OR 1.12, 95%CI 0.86−1.47) coronary angiography day 0-1.

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Conclusion: Higher patient-income was found associated with more performed coronary

angiographies after OHCA, and higher odds for 30-day survival.

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Introduction

Despite improvements in cardiac arrest management and outcomes after out-of-hospital cardiac

arrest (OHCA) [1, 2], OHCA is still a major health problem worldwide [3]. Focus has primarily

been on improving pre-hospital resuscitative care with increased bystander interventions, and to a

lesser extent post-resuscitative in-hospital and post-hospital treatment [4]. Since the most common

cause to OHCA is ischemic heart disease [5, 6], the in-hospital strategy has focused on coronary

angiographies (CAG) and revascularization (percutaneous-coronary-intervention [PCI] and

coronary-artery-bypass-grafting [CABG]) [7, 8], with varying results [6].

Many factors can potentially affect the in-hospital treatment. A recently published report by the

American Institute of Medicine, called for more research focusing on socioeconomic disparities in

OHCA-treatment and -outcomes [9]. Socioeconomic factors have previously been found associated

with pre-hospital factors as bystander cardiopulmonary resuscitation (CPR) [10]. Yet, very little is

known about whether socioeconomic factors potentially affect in-hospital care for OHCA patients.

In Denmark, the potential association of socioeconomic factors and the in-hospital care would

probably be expected to be less important due to the universal tax-financed healthcare system and

the wide access to invasive procedures from 2001 [11, 12]. Nonetheless, studies of myocardial

infarction patients have found that patients of higher socioeconomic status were offered more

coronary procedures [12, 13], which also could be expected in OHCA patients.

This study therefore aimed to examine whether patient socioeconomic factors were associated with

performed coronary procedures and survival in OHCA patients. We hypothesized that the acute

setting of OHCA and the wide access to the procedures in the Danish healthcare system would

reduce a potential socioeconomic gradient, but that patients of higher socioeconomic status still

would have a higher chance of undergoing coronary procedures and survive.

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Methods

Data sources and study design

This nationwide study was based on the Danish Cardiac Arrest Registry holding information on all

OHCA patients with a resuscitation-attempt either by bystander or the emergency medical services

(EMS) in linkage with other national registries.

From the Danish Cardiac Arrest Registry, we obtained information of date and location of the

OHCA (private or public place), bystander or EMS witnessed-status, bystander CPR-status,

bystander defibrillation-status, EMS response time (the estimated time-interval from emergency-

call based on the time for the receipt of the emergency-call or interviews of the bystanders and first

rhythm analysis by EMS), initial heart rhythm (shockable/non-shockable), and survival-status on

hospital arrival. In Denmark the EMS is activated for all medical emergencies and for every OHCA

they fill out an obligatory case-report form adding information to the registry.

From the Danish National Population Registry we obtained information on patient age, sex and vital

status. From the National Causes of Death Registry we obtained information on causes of death

from death certificates. From the Danish National Patient Registry we obtained information on

admission- and discharge-dates, previously used and validated procedure-codes for CAG, PCI and

CABG (Suppl. Table 1) [14, 15] and discharge diagnosis-codes. Discharge diagnosis-codes up to

ten years before OHCA were used to determine Charlson-Comorbidity-Index [16]. The

International Classification of Diseases system (ICD-8/ICD-10) was used for all codes.

Socioeconomic factors

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Information on individual patient income and education was obtained from Statistics Denmark [17]

and linked to each OHCA-patient. We chose income as primary exposure and used education as

supplemental measurement for investigating different socioeconomic aspects on the outcomes.

Income was divided in quartiles (lowest, low, high and highest income) based on a five-year

average household income for the individual patient’s household calculated from the year prior to

OHCA, to account for potential yearly variation minimizing the influence of acute illness [18]. It

was weighted according to the number of people living in the household by using the Organisation

for Economic Co-operation and Development (OECD) modified scale (the first adult counts as 1

and further adults count 0.5 per person) [19] and corrected for inflation to year 2015. Educational

status was based on the highest completed educational level of the patient and to allow comparison

internationally it was classified according to the ISCED-system (International Standard

Classification of Education) [20]. Patient education was divided in three groups of: (1) Basic

education including elementary school, (2) High school and short secondary education, and (3)

Bachelor or Master/Doctoral degree or equivalent.

The study population

The study population consisted of all OHCA patients that had an in-patient hospital admission after

OHCA from June 1, 2001 to December 31, 2014. To obtain a more homogenous study population

we excluded EMS-witnessed arrests <30 years of age of presumed non-cardiac cause [2], and

arrests who died in the emergency department [15]. Figure 1 shows the study selection process.

The study population was divided according to quartiles of income: (Q1) lowest, (Q2) low, (Q3)

high, and (Q4) highest (Table 1).

Outcomes

The main outcome measures were divided in two:

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1) Coronary procedures with (A) CAGs in three pre-defined time periods after OHCA: (1: day 0-1,

2: day 2-7, 3: day 8-30). The time periods were chosen for more comparable patients in each group

with similar clinical characteristics and comparable indications to the procedure. (B) Among the

patients undergoing CAG we examined the composite outcome of revascularization procedures

(PCI and CABG) in day 0-30 after OHCA. A composite outcome was chosen because of small

sample sizes when separating the two procedures.

2) 30-day survival after OHCA in patients alive on day 2 (A) with a CAG day 0-1 after OHCA, and

(B) without a CAG day 0-1 after OHCA.

The outcome measures were all examined in relation to patient income primarily and patient

education in supplemental.

Statistical analysis

Overall categorical variables were presented as frequencies with percentages and compared with

Chi-Square tests and continuous variables were presented as medians with interquartile-ranges and

compared with Kruskall-Wallis tests.

To explore the temporal improvements in coronary procedures and survival, we analysed time

trends (2001-2014) of CAGs day 0-1 after OHCA and 30-day survival by using logistic regression

adjusted for age (30-65 years, 66-75 years and >75 years) and sex.

For CAG and revascularization we calculated age-standardized incidence rates (SIR) and relative

incidence rate ratios (IRR) according to patient income-quartiles. Patients were followed until date

of death, hospital discharge, or 30-days from admission, whatever came first, for calculation of risk-

time. For CAGs, SIRs and IRRs were calculated separately for the three time periods (day 0-1, day

2-7 and day 8-30 after OHCA). The analysis was repeated in pre-defined sub-groups of: (1) Sex, (2)

Charlson-Comorbidity-Index [15], (3) witnessed arrests with bystander CPR, (4) arrests with

shockable rhythm, (5) in two calendar time periods (years 2001-2007 and years 2008-2014) and (6)

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in relation to patient education instead of income. The association was further assessed using Cox

regression analyses with death as competing risk. To avoid incorrect interpretation [21] the analyses

were adjusted for the confounders: age, sex, Charlson-Comorbidity-Index, education and calendar

year, and analysed in sub-groups of the mediators (1) witnessed arrests with bystander CPR and (2)

shockable arrests.

Survival within the first 30 days after OHCA was estimated using the empirical distribution

function according to patient income based on 2-day survivors with and without CAG day 0-1.

Logistic regression analysis was used to examine the association adjusted for age, sex, Charlson-

Comorbidity-Index, patient education and calendar year. Logistic regression was performed in (1)

2-day survivors with and without performed CAG during day 0-1, (2) based on patient education

instead of income, and (3) in sub-groups of witnessed arrests with bystander CPR and shockable

arrests opposed to confounders since they appear on the pathway between exposure and outcome.

Reported were odds ratios (ORs) and corresponding 95% confidence intervals (95% CI). The level

of statistical significance was set at 5%.

For data management and statistical analyses SAS version 9.4 (“SAS Institute Inc., Cary, NC,

USA”) and R version 3.6.1 [22] were used.

Ethics

This study was approved by the Danish Data Protection Agency (Ref.no. 2007-58-0015, local

ref.no. GEH-2014-017, I-Suite.no. 02735). Registry-based studies in Denmark do not require

ethical approval.

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Results

The total study population consisted of 6,105 patients. Table 1 shows overall characteristics of the

income-groups. Highest-income patients compared with lowest were younger, more males, had

higher education and less comorbidity-burden. In the cardiac arrest-related factors they had more

public and witnessed arrests, more bystander interventions and shockable rhythm (lowest 47.0%,

low 50.1%, high 58.8%, highest 73.0%). This persisted in age groups of 30-65, 66-75 and >75 years

(Suppl. Table 2).

Coronary procedures

From 2001 to 2014, an increase in CAGs performed day 0-1 after OHCA was observed for all

income-groups (Figure 2A), though with the highest-income patients at the top. In total, 2,580

(42.3%) patients underwent a CAG with 26.9% in lowest income, 32.6% in low income, 44.1% in

high income and 63.6% in highest income (Table 1). The vast majority of CAGs (80.5%) were

performed during the acute phase (day 0-1). Figure 3 shows the age-SIR for CAGs in the three time

periods in relation to patient income. Overall the SIR increased with increasing income, with the

largest difference between the income-groups in the first time period (day 0-1 after OHCA) with

IRR for low 1.05 (95%CI 0.90-1.23), high 1.28 (95%CI 1.10-1.51) and highest 1.79 (95%CI 1.46-

2.21) in reference to lowest income. The same trend was observed in the two other time periods

(day 2-7 and day 8-30 after OHCA), but less pronounced.

A total of 54.3% of the patients undergoing CAG received PCI or CABG during the hospitalization

up to 30 days after OHCA (Table 1). In reference to the lowest-income patients, a lower IRR was

observed for low-income (IRR 0.74, 95%CI 0.61-0.89) and no difference in high- and highest-

income patients (high: IRR 0.88, 95%CI 0.73-1.08; highest: IRR 0.95, 95%CI 0.74-1.23) (Figure

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3). The same overall trends, but less pronounced, were observed when stratifying according to (1)

sex (CAG day 0-1 highest-income in females: IRR 1.90, 95%CI 1.07-3.30; in males: IRR 1.63,

95%CI 1.30-2.06, in reference to lowest-income), (2) Charlson-Comorbidity-Index = 0 (Suppl.

Figure 1), (3) witnessed arrests with bystander CPR (Suppl. Figure 2), (4) shockable arrests (Suppl.

Figure 3), year 2001-2007 and 2008-2014 (Suppl. Figure 4), and (5) when using education (Suppl.

Figure 5) instead of income. The same trends were observed in multivariable analyses (Suppl. Table

4).

Survival

Of the 6,105 patients 38.8% survived to day 30: 22.9% in lowest and 58.9% in highest income

patients (Table 1). From 2001 to 2014, 30-day survival increased in all groups (Figure 2B).

Figure 4 shows the crude survival-probability during 30 days in 2-day survivors with and without

CAG performed day 0-1 after OHCA according to income. Again the highest-income patients were

in the top (with CAG (Figure 4A): highest: 80.3%, high: 69.0%, low: 64.3%, lowest: 58.9%; and

without CAG (Figure 4B): highest: 70.5%, high: 52.7%, low: 44.2%, lowest: 39.4%).

When examining 30-day survival in adjusted logistic regression analysis (Figure 5), we found

higher odds for survival with higher income in both 2-day survivors with CAG day 0-1 after OHCA

(highest: OR 1.61, 95%CI 1.12-2.32) and without (highest: OR 2.54, 95%CI 1.83-3.53) in reference

to lowest income. The same trend was observed using education instead of income (Suppl. Figure

6), and in sub-groups of witnessed arrests with bystander CPR and arrests with shockable rhythm

(Suppl. Table 3), but here less pronounced.

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Discussion

This nationwide study aimed to examine potential socioeconomic differences in coronary

procedures and survival in OHCA patients of presumed cardiac cause. Overall, higher-income

patients were associated with higher rates of CAGs, especially day 0-1 after OHCA, with no

difference observed in revascularizations among patients undergoing CAG, except for low-income

patients that had a lower rate. Regarding survival, we observed that higher-income patients alive at

day 2 after OHCA were more likely to survive to day 30 both with and without CAG day 0-1 after

OHCA and when adjusting for patient factors. The same was observed using education as

socioeconomic measurement instead of income. This study not only supports existing literature on

the important socioeconomic aspect in OHCA research, but also adds novel findings of

socioeconomic differences in the post-resuscitative in-hospital care.

Socioeconomic differences have been of increasing interest and are known to affect health and care

[23-25]. In patients suffering an OHCA socioeconomic differences have been observed in incidence

[26], bystander interventions [27], and survival [10]. However studies on socioeconomic differences

in post-resuscitative in-hospital care in OHCA patients are lacking, but have previously been shown

in patients suffering an acute myocardial infarction [12, 13, 28]. Since ischemic heart disease is the

most common cause of cardiac arrest [5, 6] and coronary procedures are the recommended strategy

for OHCA patients according to the European Resuscitation Council [29] and the American Heart

Association guidelines [7], we examined potential effects of socioeconomic factors on coronary

procedures of the OHCA patients.

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Overall we found that patients of higher income (and higher education) were associated with higher

rates of CAGs, especially in the acute setting (0-1 day after OHCA). This difference could be

influenced by many factors including geographical factors such as distances to invasive hospitals,

but also by both patient- and cardiac arrest-related factors, which differed across the income-groups.

Patients with higher income were younger [30], had less comorbidity-burden [31], had more

witnessed arrests, bystander CPR and shockable rhythm. All factors known to be associated with

better prognosis and could easily affect patient selection in the in-hospital treatment. However,

when we examined the rates of CAGs in relation to these factors, we still found that higher-income

patients were significantly associated with higher rates of CAGs although to a lesser extent.

Conversely, when we analysed the rate of revascularization in patients who underwent CAG, we

observed no difference between three of the four groups with only low-income patients receiving

less revascularization than the other groups indicating that the probability of coronary occlusion

seemed not to be defined by socioeconomic status for the patients undergoing CAG.

Over time both CAG and survival increased for all income-groups indicating that the improvements

in care [2] are working and benefitting all patients no matter of socioeconomic position. Though,

overall survival had the same trend as CAGs with higher survival in higher-income patients. We

examined 30-day survival among 2-day survivors with and without CAG day 0-1 after OHCA, and

observed that the survival-difference between the income-groups was smaller in patients with CAG

than in patients without CAG. This could support a previously found greater effect of

revascularization in high-risk myocardial infarction patients [32-34] and a theory that patients with

lower socioeconomic status with poorer health and more cardiovascular risk factors may benefit of

a more aggressive post-resuscitation management [12, 35]. However, the overall more CAGs and

the higher survival in higher-income patients may be a result of other factors including both better

patient and pre-hospital factors. It may be that physicians refer to a CAG in patients with better

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prognosis at baseline hence taking (intentionally or unintentionally) what is known from the EMS

and patient chart about the socioeconomic aspect into account [36, 37]. Thereby patients with lower

socioeconomic status could wait longer for important treatments [28] and doctors may refrain from

more invasive treatments when knowing of age, comorbidity-status [38], and important pre-hospital

factors. Yet, because of the more aggressive approach to CAGs and revascularizations after 2001 in

Denmark [11] and including it in international guidelines from 2006, the potential influence of

socioeconomic status on physicians’ decision-making would be expected to be less important today

[12]. This seems also supported by our time-analyses showing increased CAGs and survival from

2001-2014 in all income-groups.

Our study overall supports the existing literature on socioeconomic differences in health, care and

outcomes. Since socioeconomic differences exist in the Danish healthcare system, where it would

be expected that the treatments would be more universal and equally distributed for all patients,

socioeconomic differences would perhaps be even more prominent in other healthcare systems [13,

39, 40]. More studies are warranted to help improve future strategies in cardiac arrest management

despite patients’ socioeconomic status.

Limitations

Our study is a register-based observational study meaning that the findings are associations and not

necessarily causal relations. Another limitation of our study was the lack of more detailed

information of factors that potentially could have helped explore the socioeconomic status of the

included patients such as smoking habits, body-mass-index, and physical activity. Moreover, more

in-hospital parameters could help clarify potential socioeconomic-related differences in advanced

care further, but unfortunately the data in the registries is not complete. Also, it would have been

interesting to have some data on the decision-making process for the coronary interventions as well

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as data on intensive care units. However, all these factors are very difficult to measure and were not

available for our study.

Conclusion

In a tax-financed universal healthcare system in Denmark, available to all inhabitants independent

of socioeconomic position, patient of higher socioeconomic status, based on both income and

education, still was found associated with a higher frequency of both CAGs and survival. These

socioeconomic differences would probably be expected to be even more prominent in other sites of

the world. More research in this area and why socioeconomic differences exist is needed to help

future improvements in cardiac arrest patients.

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Sources of funding/Conflicts of interest

Dr. Møller has received a grant from Karen Elise Jensen Fond and Laerdal Foundation.

Dr. Folke has received grants from Novo Nordisk Foundation and Laerdal Foundation.

Dr. Malta Hansen has received grants from TrygFonden, Helsefonden and Laerdal Foundation.

Dr. Kragholm has received grants from Laerdal Foundation and speaker’s honoraria from Novartis.

Dr. Køber has received lecture fees from Sanofi and Novartis.

Dr. Gislason has received a grant from Novo Nordisk Foundation.

Dr. Torp-Pedersen has received grants and honoraria from Bayer and Biotronik.

The remaining authors have no disclosures to report.

Acknowledgements

This study was supported by TrygFonden that supports the Danish Cardiac Arrest Registry, but has

no commercial interest in the cardiac arrest area, as well as no influence in this study’s

management, design, data collection, analyses, data-interpretation, preparation, reviewing,

reporting, approval of manuscript or submission-decision for publication.

The Danish Cardiac Arrest Registry is based on data from the EMS-personnel supplying the registry

with data for each OHCA. Therefore a big thanks to the EMS personnel.

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22. R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://http://www.R-project.org/. 23. Nandi A, Glymour MM, Subramanian SV. Association among socioeconomic status, health behaviors, and all-cause mortality in the United States. Epidemiology. 2014;25(2):170-7. 24. Steenland K, Henley J, Calle E, Thun M. Individual- and area-level socioeconomic status variables as predictors of mortality in a cohort of 179,383 persons. American journal of epidemiology. 2004;159(11):1047-56. 25. Winkleby MA, Jatulis DE, Frank E, Fortmann SP. Socioeconomic status and health: how education, income, and occupation contribute to risk factors for cardiovascular disease. American journal of public health. 1992;82(6):816-20. 26. Reinier K, Thomas E, Andrusiek DL, Aufderheide TP, Brooks SC, Callaway CW, Pepe PE, Rea TD, Schmicker RH, Vaillancourt C, Chugh SS, Resuscitation Outcomes Consortium I. Socioeconomic status and incidence of sudden cardiac arrest. CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne. 2011;183(15):1705-12. 27. Sasson C, Magid DJ, Chan P, Root ED, McNally BF, Kellermann AL, Haukoos JS, Group CS. Association of neighborhood characteristics with bystander-initiated CPR. The New England journal of medicine. 2012;367(17):1607-15. 28. Alter DA, Naylor CD, Austin P, Tu JV. Effects of socioeconomic status on access to invasive cardiac procedures and on mortality after acute myocardial infarction. The New England journal of medicine. 1999;341(18):1359-67. 29. Monsieurs KG, Nolan JP, Bossaert LL, Greif R, Maconochie IK, Nikolaou NI, Perkins GD, Soar J, Truhlar A, Wyllie J, Zideman DA, Group ERCGW. European Resuscitation Council Guidelines for Resuscitation 2015: Section 1. Executive summary. Resuscitation. 2015;95:1-80. 30. Wissenberg M, Folke F, Hansen CM, Lippert FK, Kragholm K, Risgaard B, Rajan S, Karlsson L, Sondergaard KB, Hansen SM, Mortensen RN, Weeke P, Christensen EF, Nielsen SL, Gislason GH, Kober L, Torp-Pedersen C. Survival After Out-of-Hospital Cardiac Arrest in Relation to Age and Early Identification of Patients With Minimal Chance of Long-Term Survival. Circulation. 2015;131(18):1536-45. 31. Lee CC, Tsai MS, Fang CC, Chen YJ, Hui-Ming M, Huang CH, Chen WJ, Chen SC. Effects of pre-arrest comorbidities on 90-day survival of patients resuscitated from out-of-hospital cardiac arrest. Emergency medicine journal : EMJ. 2011;28(5):432-6. 32. Jakobsen L, Niemann T, Thorsgaard N, Thuesen L, Lassen JF, Jensen LO, Thayssen P, Ravkilde J, Tilsted HH, Mehnert F, Johnsen SP. Dimensions of socioeconomic status and clinical outcome after primary percutaneous coronary intervention. Circulation Cardiovascular interventions. 2012;5(5):641-8. 33. Kim MJ, Ro YS, Shin SD, Song KJ, Ahn KO, Hong SO, Kim YT. Association of emergent and elective percutaneous coronary intervention with neurological outcome and survival after out-of-hospital cardiac arrest in patients with and without a history of heart disease. Resuscitation. 2015;97:115-21. 34. Geri G, Dumas F, Bougouin W, Varenne O, Daviaud F, Pene F, Lamhaut L, Chiche JD, Spaulding C, Mira JP, Empana JP, Cariou A. Immediate Percutaneous Coronary Intervention Is Associated With Improved Short- and Long-Term Survival After Out-of-Hospital Cardiac Arrest. Circulation Cardiovascular interventions. 2015;8(10). 35. Schulman-Marcus J, Lin FY, Gransar H, Berman D, Callister T, DeLago A, Hadamitzky M, Hausleiter J, Al-Mallah M, Budoff M, Kaufmann P, Achenbach S, Raff G,

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Chinnaiyan K, Cademartiri F, Maffei E, Villines T, Kim YJ, Leipsic J, Feuchtner G, Rubinshtein R, Pontone G, Andreini D, Marques H, Chang HJ, Chow BJW, Cury RC, Dunning A, Shaw L, Min JK. Coronary revascularization vs. medical therapy following coronary-computed tomographic angiography in patients with low-, intermediate- and high-risk coronary artery disease: results from the CONFIRM long-term registry. European heart journal cardiovascular Imaging. 2017;18(8):841-8. 36. Barnhart JM, Monrad ES, Cohen HW. Physicians' perceptions of the effect of nonclinical factors on coronary revascularization. Heart disease. 2003;5(5):313-9. 37. Rab T, Kern KB, Tamis-Holland JE, Henry TD, McDaniel M, Dickert NW, Cigarroa JE, Keadey M, Ramee S, Interventional Council ACoC. Cardiac Arrest: A Treatment Algorithm for Emergent Invasive Cardiac Procedures in the Resuscitated Comatose Patient. Journal of the American College of Cardiology. 2015;66(1):62-73. 38. Samuels LE, Kaufman MS, Morris RJ, Promisloff R, Brockman SK. Coronary artery bypass grafting in patients with COPD. Chest. 1998;113(4):878-82. 39. Pilote L, Joseph L, Belisle P, Penrod J. Universal health insurance coverage does not eliminate inequities in access to cardiac procedures after acute myocardial infarction. American heart journal. 2003;146(6):1030-7. 40. Rosvall M, Chaix B, Lynch J, Lindstrom M, Merlo J. The association between socioeconomic position, use of revascularization procedures and five-year survival after recovery from acute myocardial infarction. BMC public health. 2008;8:44.

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Figure Legends:

Figure 1, The patient selection process, 2001-2014

Flowchart of the patient selection process.

Figure 2: Percentages of (A) coronary angiographies day 0-1 after OHCA and (B) 30-day survival in relation to patient

income from 2001 to 2014

Logistic regression analyses for temporal trends in performed coronary angiography (A) and 30-day survival (B)

following OHCA in relation to income quartiles, standardized after sex and age (30-65 years, 66-75 years, >75 years).

OHCA, out-of-hospital cardiac arrest.

Figure 3: Age-standardized incidence rates and incidence rate ratios for coronary procedures in relation to patient

income. Reference group = lowest income group

Age-standardized incidence rates and incidence rate ratios for performed coronary procedures in relation to patient

income. The coronary procedures were divided in (1) coronary angiographies and (2) revascularization (including both

PCI and CABG) in patients with coronary angiographies. The coronary angiographies were examined in three time

periods: (1) day 0-1 after OHCA, (2) day 2-7 after OHCA, and (3) day 8-30 after OHCA. The incidence rate is number

of coronary angiographies or revascularizations per 100 in-hospital person-days.

CABG, coronary artery bypass grafting; OHCA, out-of-hospital cardiac arrest; PCI, percutaneous coronary intervention

Figure 4: The probability of survival with 95% confidence intervals during 30 days after OHCA according to patient

income

The probability of survival with 95% confidence intervals during 30 days after OHCA according to the income groups:

lowest, low, high and highest, for (A) 2-day survivors with coronary angiography within day 0-1 after OHCA, and (B)

2-day survivors without coronary angiography within day 0-1 after OHCA.

OHCA, out-of-hospital cardiac arrest

Figure 5: Adjusted odds ratios with 95% confidence intervals for 30-day survival according to patient income.

Reference group = lowest income group.

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The logistic regression analysis with odds ratios for the association of income group and 30-day survival in (1) 2-day

survivors with coronary angiography within day 0-1 after OHCA, and (2) 2-day survivors without coronary

angiography within day 0-1 after OHCA. All adjusted for age, sex, calendar year, comorbidities and educational level.

Odds ratio >1.00 indicates that patients in higher income groups are positively associated with survival in reference to

patients in the lowest income group.

OHCA, out-of-hospital cardiac arrest; OR, odds ratio.

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Table 1: Characteristics of OHCA patients in relation to income quartiles, 2001-2014

All patients (6,105)

Income

quartile 1

(lowest)

1,423

Income

quartile 2

(low)

1,522

Income

quartile 3

(high)

1,573

Income

quartile 4

(highest)

1,587

p-value Missing value,

n (%)

Median household

income, EUR (IQR) 22,800

(20,900-

24,300)

29,600

(27,800-

32,100)

42,400

(38,200-

47,200)

66,800

(58,900-

81,500)

- -

Patient factors Female sex, n (%) 448

(31.5) 497

(32.7) 372

(23.6) 288

(18.1) <0.001 -

Median age, y (IQR) 76

(70-80) 70

(63-77) 65

(57-72) 58

(51-65) <0.001 -

- Age 30-65 years, n (%) 228

(16.0) 473

(31.1) 820

(52.1) 1,237

(77.9) <0.001 -

- Age 66-75 years, n (%) 483

(33.9) 597

(39.2) 476

(30.3) 269

(17.0) <0.001 -

- Age >75 years, n (%) 884

(62.1) 836

(54.9) 596

(37.9) 311

(19.6) <0.001 -

Educational level

- Basic, n (%) 884

(62.1) 836

(54.9) 596

(37.9) 311

(19.6) <0.001 -

- High school and short

secondary education, n

(%)

475

(33.4) 570

(37.5) 711

(45.2) 722

(45.5) <0.001 -

- Bachelor or

Master/Doctoral degree

or equivalent, n (%)

64

(4.5) 116

(7.6) 266

(16.9) 554

(34.9) <0.001 -

Charlson Comorbidity Index, n (%)

- 0 635

(44.6)

737

(48.4)

900

(57.2)

1,174

(74.0)

<0.001 -

- 1 269

(18.9)

271

(17.8)

229

(14.6)

150

(9.5)

<0.001 -

- >1 519

(36.5)

514

(33.8)

444

(28.2)

263

(16.6)

<0.001

Cardiac arrest-related factors

Arrest in public, n (%) 422

(33.2) 514

(37.4) 564

(39.1) 721

(49.8) <0.001 567

(9.3)

Witnessed arrest, n (%) 1,004

(73.2) 1,034

(70.7) 1,155

(75.6) 1,212

(79.0) <0.001 208

(3.4)

Bystander CPR, n (%) 663

(48.2) 819

(55.9) 925

(60.5) 1,144

(74.4) <0.001 198

(3.2)

Bystander defibrillation,

n (%) 49

(3.7) 72

(5.2) 93

(6.4) 144

(10.0) <0.001 504

(8.3)

Estimated median time

interval from recognition

10 (6-15)

10 (6-14)

10 (6-14)

10 (6-14)

4,316 (17.1)

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of arrest to ambulance

arrival, n (IQR)

Pre-hospital shockable

heart rhythm, n (%) 640

(47.0) 733

(50.1) 890

(58.8) 1,107

(73.0) <0.001 251

(4.1)

Outcomes

Survival at hospital

arrival, n (%) 819

(63.0) 951

(69.5) 1,001

(69.9) 1,077

(76.5) <0.001 595

(9.8)

Coronary angiography

under hospitalization, n

(%)

383

(26.9)

496

(32.6)

693

(44.1)

1,008

(63.5)

<0.001 -

- During day 0-1 after

OHCA, n (%)

318

(22.4)

401

(26.4)

564

(35.9)

794

(50.0)

<0.001 -

- During day 2-7 after

OHCA, n (%)

34

(2.4)

38

(2.5)

56

(3.6)

129

(8.1)

<0.001 -

- During day 7-30 after

OHCA, n (%)

31

(2.2)

57

(3.8)

73

(4.6)

85

(5.4)

<0.001 -

- Revascularization (PCI

or CABG) in coronary

angiography patients, n

(%)

206

(53.8)

252

(50.8)

388

(56.0)

556

(55.2)

0.311 -

30-day survival, n (%) 326

(22.9) 483

(31.7) 625

(39.7) 935

(58.9) <0.001 -

- 30-day survival in

coronary angiography

day 0-1 patients, n (%)

156

(49.1)

234

(58.4)

356

(63.1)

596

(75.1)

<0.001 .

1-year survival, n (%) 277

(19.5)

407

(26.7)

575

(36.6)

900

(56.7)

<0.001 -

Median household income calculated in EUR, rounded to nearest 100 EUR and adjusted to 2014, course = 7,4432 DKR per 1 EUR. CABG, coronary artery bypass grafting; COPD = Chronic obstructive pulmonary disease; CPR = cardiopulmonary resuscitation; EMS = emergency

medical system; IQR = interquartile range; OHCA = out-of-hospital cardiac arrest; PCI, percutaneous coronary intervention

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