Article, Cardiology

Association of recent major psychological stress with cardiac arrest: A case-control study

a b s t r a c t

Objective: We hypothesized that major psychological stress can be a risk factor for cardiac arrest and that effects are modified by elapsed time from specific stressful events.

Methods: Case-control study was conducted using database for cardiac arrest and emergency department (ED) vis-

iting. Cases included adult patients with cardiac arrest with presumed cardiac etiology. Controls were matched with sex and age and visiting day from unintentional injured patients in same ED. The occurrence of 9 major life events (MLEs) such as a divorce within 1 year was used as a proxy measure of major psychological stress. A mul- tivariable conditional logistic regression conducted to estimate the effect of MLEs on the risk of cardiac arrest ac- cording to the elapsed time from the MLEs.

Results: A total of 95 patients with cardiac arrest and 95 controls were assessed. In the case group,a total of 58 MLEs occurred, while 33 MLEs occurred in the control group during the same period. Recent MLEs were associated with a higher risk of sudden cardiac arrest (AOR 2.26 [95% CI:1.01-5.03]). The AORs of cardiac arrest were 4.65 (95% CI, 1.38-15.67) and 7.02 (95% CI, 2.03-24.48) among participants experiencing MLEs within the last 0-3 months and those experiencing MLEs within the last 0-6 months, respectively. Cardiac arrest and MLEs in participants experiencing MLEs between 7 and 12 months prior showed no association (AOR 4.76 [95% CI, 0.97-18.36]).

Conclusions: MLEs were associated with cardiac arrest occurrence, and the effect was modified by the elapsed time from the MLEs.

(C) 2017

Introduction

Cardiac arrest is a significant Public health problem. In the United States, 326,000 cases of cardiac arrest occur in out-of-hospital areas every year [1]. Moreover, the Incidence of cardiac arrest has increased [2]. The fatality of cardiac arrest is still high despite multi-disciplinary ef- forts during the past three decades. Several etiologies of sudden cardiac arrest have been suggested. A fatal arrhythmia like ventricular fibrillation is a representative cause of sudden cardiac arrest [3]. These results were

? This study was financially supported by the Korea Centers for Disease Control and Prevention (CDC) (2013-2014). (Cheongju-si/Chungcheongbuk-do/Korea), fund code 2014-E33001-00.

* Corresponding author at: 679-24 Hwajung-dong, Deokyang-gu, Goyang-si, Gyeonggi- do 412-270, Republic of Korea.

E-mail address: [email protected] (K.O. Ahn).

limited to the studies that only included patients diagnosed with ische- mic heart disease or heart failure [4-6]. Ironically, the majority of cardiac arrest occurs in the population without underlying structural cardiac dis- eases. There is an “epidemiological paradox” in the area of cardiac arrest [7]. To develop a strategy to prevent acute cardiac arrest, comprehensive studies are needed to explain the epidemiologic paradox. Several previ- ous studies reported that psychological stress was also associated with the genesis of cardiovascular diseases [8-12]. It is unclear whether psy- chological stress is the trigger of acute cardiac arrest. The measurement of psychological stress in patients with cardiac arrest is very difficult. One method for the measurement of psychological stress of patients with cardiac arrest is the use of Major Life Events (MLEs) including a di- vorce or dismissal. It was reported in previous studies that MLEs are re- lated to the risk of coronary heart disease [8-9,11]. An interesting research point is the elapsed time from the occurrence of MLEs to the

http://dx.doi.org/10.1016/j.ajem.2017.07.039

0735-6757/(C) 2017

occurrence of acute cardiac arrest. Wicks et al. study is the only literature available on the subject [13]. This study hypothesized that MLEs can be a risk factor for cardiac arrest. We also hypothesized that the risks are modified by the elapsed time from the MLEs.

Materials and methods

This study followed the STROBE statement and reviewed the guide- lines for the reporting of a case-control study [14].

Subject of the study

This case-control study was conducted from January to December 2014 in 12 hospitals that participated in in-depth surveillance, which in- cluded the “surveys for MLEs”.

Patients registered in the Cardiac Arrest Pursuit Trial with Unique Registration and Epidemiologic Surveillance (CAPTURES) project who agreed to participate in a study on MLEs were subsampled and included as cases. This multi-center research project aimed to investigate the or- ganic and catalytic risk factors of Sudden cardiac arrest incidence. Detailed information about this research project and quality data man- agement is described in a previous article [15]. The potential case group population comprised patients with SCA with presumed Cardiac origin, treated through emergency medical service (EMS) with resuscitation (EMS-treated SCA). We excluded cases of patients with “Do-Not-Resus- citate” cards issued by a doctor or bed-ridden state owing to a terminal disease stage. The following patients were also excluded: (1) patients who were living alone or homeless without reliable information source, and (2) patients who refused to participate in the study and did provide information for MLEs by family members.

Hospital-based controls were selected from the National Emergency

Department Information System (NEDIS) database between January and December 2013 of 12 hospitals. The NEDIS is a nationwide govern- ment-run system that contains clinical and administrative data of pa- tients who visited EDs [16]. Our sampled controls included unintentionally injured patients who were discharged from the ED and who agreed with participating in the MLE survey. Controls were matched by sex and age (in 10-year increments) and day of ED visit in the same hospital where the patients were admitted. Because of concerns for a low rate of receiving informed consent among the control group, the ratio of candidate controls to cases was set at 20:1. Trained research as- sistants contacted individuals in the control group via telephone in ran- dom order and attempted to obtain informed consent to provide information on MLEs through a survey. If the individual refused consent for the study, the assistant attempted to contact the next listed individu- al. When the survey was completed for one control group participant, the procedure was discontinued. The final ratio of those in the control group to those in the case group was 1:1 (Fig. 1).

Variables

The CAPTURES cohort registry contained information on sex, age, height, weight, past medical history, family medical history, and health-related behaviors (smoking, frequent alcohol consumption, ha- bitual physical activity, and sleeping hours). The MLE items selected through extensive review of previous studies were modified according to the study setting [13,17]. MLEs were defined as the following: 1) death or serious illness of family members; 2) divorce or break up with a spouse; 3) break-up with family members (e.g., the individual ran away from home, or a branch family); 4) dismissal from work; 5) retire- ment, 6) significant failure at work [including business and study]; 7) death, serious illness, or separation involving someone close to the indi- vidual; 8) serious illness or injury of the case/control participant them- selves; 9) other major intra-family conflicts. Each event experience was addressed with a notation as to the month and year that it occurred. In- formation on medical histories, patient health behaviors, and MLEs were

Fig. 1. Study selection flow diagram CAPTURES: Cardiac Arrest Pursuit Trial with Unique Registration and Epidemiologic Surveillance, EMS: emergency medical service, MLEs: major life events, NEDIS: National Emergency Department Information System, OHCA: out-of-hospital cardiac arrest.

obtained by a family member who lived with the participant (cases and controls). Telephone interviews were conducted to obtain the informa- tion. The telephone interview was performed by trained research assis- tants with a structured interview protocol and interview script.

Statistical analysis

We used the chi-square (?2) to test for the categorical variables’ de- scriptive analysis. A p-value less than 005 indicated statistical signifi- cance. For the matched case-control dataset, the adjusted odds ratios (OR) and 95% confidence intervals (95% CI) were calculated using a mul- tivariable conditional logistic regression model to estimate the effect of MLEs on the risk of cardiac arrest. MLEs were defined as any of 9 detailed MLEs that occurred within 12 months from ED admission. We investigat- ed the variously defined control periods (0-1 month, 0-3 months, 0- 6 months, 7-12 months, and 0-12 months) in a sensitivity analysis. Po- tential confounding factors included past medical history, family medical history, and healthy behaviors. Smoking was defined as current smoker or not. Frequent alcohol consumption was defined as more than twice per week. Habitual physical activity was defined as more than 20 min of vigorous physical activity more than twice per week. Sleeping hours was divided into 6-hour increments.

Ethics statement

The study complies with the Declaration of Helsinki and the study protocol was approved by all Institutional Review Boards of the 12 par- ticipating study institutions. Informed consent was received by the fam- ily members providing information for MLEs (IRB number; H-1401-090- 550). This study was financially supported by the Korea Centers for Dis- ease Control and Prevention (CDC) (2013-2014).

Results

Among 960 participants included over the study period, 95 patients were analyzed as the case group. Each group had 69 male participants. The average age was 66.3 years in the case group and 63.8 years in the control group. There was no significant difference in the diagnosis of di- abetes mellitus or hypertension and family medical history of cardiac ar- rest, and cerebrovascular diseases between the case and control groups (Table 1). The case group had higher proportions of current smokers

Table 1

Demographics of the cardiac arrest cases and controls.

Table 2

Count numbers of major life events of the cases and controls.

Total (N,%)

OHCA

cases (N,%)

Controls (N,%)

p-Value

OHCA

cases

Controls

Total 190 95 95

n

%

n

%

Death or serious illness of family members

4

6.9

5

15.2

Divorce or break up with a spouse

0

0.0

0

0.0

Break up with family members

0

0.0

0

0.0

Dismissal from work

3

5.2

3

9.1

Retirement

0

0.0

0

0.0

Significant failure at work

8

13.8

1

3.0

Death, serious illness or separation involving of close person

3

5.2

3

9.1

Serious illness or injury of the case/control person

26

44.8

13

39.4

Gender 1.0

Male

138

72.6

69

72.6

69

72.6

Female

52

27.4

26

27.4

26

27.4

Age 0.91

19-45

25

13.2

12

12.6

13

13.7

46-65

58

30.5

28

29.5

30

31.6

N 65

107

56.3

55

57.9

52

54.7

Frequent alcohol consumption b 0.01

Median (IQR)

Health behaviors Current Smoking

Yes

69(54

47

-75)

24.7

69(54

29

-77)

30.5

69(52-73)

b 0.01

18 18.9

themselves

Other major intra-family conflicts 14 24.1 8 24.2

Total 58 33

No

135

71.1

58

61.1

77

81.1

OHCA: out-of-hospital cardiac arrest.

Unknown

8

4.2

8

8.4

0

0.0

Yes 52 27.4 33 34.7 19 20.0

No

133

70.0

57

60.0

76

80.0

15.67), 7.02 (95% CI, 2.03-24.48), and 2.26 (95% CI, 1.01-5.03) when

Unknown

5

2.6

5

5.3

0

0.0

the control period was defined as a 3 month, 6 month, and 12 month pe-

The AOR of the cardiac arrest of case group was 4.65 (95% CI, 1.38-

Habitual physical activity 0.01

Yes

127

66.8

58

61.1

69

72.6

No

51

26.8

26

27.4

25

26.3

Unknown

12

6.3

11

11.6

1

1.1

Sleeping hours 0.01

0-6

24

12.6

12

12.6

12

12.6

N 6

145

76.3

66

69.5

79

83.2

Unknown

21

11.1

17

17.9

4

4.2

Body mass index b 0.01

>= 25

49

25.8

24

25.3

25

26.3

ac arrest, and the amount of association can vary by the elapsed time

b 25

102

53.7

40

42.1

62

65.3

from the event. The results of this study suggest that the risk of cardiac

Unknown

39

20.5

31

32.6

8

8.4

arrest associated with major psychological stress was constant up until

riod, respectively. The MLEs occurrence between 6-12 months was not significantly different (AOR 4.76 (95% CI, 0.97-18.36)).

Discussion

This case-control study revealed that MLEs are associated with cardi-

Past medical history

Hypertension diagnosis 1.0

Yes

86

45.3

43

45.3

43

45.3

No

102

53.7

51

53.7

51

53.7

Unknown

2

1.1

1

1.1

1

1.1

Diabetes mellitus diagnosis 0.19

Yes

40

21.1

23

24.2

17

17.9

No

148

77.9

70

73.7

78

82.1

Unknown

2

1.1

2

2.1

0

0.0

Family medical history

Cardiac arrest 0.70

Yes

183

96.3

91

95.8

92

96.8

No/unknown

7

3.7

4

4.2

3

3.2

Acute coronary syndrome

Yes 185

97.4

90

94.7

95

0.02

100.0

No/unknown

5

2.6

5

5.3

0

0.0

Cerebrovascular disease 0.20

Yes

173

91.1

84

88.4

89

93.7

No/unknown

17

8.9

11

11.6

6

6.3

IQR: interquartile range, OHCA: out-of-hospital cardiac arrest.

(33.3%) and participants who frequently consumed alcohol (36.7%) com- pared with those in the control group, which included 18.9% and 20.0% of the group, respectively (both p-value 0.01).

Table 2 shows the number of MLEs in the case and control groups ac-

6 months after the event occurrence.

Our findings revealed an association between MLEs with psycholog- ical stress, and subsequently cardiac arrest. MLEs can affect the risk of cardiac arrest through various channels. Psychological stress-induced MLEs can affect the sympathetic nerve system, hypothalamus-pitui- tary-adrenal axis, and the immune system [9,18-21]. It is also related with hyper-coagulation, which is known to be a risk factor for coronary diseases [22]. MLEs can also modify health-related behaviors like smoking, alcohol consumption, and sleeping behaviors. These behaviors were reported to be risk factors for cardiac arrest in previous studies [9, 18]. Table 1 shows that that case group had a higher proportion for cur- rent smoking and frequent alcohol consumption.

A previous study reported good reliability of a survey interviewing the spouse of the case/control participants [13]. Among the results of in- terviews from 85 survivors of sudden cardiac arrest survivors and their spouses, kappa statistics indicated moderate agreement between surviv- ing patients after cardiac arrest and their spouses on the occurrence (un- weighted kappa: 0.49) and timing (unweighted kappa: 0.48) of MLEs. In

Table 3

Major life event experiences in case-control group.

cording to the elapsed time from the events (0-1 month, 0-3 month, 0- 6 month, and 0-12 month periods). The incidence of serious illness or in- jury among the participants was highest in both groups (26 vs. 13 events in the case and control groups, respectively). Among the case and control groups, there were no reported experiences for “divorce or break up with a spouse” or “break up with family members.” In the case group, a total of 58 MLEs occurred in twelve months, while 33 MLEs occurred in the con- trol group during the same 0-12 month period. In all periods, except in the 0-3 month period, MLEs occurrence was significantly higher in the case group than in the control group (Table 3).

Total (N) Case (N,%) Control

(N,%)

Total 190 95 100 95 100

Number of subject who experienced MLE(s) in given period

0-1 month

12

10

10.5

2

2.1

0.02

0-3 months

29

19

20

10

10.5

0.07

0-6 months

32

22

23.2

10

10.5

0.02

7-12 months

25

20

21.1

5

5.3

0.001

Uncertain period

18

5

5.3

13

13.7

0.001

0-12 months?

66

41

43.2

25

26.3

0.01

MLE: Major life event.

p-Value

The results of the multivariable conditional logistic regression are shown in Table 4. Out-of-hospital cardiac arrest and MLE experiences during the 1-month period were higher in the case group, but this differ- ence was not statistically significant (AOR 4.55 (95% CI, 0.62-33.23)).

* Some participants experienced more than 2 MLEs before visiting EDs; these may have

occurred during different time periods. For example, one experienced between 0 and 6 months followed by a MLE between 7 and 12 months. The sum of participants in the 0-6 month and 7-12 month groups and uncertain period group was greater than the number of participants in the 0-12 month group.

Table 4

Multivariable logistic regression analysis of association between major life event experi- ences and out-of-hospital cardiac arrest.

Unadjusted model Adjusted model

(OR, 95% CI) (OR, 95% CI)

People who experienced MLE(s)

0-1 month

5.47 (1.17-25.68)

4.55 (0.62-33.23)

0-3 months

2.13 (0.93-4.85)

4.65 (1.38-15.67)

0-6 months

2.56 (1.14-5.76)

7.01 (2.03-24.24)

7-12 months

4.80 (1.72-13.4)

4.76 (0.97-23.48)

Uncertain period

0.35 (0.12-1.03)

4.76 (0.97-23.48)

0-12 months

2.13 (1.15-3.92)

2.26 (1.01-5.03)

this study, the reliability of family-reported occurrence and timing of MLEs was not evaluated.

A notable point in this study was the modification of MLEs as a pre- cipitating factor for cardiac arrest. In a previous study by Wick et al, the authors included “relocation of residence” as an MLE [13]. Considering the cultural difference involving frequent moving in South Korea, au- thors in this study excluded “relocation of residence” as an MLE. Contrary to the previous study of Wick et al, “death of spouse,” which was consid- ered in most studies as a MLE, was included in this study as an MLE. This modification of the definition of MLEs could affect the results of this study.

In our study, we found that the association between MLEs and cardiac arrest differs by the elapsed time from the event. In the previous study by Wick et al., major events involving family or friends after 1 month was not associated with a risk of cardiac arrest [13]. However, in our results, the effects of MLEs were constant up until 6 months. We believe these contrary results were the result of the use of a different study population in Wick et al.’s study. In Wick et al.’s study, telephone interview respon- dents were limited to spouse inclusion. A spouse can play a preventing role in the risk of cardiac arrest after MLEs. In this study, the participants’ marital status was not distinguishable. Considering the patient’s median age was 69 years in this study, some participants may not have had a spouse. The presence of a spouse is important for psychological support; hence, this may have affected our results.

In previous studies, habitual physical activities have a modified trig- gering effect of episodic exertion on the occurrence of cardiac arrests [23-26]. In this study, the control group had a significantly higher pro- portion of habitual physical activities (Table 1). However, habitual phys- ical activities did not demonstrate a modified effect on the occurrence of cardiac arrest in the multiple logistic regression model. Other potential modified factors for the triggering effect of psychological stress on cardi- ac arrest should be considered.

Our study has several limitations. First, we did not focus on a healthy population without a history of clinically recognized heart disease or life- threatening comorbidity. However, we excluded bed-ridden patients without a further treatment plan in an attempt to isolate patients with sudden cardiac arrest. Additionally, controls in this study were not sam- pled in the general population. It was difficult to obtain informed consent for the survey of MLEs from the general population. We sampled ED- based controls among discharged patients with unintentional injury be- cause they were most similar to the general population among patients visiting the ED. No comparative analysis was performed to investigate the difference in the characteristics between the included and excluded controls. The potential for unmeasured biased characteristics of excluded controls was considered in this study. Second, vulnerability to personal stress is different in each person. Clinical depression was reported as a risk factor for cardiac arrest [27]. Because that the reliability of history for depression from representatives was not guaranteed because of the very reluctant culture for psychiatric service and strong stigma on people with Mental illness in South Korea, we did not include information for clinical depression in-depth surveillance. The measure of social avoid- ance or social network was a potential proxy for those vulnerable; a few studies have reported on the association between the incidence of

cardiovascular disease and these measurements [28,29], but adaption to cardiac arrest was very difficult to ascertain because there was no ev- idence for the reliability of those measurements from representatives. Fi- nally, because the cohorts were defined by time periods, a priori sample size analysis was not performed. The calculated total sample size was 1,988 (994 pairs) when the alpha error was assumed at 5% and the study power was assumed at 90%. The estimated power of this 1:1 matched case-control study was 78.9%.

Conclusion

MLEs were associated with cardiac arrest occurrence, and the effect was modified by the elapsed time from the MLEs.

Acknowledgments

This study was financially supported by the Korea Centers for Disease Control and Prevention (CDC) (2013-2014). (Cheongju-si/ Chungcheongbuk-do/Korea).

Disclosure

The authors have no conflicts of interest to disclose.

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