Differences in prehospital delay between acute ischemic stroke and acute myocardial infarction

Abstract

Background and Purpose

There has been no nationwide study directly comparing the prehospital delay between acute ischemic stroke (AIS) and acute myocardial infarction (AMI). In present study, we aimed to evaluate and compare the factors related with prehospital delay in AIS and AMI by using the nationwide data of Korean regional cardiocerebrovascular centers (RCCVCs).

Methods

We included AIS and AMI patients identified through RCCVCs registry who admitted to 11 RCCVCs via emergency room within 1 week of symptom onset from July 2016 to December 2018. To test an effect of each predictor on prehospital delay, general linear mixed-effects model was used with hospital as a random effect.

Results

A total of 17,895 AIS and 8,322 AMI patients were enrolled. The median (interquartile range) time of prehospital delay for AIS and AMI patients was 6.05 (1.83-24.65) and 3.00 (1.25-7.92) hours, respectively. Sex showed an effect on prehospital delay in opposite direction between AIS and AMI. Women showed more prolonged prehospital delay compared to men in AMI, whereas the reverse pattern was observed for AIS patients. Some factors had effect on prehospital delay in same direction between AIS and AMI but with differences in significance (one-person household, symptom onset at night, and severe symptom profile) or magnitude (age, patients' prehospital awareness of the disease and the use of EMS). Previous experience of each disease and interhospital transfer significantly affected to longer prehospital delay without any difference by disease.

Conclusions

There are some differences in the effect of each factor on prehospital delay, therefore, these differences should be considered to make differentiated strategy and effort to reduce hospital delay in AIS and AMI.

Introduction

Acute ischemic stroke (AIS) and acute myocardial infarction (AMI) are two similar medical emergency conditions which characterized by a sudden decrease or stoppage of blood flow to respective organs and required urgent revascularization. Early hospital visit is essential to achieve early diagnosis and timely management for better outcome in AIS and AMI. For this reason, many efforts have been undertaking to reduce prehospital delay in AIS and AMI.

In South Korea, regional cardiocerebrovascular center (RCCVC) project was begun from 2008 for the better prevention and treatment of AIS and AMI.1, 2 Currently, 11 RCCVCs at local university hospitals are operating with a 24-hour specialized care system, facilities and equipment that satisfy the relevant standards. After establishment and operation of RCCVCs, in-hospital delay has been shortened, however, prehospital delay is still a problem yet to be solved.1

As RCCVCs have been established and operated, we have had opportunities to collect the nationwide data of prehospital delay in AIS and AMI simultaneously and directly compare the prehospital delay between two diseases within the same capture area. To our best knowledge, there has been no nationwide study directly comparing the prehospital delay between AIS and AMI. Furthermore, a previous review has shown that there is large variability in the prehospital delay by geographical factors in AIS and AMI, therefore, the comparison of two diseases within the same capture area is meaningful.3 In present study, we aimed to evaluate and compare the factors related with prehospital delay in AIS and AMI by using the nationwide data of Korean RCCVCs.

Methods

Participants and data collection

From 2008 to 2012, 11 local university hospitals outside the Seoul metropolitan area (Gangwon, Daegu-Gyeongbuk, and Jeju in 2008; Gyeongnam, Gwangju-Jeonnam, and Chungbuk in 2009; Busan-Ulsan, Jeonbuk, Daejeon-Chungnam in 2010; and Gyeonggi and Incheon in 2012) were designated as RCCVCs by the Ministry of Health and Welfare of South Korea (Figure 1). In this study, we included AIS and AMI patients identified through RCCVCs registry who admitted to 11 RCCVCs via emergency room (ER) within 1 week of symptom onset from July 2016 to December 2018. Patients with no available data or error in data of symptom onset were excluded. The institutional review boards of the respective designated hospitals provided ethical approval for this study.

Outcome and predictors

The outcome of this study was prehospital delay defined as the time from symptom onset to the documented hospital arrival time. Symptom onset was defined as the time when the disease related symptoms first developed. In AIS patients with unclear onset time including wake-up onset, symptom onset was defined as first observed abnormal time. The time of hospital arrival was defined as the time when the patients arrived to the ER of the hospital.

Predictors evaluated in this study were demographic factors (age and sex), household factors, previous experience of each disease, patient’s prehospital awareness, transportation and transfer system including the use of emergency medical services (EMS) and inter-hospital transfer, and time of symptom onset. The nature and severity of symptom might be one of the important factors related to prehospital delay. However, there was no common criteria or scale used for measuring symptom severity between AIS and AMI. Therefore, in present study, we defined milder symptom profile separately as a National Institute of Health Stroke Scale (NIHSS) score of 0-3

Statistical analysis

Subject’s demographic and clinical characteristics were summarized as mean and standard deviation or number (percentage) according to the type of variables. Baseline differences between AIS and AMI patients were compared by chi-square test or the Fisher’s exact test for categorical variables, and Student’s t-test for numeric variables. For the prehospital delay time, a logarithmic transformed value was used since its distribution was positively skewed.

To test an effect of each predictor on prehospital delay, general linear mixed-effects model was used with hospital as a random effect to account for the effect of clustering at the hospital level. In the multivariable mixed regression analysis, all predictors and interaction terms having significant interaction effect with disease (AIS vs. AMI) were used as independent variables. All statistical analyses were performed using the SAS software, version 9.4 (SAS Institute, Cary, NC). P-values reported were two-tailed, and a p-value < 0.05 was considered as statistical significance.

Results

Baseline characteristics of patients

Of 26,826 patients initially screened for eligibility, 609 patients (2.3%) were excluded because of no available data or error in data of symptom onset. Finally, a total of 17,895 AIS and 8,322 AMI patients were enrolled. Baseline characteristics of the patients are shown in Table 1. Patients with AIS were older than those with AMI (69.6 ± 12.7 versus 65.3 ± 13.0; P < 0.001). The male ratio was higher in AMI patients compared to AIS patients (75.2% versus 58.9%; P < 0.001). The prevalence of hypertension, diabetes, hyperlipidemia, and atrial fibrillation was higher in AIS patients compared to AMI patients (all P < 0.001). On the other hand, the prevalence of smoking was much higher in AMI patients than AIS patients (37.5% versus 22.9%; P < 0.001). A history of previous stroke was more common in AIS patients, while a history of previous coronary artery disease was more common in AMI patients.

There were no significant differences between the two groups with respect to the ratio of one-person households and the proportion of patients with symptom onset on the weekend. The proportion of patients with symptom onset at night was much higher in AMI patients compared to AIS patients (40.0% versus 34.6%; P < 0.001). Patients' prehospital awareness of the disease was much higher in AIS than AMI (21.4% versus 17.1%; P < 0.001). Regarding transportation and transfer system, the proportions of patients using EMS and patients who underwent interhospital transfer were both higher in AMI group than AIS group (64.6% versus 54.7%; P < 0.001 and 51.0% versus 33.4%; P < 0.001, respectively).

In AIS patients, median (interquartile range, IQR) NIHSS score was 4 (2-8) and the proportion of patients with a NIHSS score of ≥ 4 was 52.9%. The proportion of AMI patients with predominant chest pain was 88.6%.

Prehospital delay in AIS and AMI

The median (IQR) time of prehospital delay for AIS and AMI patients was 6.05 (1.83-24.65) and 3.00 (1.25-7.92) hours, respectively. Prehospital delay was significantly longer in AIS patients compared to AMI patients (P < 0.001).

The distribution of prehospital delay time for each group is shown in Table 2 & Figure 2. 49.8% of AIS patients and 69.7% of AMI patients arrived to the hospital within 6 hours of symptom onset. Nearly 50% of AMI patients were arrived to the hospital within 3 hours of symptom onset, while about 35% in AIS patients. The proportion of patients who presented to the hospital after 24 hours of symptom onset was 25.7% in AIS patients, but only 10.5% in AMI patients.

The factors related with prehospital delay (Table 3)

Demographic factors

Among AMI patients, women showed more prolonged prehospital delay compared to men, whereas the reverse pattern was observed for AIS patients (Figure 3A). Increasing age was significantly associated with longer prehospital delay in both groups, however, showed much larger effect in AMI patients compared to AIS patients (Figure 3B). In AIS patients, the age-related delay was more significant in male than in female subjects (Figure 3B).

Household factor

Single person household was significant independent factor for delayed presentation to hospital only in AIS patients (P < 0.001). Similar tendency was found in AMI patients, but without statistical significance.

Previous history and prehospital awareness

Previous experience of each disease (previous stroke history in AIS patients and previous coronary artery disease history in AMI patients) was associated with longer prehospital delay without any interaction by disease (AIS vs. AMI). Statistically significant association between prehospital awareness and earlier presentation to hospital was observed in both AIS and AMI groups with quantitative interaction; much larger effect in AIS group compared to AMI group.

Transportation and transfer system

The use of EMS showed statistically significant effect on shortening of prehospital delay in both groups, but with a quantitative difference; much larger effect in AIS patients. Interhospital transfer were significantly related to much longer hospital delay without any interaction by disease.

Time of symptom onset

AIS patients who experienced symptoms at night delayed longer than those who experienced symptom at daytime. However, in AMI patients, having symptoms at night was not significantly associated with a longer prehospital delay. In both AIS and AMI groups, there were no significant differences in prehospital delay between symptom onset on weekday and on weekend.

Symptom nature and severity

More severe symptom profile in AIS patients which defined as a NIHSS score of ≥ 4 was associated with earlier presentation to hospital (P < 0.001). There was no significant difference in prehospital delay between AMI patients with predominant chest pain and those with symptoms other than chest pain including .

Discussion

We believe this is the first nationwide study to directly compare the prehospital delay between AIS and AMI. In this study, we compared the factors associated with prehospital delay between AIS and AMI. Factors were divided into three types in our results: (1) factor showing effect on prehospital delay in opposite direction between AIS and AMI; (2) factor showing effect on prehospital delay in same direction between AIS and AMI but with differences in significance or magnitude; (3) factor showing no difference in effect on prehospital delay between AIS and AMI.

Sex was the only factor showing effect on prehospital delay in opposite direction between AIS and AMI. In our AMI patients, women showed more prolonged prehospital delay compared to men, which has been consistently reported in previous AMI studies.3, 4 Although the reasons for the women’s longer prehospital delay in AMI have not been fully understood, prolonged decision making in women has been thought to be one of the reasons.5 Therefore, specific intensive strategies for women to make more rapid decision to visit hospital should be prepared and focused in AMI. On the other hand, women showed a tendency towards a shorter prehospital delay in AIS, however, statistically not significant in our study. Previous studies have reported inconsistent findings on the sex effect on prehospital delay in AIS.6-8 Further studies are needed to evaluate the reasons accounting for these conflicting data.

Previous experience of each disease and interhospital transfer significantly affected to longer prehospital delay without any difference by disease. On the other hand, age, patients' prehospital awareness of the disease and the use of EMS were significantly related with prehospital delay in both groups, however, showed a quantitative difference by disease. The effect of advanced age on delayed hospital presentation was much larger in patients with AMI compared to those with AIS, while patients' prehospital awareness and the use of EMS had much larger effect on shortening of prehospital delay in AIS patients than AMI patients. These differences in the magnitude of the effect could be considered to provide a differentiated plan for each disease to reduce prehospital delay.

One-person household, symptom onset at night, and severe symptom profile were associated with prehospital delay, but only significantly in AIS patients. These differences in significance between two diseases might be caused by the nature of symptom of each disease. Because of the patient’s disability to visit hospital alone by stroke symptom, living with family or housemate might be especially important for AIS patients. Symptom at night might have less influence to the prehospital delay in AMI which mostly manifested as severe chest pain hard to endure even at night. In AIS, more severe symptom defined by NIHSS score was significantly associated with early hospital visit, which might be caused by patient's perceived urgency. Whereas, there was no difference of prehospital delay by presenting symptom (predominant chest pain vs. other symptoms) in AMI. However, this negative finding could be resulted from a relatively smaller number of patients with no chest pain (11.4%) compared those with chest pain (88.6%).

There were some limitations in this study that should be noted. We did not have detailed information on the patients' socioeconomic status including education, medical insurance, occupation and annual income. Accurate paramedic recognition of the disease is one of key factors regarding early hospital visit, however, we could not evaluate this because of insufficient data collection on this. Finally, only Koreans were included in this study, which could limit the generalizability of our results because there might be a large variability in the prehospital delay by cultural and geographical factors such as race, ethnicity and nationality.

In conclusion, this is the first nationwide study to directly compare the prehospital delay between AIS and AMI. Our study shows that there are some differences in the effect of each factor on prehospital delay, therefore, these differences should be considered to make differentiated strategy and effort to reduce hospital delay in AIS and AMI.

References

1.	Kim J, Hwang Y-H, Kim J-T, Choi N-C, Kang S-Y, Cha J-K, et al. Establishment of government-initiated comprehensive stroke centers for acute ischemic stroke management in south korea. Stroke. 2014;45:2391-2396

2.	Cho SG, Kim Y, Choi Y, Chung W. Impact of regional cardiocerebrovascular centers on myocardial infarction patients in korea: A fixed-effects model. Journal of Preventive Medicine and Public Health. 2019;52:21

3.	Herlitz J, WireklintSundström B, Bång A, Berglund A, Svensson L, Blomstrand C. Early identification and delay to treatment in myocardial infarction and stroke: Differences and similarities. Scandinavian journal of trauma, resuscitation and emergency medicine. 2010;18:48

4.	Zijlstra F, Patel A, Jones M, Grines C, Ellis S, Garcia E, et al. Clinical characteristics and outcome of patients with early (< 2h), intermediate (2–4h) and late (> 4h) presentation treated by primary coronary angioplasty or thrombolytic therapy for acute myocardial infarction. European Heart Journal. 2002;23:550-557

5.	Turris SA, Finamore S. Reducing delay for women seeking treatment in the emergency department for symptoms of potential cardiac illness. Journal of Emergency Nursing. 2008;34:509-515

6.	Mandelzweig L, Goldbourt U, Boyko V, Tanne D. Perceptual, social, and behavioral factors associated with delays in seeking medical care in patients with symptoms of acute stroke. Stroke. 2006;37:1248-1253

7.	Derex L, Adeleine P, Nighoghossian N, Honnorat J, Trouillas P. Factors influencing early admission in a french stroke unit. Stroke. 2002;33:153-159

8.	Lacy CR, Suh D-C, Bueno M, Kostis JB. Delay in presentation and evaluation for acute stroke: Stroke time registry for outcomes knowledge and epidemiology (stroke). Stroke. 2001;32:63-69

Table 1. Patients’ characteristics

	Acute ischemic stroke N = 17,895	Acute myocardial infarction N = 8,322	p value
Age, mean ± SD (years)	69.6 ± 12.7	65.3 ± 13.0	< 0.001
Male, N (%)	10,538 (58.9)	6,258 (75.2)	< 0.001
Risk factor, N (%)
Hypertension	11,425 (63.8)	4,202 (50.5)	< 0.001
Diabetes	5,670 (31.7)	2,396 (28.8)	< 0.001
Hyperlipidemia	5,359 (30.0)	979 (11.8)	< 0.001
Atrial fibrillation	3,804 (21.3)	650 (7.8)	< 0.001
Smoking	4,102 (22.9)	3,120 (37.5)	< 0.001
Previous stroke	4,036 (22.6)	599 (7.2)	< 0.001
Previous coronary artery disease	1,570 (8.8)	806 (9.6)	0.023
-, N (%)	3,156 (17.6)	1,528 (18.4)	0.154
Onset day, N (%)*			0.139
Weekday	11,885 (66.4)	5,604 (67.3)
Weekend	6,010 (33.6)	2,718 (32.7)
Onset time, N (%)*			< 0.001
Daytime (6am-6pm)	11,710 (65.4)	4,993 (60.0)
Nighttime (6pm-6am)	6,185 (34.6)	3,329 (40.0)
Prehospital awareness, N (%)	N = 17,895	N = 8,315	< 0.001
Yes	3,823(21.4)	1,426 (17.1)
No	11,835 (66.1)	6,433 (77.3)
Not-applicable	2,237 (12.5)	456 (5.5)
Use of EMS, N (%)	9,784 (54.7)	5,374 (64.6)	< 0.001
Interhospital transfer, N (%)	5,974 (33.4)	4,246 (51.0)	< 0.001
NIHSS, median (IQR)	4 (2-8)
NIHSS ≥ 4	9,472 (52.9)
Predominant chest pain, N (%)		7,377 (88.6)

EMS=emergency medical services; NIHSS= National Institute of Health Stroke Scale.

*Defined as first abnormal time in unclear-onset stroke

Table 2. Delay from symptom onset to hospital arrival

	Acute ischemic stroke N = 17,895	Acute myocardial infarction N = 8,322	p value
Onset to door time median (IQR) (hours)	6.05 (1.83-24.65)	3.00 (1.25-7.92)	< 0.001*
Time distrubtion, N (%)			< 0.001
< 1 hr	2,443 (13.7)	1,574 (18.9)
≥ 1 to < 3 hr	3,869 (21.6)	2,559 (30.8)
≥ 3 to < 6 hr	2,600 (14.5)	1,663 (20.0)
≥ 6 to < 12 hr	2,218 (12.4)	981 (11.8)
≥ 12 to < 24 hr	2,167 (12.1)	672 (8.1)
≥ 24 to < 72 hr	3,089 (17.3)	615 (7.4)
≥ 72 hr	1,509 (8.4)	258 (3.1)

IQR= interquartile range.

* P-value by two-sample test using log-transformed variable

Table 3. Predictors of prehospital delay (log-transformed hours) in patients with acute ischemic stroke and acute myocardial infarction

	Acute ischemic stroke (AIS)				Acute myocardial infarction (AMI)			p for interaction‡
	Coefficient	SE	p value		Coefficient	SE	p value
Sex (male)	0.036	0.022	0.091		-0.188	0.038	< 0.0001	< 0.0001
Age (per 10 years increase)	0.018	0.008	0.030		0.146	0.013	< 0.0001	< 0.0001
One-person household	0.146	0.027	< 0.0001		0.038	0.039	0.335	0.025
Prehospital awareness	-0.416	0.026	< 0.0001		-0.148	0.041	< 0.001	< 0.0001
Use of EMS	-1.038	0.022	< 0.0001		-0.708	0.032	< 0.0001	< 0.0001
Symptom onset at night	0.210	0.021	< 0.0001		0.005	0.030	0.881	< 0.0001
More severe symptom profile*	-0.225	0.022	< 0.0001		0.023	0.048	0.634	< 0.0001
	Variables with no interaction by disease group (AIS vs. AMI)
	Coefficient			SE		p value
Previous history†	0.097			0.023		< 0.0001		0.978
Interhospital transfer	0.969			0.018		< 0.0001		0.141
Symptom onset on the weekend	0.018			0.018		0.318		0.478

Figure 1. Locations of the 11 established regional cardiocerebrovascular centers (RCCVCs) in South Korea

Figure 2. Distribution of time from symptom onset to hospital arrival

Figure 3. Mean predicted value of prehospital delay for each disease group according to sex and age