Adverse Effects of Coronavirus Disease 2019 (COVID-19) on First Medical Contact to Reperfusion Time in Urban ST-Segment Elevation Myocardial Infarction Patients and Advantage of Prehospital Electrocardiography

Abstract

Background: We have previously reported the advantages of a prehospital 12-lead electrocardiography system (P-ECG) for ST-segment elevation myocardial infarction (STEMI) patients (Circ Rep 2019; Circ J 2022, 2023). Since 2020 with Coronavirus disease 2019 (COVID-19), the patient transport situation has changed dramatically. We investigated how patient transport was changed by COVID-19. The effect of prehospital electrocardiography (ECG) was also evaluated.

Methods and Results: Recent urban STEMI patients who received primary percutaneous coronary intervention (PCI) using P-ECG were assigned to a P-ECG group (n=87; age 69±14 years), and comparable urban STEMI patients not using P-ECG were assigned to a Conventional group (n=87; age 71±13 years). The pre-COVID-19 period is defined as the period before the pandemic began, and the COVID-19 period is the time thereafter. In the Conventional group, first medical contact (FMC)-to-reperfusion time (110±45 vs. 90±31 min; P=0.025) and door-to-reperfusion time (89±41 vs. 70±29 min; P=0.015) in the COVID-19 period were significantly longer than in the pre-COVID-19 period. However, in the P-ECG group, there was no difference in FMC-to-reperfusion time and door-to-reperfusion time between the 2 periods. In the Conventional group, Killip class (2.0±1.3 vs. 1.1±0.5; P=0.001) and left ventricular ejection fraction (49±12 vs. 57±9.0%; P=0.002) were significantly poorer in the COVID-19 period than in the pre-COVID-19 period. However, in the P-ECG group, there was no significant difference between the 2 periods.

Conclusions: During the COVID-19 pandemic, P-ECG might have provided advantages for patient transport and outcomes in urban STEMI patients.

Since 2020 with Coronavirus disease 2019 (COVID-19), there has been a dramatic change in the patient transport situation. The pandemic caused a severe shortage of general hospital beds and an inability of emergency patients to be promptly admitted to hospital. The COVID-19 pandemic altered medical management before and during hospitalization, and changed the severity and prognosis of acute coronary syndrome (ACS) patients.^1,2 Primary percutaneous coronary intervention (PCI) represents the preferred revascularization strategy among patients with ST-segment elevation myocardial infarction (STEMI). During the COVID-19 pandemic, a decrease in PCI rates has been observed worldwide.³ Some studies from different regions of the world have reported that STEMI patients undergoing PCI during the COVID-19 pandemic experienced delayed treatment, prolonged treatment times, and therefore worse clinical outcomes.^4–6 Fear of nosocomial infection has been hypothesized as the primary mechanism for this phenomenon and, coupled with delays in responding to emergency medical services (EMS), may contribute to delays in STEMI patient visits.⁷ A systematic and efficient strategy is needed to address this detrimental global trend in STEMI treatment during a pandemic.

We have reported that the prehospital 12-lead electrocardiography system (P-ECG) shortened door-to-balloon time (DTBT) in STEMI patients in Oita,⁸ and subsequently that it helped to transport suspected ACS patients to optimal institutes.⁹ P-ECG is useful even in urban areas, especially for patients who develop STEMI during the night on a weekday or while on holiday.¹⁰ However, there are still few reports of P-ECG evaluation of STEMI patients during the COVID-19 pandemic.

We investigated how COVID-19 changed the transport status of STEMI patients, particularly in ambulance transport, and whether P-ECG had any effect on patient transport time or time from arrival to coronary revascularization.

Methods

Prehospital ECG System

On April 17, 2017, the P-ECG (Cloud Cardiology®, Labtech Co., Debrecen, Hungary) system was started in 18 hospitals and 10 ambulances of 10 respective fire departments in Oita prefecture. This system has been extended to 24 hospitals and 14 respective fire departments in Oita prefecture, in which we have encouraged participation. As of March 2024, 53 of a total of 75 ambulances are equipped with ECGs. Nineteen PCI institutions have 24-h PCI availability, while 5 other regional core hospitals do not. The urban areas of Oita City and Beppu City, where 15 (79%) of the 19 participating PCI institutes are concentrated, account for more than half of the population of Oita Prefecture and 98% of the STEMI cases transported by P-ECG. EMS obtain a 12-lead ECG and transmit to a secure cloud server (SCUNA®, Mehergen, Japan) using the network of the existing image transmission system. The ECG in the cloud server can be browsed simultaneously from personal computers, smartphones, and tablets from anywhere after access key authentication. Immediately after the diagnosis of suspected ACS, a cardiologist participating in the P-ECG system performs emergency cardiac catheterization examination before the patient arrives at hospital.¹⁰

During the 2-year period from September 2019 to August 2021, in Oita City, which accounts for 43% of the population of Oita Prefecture and has the highest number of P-ECG transports, P-ECG was performed in 79 of 200 cases, excluding 151 inter-hospital transports and 34 cases of cardiopulmonary arrest, out of 385 total transports due to acute myocardial infarction.

Patient Selection and Grouping

The decision to transmit a P-ECG for suspected ACS was left to the judgment of the EMS team on site. During the 64 months between April 2017 and July 2022, when data were available, the total number of prehospital P-ECG transports was 2,340, of which 123 patients with STEMI and successful primary PCI were in the P-ECG group. Of these patients, only 87 urban cases (20 female; age 69±14 years) were entered. To avoid bias in first medical contact to reperfusion time, only urban cases were included. Urban cases were defined as cases transported from the same city as the hospital where the PCI was performed. The comparable 80 urban STEMI patients without using P-ECG in urban cases were assigned to the Conventional group (23 female; age 71±13 years). The Conventional group consisted of patients who were transported directly by ambulance to the 5 participating hospitals in Oita City and Oita University Hospital during the same period, excluding walk-in patients.

Holidays were defined as national holidays and weekends. Nighttime was defined as the patient›s arrival at the hospital after 6:00 p.m. and before 8:00 a.m.¹¹

This investigation was conducted according to the principles expressed in the Declaration of Helsinki. The study protocol was approved by the Oita University Research Ethics Committee (No. 1262).

Definitions of Periods and Time Interval

The period before the COVID-19 pandemic began was defined as the pre-COVID-19 period and the period after it began was the COVID-19 period. The beginning of the pandemic was defined as April 7, 2020, when a state of emergency was declared in Japan.

First medical contact to reperfusion time was defined as the interval from the time of EMS arrival on the scene to the reperfusion. EMS stay time was defined as the time between the arrival of the EMS at the scene and the departure of the EMS from the scene. Patient transfer time was defined as the interval from the time the EMS departed the scene to the door time (i.e., the arrival time at the emergency department where the emergency catheterization was performed). Door-to-reperfusion time was defined as the interval from the door time, to the reperfusion (Figure 1).

Figure 1.

Definitions of time intervals. EMS, emergency medical services.

Statistical Analysis

Data are presented as the mean±SD. A chi-square test was used for categorical variables and analysis of variance (ANOVA) was used for continuous variables. The differences between groups were analyzed using the Student’s t-test. To compare differences among the 4 groups, 1-way ANOVA was utilized, followed by Tukey’s HSD to account for multiple comparisons. Multivariate logistic regression analysis was performed to determine factors of clinical presentation associated with longer time to reperfusion (>90 min). Killip class, maximal creatine kinase (CK), and left ventricular ejection fraction (LVEF) were entered as independent variables. Odds ratios and the 95% confidence intervals (CI) were calculated. The ability of defining factors to predict the effect of door to reperfusion time by P-ECG was assessed using the area under the curve (AUC) generated from receiver-operating characteristics (ROC) analysis. P<0.05 was considered significant. All computations were performed with JMP (version 13.2.0; SAS, Cary, NC, USA) running under Windows 10 (Microsoft, Redmond, WA, USA).

Results

Baseline Characteristics

The baseline characteristics of the pre-COVID-19 Conventional, the pre-COVID-19 P-ECG, the COVID-19 Conventional, and the COVID-19 P-ECG patients are presented in Table 1. No significant difference was observed with respect to age, gender, culprit vessel, or number of diseased vessels.

Table 1.

Baseline Characteristics

	Conventional group		P-ECG group		P value
	Pre-COVID-19 (n=48)	COVID-19 (n=32)	Pre-COVID-19 (n=23)	COVID-19 (n=64)
Age (years)	72±14	70±13	68±15	70±13	0.68
Female (%)	11 (23)	2 (38)	6 (26)	14 (22)	0.41
Culprit vessel					0.60
LMT (%)	0 (0)	0 (0)	1 (4)	3 (5)
LAD (%)	26 (54)	18 (56)	14 (61)	30 (47)
LCX (%)	3 (6)	3 (9)	1 (4)	6 (9)
RCA (%)	19 (40)	11 (34)	7 (30)	25 (39)
No. diseased vessels					0.19
1 (%)	23 (48)	16 (50)	12 (52)	39 (61)
2 (%)	19 (40)	12 (38)	9 (39)	13 (20)
3 (%)	6 (13)	4 (13)	1 (4)	9 (14)
LMT	0 (0)	0 (0)	1 (4)	3 (5)

COVID-19, Coronavirus disease 2019; LAD, left anterior descending; LCX, left circumflex artery; LMT, left main trunk; P-ECG, prehospital 12-lead electrocardiography system; RCA, right coronary artery.

Comparison of First Medical Contact to Reperfusion Time Between the COVID-19 and Pre-COVID-19 Periods

In the Conventional group, the first medical contact to reperfusion time in the COVID-19 period was significantly longer than that in the pre-COVID-19 period (110±45 vs. 90±31 min; P=0.025; Figure 2). However, there was no significant difference between the 2 periods in the P-ECG group (87±24 vs. 79±16 min; P=0.758; Figure 2).

Figure 2.

Comparison of first medical contact to reperfusion time between the prehospital 12-lead electrocardiography system (P-ECG) and Conventional groups in the pre-COVID-19 and COVID-19 periods.

Comparison of Breakdown Time of First Medical Contact to Reperfusion Time Between the COVID-19 and Pre-COVID-19 Periods

There was no significant difference in the EMS stay time (Figure 3A) or patient transfer time (Figure 3B) between the COVID-19 and pre-COVID-19 periods in either the Conventional or P-ECG groups. Five patients in the Conventional group were excluded from this analysis. Three patients in the pre-COVID-19 period, and 2 patients in the COVID-19 periods were of indeterminate patient EMS stay time or patient transfer time due to unknown onsite departure time.

Figure 3.

(A) Comparison of emergency medical services (EMS) stay time between the prehospital 12-lead electrocardiography system (P-ECG) and Conventional groups in the pre-COVID-19 and COVID-19 periods. (B) Comparison of patient transfer time between the P-ECG and Conventional groups in the pre-COVID-19 and COVID-19 period.

In the Conventional group, the door-to-reperfusion time in the COVID-19 period were significantly longer than that in the pre-COVID-19 period (89±41 vs. 70±29 min; P=0.015; Figure 4). However, there was no significant difference between the 2 periods in the P-ECG group (62±22 vs. 58±15 min; P=0.923; Figure 4).

Figure 4.

Comparison of door-to-reperfusion time between the prehospital 12-lead electrocardiography system (P-ECG) and Conventional groups in the pre-COVID-19 and COVID-19 periods.

Analysis of the Clinical Profile and Outcomes

The clinical profile and outcomes of patients for whom measurement data were available were analyzed (Table 2).

Table 2.

Clinical Data After Admission

	Conventional group		P-ECG group		P value
	Pre-COVID-19 (n=48)	COVID-19 (n=32)	Pre-COVID-19 (n=23)	COVID-19 (n=64)
Killip class (no. Killip 4)	1.1±0.5** (1)	2.0±1.3 (7)	1.4±0.9 (2)	1.6±1.1 (10)	0.0017
Max. CK (U/L)	2,228±2,129	3,281±2,444	2,988±2,848	3,319±3,252	0.18
Ejection fraction (%)	57±9.0*,## (n=48)	49±12 (n=31)	52±8.2 (n=19)	51±10 (n=51)	0.0014
Mortality (%)	2.1	3.1	0	4.7	0.55

*P<0.05 vs. COVID-19 in the Conventional group. **P<0.01 vs. COVID-19 in the Conventional group. ^##P<0.01 vs. COVID-19 in the P-ECG group. Max. CK, maximum creatine kinase. Other abbreviations as in Table 1.

Killip class was greater during the COVID-19 period than during the pre-COVID-19 period in the Conventional group (2.0±1.3 vs. 1.1±0.5; P=0.001). However, there was no significant difference between the COVID-19 and pre-COVID-19 periods in the P-ECG group (1.6±1.1 vs. 1.4±0.9; P=0.835). The number of patients presenting with Killip 4 was 1 in the pre-COVID-19 period in the Conventional group, 7 in the COVID-19 period in the Conventional group, 2 in the pre-COVID-19 period in the P-ECG group, and 10 in the COVID-19 period in the P-ECG group, respectively.

There was no significant difference in maximum CK between the COVID-19 and pre-COVID-19 periods in either the Conventional or P-ECG groups (P=0.18).

LVEF was lower during the COVID-19 period than during the pre-COVID-19 period in the Conventional group (49±12 vs. 57±9.0%; P=0.002). However, there was no significant difference between the COVID-19 and pre-COVID-19 periods in the P-ECG group (51±10 vs. 52±8.2%; P=0.980). Eighteen patients were excluded from this analysis. In the Conventional group, 1 patient in the COVID-19 period in the P-ECG group, 4 patients in the pre-COVID-19 period and 13 patients in the COVID-19 period were of indeterminate ejection fraction.

There was no significant difference in the in-hospital mortality between the COVID-19 and pre-COVID-19 periods in either the Conventional (3.1% vs. 2.1%; P=0.772) or P-ECG (4.7% vs. 0%; P=0.170) groups.

Multivariate logistic regression analysis of the clinical profile for longer time to reperfusion (≥90 min) is shown in Table 3. In the model, Killip class (odds ratio 1.85; 95% CI 1.26–2.72; P=0.0018) was significantly associated with long door-to-reperfusion time (Table 3).

Table 3.

Multivariate Logistic Regression Analysis of the Clinical Profile for Long Door-to-Reperfusion Time (≥90 min)

Valuable	Multivariate P value	Odds ratio	95% CI
Model
Killip class	0.002**	1.85	1.26–2.72
Max. CK (U/L)	0.967	1.00	1.00–1.00
LVEF (%)	0.459	1.02	0.97–1.06

**P<0.01. CI, confidence interval; LVEF, left ventricular ejection fraction; Max. CK, maximum creatine kinase.

Effect of Transport Time Zone and Holiday/Weekday on Door-to-Reperfusion Time in the COVID-19 and Pre-COVID-19 Periods

Table 4 shows the AUC predicting the effect of door-to-reperfusion time by P-ECG in the ROC analysis was the largest on holidays (AUC=0.79; P=0.020), and was not significantly different on weekdays (AUC=0.55; P=0.41) and daytime (AUC=0.54; P=0.77) during the pre-COVID-19 period. In contrast, the AUC was the largest on holidays (AUC=0.77; P=0.0057) and was significant even on weekdays (AUC=0.65; P=0.0097) and daytime (AUC=0.68; P=0.038) in the ROC analysis during the COVID-19 period.

Table 4.

Ability of Defining Factors to Predict the Effect of Door-to-Reperfusion Time With P-ECG Using Receiver-Operating Characteristics Analysis

	Cut-off value (min)	Sensitivity (%)	Specificity (%)	AUC	95% CI	P value
Pre-COVID-19 period
Holiday	68	88	63	0.79	0.62–0.95	0.020*
Weekday	64	80	38	0.55	0.41–0.69	0.41
Nighttime	68	83	62	0.74	0.60–0.87	0.04*
Daytime	39	100	26	0.54	0.37–0.72	0.77
COVID-19 period
Holiday	65	56	92	0.77	0.63–0.92	0.0057**
Weekday	48	46	84	0.65	0.53–0.77	0.0097**
Nighttime	110	100	35	0.69	0.56–0.82	0.0029**
Daytime	59	71	67	0.68	0.55–0.81	0.038*

*P<0.05. **P<0.01. AUC, area under the curve. Other abbreviations as in Tables 1,3.

Discussion

The core findings of the present study are as follows: (1) in the Conventional group, first medical contact to reperfusion time was longer in the COVID-19 period than in the pre-COVID-19 period, while in the P-ECG group, there was no significant difference between the 2 periods; (2) of note, in the Conventional group, door-to-reperfusion time was significantly longer in the COVID-19 period than in the pre-COVID-19 period, while in the P-ECG group, there was no significant difference between the 2 periods; and (3) the ROC analysis predicting the effect of door-to-reperfusion time by P-ECG during both the COVID-19 and pre-COVID-19 periods showed the largest AUC was during holidays. Furthermore, it was not significant on weekdays or daytime during the pre-COVID-19 period, but was significant during weekdays and the daytime during the COVID-19 period.

Impact of the Pandemic on STEMI Patient Transport

Most studies on STEMI patients undergoing primary PCI during the COVID-19 pandemic, including both DTBT and total ischemic time, reported longer treatment times.^12–14 In addition to longer treatment times, clinical outcomes were worse and in-hospital mortality was significantly increased.¹⁵ The prolonged time between arrival of EMS at the scene and reperfusion in this study due to the pandemic was consistent with the previous results. This phenomenon has been noted in many countries around the world; De Luca et al. reported on 16,674 patients treated at 109 high-volume PCI centers in Europe, Latin America, Southeast Asia, and North Africa and found significantly longer treatment times.⁴ A study from 12 facilities in the United States showed that DTBT prolonged from a median of 70 min to 87 min before and after the pandemic.¹⁶ From a systematic review and meta-analysis of 32 papers, it was observed that DTBT was significantly longer during the pandemic by a weighted mean difference of 4.75 min in Western studies and 14.55 min in Eastern studies.⁶ In this study, the door-to-reperfusion time during the COVID-19 period in the Conventional group increased from an average of 70 min to 89 min compared with the pre-COVID-19 period, similar to previous studies. The delay in treatment of STEMI patients seen during the pandemic period in this study was mainly due to prolonged door-to-reperfusion time: imaging such as cardiac computed tomography (CT) and echocardiography to triage STEMI patients with suspected COVID-19,¹⁶ chest CT to screen for COVID-19 pneumonia before primary PCI,¹⁷ and the use of personal protective equipment by health care providers may have prolonged DTBT.¹⁸ These did not affect mortality in the present study, but may have been associated with worsening Killip classification. There were some serious emergency cases that could not afford a 12-lead ECG, and it can be assumed that some cases, especially during the COVID-19 period, would have been transported without a prehospital 12-lead ECG. This may have had some influence on the results of the analysis in this study.

Effects of P-ECG on Treatment Delays in STEMI Patients During the Pandemic

As much as we could retrieve from the past, we have not found any reports describing the effectiveness of P-ECG for delayed treatment of STEMI patients during a pandemic. In this study, there was a significant treatment delay during the COVID-19 period in the Conventional group compared with the pre-COVID-19 period, but there was no significant difference in treatment delay between the 2 periods in the P-ECG group, suggesting that P-ECG may be a useful tool to eliminate treatment delays. The effectiveness of P-ECG was found to provide the greatest advantage in reducing the time from hospital arrival to reperfusion rather than EMT stay time or patient transport time.

Kobayashi et al. showed that chest CT as a screening tool for COVID-19 pneumonia before primary PCI is the most significant cause of delayed DTBT in the COVID-19 phase.¹⁷ They stated that chest CT requires an additional 10–15 min, including travel time, and this additional time directly affects DTBT. In this regard, it was thought that this time was similar to our emergency department situation. Even overcoming this situation, P-ECG seemed to be effective in shortening DTBT during the pandemic period.

Patient Transport Time Showing Efficacy of P-ECG During the Pandemic

In the previous study,¹¹ patients treated with primary PCI during off-hours, referring to weekends, statutory holidays, or night hours on weekdays, had longer DTBT. Treatment during off-hours was an independent predictor of longer DTBT and a longer DTBT was associated with higher mortality.¹¹ We have already reported that P-ECG is useful in urban areas, especially in patients who developed STEMI on weekday nights or during holidays.¹⁰ We described that P-ECG may result in a reduction in time for the cardiologist to know from the EMS that a patient is coming to the hospital in need of primary PCI.¹⁰ Similarly, in this study, the effectiveness of P-ECG was significant, especially during holidays, in the COVID-19 period. The early sharing of information by cardiologists during holidays in the COVID-19 period may have been an important factor, and the same effect may have been more pronounced.

Consideration of the Differences in Clinical Profiles and Outcomes Before and After the Pandemic

Previous studies have shown that time-sensitive interventions such as DTBT are important determinants of mortality risk in STEMI patients, especially those with Killip classification ≥2 during the COVID-19 pandemic.¹⁹ Shortening specific treatment intervals significantly reduces this risk.¹⁹ Another study showed that DTBT ≤90 min affected the 30-day mortality in STEMI patients transported by EMS with Killip 2, although not those with Killip 1. During the COVID-19 pandemic, especially in STEMI patients with Killip 1, there may be a grace period to confirm antigen and PCR test results to prevent the spread of infection. In contrast, early reperfusion therapy should be performed as quickly as possible in STEMI patients with Killip 2.²⁰ Although some studies showed a positive effect of P-ECG on LVEF^21,22 and others showed no significant difference,^23,24 the present study showed that P-ECG was effective in eliminating the significant difference in the trend of LVEF decline during the pandemic period.

In this study, the absence of Killip class and LVEF deterioration during the pandemic period in the P-ECG group, which had been observed in the Conventional group, may be due to the effect of P-ECG in shortening the time from onset of illness to treatment, although an exact reason is not clear.

Given the multifaceted impact of the pandemic, it would be important in the future to not only compare pre- and post-pandemic conditions in order to fully understand the changes in patient transport and management, but also to examine how these parameters changed or ‘recovered’ as the pandemic progressed. It would also be valuable in the future to investigate factors that may reduce door-to-reperfusion time, such as the ability of P-ECG to avoid screening for pneumonia or infection with COVID-19 and lung CT scan, or to perform them in a shorter time.

Study Limitations

Several limitations need to be considered in this study. First, when analyzed using the definitions of urban and rural in this study, it is likely that there are cases in which transportation from outside the nearby metropolitan area is more distant, even within the same city. Second, the time from onset to reperfusion could not be assessed because the time of onset of STEMI was unknown. Third, the small number of patients in this study may have been insufficient to make meaningful adjustments or draw firm conclusions about the broad impact of COVID-19 on transport and outcomes for STEMI patients. Fourth, information on infarct size, troponin levels, and comorbidities was not available from eligible patients, which prevented a more detailed assessment of ACS severity and outcome. Last, not all PCI institutions participating were able to cooperate in providing data on the Conventional group cases.

Conclusions

Our results demonstrated that P-ECG might provide advantages for patient transport and outcomes in urban STEMI patients during the COVID-19 pandemic.

Acknowledgments

We thank all the cardiologists at the hospitals and firemen at the fire departments that participated in the Oita remote image transmission system. We also thank Masae Hayashi, and Tomomi Syuto for their assistance with the manuscripts.

Sources of Funding

This research received no financial support and no grant from any funding agency in the public, commercial or not-for-profit sectors.

Disclosures

N.T. is a member of Circulation Reports’ Editorial Team.

Statement of Ethics

The authors have no ethical conflicts to disclose.

IRB Information

The Oita University Research Ethics Committee (No. 1262) approved this study.

References

• 1.   Alharbi A, Franz A, Alfatlawi H, Wazzan M, Alsughayer A, Eltahawy E, et al. Impact of COVID-19 pandemic on the outcomes of acute coronary syndrome. Curr Probl Cardiol 2023; 48: 101575, doi:10.1016/j.cpcardiol.2022.101575.
• 2.   Takasaki A, Kurita T, Yanagisawa M, Ino A, Hiramatsu D, Ikami A, et al. Demographic trends and changes in the pre- and in-hospital medical management of acute myocardial infarction during the first 12 months of the COVID-19 pandemic in Mie Prefecture: Report from the Mie ACS Registry. Circ Rep 2022; 4: 412–421, doi:10.1253/circrep.CR-22-0050.
• 3.   Piccolo R, Bruzzese D, Mauro C, Aloia A, Baldi C, Boccalatte M, et al. Population trends in rates of percutaneous coronary revascularization for acute coronary syndromes associated with the COVID-19 outbreak. Circulation 2020; 141: 2035–2037.
• 4.   De Luca G, Algowhary M, Uguz B, Oliveira DC, Ganyukov V, Zimbakov Z, et al. COVID-19 pandemic, mechanical reperfusion and 30-day mortality in ST elevation myocardial infarction. Heart 2022; 108: 458–466, doi:10.1136/heartjnl-2021-319750.
• 5.   Wienbergen H, Retzlaff T, Schmucker J, Marin LAM, Rühle S, Garstka D, et al. Impact of COVID-19 pandemic on presentation and outcome of consecutive patients admitted to hospital due to ST-elevation myocardial infarction. Am J Cardiol 2021; 151: 10–14, doi:10.1016/j.amjcard.2021.04.011.
• 6.   Chew NWS, Ow ZGW, Teo VXY, Heng RRY, Ng CH, Lee CH, et al. The global effect of the COVID-19 pandemic on STEMI care: A systematic review and meta-analysis. Can J Cardiol 2021; 37: 1450–1459, doi:10.1016/j.cjca.2021.04.003.
• 7.   Piccolo R, Leone A, Avvedimento M, Galano G, Esposito G. Pre-hospital electrocardiogram in patients with acute myocardial infarction during the COVID-19 pandemic. Eur Heart J Acute Cardiovasc Care 2022; 11: 510–511, doi:10.1093/ehjacc/zuac051.
• 8.   Yufu K, Shimomura T, Fujinami M, Nakashima T, Saito S, Ayabe R, et al. Impact of mobile cloud electrocardiography system on door-to-balloon time in patients with acute coronary syndrome in Oita Prefecture. Circ Rep 2019; 1: 241–247.
• 9.   Kawano K, Yufu K, Shimomura T, Sato H, Ishii Y, Yonezu K, et al. Prehospital 12-lead electrocardiography system in Oita assisted transport of ‘true’ acute coronary syndrome patients to optimal institutes. Circ J 2022; 86: 1481–1487.
• 10.   Yufu K, Shimomura T, Kawano K, Sato H, Yonezu K, Saito S, et al. Usefulness of prehospital 12-lead electrocardiography system in ST-segment elevation myocardial infarction patients in Oita: Comparison between urban and rural areas, weekday daytime and weekday nighttime/holidays. Circ J 2024; 88: 1293–1301, doi:10.1253/circj.CJ-23-0365.
• 11.   Rashid MK, Wells G, So DY, Chong AY, Dick A, Froeschl M, et al. Off-hours presentation, door-to-balloon time, and clinical outcomes in patients referred for primary percutaneous coronary intervention. J Invasive Cardiol 2023; 35: E185–E193, doi:10.25270/jic/22.00367.
• 12.   Xiang D, Xiang X, Zhang W, Yi S, Zhang J, Gu X, et al. Management and outcomes of patients with STEMI during the COVID-19 pandemic in China. J Am Coll Cardiol 2020; 76: 1318–1324.
• 13.   De Luca G, Verdoia M, Cercek M, Jensen LO, Vavlukis M, Calmac L, et al. Impact of COVID-19 pandemic on mechanical reperfusion for patients with STEMI. J Am Coll Cardiol 2020; 76: 2321–2330, doi:10.1016/j.jacc.2020.09.546.
• 14.   Kwok CS, Gale CP, Kinnaird T, Curzen N, Ludman P, Kontopantelis E, et al. Impact of COVID-19 on percutaneous coronary intervention for ST-elevation myocardial infarction. Heart 2020; 106: 1805–1811, doi:10.1136/heartjnl-2020-317650.
• 15.   Popovic B, Varlot J, Metzdorf PA, Jeulin H, Goehringer F, Camenzind E. Changes in characteristics and management among patients with ST-elevation myocardial infarction due to COVID-19 infection. Catheter Cardiovasc Interv 2021; 97: E319–E326, doi:10.1002/ccd.29114.
• 16.   Garcia S, Stanberry L, Schmidt C, Sharkey S, Megaly M, Albaghdadi MS, et al. Impact of COVID-19 pandemic on STEMI care: An expanded analysis from the United States. Catheter Cardiovasc Interv 2021; 98: 217–222, doi:10.1002/ccd.29154.
• 17.   Kobayashi S, Sakakura K, Jinnouchi H, Taniguchi Y, Tsukui T, Watanabe Y, et al. Comparison of door-to-balloon time and in-hospital outcomes in patients with ST-elevation myocardial infarction between before versus after COVID-19 pandemic. Cardiovasc Interv Ther 2022; 37: 641–650, doi:10.1007/s12928-022-00836-4.
• 18.   Mahmud E, Dauerman HL, Welt FGP, Messenger JC, Rao SV, Grines C, et al. Management of acute myocardial infarction during the COVID-19 pandemic: A position statement from the Society for Cardiovascular Angiography and Interventions (SCAI), the American College of Cardiology (ACC), and the American College of Emergency Physicians (ACEP). J Am Coll Cardiol 2020; 76: 1375–1384, doi:10.1016/j.jacc.2020.04.039.
• 19.   Zhang L, Zeng J, Huang H, Zhu Y, Peng K, Liu C, et al. Impact of chest pain center quality control indicators on mortality risk in ST-segment elevation myocardial infarction patients: A study based on Killip classification. Front Cardiovasc Med 2024; 10: 1243436, doi:10.3389/fcvm.2023.1243436.
• 20.   Sakamoto A, Yanishi K, Shoji K, Kawamata H, Hori Y, Fujioka A, et al. Impact of door-to-balloon time reduction depending on the Killip classification in patients with ST-segment elevation myocardial infarction transported by emergency medical services. Int Heart J 2022; 63: 226–234, doi:10.1536/ihj.21-583.
• 21.   Canto JG, Rogers WJ, Bowlby LJ, French WJ, Pearce DJ, Weaver WD. The prehospital electrocardiogram in acute myocardial infarction: Is its full potential being realized? National Registry of Myocardial Infarction 2 Investigators. J Am Coll Cardiol 1997; 29: 498–505, doi:10.1016/s0735-1097(96)00532-3.
• 22.   Sørensen JT, Terkelsen CJ, Nørgaard BL, Trautner S, Hansen TM, Bøtker HE, et al. Urban and rural implementation of pre-hospital diagnosis and direct referral for primary percutaneous coronary intervention in patients with acute ST-elevation myocardial infarction. Eur Heart J 2011; 32: 430–436, doi:10.1093/eurheartj/ehq437.
• 23.   Carstensen S, Nelson GC, Hansen PS, Macken L, Irons S, Flynn M, et al. Field triage to primary angioplasty combined with emergency department bypass reduces treatment delays and is associated with improved outcome. Eur Heart J 2007; 28: 2313–2319, doi:10.1093/eurheartj/ehm306.
• 24.   Brown JP, Mahmud E, Dunford JV, Ben-Yehuda O. Effect of prehospital 12-lead electrocardiogram on activation of the cardiac catheterization laboratory and door-to-balloon time in ST-segment elevation acute myocardial infarction. Am J Cardiol 2008; 101: 158–161, doi:10.1016/j.amjcard.2007.07.082.