Circulation Journal
Online ISSN : 1347-4820
Print ISSN : 1346-9843
ISSN-L : 1346-9843
Acute Coronary Syndrome
Impact of the COVID-19 Pandemic on Door-to-Balloon Time for Primary Percutaneous Coronary Intervention ― Results From the Singapore Western STEMI Network ―
Nicholas WS ChewChing-Hui SiaHwee-Lin WeeLoh Jia-Da BenedictSaurabh RastogiPipin KojodjojoWei Ping Daniel ChorBenjamin Sieu-Hon LeongBrandon Chi-Ping KohHowen TamLit-Sin QuekWinnie CH SiaKalyar Win SawBenjamin Wei-Liang TungZan Zhe-Yan NgAnand AmbhoreEdgar Lik-Wui TayKoo-Hui ChanChi-Hang LeeJoshua Ping-Yun LohAdrian Fatt-Hoe LowMark Yan-Yee ChanTiong-Cheng YeoHuay-Cheem TanPoay-Huan Loh
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2021 年 85 巻 2 号 p. 139-149

詳細
Abstract

Background: Little is known about the effect of the coronavirus disease 2019 (COVID-19) pandemic and the outbreak response measures on door-to-balloon time (D2B). This study examined both D2B and clinical outcomes of patients with STEMI undergoing primary percutaneous coronary intervention (PPCI).

Methods and Results: This was a retrospective study of 303 STEMI patients who presented directly or were transferred to a tertiary hospital in Singapore for PPCI from October 2019 to March 2020. We compared the clinical outcomes of patients admitted before (BOR) and during (DOR) the COVID-19 outbreak response. The study outcomes were in-hospital death, D2B, cardiogenic shock and 30-day readmission. For direct presentations, fewer patients in the DOR group achieved D2B time <90 min compared with the BOR group (71.4% vs. 80.9%, P=0.042). This was more apparent after exclusion of non-system delay cases (DOR 81.6% vs. BOR 95.9%, P=0.006). Prevalence of both out-of-hospital cardiac arrest (9.5% vs. 1.9%, P=0.003) and acute mitral regurgitation (31.6% vs. 17.5%, P=0.006) was higher in the DOR group. Mortality was similar between groups. Multivariable regression showed that longer D2B time was an independent predictor of death (odds ratio 1.005, 95% confidence interval 1.000–1.011, P=0.029).

Conclusions: The COVID-19 pandemic and the outbreak response have had an adverse effect on PPCI service efficiency. The study reinforces the need to focus efforts on shortening D2B time, while maintaining infection control measures.

The coronavirus disease 2019 (COVID-19) pandemic has strained the global health system in an unprecedented manner. The effect on the delivery of health services is likely to be greater in time-sensitive services such as primary percutaneous coronary intervention (PPCI) for acute ST-segment elevation myocardial infarction (STEMI). Delay in treatment, including time from symptom onset to PCI-capable hospital (symptom onset-to-door [O2D]) and from arrival at PCI-capable hospital to device deployment (door-to-balloon [D2B]), can adversely affect the outcome of STEMI patients.14 Major guidelines have advocated early intervention with D2B <60–90 min.24 In the wake of the COVID-19 pandemic, PPCI services have been reorganized in order to meet local or national strategies to cope with the strain from the pandemic.58

Singapore has experienced a surge of COVID-19 cases. The Disease Outbreak Response System Condition (DORSCON) alert level, the national disease outbreak warning system, was raised to Orange on 7 February 2020. This indicated that the spread of disease was expected to result in a moderate to high public health impact,911 necessitating drastic changes to public health measures and workflows, such as deferring elective procedures. By 31 March 2020, the number of confirmed COVID-19 cases in Singapore had increased from 33, when DORSCON Orange was implemented, to 926 (165.4/1,000,000 population) with 3 patients having died of the infection.9

Reports have suggested an estimated 60-min intrinsic delay from diagnosis to reperfusion, especially in hospitals overwhelmed with COVID-19 patients, because of the strain on the emergency medical system and the requirement to don personal protective equipment (PPE).12 Paradoxically, there has also been an unexplained phenomenon of a large reduction in the number of STEMI patients.6,13 There is concern that STEMI patients tended to present later because of fear of COVID-19 exposure in hospital settings, with the consequence of STEMI-related complications.12 Hence, we aimed to evaluate the effect of the COVID-19 outbreak response on D2B time and clinical outcomes of STEMI patients undergoing PPCI within our local PPCI network that serves the community in the western area of Singapore before and after the implementation of DORSCON Orange.

Methods

Setting and Design

This was a retrospective cohort study of 303 consecutive patients who presented with STEMI and underwent PPCI at National University Hospital Singapore (NUH), a PCI-capable tertiary healthcare institution, between 1 October 2019 and 31 March 2020. The patients presented via 2 routes: (1) a direct visit, in which the patient either self-presented to the Emergency Department (ED) or was brought in by the emergency medical services (EMS), or (2) via an interhospital transfer from 2 other hospitals (Ng Teng Fong General Hospital [NTFGH] and Alexandra Hospital [AH]), which together with NUH, form the Western STEMI network in Singapore. The Western STEMI network has received 531–571 cases of STEMI per year since 2017, with a population in the catchment area of approximately 1.2 million. All patients diagnosed with STEMI by the EMS have their ECG transmitted to the ED and are transferred directly to NUH on a 24-h/7-day basis. Prehospital activation is defined as an alert by the EMS occurring >10 min prior to arrival at the receiving PCI-capable hospital.13 When a STEMI is confirmed by the ED, the PPCI team is activated. The duty cardiology fellow assesses the patient and obtains informed consent. The patient is then brought to the catheterization laboratory for PPCI. Prior to DORSCON Orange, STEMI patients who self-presented to NTFGH (distance between NTFGH and NUH is 7.3 km) after-hours or to AH (distance between AH and NUH is 3.1 km) throughout the day were transferred to NUH for emergency treatment. After implementation of DORSCON Orange, all STEMI patients were diverted to the NUH for PPCI.

STEMI was diagnosed by concomitant raised cardiac troponin levels with at least 1 value >99th percentile of the upper reference limit, and at least 1 of the following: symptoms of angina, ECG changes (new ST-elevation in 2 contiguous leads, measuring >0.2 mV in leads V1–3 or 0.1 mV in all other leads, or new-onset left bundle branch block) or cardiac imaging suggestive of MI (regional wall motion abnormality). Evolved MI was defined as a rise and fall of troponin, together with development of pathologic Q waves and ischemic ECG changes.14 During the study period, NUH was actively involved in the care of COVID-19 patients. All patients were screened with a nasopharyngeal swab for COVID-19 testing in accordance with Ministry of Health guidelines and the suspect case definition. As of 4 February 2020, the suspect case criteria included (1) patients with pneumonia and travel to mainland China within 14 days before onset of illness; and (2) with acute respiratory illness within 14 days before onset of illness, had been to Hubei or Zhejiang Province, China, or been to a hospital in China or had contact with a confirmed COVID-19 case.15 Furthermore, the Ministry of Health developed a workflow for surveillance of patients who did not meet the suspect case definition, in which patients with clinical assessment of pneumonia or were medically unstable would need to be evaluated in the ED for COVID-19.16

Study Periods

The study defined 2 time periods for comparison: (1) before the outbreak response (BOR), from 1 October 2019 to 6 February 2020, and (2) during the outbreak response (DOR), from 7 February 2020 to 31 March 2020. This study focused on the time period before and after 7 February 2020 because that was the date when the Singapore DORSCON alert level was raised to Orange, resulting in hospitals implementing outbreak control protocols and reorganizing all emergency workflows.

Data Collection and Study Outcomes

Data on demographics, clinical characteristics, mode of presentation, clinical outcomes, procedural-related variables and complications, and discharge medications were collected from the electronic medical records. Differences between the study groups were compared. All pertinent information was recorded as part of the STEMI registry of the Western STEMI network.

The study defined the symptom O2D time as the time from the onset of chest pain to the time the patient presented to the hospital’s ED. The recipient hospital’s D2B time was defined as the time taken from the patient’s arrival at the receiving hospital to the time of first device deployment, defined as balloon inflation, manual thrombectomy or direct stenting, during PCI.4 The first D2B time (Dto1B) was defined as time of arrival at the referring hospital to the time of first device deployment at the receiving hospital.17 D1toB was further categorized according to the following time intervals: the door-in to door-out (DIDO) time was defined as the time from arrival to discharge at the referring hospital, ambulance transport time from referring to receiving hospital (D1toD2), and the time from arrival at receiving hospital to first device deployment during PCI (D2toB).17

The D2toB time analysis was done for patients presenting directly to the PPCI-capable hospital (either as a self-presentation or via EMS). This included comparison of the median D2toB time and D2toB time within 60 and 90 min. Subgroup analysis was done on the D2toB time in the patients without non-system delays. Examples of non-system delays included delays in obtaining procedure consent, those presenting with cardiac arrest requiring resuscitation before PCI, and evolved MI.18

Analysis of the D1toB time and its components of DIDO, D1toD2 and the receiving hospital’s D2toB for the hospital transfer cases was done separately.

The primary outcome of the study was in-hospital death. Other outcomes included treatment time intervals, readmission within 30 days and cardiogenic shock, which was defined as systolic blood pressure (SBP) <90 mmHg for >30 min or the need for supportive intervention to maintain SBP >90 mmHg. Acute mitral regurgitation (MR) was defined as new-onset MR post-STEMI, in comparison with a previous echocardiogram, or based on the physician’s clinical assessment.

Statistical Analysis

Categorical variables are expressed as percentages and continuous variables as median with interquartile range (IQR). Between-group comparisons were done using Mann-Whitney U test for continuous variables and Pearson’s chi-square test (or Fisher’s test where appropriate) for categorical variables. Univariable and multivariable logistic regression analysis was performed in order to identify independent factors associated with in-hospital death. Odds ratios (OR) with 95% confidence intervals (95% CIs) were calculated.

We examined the effect of D2B on in-hospital death by adjusting for traditional confounders. The multivariable logistic regression model included variables such as D2B time, admission during the outbreak response, as well as traditional prognostic factors in STEMI patients. As such, the following important covariates were included: age, left ventricular ejection fraction post-STEMI, previous coronary artery disease, native left main stem artery (LMS) or left anterior descending artery (LAD) infarction, and the initial presentation of cardiac arrest, Killip class III presentation or cardiogenic shock. With regards to the multivariable model, the D2B time was taken as the recipient hospital’s D2B time (D2toB) for patients presenting directly, and first D2B time (D1toB) for interhospital transfer patients. A P value <0.05 was considered statistically significant.

All statistical analyses were performed using IBM SPSS Statistics for Windows, Version 25.0 (Armonk, NY, USA). The study was conducted in accordance with the revised Declaration of Helsinki and approved by the institutional and local ethics committees.

Results

Baseline Characteristics BOR and DOR the Outbreak Response

A total of 303 patients with STEMI underwent PPCI during the study period and only 10 were considered to have high risk of COVID-19 infection; none tested positive for COVID-19. Overall, 130 (42.9%) patients were admitted via the EMS, 85 (28.1%) were self-presentations, and 88 (29.0%) were interhospital transfers. There were 208 (68.6%) patients BOR and 95 (31.4%) DOR. Although the route of first medical contact was similar, there was a higher proportion of prehospital activations in the DOR group compared with the BOR group. The prevalence of out-of-hospital cardiac arrest was also higher in the DOR group compared with the BOR group (9.5% vs. 1.9%, P=0.003). All of the out-of-hospital cardiac arrests, assessed by independent qualified interventional cardiologists and coronary care unit physicians, were attributed to acute MI. The baseline demographic and clinical characteristics and initial hemodynamic variables were similar between groups (Table 1).

Table 1. Baseline Characteristics and Clinical History of Patients Admitted for ST-Elevation Myocardial Infarction, Before (BOR) and During (DOR) an Outbreak Response (n=303) to COVID19 Pandemic
  Total
(n=303)
BOR
(n=208)
DOR
(n=95)
P value
Demographics
 Age (years) 58 (49–66) 57 (49–64) 59 (48–69) 0.218
 Sex, male 188 (62.0) 134 (64.4) 54 (56.8) 0.377
 Ethnicity       0.487
  Chinese 151 (49.8) 101 (48.6) 50 (52.6)  
  Malay 62 (20.5) 45 (21.6) 17 (17.9)  
  Indian 62 (20.5) 40 (19.2) 22 (23.2)  
  Other 28 (9.2) 22 (10.6) 6 (6.3)  
Medical history
 Hypertension 165 (54.5) 114 (54.8) 51 (53.7) 0.855
 Diabetes mellitus 110 (36.3) 76 (36.5) 34 (35.8) 0.900
 Hyperlipidemia 201 (66.3) 145 (69.7) 56 (58.9) 0.066
 Current smoker 175 (57.8) 122 (58.7) 53 (55.8) 0.640
 Significant family cardiac history 39 (12.9) 25 (12.0) 14 (14.7) 0.512
 Congestive cardiac failure 4 (1.3) 1 (1.1) 1 (1.4) 0.783
 Atrial fibrillation 7 (2.3) 5 (2.4) 2 (2.1) 0.872
 CKD (eGFR <60 mL/min/1.73 m2) 20 (6.6) 15 (7.3) 5 (5.3) 0.526
 Stroke 11 (3.6) 5 (2.4) 6 (6.3) 0.091
 Previous myocardial infarction 30 (9.9) 22 (10.6) 8 (8.4) 0.560
 Previous PCI 39 (12.9) 27 (13.0) 12 (12.6) 0.933
 Previous CABG 0 0 0  
First medical contact
 Direct visit: emergency medical service 130 (42.9) 90 (43.3) 40 (42.1) 0.849
 Direct visit: hospital ED 85 (28.1) 61 (29.3) 24 (25.3) 0.465
 Interhospital transfer 88 (29.0) 57 (27.4) 31 (32.6) 0.352
 Prehospital activation (for EMS) 79 (49.1) 49 (43.4) 30 (62.5) 0.027*
Presenting diagnosis
 STEMI 265 (87.5) 185 (88.9) 80 (84.2) 0.249
 Evolved STEMI 25 (8.3) 19 (9.1) 6 (6.3) 0.408
 Out-of-hospital cardiac arrest 13 (4.2) 4 (1.9) 9 (9.5) 0.003*
Initial hemodynamics
 Heart failure (Killip 3) 39 (13.0) 27 (13.1) 12 (12.6) 0.909
 LVEF, % 45 (40–55) 45 (40–55) 48 (38–55) 0.842
Culprit vessel
 Left main coronary artery 4 (1.3) 4 (1.9) 0 0.176
 Left anterior descending artery 171 (56.4) 113 (54.3) 58 (61.0) 0.307
 Left circumflex artery 32 (10.6) 23 (11.1) 9 (9.5) 0.700
 Right coronary artery 96 (31.7) 68 (32.7) 28 (29.5) 0.619
Procedural characteristics
 No. of stents       0.721
  0 56 (18.6) 38 (18.4) 18 (18.9)  
  1 188 (63.1) 130 (63.1) 58 (61.1)  
  2 49 (16.3) 34 (16.5) 15 (15.8)  
  3 8 (2.7) 4 (1.9) 4 (4.2)  
 Use of glycoprotein IIb/IIIa inhibitors 88 (29.2) 60 (29.1) 28 (29.5) 0.951
 Adjunct devices       0.694
  IABP 28 (9.2) 21 (10.1) 7 (7.4)  
  Transvenous pacing 5 (1.7) 3 (1.4) 2 (2.1)  
 Pre-PCI TIMI flow       0.089
  0 231 (77.8) 164 (80.4) 67 (72.0)  
  1 11 (3.7) 6 (2.9) 5 (5.4)  
  2 27 (9.1) 20 (9.8) 7 (7.5)  
  3 28 (9.4) 14 (6.9) 14 (15.1)  
 Post-PCI TIMI flow       0.276
  0 7 (2.3) 5 (2.4) 2 (2.1)  
  1 2 (0.7) 1 (0.5) 1 (1.1)  
  2 13 (4.3) 12 (5.8) 1 (1.1)  
  3 278 (92.7) 188 (91.3) 90 (95.7)  
 PCI success 293 (97.3) 202 (98.1) 91 (95.8) 0.255
 Requiring CABG 3 (1.0) 2 (1.0) 1 (1.1) 0.947
Complications
 Sepsis 18 (6.0) 8 (3.9) 10 (10.5) 0.024*
 New-onset atrial fibrillation 21 (7.0) 12 (5.8) 9 (9.5) 0.248
 Severe bleeding 26 (8.6) 14 (6.8) 12 (12.6) 0.094
 Requiring transfusion 3 (1.0) 1 (0.5) 2 (2.1) 0.189
 Ventricular septal rupture 0 0 0  
 Acute mitral regurgitation 66 (21.9) 36 (17.5) 30 (31.6) 0.006*
 Pericardial tamponade 1 (0.3) 1 (0.5) 0 0.496
 Post-procedural stroke 5 (1.3) 2 (1.0) 2 (2.1) 0.424
 Arrhythmia
  Non-sustained ventricular tachycardia 20 (6.6) 15 (7.3) 5 (5.3) 0.513
  Sustained ventricular tachycardia 11 (3.7) 9 (4.4) 2 (2.1) 0.331
  Ventricular fibrillation 32 (10.6) 18 (8.7) 14 (14.7) 0.117
 Acute kidney injury 51 (16.9) 34 (16.5) 17 (17.9) 0.765
 Requiring intubation 43 (14.3) 24 (11.7) 19 (20.0) 0.054
 Hospital admission duration, days 4 (4–5) 4 (4–5) 4 (4–6) 0.156
Discharge medications
 Aspirin 294 (97.7) 202 (98.1) 92 (96.8) 0.515
 P2Y12
  Clopidogrel 10 (3.3) 7 (3.4) 3 (3.2) 0.914
  Ticagrelor 291 (96.7) 199 (96.9) 92 (96.8) 0.914
 Warfarin 11 (3.7) 9 (4.4) 2 (2.1) 0.331
 NOAC 18 (6.0) 12 (5.8) 6 (6.3) 0.868
 β-blocker 233 (77.7) 158 (76.3) 75 (80.6) 0.406
 ACEI 201 (67.2) 135 (65.5) 66 (71.0) 0.354
 Statins 284 (93.7) 194 (3.3) 90 (94.7) 0.844

*P<0.05. Categorical data presented as n (%). Continuous data presented as median values (interquartile range). ACEI, angiotensin-converting enzyme inhibitor; CABG, coronary artery bypass graft; CKD, chronic kidney disease; LVEF, left ventricular ejection fraction; PCI, percutaneous coronary intervention; STEMI, ST-segment elevation myocardial infarction; TIMI flow, Thrombolysis In Myocardial Infarction flow grading system.

The majority of patients presented with LAD (56.4%) as the culprit lesion, followed by the right coronary artery (31.7%), left circumflex artery (10.6%) and left main coronary artery (1.3%). The number of stents used, adjunct mechanical circulatory support devices and PCI success were similar between groups (Table 1).

The rates of sepsis (10.5% vs. 3.9%, P=0.024) and acute MR (31.6% vs. 17.5%, P=0.006) were higher in the DOR group compared with the BOR group. Incidences of bleeding, mechanical and arrhythmic complications were similar between groups. There was no difference in hospital admission duration between groups. Overall, there was adequate guideline-directed medical therapy at discharge (Table 1).

Study Outcomes BOR and DOR the Outbreak Response

The prevalence of cardiogenic shock and in-hospital death was similar between the BOR and DOR groups regardless of the mode of presentation. The 30-day readmission rate was lower in the DOR group compared with the BOR group (8.4% vs. 20.2%, P=0.010). In the BOR group, 21 of 42 (50%) readmissions were for elective staged PCI, but only 1 of 8 (12.5%) readmissions in the DOR group was a staged PCI. After excluding these elective admissions, the rate of unplanned readmission was similar between the DOR and BOR groups (7.4% vs. 10.1%, P=0.447). The main reasons for unplanned 30-day readmissions (n=28) included acute decompensated heart failure (35.7%, n=10), atypical chest pain (32.1%, n=9), musculoskeletal-related bleeding (10.7%, n=3), and non-cardiac related readmissions (21.5%, n=6). The incidence of heart failure readmission in the study cohort was 3% within 30 days, with the main precipitants identified as symptomatic ischemic MR, sepsis, residual coronary artery disease awaiting staged PCI, medication compliance and fluid indiscretion. These patients were readmitted for first-onset heart failure with reduced ejection fraction, and the median duration of the index STEMI hospital stay for the heart failure group was similar to that of the whole cohort (i.e., 5 days). The incidence of heart failure readmission in the BOR group was 3.8%, and 2.1% in the DOR group.

Door-to-Balloon Time BOR and DOR the Outbreak Response

Of the patients who presented directly (either self-presenting or via EMS, [n=215]), 133 (63.3%) had a D2toB time <60 min, and 168 (80.0%) had a D2toB time <90 min. There were fewer patients with D2toB time <90 min in the DOR group compared to the BOR group (71.4% vs. 80.9%, P=0.042). The O2D and D2toB times, or proportion of patients with D2toB time <60 min, were similar between groups (Table 2). By assessing the percentage of patients with D2toB within 60 and 90 min on a 2-weekly basis, the trend was similar before and during the outbreak response but with a transient decrease between weeks 17–18 (i.e., the 2 weeks prior to the implementation of DORSCON Orange) (Figure 1A). In the subgroup of 139 (64.7%) patients who did not encounter any in-hospital non-system delay, a similar trend was observed (Table 2, Figure 1B).

Table 2. Comparison of Symptom Onset-to-Door Time (O2D), Door-in to Door-out Time (DIDO), Ambulance Transport Time (D1toD2), Receiving Hospital Door-to-Balloon Time (D2toB), First Door-to-Balloon Time (D1toB), and Study Outcomes for Patients With STEMI Undergoing Primary PCI, Before and During COVID-19 Outbreak Response (n=303)
  Presentation: direct visit or EMS (n=215) Presentation:
interhospital transfer (n=88)
All cases (n=215) Excluding cases of non-system
delay (n=139)
BOR
(n=152)
DOR
(n=63)
P value BOR
(n=100)
DOR
(n=39)
P value BOR
(n=57)
DOR
(n=31)
P value
Duration, min
 O2D 126
(73–259)
121
(70–229)
0.587 107
(62–197)
124
(75–236)
0.319 231
(125–510)
242
(140–353)
0.333
 DIDO             39
(28–76)
43
(32–63)
0.493
 D1toD2             10
(7–14)
11
(8–16)
0.252
 D2toB 52
(39–74)
55
(39–74)
0.426 42
(35–52)
43
(33–55)
0.717 30
(26–39)
32
(23–42)
0.556
 D1toB             85
(71–114)
94
(76–123)
0.493
 Receiving hospital
D2toB <60 min
98 (64.4) 35 (55.6) 0.126 85 (87.6) 30 (78.9) 0.202 52 (98.1) 26 (86.7) 0.035*
 Receiving hospital
D2toB <90 min
123 (80.9) 45 (71.4) 0.042* 93 (95.9) 31 (81.6) 0.006* 57 (100) 31 (100) NA
 D1toB <120 min             42 (75.0) 22 (71.0) 0.683
Study outcomes
 Cardiogenic shock 20 (13.2) 10 (15.6) 0.658 3 (3.0) 1 (2.6) 0.890 4 (7.1) 3 (9.7) 0.677
 Readmission within
30 days
30 (19.7) 4 (6.3) 0.012* 22 (22.0) 1 (2.6) 0.006* 12 (21.1) 4 (12.9) 0.344
 In-hospital death 12 (7.9%) 4 (6.3%) 0.665 2 (2.0) 1 (2.6) 0.837 6 (10.5) 1 (3.2) 0.227

*P<0.05. Continuous variables presented as median (interquartile range) in minutes. Categorical variables presented as n (%). Abbreviations as in Table 1.

Figure 1.

(A) Percentage of study population (direct and emergency medical service (EMS) presentations), inclusive of non-system delays, with door-to-balloon time <60 and 90 min categorized 2-weekly, before and during the COVID-19 outbreak response (n=215). (B) Percentage of study population (direct and EMS visits), excluding non-system delays, with door-to-balloon time <60 and 90 min categorized 2-weekly, before and during the COVID-19 outbreak response (n=139). (C) Percentage of study population (interhospital transfers) with first door-to-balloon time (D1toB) <120 min categorized 2-weekly, before and during the COVID-19 outbreak response (n=88). (D) Percentage of study population (interhospital transfers), excluding non-system delays, with D1toB <120 min categorized 2-weekly, before and during the COVID-19 outbreak response (n=55). No cases at this time point. COVID19, coronavirus disease 2019.

Among the interhospital transfer patients (n=88), the median times of O2D, DIDO, D1toD2, D2toB, D1toB were 233 (IQR 131–332), 41 (IQR 29–72), 10 (IQR 8–15), 31 (IQR 24–40) and 90 (IQR 73–120) min, respectively; 73.6% of these patients had a D1toB time <120 min. The proportion of D1toB time <120 min was lower in the DOR group compared with the BOR group (71.0% vs. 75.0%, P=0.683), although it did not reach statistical significance (Table 2). There was no apparent pattern in the 2-weekly trend in D1toB time <120 min (Figure 1C,D).

In the study population, after exclusion of procedures with non-system delays, there was a trend of a higher median D2toB time in the 2 weeks (weeks 17–18) prior to implementation of DORSCON Orange due to a longer time needed in the respective EDs. The median D2toB time and sector time are shown 2-weekly for both groups of patients presenting directly (either self-presenting or via EMS), and interhospital transfer patients (Figure 2A,B).

Figure 2.

(A) Median door-to-balloon time and sector time of study population (direct and emergency medical service presentations), excluding non-system delays, per 2 weeks. (B) Median first door-to-balloon time and sector time of study population (interhospital transfers), excluding non-system delays, per 2 weeks. *A patient with delayed diagnosis and door-in to door-out time of 433 min was removed from the graph (week 7–8) to allow optimal graph presentation before the outbreak response period.

Multivariable logistic regression analysis showed that the D2toB time was independently associated with in-hospital death (OR 1.005, 95% CI 1.000–1.011, P=0.029). Other independent predictors of in-hospital death included older age, native LMS or LAD infarction, and cardiac arrest of Killip class III on presentation or cardiogenic shock. Importantly, admission during the outbreak response period was not associated with in-hospital death (Table 3).

Table 3. Multivariable Logistic Regression Analysis for In-Hospital Death of Patients With STEMI Treated With Primary Percutaneous Intervention
  OR (95% CI) P value
Age 1.082 (1.026–1.153) 0.007*
LVEF 0.948 (0.891–1.004) 0.076
Previous CAD 0.700 (0.095–3.965) 0.706
Native LMS or LAD infarction 15.081 (2.900–132.617) 0.004*
Cardiac arrest or Killip class III on presentation, or cardiogenic shock 18.728 (4.823–101.966) <0.001*
Admission during outbreak response 0.391 (0.086–1.455) 0.185
Route of presentation (direct or EMS) 0.423 (0.065–1.984) 0.314
Door-to-balloon time 1.005 (1.000–1.011) 0.029*

*P<0.05. Door-to-balloon time is taken as the first door-to-balloon time for interhospital transfer patients, and recipient hospital door-to-balloon time for patients presenting directly or via EMS. CAD, coronary artery disease; CI, confidence interval; EMS, emergency medical system; LAD, left anterior descending coronary artery; LMS, left main stem artery; OR, odds ratio. Other abbreviations as in Table 1.

Discussion

The trends of reduced STEMI presentations, increased delay in presentation, longer average D2B times during the COVID-19 pandemic have been reported in Belgium,19 Austria,20 and the USA.21 Those studies focused on the delay and reduction in STEMI presentations, which were mainly attributed to patient-related factors such as reluctance in seeking medical care,19 and fear of COVID-19 transmission in the hospital.21 The present study demonstrated a number of novel findings on the effect of an outbreak response on PPCI efficiency and its clinical outcomes. First, this study is the first to have examined the individual components of theD2B time, in a 2-weekly trend, before and during an outbreak response. Our results showed that PPCI efficiency was mainly affected just prior to the period when the DORSCON level was raised, which was attributed to frontline ED delays, but with a subsequent trend of recovery. Second, important clinical outcomes of STEMI presentations before and during the outbreak response were investigated and higher incidences of out-of-hospital cardiac arrest, intubation, sepsis and acute MR were observed during the higher DORSCON alert period. Third, our study demonstrated that the D2B time remained an independent predictor of in-hospital death despite adjusting for known prognostic factors.

The strain of the COVID-19 pandemic on the national health system as a whole is clearly be evident by the lower proportion of patients treated within the guideline-recommended threshold regardless of the route of presentation. The same trend was observed after excluding potential confounding non-system delay factors. Although our findings appear consistent with a smaller study in Hong Kong conducted around the same period,8 we did not observe a large increase in median time for all components of PPCI workflow. In fact, the increase in D2toB and D1toB times was apparent only in the 2 weeks preceding the implementation of DORSCON Orange and can be attributed to longer time needed in the EDs (Figure 2A,B) of both the referral and recipient hospitals. Importantly, there were no in-hospital deaths among patients admitted during those 2 weeks.

The possible causes for a longer D2B time during the pandemic include the need for a thorough screening for respiratory symptoms, sick contacts, and travel history and a chest radiography for risk stratification at the ED prior to transfer to the catheterization laboratory.8,12 Moreover, the national COVID-19 suspect case definition remained dynamic due to the ever-changing global epicenter, resulting in frequent alteration of risk-stratifying workflows in the EDs.16 Stringent surveillance was carried out in the ED before triaging patients to the respective departments. It is plausible that these additional measures contributed to the prolonged ‘ED-to-activate’ time. Such delay may have been accentuated in the earlier period leading up to the formal implementation of DORSCON Orange, which might be attributed to the unfamiliarity of the workflow in the early stages of the pandemic. All staff, including the PPCI team, needed time to don PPE when dealing with suspect COVID-19 cases, which may have extend the treatment time.8 Time and personnel were needed to organize safe and appropriate transfers from ED to catheterization laboratory (Figure 3).

Figure 3.

Association of COVID-19 and the STEMI care workflow from symptom onset to balloon time. D1toD2, ambulance transport time; D1toB, first door-to-balloon time; D2toB, recipient hospital’s door-to-balloon time; DIDO, door-in to door-out time; O2D, symptom onset-to-door time; EMD-to-Activate time, time from patient’s arrival at hospital to the time of activating the interventionist; Activate-to-Cath lab time, time from activation of the interventionist to time of patient’s arrival in catheterization laboratory; Cath lab-to-start time, time of patient’s arrival in catheterization laboratory to time of first puncture; Start-to-balloon time, time of first puncture to the time of first device deployment; COVID-19, coronavirus disease 2019; STEMI, ST-segment elevation myocardial infarction.

Nevertheless, a trend of recovery was apparent once the workflows for DORSCON Orange were implemented. An initial reduction in the efficiency of PPCI is understandable as many of the measures were gradually put in place in the weeks leading to DORSCON Orange. Time was needed for all staff to be familiarized with the new workflows. Such improvement was evident by the increase in prehospital activation in the DOR period, which might have partly mitigated the initial increase in the median D2B time. Hence, it is intuitive to suggest that prehospital activation and early COVID-19 risk stratification by the EMS can improve the efficiency of PPCI.22

Similar trends were observed in the EDs of the referring hospitals, with a transient deterioration in DIDO time performance. With the geographic advantage of Singapore as a small developed country, coupled with a well-established STEMI network, more than two-thirds of the transfer patients had D1toB times within 120 min during both study periods. Such efficiency is in accordance with the 65% reported in the USA despite the pandemic.23

Singapore took an early strategy of intensive disease containment through extensive contact tracing and quarantine, and a multipronged surveillance strategy in applying the suspect case definition at all medical consultations.24 This strategy included the diversion of resources to essential services in order to limit disease spread among healthcare establishments, which was evident in the sharp reduction in the number of elective staged PCI during DOR period. A mature STEMI network with cohesive collaboration among all stakeholders permitted immediate consolidation of PPCI service within a tertiary center, allowing the referring centers to divert resources in order to cope with the strain of pandemic at the local level. This could have contributed to the recovery of PPCI efficiency without adversely affecting clinical outcomes.

There is concern that STEMI patients may be inclined to present later during the pandemic with the consequence of a more severe presentation with increased complications. We observed an approximately 9% reduction in STEMI cases during the pandemic, which is much smaller than the 40% reduction experienced in Spain6 and the USA.13 The decline in presentations in the USA and Spain has been attributed to the public’s avoidance of medical care due to social distancing or concerns of COVID-19 contact in the hospital.6,12 Although we did not observe a longer O2D time or a greater number of patients with evolved STEMIs, there was a higher incidence of out-of-hospital cardiac arrest among patients in the DOR group. Out-of-hospital cardiac arrest at the point of presentation was the strongest independent predictor of death as described in our study. The reasons for the increased incidence of out-of-hospital cardiac arrest remain speculative, but could include a fear of patients visiting a hospital, or even altered threshold and clinical judgement among clinicians to diagnose or admit a patient. One example is a 34-year-old man living in Singapore, identified as case 1,604, who was swabbed for COVID-19 and advised to return home to wait for the result after a visit to the ED; he later died in the community due to ischemic heart disease.25

There were also higher incidences of intubation and acute MR. We do acknowledge that there might have been a lower threshold to intubate patients during the DOR phase due to the concerns of COVID-19 transmission risk associated with non-invasive ventilation. However, after excluding all out-of-hospital cardiac arrest cases, we found that the percentage of intubation in the BOR and DOR groups remained similar (10.7% and 10.8%, respectively). This might suggest that the difference in overall intubation rates was most likely attributed to the difference in out-of-hospital cardiac arrest cases. An interesting finding of the study was the higher rate of sepsis in the DOR group, suggesting a more severe clinical status at admission. For example, 55.6% (n=10) of those with sepsis in the DOR group developed hospital-acquired infection (hospital-acquired or ventilator-associated pneumonia), with the most common microbiological pathogen being Klebsiella pneumoniae. This was followed by bacteremia from gut translocation (33.3%, n=6) with pathogens such as Escherichia coli and Salmonella. The remaining infections included community-acquired cases such as community-acquired pneumonia. The treatment pattern included broad-spectrum antibiotics such as piperacillin/tazobactam. Only the patient with community-acquired pneumonia displayed signs of infection prior to the STEMI. None of these patients had COVID-19 infection.

Our findings have wider implications and may apply to many time-sensitive acute medical services. PPCI may be considered as the standard care if the health resources allow, and it can be safely carried out within the recommended time frame without compromising the safety of the healthcare staff or patients.6,7 We should aim to eliminate unnecessary morbidity and mortality in essential non-COVID-19 health services.

Study Limitations

Our study has several limitations that merit consideration. It was a single-center retrospective observational study with a small study size, but it represents the actual clinical settings of a PPCI network during the early stages of the pandemic when data remained scarce. The results of the Western STEMI network are likely applicable to other regions of Singapore, as the country shares the same EMS and STEMI care (i.e., fibrinolysis is rarely used, because distances are not great in a small country; the transport system is efficient; the entire population has proximity to hospitals). Even though fibrinolysis is not commonly performed, immediate fibrinolysis in the ED may mitigate the delays, particularly in a pandemic with increased infection control measures. In these circumstances, the notion of early reperfusion may supersede the mode of reperfusion.26

The time when the patients accessed EMS was not available and any prehospital delays could not be evaluated. However, the prognostically relevant O2D time did not differ across the 2 study periods nor did it affect the outcome of the study patients. In addition, even though the individual culprit vessels were assessed, the study did not compare infarction size between the 2 study periods. Furthermore, the difficulty in distinguishing preexisting and new-onset MR, particularly in those without an index echocardiogram prior to the STEMI, is a common limitation for studies in similar settings.

Seasonal variation in STEMI incidence may be less relevant to a tropical country such as Singapore where the weather is humid throughout the year. Our data monitoring did not show any trend of seasonal variation in STEMI incidence (Supplementary Figure). Hence, the current study periods could account for the effects of the pandemic and its outbreak measures.

From our investigation, the logistic regression of death on D2B and prognostic variables meets the assumption of additivity, although not linearity. Nonetheless, this finding supports the result that D2B predicts death when controlling for important prognostic covariates and the DORSCON Orange time period. This indicates that the latter result is robust to an alternative model specification.

Although only a small number of study patients underwent COVID-19 swab tests, all patients were thoroughly risk-stratified based on a uniform national case definition standard. Retrospectively, such a strategy was effective because we did not observe any transmission of COVID-19 from patients to healthcare workers within our center during the study period. This could serve as a reference when planning future outbreak response strategies.

Conclusions

The pandemic has strained the healthcare system and led to stringent infection control measures, which reduce the efficiency of PPCI service and may adversely affect the outcomes of patients because fewer patients are treated within the recommended D2B time threshold and delayed D2B could increase in-hospital mortality. Our study also demonstrated an increased prevalence of out-of-hospital cardiac arrest and STEMI complications such as acute MR. Concerted effort by all PPCI stakeholders at the regional level could mitigate the reduction in service efficiency. Closer collaboration between the EMS and hospitals with early implementation of prehospital workflows could minimize service disruption and potentially improve efficiency, which should form one of the management strategies for future outbreaks.

Acknowledgment

We express our gratitude to colleagues who put themselves in the frontline to care for these patients.

Conflict of Interest / Relationship With Industry / Funding

None.

IRB Information

This study was approved by the local institution review board (NHG DSRB no. 2013/00442).

Supplementary Files

Please find supplementary file(s);

http://dx.doi.org/10.1253/circj.CJ-20-0800

References
 
© 2021 THE JAPANESE CIRCULATION SOCIETY

This article is licensed under a Creative Commons [Attribution-NonCommercial-NoDerivatives 4.0 International] license.
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