Abstract
Background:
The coronavirus disease 2019 infection has significantly impacted the world and placed a heavy strain on the medical system and the public, especially those with cardiovascular diseases. Hoverer, the differences in door-to-balloon time and outcomes in ST-segment elevation myocardial infarction (STEMI) patients undergoing primary percutaneous coronary intervention after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are not known too much.
Methods:
Web of Science, EMBASE, PubMed, Cochrane Library, Wanfang, VIP, and China’s National Knowledge Infrastructure were utilized to perform a systematic literature search until April 30, 2023. We computed the odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) to determine the correlation. A random-effects model was used for the meta-analysis if the study had significant heterogeneity. Meanwhile, sensitivity analysis and Trial sequential analysis were also accomplished using Rveman5.4 and trial sequential analysis 0.9.5.10 Beta software, respectively.
Results:
A total of 5 eligible studies were explored in our meta-analysis, including 307 cases and 1804 controls. By meta-analysis, the pooled data showed that SARS-CoV-2-positive STEMI patients undergoing percutaneous coronary intervention had a longer door-to-balloon time (OR 6.31, 95% CI 0.99, 11.63, P = .02) than the negative subjects. The glycoprotein IIb/IIIa inhibitor use after SARS-CoV-2 infection (OR 2.71, 95% CI 1.53, 4.81, P = .0006) was relatively frequent compared with controls, and the postoperative Thrombolysis in Myocardial Infarction blood flow (OR 0.48, 95% CI 0.34, 0.67, P < .0001) was worse compared that. The in-hospital mortality (OR 5.16, 95% CI 3.53, 7.53, P < .00001) was higher than non-SARS-CoV-2 infection ones. In addition, we also discovered that age, gender (male), hypertension, diabetes mellitus, hyperlipidemia, smoking, previous myocardial infarction, total ischemia time, and thrombus aspiration use did not have a significant association with the development of STEMI patients with SARS-CoV-2.
Conclusion:
SARS-CoV-2 positivity is significantly associated with longer door-to-balloon time and higher in-hospital mortality in STEMI patients undergoing primary percutaneous coronary intervention.
Keywords: COVID-19, door-to-balloon time, in-hospital mortality, STEMI
1. Introduction
The coronavirus disease 2019 (COVID-19) has seriously affected the global medical system, which needs more resources to manage the unpredictable modern pandemic.[1,2] Some studies have reported that infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) would accelerate the mortality rate, especially cardiovascular mortality, during the COVID-19 pandemic because of the indirect and direct effects.[3,4] For instance, the interaction between previous cardiovascular disease and COVID-19 infection participated in the procedure, as well as the myocardial damage from virus infection.[5] Most notably, the virus infection could fulfill a role in thrombosis formation in blood vessels.[6,7] COVID-19 could produce an abnormal systemic inflammatory response, excessive activation of the coagulation system, oxygen supply and demand imbalance, and atherosclerotic plaque rupture.
Except for the biological effects of the disease, the COVID-19 pandemic could induce numerous indirect influences, such as fear of infection, maintaining social distance, over attention to the uncontrolled spread of the disease, and so on, which might discourage patients from seeking medical care.[8,9] The reallocation of medical resources would influence the emergency network worldwide, leading to delays in treatment.[10]
Previous researchers have investigated that ST-segment elevation myocardial infarction (STEMI) patients with COVID-19-positive have a high in-hospital mortality.[11,12] However, the effect of this finding was finite because of the limited statistical power, and we could not calculate indirect and direct causes of enhancement mortality in COVID-19-positive patients.
To understand the clinical manifestations of COVID-19-positive STEMI patients during the global pandemic, our meta-analysis attempted to pursue the differences in clinical features, response to acute myocardial infarction, and outcomes in STEMI patients with concomitant COVID-19 compared to those without concomitant COVID-19.
2. Materials and methods
2.1. Search strategy
According to the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines, we performed the current meta-analysis, which has been registered beforehand in PROSPERO (CRD42023422705).[13] Articles related to this review were confirmed by Minli Cheng, Lei Zou, and Qine Zhang independently through the database including Web of Science, EMBASE, PubMed, Cochrane Library, Wanfang, VIP, and China’s National Knowledge Infrastructure until April 30, 2023. The retrieved keywords were as follows: (“ST-segment elevation myocardial infarction” odds ratios [OR] “STEMI”) AND (“COVID-19” OR “SARS-CoV-2” OR “Coronavirus Disease 2019” OR “severe acute respiratory syndrome coronavirus 2” OR “2019, novel coronavirus” OR “2019-nCoV”). To determine other eligible articles, Minli Cheng, Lei Zou, and Qine Zhang manually reviewed all relevant original studies. Since the meta-analysis used previously published studies, there was no requirement for patient consent or ethical approval.
2.2. Inclusion and exclusion criteria
Chunhua Pu and Qun Wang searched the abstracts independently, and Shan Wang, a third reviewer, settled any discrepancies. The inclusion criteria were as follows: STEMI patients undergoing primary percutaneous coronary intervention (PPCI) were SARS-CoV-2-positive, confirmed by reverse transcription-polymerase chain reaction; Clinical manifestations and outcomes of patients; Available data of door-to-balloon time and ischemia time; Research in English and Chinese. We excluded those articles that compare to populations before the COVID-19 pandemic. An abstract, letter, comments, meta-analysis, review, and case report would be eliminated simultaneously. We also excluded these studies which did not conform to the inclusion criteria.
2.3. Data extraction and quality evaluation
Shan Wang and Chao Liu fulfilled the data extraction, respectively. The items exhibited as follows: the author, publication year, country, study design, sample size, age, gender (male), hypertension, diabetes mellitus, hyperlipidemia, smoking, previous myocardial infarction (MI), door-to-balloon time, total ischemia time, glycoprotein IIb/IIIa (GP2b3a) inhibitor use, thrombus aspiration use, thrombolysis in myocardial infarction (TIMI) flow 3 at end of case, and in-hospital mortality, which shown in Table 1. The Newcastle-Ottawa quality assessment scale was conducted to assess the quality of the articles.
Table 1.
The main features of studies in this meta-analysis.
| Author | Mohsenizadeh | Guler | De Luca | Little | Choudry | |
|---|---|---|---|---|---|---|
| Year | 2022 | 2022 | 2021 | 2020 | 2020 | |
| Country | Iran | Turkey | Italy | United Kingdom | United Kingdom | |
| Study design | Retrospective observational cohort | Retrospective study | Retrospective multicenter registry | Retrospective observational analysis | Single-center, observational study | |
| Sample size | COVID-19+ | 98 | 62 | 62 | 46 | 39 |
| COVID-19- | 1052 | 64 | 310 | 302 | 76 | |
| Age | COVID-19+ | 62.92 ± 12.02 | 60.2 ± 9.5 | 70 (62–76) | 63 (58–67) | 61.7 ± 11.0 |
| COVID-19- | 59.93 ± 11.61 | 63 ± 8 | 70 (62–75) | 63 (55–72) | 61.7 ± 12.6 | |
| Gender (male) | COVID-19+ | 75 (76.5) | 41 (66.1) | 49 (79) | 37 (80.4) | 33 (84.6) |
| COVID-19- | 819 (77.9) | 45 (70.3) | 245 (79) | 241 (79.8) | 57 (75.0) | |
| Hypertension | COVID-19+ | 43 (43.9) | 37 (59.7) | 35 (56.5) | 25 (54) | 28 (71.8) |
| COVID-19- | 506 (48.1) | 37 (57.8) | 176 (56.8) | 153 (50.7) | 32 (42.1) | |
| Diabetes mellitus | COVID-19+ | 54 (55.1) | 30 (48.4) | 10 (16.1) | 15 (32.6) | 18 (46.2) |
| COVID-19- | 483 (45.9) | 35 (54.7) | 67 (21.6) | 71 (23.5) | 20 (26.3) | |
| Hyperlipidemia | COVID-19+ | 44 (44.9) | 27 (43.5) | 25 (40.3) | 24 (52.2) | 24 (61.6) |
| COVID-19- | 612 (58.2) | 22 (34.3) | 125 (40.3) | 100 (33.1) | 28 (36.8) | |
| Smoking | COVID-19+ | 30 (30.6) | 32 (51.6) | 15 (24.2) | 1 (2.2) | 24 (61.6) |
| COVID-19- | 394 (37.5) | 36 (56.3) | 91 (29.4) | 10 (3.3) | 35 (46.1) | |
| Previous MI | COVID-19+ | 13 (13.3) | 6 (9.7) | 8 (12.9) | 5 (10.9) | 6 (15.4) |
| COVID-19- | 92 (8.7) | 18 (28.1) | 29 (9.4) | 38 (12.6) | 3 (3.9) | |
| Door-to-balloon time | COVID-19+ | 56.5 (41–90) | 39 (32–48) | 40 (28–65) | 51 (39–77) | 52 (39–70) |
| COVID-19- | 55 (37–89) | 31 (27–35) | 35 (23–68) | 47 (32–63) | 50 (34.8–57.5) | |
| Total ischemia time | COVID-19+ | 395 (185–655) | 203 (171 –267 | 200 (107–500) | 360 (223–1418) | 240 (120–360) |
| COVID-19- | 375 (195–795) | 185 (137 –242) | 179 (120–291) | 257 (172–580) | 240 (120–420) | |
| Gp2b3a inhibitor use | COVID-19+ | 61 (62.2) | 13 (21) | 21 (33.9) | 26 (56.5) | 23 (59.0) |
| COVID-19- | 483 (45.9) | 6 (9.4) | 71 (22.9) | 117 (38.7) | 7 (9.2) | |
| Thrombus aspiration use | COVID-19+ | 9 (9.2) | 4 (6.2) | 23 (37.1) | 14 (30.4) | 7 (17.9) |
| COVID-19- | 114 (10.8) | 3 (4.7) | 64 (20.6) | 54 (17.9) | 1 (1.3) | |
| TIMI flow 3 at end of case | COVID-19+ | 65 (66.3) | 51 (82.3) | 57 (91.9) | 37 (80.4) | 35 (89.7) |
| COVID-19- | 878 (83.5) | 57 (89.1) | 285 (91.9) | 278 (92.0) | 70 (93.3) | |
| In-hospital mortality | COVID-19+ | 20 (20.4) | 10 (16.1) | 18 (29) | 10 (21.7) | 7 (17.9) |
| COVID-19- | 29 (2.8) | 3 (4.7) | 17 (5.5) | 28 (9.3) | 5 (6.5) | |
COVID-19 = coronavirus disease 2019, GP2b3a = glycoprotein IIb/IIIa, MI = myocardial infarction, TIMI = thrombolysis in myocardial infarction.
2.4. Statistical analysis
The review manager software (Rveman5.4, Cochrane Collaboration, London, UK) was used for the statistical analysis by Qinxue Bao and Chengfeng Wang. The ORs were performed to evaluate the clinical differences in SARS-CoV-2-positive STEMI patients and SARS-CoV-2-negative STEMI patients, with 95% confidence intervals (CIs). The I2 index was applied to assess the statistical heterogeneity among eligible articles. A fixed-effects model was employed if the I2 index was < 50%, demonstrating acceptable heterogeneity; additionally, a random-effects model was used.[14] If there was substantial heterogeneity in our meta-analysis, the sensitivity analysis was applied to identify studies that lead to heterogeneity. When the P value was < .05, the difference was considered statistically significant. Begg funnel plot was performed to evaluate the publication bias. During the repeated updates in the current meta-analysis, the trial sequential analysis (TSA) was performed to analyze random errors,[15] including false-positive errors and false-negative errors, meanwhile to calculate the required information size (RIS) by TSA software (TSA 0.9.5.10 Beta, Copenhagen Trial Unit, Centre for Clinical Intervention Research, Denmark.) to draw a clear conclusion.
3. Results
3.1. Selection flow
Figure 1 displays the selection flow for these qualified studies. According to the retrieved keywords, 11,130 articles were confirmed from Web of Science, EMBASE, PubMed, Cochrane Library, Wanfang, VIP, and China’s National Knowledge Infrastructure databases. Among them, 1661 copies were eliminated. Then, 9496 studies were sifted based on titles and abstracts, and 402 were assessed according to a full-text review. Ultimately, 5 studies satisfied the inclusion criteria, which contained 307 COVID-19-positive STEMI patients and 1804 confirmed controls of COVID-19-negative STEMI patients. The basic information and crucial features of the original studies are proved in Table 1. The Newcastle-Ottawa Scale was conducted to evaluate the quality of studies in our meta-analysis, as shown in Table 2.
Figure 1.
Flow chart of the selection process in this meta-analysis.
Table 2.
The quality assessment of included studies by the Newcastle-Ottawa quality assessment scale.
| Study | Selection | Comparability | Outcome | Scores | |||||
|---|---|---|---|---|---|---|---|---|---|
| Representativeness of the exposed cohort | Selection of the nonexposed cohort | Ascertainment of exposure | Demonstration that outcome of interest was not present at start of study | Assessment of utcome | Was follow-up long enough for outcomes to occur | Adequacy of follow-up of cohorts | |||
| Mohsenizadeh, 2022 | ✵ | ✵ | ✵ | ✵ | ✵✵ | ✵ | ✵ | ✵ | 9 |
| Guler, 2022 | ✵ | ✵ | ✵ | ✵ | ✵✵ | ✵ | ✵ | - | 8 |
| De Luca, 2021 | ✵ | ✵ | ✵ | ✵ | ✵✵ | ✵ | ✵ | ✵ | 9 |
| Little, 2020 | ✵ | ✵ | ✵ | ✵ | ✵ | ✵ | ✵ | ✵ | 8 |
| Choudry, 2020 | ✵ | ✵ | ✵ | ✵ | ✵✵ | ✵ | ✵ | - | 8 |
3.2. Results of the meta-analysis
All the results of our meta-analysis for the differences between SARS-CoV-2-positive STEMI patients and SARS-CoV-2-negative STEMI patients are exhibited in Figure 2 and Table 3. We acquired 307 cases and 1804 controls from 5 eligible studies that detected the association between age and the development of COVID-19-positive STEMI patients. A random-effects model was used for data consolidation, with an OR value of −0.50 (95% CI −2.73, 1.73) for age (Fig. 2A). We also explored the relationship between gender (male) and the development of COVID-19-positive STEMI patients and the relationship between smoking and that, yielding an OR value of 1.01 (95% CI 0.74, 1.36) for gender(male) (Fig. 2B) and an OR value of 0.86 (95% CI 0.64, 1.16) for smoking (Fig. 2C), which used a fixed-effects model.
Figure 2.
Forest plots of odds ratios for the relationship between risk factors and STEMI patients with COVID-19. (A) Age, (B) gender (male), (C) smoking, (D) hypertension, (E) diabetes mellitus, (F) hyperlipidemia, (G) previous MI, (H) Gp2b3a inhibitor use, (I) TIMI flow 3 at end of case, (J) thrombus aspiration use, (K) door-to-balloon time, (L) total ischemia time, and (M) in-hospital mortality. COVID-19 = coronavirus disease 2019, GP2b3a = glycoprotein IIb/IIIa, MI = myocardial infarction, STEMI = ST-segment elevation myocardial infarction, TIMI = thrombolysis in myocardial infarction.
Table 3.
Risk factors of STEMI patients with COVID-19.
| Baseline characteristic | OR [95% CI] | Z (P value) | Heterogeneity of study design | ||
|---|---|---|---|---|---|
| χ2 | Df (P value) | I2 (%) | |||
| Age | −0.50 [−2.73, 1.73] | 0.44 (.66) | 11.41 | 4 (.02) | 64% |
| Gender (male) | 1.01 [0.74, 1.36] | 0.04 (.97) | 1.73 | 4 (.79) | 0% |
| Hypertension | 0.05 [−0.06, 0.15] | 0.91 (.36) | 10.65 | 4 (.03) | 62% |
| Diabetes mellitus | 1.26 [0.96, 1.65] | 1.69 (.09) | 7.63 | 4 (.11) | 48% |
| Hyperlipidemia | 1.33 [0.74, 2.40] | 0.95 (.34) | 19.32 | 4 (.0007) | 79% |
| Smoking | 0.86 [0.64, 1.16] | 0.99 (.32) | 4.42 | 4 (.35) | 10% |
| Previous MI | 1.13 [0.53, 2.38] | 0.32 (.75) | 12.99 | 4 (.01) | 69% |
| Door-to-balloon time | 6.31 [0.99, 11.63] | 2.32 (.02) | 9.04 | 4 (.06) | 56% |
| Total ischemia time | 5.44 [−109.32, 120.20] | 0.09 (.93) | 28.23 | 4 (.0001) | 86% |
| Gp2b3a inhibitor use | 2.71 [1.53, 4.81] | 3.41 (.0006) | 14.25 | 4 (.007) | 72% |
| Thrombus aspiration use | 1.84 [0.99, 3.44] | 1.91 (.06) | 9.39 | 4 (.05) | 57% |
| TIMI flow 3 at end of case | 0.48 [0.34, 0.67] | 4.32 (<.0001) | 3.91 | 4 (.42) | 0% |
| In-hospital mortality | 5.16 [3.53, 7.53] | 8.50 (<.00001) | 7.19 | 4 (.13) | 44% |
95% CI = 95% confidence interval, COVID-19 = coronavirus disease 2019, GP2b3a = glycoprotein Iib/IIIa, MI = myocardial infarction, ORs = odds ratios, STEMI = ST-segment elevation myocardial infarction, TIMI = thrombolysis in myocardial infarction.
Several comorbidities were involved in the current meta-analysis to investigate their correlation to the development of COVID-19-positive STEMI patients, including hypertension, diabetes mellitus, hyperlipidemia, and previous MI. As shown in Figure 2 and Table 3, hypertension (OR = 0.05, 95% CI = −0.06, 0.15, P = .36) (Fig. 2D), diabetes mellitus (OR = 1.26, 95% CI = 0.96, 1.65, P = .09) (Fig. 2E), hyperlipidemia(OR = 1.33, 95% CI = 0.74, 2.40, P = .34) (Fig. 2F), and previous MI (OR = 1.13, 95% CI = 0.53, 2.38, P = .75) (Fig. 2G) did not have a significant association with the development of COVID-19-positive STEMI patients.
The random-effects model was applied to calculate an OR of 2.71 (95% CI 1.53, 4.81, P = .0006) for Gp2b3a inhibitor use after COVID-19 infection in STEMI patients (Fig. 2H), suggesting that COVID-19-positive STEMI patients have a heavier thrombus burden. Furthermore, the pooled data of TIMI flow 3 at end of case on the incidence of STEMI in COVID-19-positive patients was also significant, indicating that COVID-19-positive might aggravate the degree of vascular lesions in STEMI patients (shown in Fig. 2I). Nevertheless, as shown in Figure 2J, the pooled estimate of the effect of thrombus aspiration use was not statistically remarkable.
The relationship between door-to-balloon time and STEMI patients was estimated (OR 6.31, 95% CI 0.99, 11.63, P = .02) (Fig. 2K), and apparent heterogeneity was confirmed. Then, the random-effects model identified that COVID-19-positive was a disadvantage for patients with STEMI. A random-effects model was utilized to get an OR of 5.44 (95% CI −109.32, 120.20) for total ischemia time and STEMI patients (Fig. 2L). Furthermore, the pooled data on the effect of total ischemia time on STEMI patients was not statistically significant. In-hospital mortality is an essential indicator for STEMI patients. The fixed-effects model was used to forecast an OR of 5.16 (95% CI 3.53, 7.53) for in-hospital mortality and STEMI patients, proposing that COVID-19 is a risk factor for STEMI patients (Fig. 2M).
3.3. Publication bias and sensitivity analysis
Begg funnel plot was untilled to detect the potential publication bias in our meta-analysis. Taking the in-hospital mortality as an example, the funnel plot was basically symmetric, suggesting that the publication bias risk was low (Fig. 3). After omitting 1 article at a time, the impact on the sensitivity analysis results was not highlighted, indicating that our current meta-analysis findings were relatively reliable.
Figure 3.
Begg funnel plot of publication bias for the in-hospital mortality in STEMI patients with COVID-19. COVID-19 = coronavirus disease 2019, STEMI = ST-segment elevation myocardial infarction.
3.4. The results of trial sequential analysis
As shown in Figure 4, by TSA software, we conducted the trial sequential analysis to evaluate the accuracy of our meta-analysis. After Gp2b3a inhibitor use, the cumulative z-curve reached the TSA boundary and did not cross the RIS, reflecting that the current sample size was sufficient to reach robust conclusions (Fig. 4A). However, in Figure 4D, the cumulative z-curve about in-hospital mortality was close to the TSA boundary rather than reached, indicating the possibility of false positives in the result of in-hospital mortality. In Figure 4C, the cumulative z-curve reached the TSA boundary and the RIS, implying that the result about door-to-balloon time was powerful and crucial. The pooled data of TIMI flow 3 at end of case showed that the z-curve did not reach the TAS boundary before intersecting the RIS and the conventional test boundary, suggesting that even with appropriate sample size, the conclusion concerning the TIMI flow 3 at end of case was not reliable enough (Fig. 4B). Therefore, more research will be needed to validate this outcome moreover.
Figure 4.
Trial sequential analysis (TSA) analysis for meta-analysis of risk factors and STEMI patients with COVID-19. (A) Gp2b3a inhibitor use, (B) TIMI flow 3 at end of case, (C) door-to-balloon time, and (D) in-hospital mortality. COVID-19 = coronavirus disease 2019, GP2b3a = glycoprotein IIb/IIIa, STEMI = ST-segment elevation myocardial infarction, TIMI = thrombolysis in myocardial infarction, TSA = Trial sequential analysis.
4. Discussion
Our meta-analysis, including 5 articles, explored the clinical characteristics and in-hospital mortality of COVID-19-positive STEMI patients receiving PPCI. The main discoveries of the current meta-analysis can be described as follows: COVID-19 positivity might prolong the door-to-balloon time and increase the in-hospital mortality of STEMI patients undergoing PPCI; COVID-19 positivity would deteriorate the thrombus burden of the coronary artery and affect the postoperative TIMI flow; that is, the blood flow is worse after PPCI.
COVID-19 quickly became a worldwide pandemic, posing severe pressure on the global medical system.[16] Our meta-analysis discovered that SARS-CoV-2-positive STEMI patients have meaningfully higher risk mortality in hospitals compared to SARS-CoV-2-negative controls.
STEMI is a critical condition that significantly affects patient survival and clinical outcomes due to the short interval between vascular blockage and the restoration of coronary artery blood flow, which means total ischemic time. Delaying total ischemic time affects the survival and prognosis of myocardial infarction patients.[17] Fortunately, the average time from door-to balloon can be reduced to just 60 minutes, improving patient outcomes.[18] The first medical contact-to-device time, which measures the duration from initial medical contact-to device insertion, offers a more comprehensive system efficiency assessment. Hence, prioritizing the reduction of first medical contact-to-device time provides tremendous potential for minimizing the overall duration for ischemic patients.[19] The prompt performance of an electrocardiogram (ECG) is crucial in detecting STEMI and initiating timely measures to reestablish blood flow to the coronary arteries. Swiftly acquiring an ECG and initiating the catheterization laboratory are critical steps in expeditiously reinstating blood circulation to the heart. Shortening the door-to-ECG time can improve door-to-balloon time.[20] The first diagnostic ECG to balloon time (FDECG2BT) is particularly vital in contemporary medical care to guarantee prompt intervention for most patients with STEMI.[21] Some have reported that SARS-CoV-2 positivity was associated with increasing in-hospital mortality in STEMI patients; meanwhile, several indirect and direct impressions could explain this phenomenon.[22–24] In the indirect impact, the fear of infection may influence patients willingness to seek medical treatment at the hospital, leading to significant delays in initiating cardiac catheterization laboratories and then longer ischemic times.
Even though we did not acquire that SARS-CoV-2-positive patients had a longer total ischemic time in our meta-analysis. We confirmed that SARS-CoV-2-positive STEMI patients took a longer door-to-balloon time, reflecting the hospitalization delay. Different reasons can cause this result. For example, various hospitals used diverse triage systems for STEMI patients suspected of COVID-19.[25] Some hospitals used the COVID-19 dedicated channels, and medical personnel wore personal protective equipment more than before, especially at the beginning of the pandemic era.[26]
Wang et al[27] have investigated that the use rate of Gp2b3a inhibitor and thrombus aspiration was higher in COVID-19-positive STEMI patients compared with COVID-19-negative controls. In our study, the use of thrombus aspiration in COVID-19-positive patients with STEMI did not achieve statistical significance. However, a high trend was seen in using thrombus aspiration in positive patients. This result might reflect the heterogeneity in different catheter rooms and registration systems using TIMI blood flow grading. At the same time, the use of Gp2b3a inhibitor was higher in patients with SARS-CoV-2 infection. These indicated that COVID-19-positive STEMI patients had a higher proportion of using Gp2b3a inhibitor and thrombectomy, meaning a higher thrombus burden after SARS-CoV-2 infection. Antecedently, Nappi et al[28] emphasized the direct effect of SARS-CoV-2 infection, which was thrombogenic. Some mechanisms were involved in the procedure, including inflammation activation and dysfunction of endothelial cells. Then, these could accelerate platelet activation, leading to a coagulation cascade and thrombogenesis.[29,30] All the interaction among these mechanisms might result in the high thrombus burden of the coronary artery and influence the microcirculation. Then, it damaged the perfusion of the coronary artery and issued a larger area of infarction. This was a possible cause that SARS-CoV-2 infection affected the in-hospital mortality of STEMI patients. In our meta-analysis, COVID-19-positive STEMI patients have worse blood flow after PPCI, which was less TIMI flow 3 at end of case, confirming this phenomenon.
Coronary artery reperfusion injury in infarct-related arteries was one of the indicators of the success and prognosis of PPCI surgery.[31] In the current meta-analysis, these indicators were associated with in-hospital mortality in COVID-19-positive STEMI patients, suggesting that thrombus burden and TIMI blood flow after PPCI might be helpful for prognostic stratification, which might be possible profits of therapy.
The disadvantages of SARS-CoV-2 infection on other organs and systems may be partly interpreted as the reason for the higher in-hospital mortality in SARS-CoV-2-positive patients, such as the respiratory and digestive systems.[32,33] For example, except for the pulmonary symptoms, the involvement of the liver and gallbladder systems has been widely explored. SARS-CoV-2 infection may result in the dysfunction of liver function tests and significant damage to liver cells or bile stasis.[34] Previous reports have investigated that COVID-19-positive ACS patients had a higher hospital mortality rate associated with cardiac and noncardiac matters.[35–37] Although this information was not obtained in our meta-analysis, we discovered that the in-hospital mortality of SARS-Cov-2-positive patients remained significantly higher than the negative ones.
We found a significant association between thrombus burden and in-hospital mortality in SARS-Cov-2-positive patients, which might be a novelty. It suggested the possible relationship between outcome and postoperative TIMI blood flow, reflecting that the poor prognosis after PPCI may result from impaired coronary artery reperfusion. In practice, postoperative TIMI blood flow was a separate predictor of in-hospital mortality in SARS-CoV-2-positive patients, consistent with previous reports on STEMI patients.[38] The interaction between inflammation, thrombogenic factors, and others may influence the efficacy of refusion in the coronary artery of STEMI patients, subsequently affecting the outcomes of patients.
The relationship between baseline features and outcomes of COVID-19 patients indicated that age, sex, and some complications, including hypertension, diabetes mellitus, and previous MI, may promote the clinical process, as reported by some previous studies.[39,40] Nevertheless, our study found that among the baseline risk factors and complications, they cannot independently predict the hospital mortality rate of SARS-COV-2-positive patients. This might be due to the finite population and data. Therefore, more studies with larger populations and different regions are needed to confirm these results further to explore their potential mechanisms and the therapeutic benefits for this high-risk group.
Our article still had some limitations, leading to cautiously interpreting the results. Firstly, a shortcoming of this article was the restriction of study design. All the studies in the meta-analysis were retrospective and non-randomized. The retrospective study was prone to selection bias, and the data were limited. The analysis results of the randomized controlled study were more accurate and reliable. Secondly, this study needed more research on racial differences. The results may have been affected by variations in geographic location and ethnicity. For example, Feyman et al[41] reported that racial differences affected the mortality of COVID-19-positive patients, with minority veterans having higher mortality than white veterans during the COVID-19 pandemic. Thirdly, the sample size of this meta-analysis was relatively small, which may impact the conclusions.
Meanwhile, the FDECG2BT is crucial in promptly intervening for STEMI patients in modern medical care.[42] Due to the limitations of the available articles, we could not evaluate the overall system delay for the FDECG2BT. We could not analyze the reasons for the delay more effectively. Our upcoming study will investigate the correlation between the duration from the first diagnostic ECG to the balloon and its impact on the delay of the door-to-balloon time and total ischemic time. One of the disadvantages of this article was the lack of sufficient data concerning the use of mechanical ventilation, oxygen saturation, results of coronary angiography, detailed treatment protocols, and COVID-19-related deaths. Therefore, further research is needed based on clinical data such as race, larger sample size, and more complex clinical characteristics, including smoking, age, gender, and biochemical Data, to exclude the bias because of confounding factors. Thus, the subgroup analysis will be necessary based on gender, age, race, and other relevant factors. Finally, during the epidemic period of COVID-19, no subgroup analysis was performed. Because the variation of viruses, the use of vaccines, and improved treatment for COVID-19 will affect the results.
5. Conclusion
Our meta-analysis figured that the prolonged door-to-balloon time and higher in-hospital mortality might be significantly associated with SARS-CoV-2 positivity in STEMI patients receiving PPCI during the epidemic era. Accordingly, thrombus burden, reperfusion injury, and postoperative TIMI blood flow might be independent predictors of in-hospital mortality in SARS-CoV-2-positive patients.
Author contributions
Conceptualization: Qinxue Bao, Rui Li.
Data curation: Qinxue Bao, Chengfeng Wang, Shan Wang, Minli Cheng, Chunhua Pu, Lei Zou, Chao Liu, Qine Zhang, Qun Wang.
Methodology: Qinxue Bao.
Software: Qinxue Bao, Chengfeng Wang.
Supervision: Rui Li.
Validation: Qinxue Bao, Rui Li, Chengfeng Wang, Shan Wang, Minli Cheng, Chunhua Pu, Lei Zou, Chao Liu, Qine Zhang, Qun Wang.
Writing – original draft: Qinxue Bao.
Writing – review & editing: Rui Li.
Abbreviations:
- CIs
- confidence intervals
- COVID-19
- coronavirus disease 2019
- ECG
- electrocardiogram
- FDECG2BT
- first diagnostic ECG to balloon time
- GP2b3a
- glycoprotein IIb/IIIa
- MI
- myocardial infarction
- ORs
- odds ratios
- PPCI
- primary percutaneous coronary intervention
- RIS
- required information size
- SARS-CoV-2
- severe acute respiratory syndrome coronavirus 2
- STEMI
- ST-segment elevation myocardial infarction
- TIMI
- thrombolysis in myocardial infarction
- TSA
- trial sequential analysis
The authors have no funding and conflicts of interest to disclose.
All data generated or analyzed during this study are included in this published article [and its supplementary information files].
How to cite this article: Bao Q, Li R, Wang C, Wang S, Cheng M, Pu C, Zou L, Liu C, Zhang Q, Wang Q. Differences in door-to-balloon time and outcomes in SARS-CoV-2-positive ST-segment elevation myocardial infarction patients undergoing primary percutaneous coronary intervention: A systematic review and meta-analysis. Medicine 2023;102:41(e35612).
Contributor Information
Rui Li, Email: sclihou@163.com.
Chengfeng Wang, Email: 18380456270@163.com.
Shan Wang, Email: 18380456270@163.com.
Minli Cheng, Email: chengminli19810920@163.com.
Chunhua Pu, Email: puchunhua12@163.com.
Lei Zou, Email: 277710295@qq.com.
Chao Liu, Email: liuchao_202112@163.com.
Qine Zhang, Email: zhangqine1985@163.com.
Qun Wang, Email: 18380456270@163.com.
References
- [1].Sharma A, Ahmad Farouk I, Lal SK. COVID-19: a review on the novel coronavirus disease evolution, transmission, detection, control and prevention. Viruses. 2021;13:202. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [2].Ciotti M, Ciccozzi M, Pieri M, et al. The COVID-19 pandemic: viral variants and vaccine efficacy. Crit Rev Clin Lab Sci. 2022;59:66–75. [DOI] [PubMed] [Google Scholar]
- [3].Long B, Carius BM, Chavez S, et al. Clinical update on COVID-19 for the emergency clinician: presentation and evaluation. Am J Emerg Med. 2022;54:46–57. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [4].Ejaz H, Alsrhani A, Zafar A, et al. COVID-19 and comorbidities: deleterious impact on infected patients. J Infect Public Health. 2020;13:1833–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [5].Aleksova A, Fluca AL, Gagno G, et al. Long-term effect of SARS-CoV-2 infection on cardiovascular outcomes and all-cause mortality. Life Sci. 2022;310:121018. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [6].Sastry S, Cuomo F, Muthusamy J. COVID-19 and thrombosis: the role of hemodynamics. Thromb Res. 2022;212:51–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [7].Gómez-Mesa JE, Galindo-Coral S, Montes MC, et al. Thrombosis and coagulopathy in COVID-19. Curr Probl Cardiol. 2021;46:100742. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [8].Nongpiur A, Barman B, Syiem K, et al. A cross-sectional study of the mental health burden among COVID-19 survivors. Ind J Psychiatry. 2023;65:661–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [9].Efstathiou V, Stefanou MI, Demetriou M, et al. Long COVID and neuropsychiatric manifestations (review). Exp Ther Med. 2022;23:363. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [10].Sachs JD, Karim SSA, Aknin L, et al. The lancet commission on lessons for the future from the COVID-19 pandemic. Lancet. 2022;400:1224–80. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [11].Zahid B, Kamal M, Said M, et al. Effect of COVID-19 pandemic on six-month mortality and clinical outcomes of patients with ST-elevation myocardial infarction. Adv Intervent Cardiol. 2022;18:228–36. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [12].Baral N, Abusnina W, Balmuri S, et al. COVID-19 positive status is associated with increased in-hospital mortality in patients with acute myocardial infarction: a systematic review and meta-analysis. J Commun Hospital Internal Med Perspect. 2022;12:17–24. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [13].Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [14].Kanters S. Fixed- and random-effects models. Methods Mol Biol. 2022;2345:41–65. [DOI] [PubMed] [Google Scholar]
- [15].Wetterslev J, Jakobsen JC, Gluud C. Trial sequential analysis in systematic reviews with meta-analysis. BMC Med Res Methodol. 2017;17:39. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [16].Mohamadian M, Chiti H, Shoghli A, et al. COVID-19: virology, biology and novel laboratory diagnosis. J Gene Med. 2021;23:e3303. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [17].Lee CK, Meng SW, Lee MH, et al. The impact of door-to-electrocardiogram time on door-to-balloon time after achieving the guideline-recommended target rate. PLoS One. 2019;14:e0222019. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [18].Aly S, Coolahan K, Tomlinson K, et al. Does inclusion of emergency medicine (EM) residents in ECG screening for STEMI change the time to catheterization lab activation? Crit Pathways Cardiol. 2023;22:50–3. [DOI] [PubMed] [Google Scholar]
- [19].Su HY, Tsai JL, Hsu YC, et al. A modified cardiac triage strategy reduces door to ECG time in patients with ST elevation myocardial infarction. Sci Rep. 2021;11:6358. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [20].Gao H, Peng H, Sun Z, et al. Contemporary implications of ECG to activation time on long-term outcomes in patients with ST-segment elevation myocardial infarction treated with primary percutaneous coronary intervention. Clin Ther. 2021;43:2104–15. [DOI] [PubMed] [Google Scholar]
- [21].Coyne CJ, Testa N, Desai S, et al. Improving door-to-balloon time by decreasing door-to-ECG time for walk-in STEMI patients. Western J Emer Med. 2015;16:184–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [22].Chung MK, Zidar DA, Bristow MR, et al. COVID-19 and cardiovascular disease: from bench to bedside. Circ Res. 2021;128:1214–36. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [23].Gitto M, Novelli L, Reimers B, et al. Specific characteristics of STEMI in COVID-19 patients and their practical implications. Kardiol Pol. 2022;80:266–77. [DOI] [PubMed] [Google Scholar]
- [24].Thakker RA, Elbadawi A, Chatila KF, et al. Comparison of coronary artery involvement and mortality in STEMI patients with and without SARS-CoV-2 during the COVID-19 pandemic: a systematic review and meta-analysis. Curr Probl Cardiol. 2022;47:101032. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [25].Tam CF, Siu CD, Tse HF. Challenges in management of ST elevation myocardial infarction during COVID-19 pandemic. Cardiol Plus. 2021;6:218–30. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [26].Yasmin F, Shujauddin SM, Naeem A, et al. Exploring the impact of the COVID-19 pandemic on provision of cardiology services: a scoping review. Rev Cardiovasc Med. 2021;22:83–95. [DOI] [PubMed] [Google Scholar]
- [27].Wang Y, Kang L, Chien CW, et al. Comparison of the characteristics, management, and outcomes of STEMI patients presenting with vs those of patients presenting without COVID-19 infection: a systematic review and meta-analysis. Front Cardiovasc Med. 2022;9:831143. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [28].Nappi F, Nappi P, Gambardella I, et al. Thromboembolic disease and cardiac thrombotic complication in COVID-19: a systematic review. Metabolites. 2022;12:889. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [29].Al-Gburi S, Beissert S, Günther C. Molecular mechanisms of vasculopathy and coagulopathy in COVID-19. Biol Chem. 2021;402:1505–18. [DOI] [PubMed] [Google Scholar]
- [30].Moriarty PM, Gorby LK, Stroes ES, et al. Lipoprotein(a) and its potential association with thrombosis and inflammation in COVID-19: a testable hypothesis. Curr Atheroscler Rep. 2020;22:48. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [31].Konijnenberg LSF, Damman P, Duncker DJ, et al. Pathophysiology and diagnosis of coronary microvascular dysfunction in ST-elevation myocardial infarction. Cardiovasc Res. 2020;116:787–805. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [32].Cao TT, Zhang GQ, Pellegrini E, et al. COVID-19 and its effects on the digestive system. World J Gastroenterol. 2021;27:3502–15. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [33].Umakanthan S, Sahu P, Ranade AV, et al. Origin, transmission, diagnosis and management of coronavirus disease 2019 (COVID-19). Postgrad Med J. 2020;96:753–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [34].Zhao X, Lei Z, Gao F, et al. The impact of coronavirus disease 2019 (COVID-19) on liver injury in China: a systematic review and meta-analysis. Medicine (Baltim). 2021;100:e24369. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [35].Tajbakhsh A, Gheibi Hayat SM, Taghizadeh H, et al. COVID-19 and cardiac injury: clinical manifestations, biomarkers, mechanisms, diagnosis, treatment, and follow up. Expert Rev Anti Infect Ther. 2021;19:345–57. [DOI] [PubMed] [Google Scholar]
- [36].Akinrinmade AO, Obitulata-Ugwu VO, Obijiofor NB, et al. COVID-19 and acute coronary syndrome: a literature review. Cureus. 2022;14:e29747. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [37].Esposito L, Cancro FP, Silverio A, et al. COVID-19 and acute coronary syndromes: from pathophysiology to clinical perspectives. Oxid Med Cell Longev. 2021;2021:4936571. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [38].Raj K, Mahajan P, Watts A, et al. Independent predictors of mortality in COVID-19 myocardial injury: the role of troponin levels, GRACE score, SOFA score, and TIMI score. Cureus. 2022;14:e32082. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [39].Abuzeyad FH, Chomayil Y, Amin MI, et al. Effects of COVID-19 on STEMI patients: single-center experience. Heart Views. 2022;23:138–43. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [40].Zhu Y, Xing W, Wang H, et al. Characteristics of patients with ST-segment elevated myocardial infarction (STEMI) at the initial stage of the COVID-19 pandemic: a systematic review and meta-analysis. Infect Diseases (Lond). 2021;53:865–75. [DOI] [PubMed] [Google Scholar]
- [41].Feyman Y, Avila CJ, Auty S, et al. Racial and ethnic disparities in excess mortality among U.S. veterans during the COVID-19 pandemic. Health Serv Res. 2023;58:642–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [42].Kontos MC, Gunderson MR, Zegre-Hemsey JK, et al. Prehospital activation of hospital resources (PreAct) ST-segment-elevation myocardial infarction (STEMI): a standardized approach to prehospital activation and direct to the catheterization laboratory for STEMI recommendations from the American heart association’s mission: lifeline program. J Am Heart Assoc. 2020;9:e011963. [DOI] [PMC free article] [PubMed] [Google Scholar]