Abstract
Introduction
Coronavirus-2019 (COVID-19) pandemic placed unprecedented levels of stress on healthcare systems leading to prolonged waiting times and reduced access to emergency medical services. With acute coronary syndrome (ACS) longer delays could mean worsening of the symptoms of admitted patients. Studies exploring ACS in COVID-19 reported either results from one hospital or nation-wide registries and many of them did not report laboratory values. Aim of our study was to compare differences in patients and procedural characteristics before and during COVID-19 period in two hospitals differing mainly in population characteristics.
Methods
Data was gathered in two polish cities – Krakow (2nd biggest city in Poland) and Krosno (smaller city with big rural areas). We have analyzed years 2019 and 2020 and included 448 patients in Krosno and 678 patients in Krakow.
Results
In Krosno during pandemic patients were significantly more often transported from home by emergency medical services as opposed to period before COVID-19 (16.3 % vs. 62.2 %). Killip class at admission in Krosno was higher during pandemic (3.5 % vs. 10.4 % for Killip class 4). Similarly, patients in Krosno in 2020 had significantly higher troponin and NT-proBNP levels. We did not observe any of those differences in Krakow. Procedural characteristics were comparable in both interventional cardiology centers.
Conclusions
Even among the same country large differences in health condition of patients with ACS may be observed between different areas. Those results highlight the need of regional protocols on how to improve patient related factors and accessibility to healthcare system during unprecedented events.
Keywords: Acute coronary syndromes, Percutaneous coronary intervention, Coronavirus-2019
Highlights
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Even among the same country we have observed different patterns of seeking help during pandemic
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During pandemic in smaller city with bigger rural areas patients with acute coronary syndrome waited till their symptoms were more severe
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In Krakow we did not observe change of behavior pre- and during pandemic
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In case of pandemic not only nation-wide but also regional protocols should be implemented
1. Introduction
Coronavirus-2019 (COVID-19) was first reported in China in 2019 and several months later in March 2020 it was declared a pandemic by World Health Organization. COVID-19 negatively affected plethora of different areas of life including healthcare systems which were required to restructure and adapt to an entirely novel disease entity. Contemporaneously hospitals tried to provide routine and emergency care for existing illnesses. This rapid change has placed unprecedented levels of stress on healthcare systems all around the World [1,2]. Undoubtedly one of the parts of healthcare system which requires swift decision making and treatment is interventional cardiology. Cardiovascular disease including atherosclerosis is one of the leading causes of death around the world [3,4]. Advances in understanding, diagnosis, and treatment of atherosclerosis have been made during the past century - treatment of acute myocardial infarction (AMI) with obstructive coronary artery disease (CAD) with newest generations of stents and medications significantly lowered morality rate. However, majority of AMI related deaths occur in the first hours of the symptoms. Thus, patients exposed to longer delays may be at risk of greater morbidity and mortality [[5], [6], [7]]. Further, longer delays could mean worsening of the symptoms including dyspnea and greater myocardial injury expressed in laboratory findings and echo measurements. Prolonged time to percutaneous coronary intervention (PCI) was indeed observed during COVID-19 in many studies. However, majority of those studies did not report laboratory values of the patients admitted with ACS. Importantly, most of the studies concentrated either on results from one hospital or nation-wide registries where unified results from bigger parts of the countries were reported. That may implement potential bias as theoretically number of hospitals in selected area, education level of patients or type of the area (ex. rural or suburbs) could influence both patients' decision and procedural outcomes. To our knowledge, no direct comparison of patients with ACS who were treated within the same healthcare system but lived in different areas of the same country were made. Aim of our study was to compare differences in ACS patients in regard to their condition at admission, procedural characteristics and procedural outcomes. We aimed to evaluate those differences between two hospitals differing mainly in population characteristics.
2. Methods
All data was gathered from two medical centers: Department of Interventional Cardiology in St. John Paul Hospital in Krakow and in Interventional Cardiology Centre in Krosno Poland. Krakow is a major Polish with more than 800,000 people with 8 hospitals with cardiology units and 3 hospitals with catheterization laboratories in Krakow alone. Moreover, Krakow is major academic and financial center in Poland with 23 higher education institutions. On the other hand, Krosno has population of about 44,000 with one hospital covering city and nearby rural areas. Distance between both cities is 137 kilometers (km) in straight line and about 165 km when travelling by car. Data was matched with Polish Registry of Acute Coronary Syndrome (PL-ACS). The methodology and analysis of PL-ACS registry have been previously described. In brief, the PL-ACS registry is one of the largest ongoing registries in Europe. It is a multi-center, prospective, observational study of consecutively hospitalized Polish patients with ACS. All patients matching both our database and PL-ACS registry were included in the analysis. We have excluded patients with missing data or patients we could not match by their identification number. As this was retrospective analysis we did not have any other exclusion criteria. We have analyzed years 2019 and 2020 (555 patients in Krosno and 1054 patients in Krakow) and ultimately included patients from April 2019 (May in Krakow) to December 2019 and from April 2020 to December 2020. Altogether 678 patients were included in Krakow (280 in 2019 and 398 in 2020) and 448 in Krosno (313 in 2019 and 135 in 2020). The ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI) were defined according to the Fourth Universal Definition of Myocardial Infarction [8]. All data was gathered retrospectively, and the study was approved by institutional review committee.
3. Statistical analysis
All continuous variables are presented as mean with standard deviation (SD) or median (25th–75th percentiles). Categorical variables are presented as percentages or number of patients. All variables were tested for normal distribution. For categorical variable comparison we used Fisher or c2 tests. The Kruskal-Wallis (nonparametric test) test was used to compare multiple groups. To compare continuous variables we used the 2-sample unpaired Student's t-test (normal distribution) or Mann-Whitney U test. Correlations were tested using the Spearman rank order test. Two-sided p < 0.05 was considered significant. The IBM SPSS version 29 (IBM Corp. in Armonk, NY) was used.
4. Results
A total of 1126 patients were included in the study. Baseline characteristics pre-pandemic and during COVID-19 pandemic were comparable in both centers (Table 1). In Krosno during pandemic patients were significantly more often transported from home by emergency medical services (EMS) as opposed to period before COVID-19 (16.3 % pre-pandemic vs. 62.2 % during pandemic, p < 0.001; Table 2, Fig. 1). We did not observe differences in ways of presentation in hospital in Krakow (42.5 % both pre- and during pandemic for EMS transport). Killip class at admission in Krosno was higher during pandemic as compared to year 2019 (3.5 % vs. 10.4 % of patients with Killip 4 before and during COVID-19; p = 0.004). Again, those differences were not observed in Department of Interventional Cardiology in Krakow (1.4 % vs. 2.5 % for Killip 4; p = 0.398).
Table 1.
Baseline characteristics.
| Krosno |
Krakow |
|||||
|---|---|---|---|---|---|---|
| Pre-pandemic (313) |
Pandemic (135) |
p value | Pre-pandemic (280) |
Pandemic (398) |
p value | |
| Age, years | 66.1 ± 11.0 | 65.6 ± 11.6 | 0.219 | 67.7 ± 11.5 | 66.7 ± 11.8 | 0.725 |
| Sex (male), n (%) | 221 (70.6) | 87 (64.4) | 0.197 | 193 (68.9) | 277 (69.6) | 0.852 |
| BMI, kg/m2 | 28.2 ± 4.7 | 28.8 ± 5.2 | 0.167 | 29.9 ± 5.5 | 28.9 ± 5.2 | 0.827 |
| Diabetes mellitus, n (%) | 89 (28.4) | 39 (28.9) | 0.922 | 58 (20.7) | 69 (17.3) | 0.267 |
| Hypertension, n (%) | 215 (68.7) | 86 (63.7) | 0.302 | 156 (55.7) | 200 (50.3) | 0.161 |
| Hyperlipidemia, n (%) | 153 (48.9) | 52 (38.5) | 0.043 | 123 (43.9) | 153 (38.4) | 0.152 |
| Current smoker, n (%) | 92 (29.4) | 29 (21.5) | 0.210 | 52 (18.6) | 61 (15.3) | 0.378 |
| PCI, n (%) | 33 (10.5) | 12 (8.9) | 0.593 | 75 (26.8) | 68 (17.1) | 0.002 |
| CABG, n (%) | 8 (2.6) | 2 (1.5) | 0.480 | 18 (6.4) | 15 (3.8) | 0.113 |
Values are mean ± standard deviation (SD) or n (%). BMI indicates body mass index; CABG, coronary artery bypass grafting; PCI, percutaneous coronary intervention.
Table 2.
Characteristics during presentation at cathlab.
| Krosno |
Krakow |
|||||
|---|---|---|---|---|---|---|
| Pre-pandemic (313) |
Pandemic (135) |
p value | Pre-pandemic (280) |
Pandemic (398) |
p value | |
| Presentation in PCI centre | <0.001 | 0.991 | ||||
| Directly at PCI centre, n (%) | 3 (1.0) | 0 (0.0) | 19 (6.8) | 28 (7.0) | ||
| Transported from another hospital, n (%) | 259 (82.7) | 51 (37.8) | 142 (50.7) | 201 (50.5) | ||
| Transported from home by EMC, n (%) | 51 (16.3) | 84 (62.2) | 119 (42.5) | 169 (42.5) | ||
| ACS presentation | 0.194 | 0.095 | ||||
| STEMI, n (%) | 146 (46.6) | 72 (53.3) | 99 (35.4) | 166 (41.7) | ||
| NSTEMI, n (%) | 167 (53.4) | 63 (46.7) | 181 (64.6) | 232 (58.3) | ||
| Killip class at admission | 0.004 | 0.398 | ||||
| 1, n (%) | 277 (88.5) | 102 (75.6) | 229 (81.8) | 320 (80.4) | ||
| 2, n (%) | 20 (6.4) | 17 (12.6) | 42 (15.0) | 54 (13.6) | ||
| 3, n (%) | 5 (1.6) | 2 (1.5) | 5 (1.8) | 13 (3.3) | ||
| 4, n (%) | 11 (3.5) | 14 (10.4) | 4 (1.4) | 11 (2.8) | ||
Values are mean ± standard deviation (SD) or n (%). ACS indicates acute coronary syndrome; NSTEMI, non-ST elevation myocardial infarction; PCI, percutaneous coronary intervention; STEMI, ST-elevation myocardial infarction.
Fig. 1.
Differences in means of transport of patients with acute coronary syndrome between Krosno and Krakow before and during COVID-19.
EMC, emergency medical services.
Patients admitted to Interventional Cardiology Department in Krosno in 2020 had significantly higher high sensitive troponin (281 pre- vs. 430 ng/l during COVID-19; p < 0.001), CKMB (13.4 pre- vs. 26.6 U/I during COVID-19; p < 0.001) and NT-proBNP levels (1897 pre- vs. 7471 pg/ml during COVID-19; p < 0.025) as compared to pre-pandemic period. Interestingly, we did not observe major differences in laboratory values in patients admitted to hospital in Krakow in 2019 and 2020 (Table 3). In Krakow high sensitive troponin, CKMB and NT-proBNP levels were comparable before and during COVID-19 (163 vs. 189 ng/l; 27 vs 30 U/I; 1121 vs. 1132 pg/ml respectively, all p = NS).
Table 3.
Laboratory characteristics.
| Krosno |
Krakow |
|||||
|---|---|---|---|---|---|---|
| Pre-pandemic (313) |
Pandemic (135) |
p value | Pre-pandemic (280) |
Pandemic (398) |
p value | |
| Hs-troponin at admission, ng/l | 281 (74, 584) | 430 (223, 1411) | <0.001 | 163 (50, 500) | 189 (50, 620) | 0.404 |
| Maximum hs-troponin, ng/l | 1128 (375, 2942) | 1989 (666, 5039) | <0.001 | 920 (300, 3380) | 1300 (340, 3880) | 0.096 |
| CKMB at admission | 13.4 (5.5, 35.5) | 26.6 (11.7, 79.2) | <0.001 | 27 (17, 53) | 30 (18, 59) | 0.087 |
| Maximum CKMB, U/I | 33.9 (11.7, 108.1) | 71.8 (18.7, 169) | <0.001 | 48 (25, 126) | 72 (31, 158) | 0.009 |
| WBC, 1000/μL | 10.8 ± 4.2 | 12.1 ± 5 | 0.174 | 10.6 ± 4.2 | 10.7 ± 4.2 | 0.330 |
| NTproBNP, pg/ml | 1897 (510, 4495) | 7471 (1368, 16270) | 0.025 | 1121 (225, 2730) | 1132 (385, 3859) | 0.279 |
| Total cholesterol, mg/dl | 4.9 ± 1.4 | 4.8 ± 1.0 | 0.367 | 4.2 ± 1.2 | 4.5 ± 1.2 | 0.394 |
| LDL-C, mg/dl | 3.0 ± 1.3 | 3.4 ± 0.9 | 0.279 | 2.8 ± 1.1 | 3.1 ± 1.2 | 0.525 |
| HDL-C, mg/dl | 1.3 ± 0.5 | 1.3 ± 0.3 | 0.758 | 1.2 ± 0.3 | 1.2 ± 0.6 | 0.724 |
| Triglyceride, mg/dl | 2.0 ± 0.6 | 1.5 ± 0.6 | 0.235 | 1.6 ± 1.1 | 1.6 ± 1.0 | 0.773 |
| Creatinine, mg/dL | 0.98 ± 0.31 | 0.91 ± 0.28 | 0.822 | 1.1 ± 0.6 | 1.2 ± 0.6 | 0.988 |
| Hemoglobin, g/dl | 14.5 ± 4.9 | 13.5 ± 2.5 | 0.648 | 15.1 ± 3.5 | 14.5 ± 3.1 | 0.108 |
Values are mean ± standard deviation (SD), median (25th–75th percentiles) or n (%). HDL-C indicates high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; WBC, white blood cells.
Procedural characteristics were also comparable before and during pandemic in both interventional cardiology centers (Table 4). Time of procedure was comparable in both centers before and during COVID-19 (45 vs 40 min; p = 0.060 in Krosno and 75 vs 78 min; p = 0.102 in Krakow respectively). Radial access was most frequently used pre- and during pandemic both in Krosno (83.4 vs. 84.4 %; p = 0.947) and Krakow (80.0 vs. 78.9 %; p = 0.730). In Krakow time from first symptoms onset to admission (324 (151;698) min vs. 347 (153; 773) min; p = 0.438) did not differ before and during COVID-19. On the contrary, in Krosno we observed difference in time from first symptoms onset to admission (290 (120; 549) min vs. 420 (191; 885) min; p = 0.001). However, this data should be interpreted carefully as we did not have time information for all of the patients. For time from first symptoms onset to admission data was missing in 23.3 % (n = 158) of cases in Krakow and 18.5 % (n = 83) of cases in Krosno.
Table 4.
Procedural and anatomical characteristics.
| Krosno |
Krakow |
|||||
|---|---|---|---|---|---|---|
| Pre-pandemic (313) |
Pandemic (135) |
p value | Pre-pandemic (280) |
Pandemic (398) |
p value | |
| Contrast, ml | 197 ± 87 | 193 ± 81 | 0.621 | 189 ± 91 | 182 ± 95 | 0.659 |
| Time from admission to CAG, min | 63 (33, 156) | 54 (23,110) | 0.990 | 53 (26, 140) | 50 (29, 152) | 0.827 |
| Time of procedure, min | 45 ± 21 | 40 ± 26 | 0.060 | 75 ± 21 | 78 ± 21 | 0.102 |
| Radial access, n (%) | 261 (83.4) | 114 (84.4) | 0.947 | 224 (80.0) | 314 (78.9) | 0.730 |
| Multivessel disease, n (%) | 163 (52.1) | 63 (46.7) | 0.647 | 191 (68.2) | 274 (68.8) | 0.862 |
| IRA | 0.641 | 0.485 | ||||
| RCA, n (%) | 140 (44.7) | 63 (46.7) | 85 (30.4) | 117 (29.4) | ||
| LM, n (%) | 6 (1.9) | 2 (1.5) | 17 (6.1) | 33 (8.3) | ||
| LAD, n (%) | 98 (31.3) | 39 (28.9) | 99 (35.4) | 145 (36.4) | ||
| Cx, n (%) | 62 (19.8) | 31 (23.0) | 44 (15.7) | 70 (17.6) | ||
| Bypass graft, n (%) | 4 (1.3) | 0 (0.0) | 5 (1.8) | 5 (1.3) | ||
Values are mean ± standard deviation (SD), median (25th–75th percentiles) or n (%). CAG indicates coronary angiogram; Cx, circumflex coronary artery; IRA, infarct related artery; LAD, left anterior descending coronary artery; LM, left main coronary artery; RCA, right coronary artery.
Importantly, we did not observe increased complication rate during hospitalization in both centers. Death of any cause was comparable both in Krosno (4.5 % vs. 5.2 %, p = 0.743) and Krakow (7.5 % vs. 5.8 %, p = 0.370) pre- and during pandemic respectively. No re-myocardial infarctions were observed in Krosno while in Krakow differences were not statistically significant (0.4 % vs 0.8 %; p = 0.507). Similarly, mechanical complication rate also did not differ pre- and during pandemic in both cities (0.9 % vs. 0.7 %; p = 0.822 in Krosno and 0.7 % vs. 2.0 %; p = 0.168 in Krakow).
5. Discussion
In the present study we have demonstrated that changes in characteristics of patients who were admitted to hospital with ACS before and during COVID-19 pandemic may be region-dependent even when analysis. We have analyzed two catheterization laboratories located within the same country in the cities with the distance between them measuring only 137 km.
Most of the studies demonstrated prolonged time from symptom onset to first medical contact (FMC) during COVID-19 pandemic. Haddad et al. reported data from Greater Montreal Area where time from first symptoms to FMC increased over 1 h in patients with ACS [9]. On the contrary, Authors have not reported increased times from FMC to first intracoronary device activation. Similar results were reported by Sutherland et al. where time from first symptoms to FMC increased by about 100 min [1]. Importantly studies did not observe any differences between COVID negative and COVID positive patients during pandemic [6,10]. On the other hand, study which included 1287 AMI patients in Indonesia did not observe any differences in time from first symptom onset to FMC before and during COVID-19 pandemic [11]. Those discrepancies in results may highlight differences between healthcare systems and emergency medical services around the world. Notably, those studies did not analyze results on the regional level, nor reported results of laboratory tests. In our study we did not observe any differences in time from first symptoms onset to admission to hospital in Krakow, whereas this index was longer in Krosno during COVID-19 as opposed to period before pandemia. We have compared laboratory values such as NT-proBNP levels or troponin levels which are widely used and recognized markers of myocardial function and ischemia. Interestingly, we found that differences in NT-proBNP, troponin and CKMB levels were only visible in Krosno while they did not differ in Krakow. In line with our results regarding admission delay during COVID-19, patients in Krosno were admitted with greater myocardial injury and with more advanced heart failure expressed in NT-proBNP levels. Further, Killip class at admission in Krosno was also greater during COVID-19 pandemic as compared to pre-pandemic period. What is more, we observed change of pattern of admission of patients with ACS in Krosno with more patients being transported directly from home by EMS during pandemic, whereas there were no such changes in Krakow. We can only speculate on the reason of this finding, however we believe that there were few factors which could lead to this results.
According to different studies the main reason for not seeking medical help during COVID-19 pandemic was a belief that the system was already overloaded with COVID-19 patients and fear of being infected with COVID-19 [7]. Presumably patients with less severe symptoms could have delayed presenting at the hospital till their symptoms worsened. This behavior could have been caused by several reasons. First, during pandemic there were daily reports broadcasted in most of the TV channels regarding increase in number of COVID-19 patients, increase in mortality and crowded hospitals with long waiting times for both EMC and walk-in patients. What is more, media campaign encouraged people to self-isolate and this in turn could have stopped patients with milder symptoms to call EMC at the very beginning of the chest pain. Moreover, isolation could reduce possibility for elderly to seek immediate help. Lastly, EMC systems and hospitals depending on the region could have been more or less overwhelmed with too many patients and reports to EMS. Krakow is one of the major Polish cities with 8 hospitals with cardiology wards. Moreover, Krakow had two dedicated COVID-19 hospitals (one temporary hospital and one in academic center – St. John Paul II Hospital was not COVID center). Last but not least, Krakow is wealthier city with many international companies and several universities. With dedicated COVID-19 hospitals as well as larger number of hospitals in general patients might have been less afraid to seek immediate medical help and crowding could also have been smaller. Moreover, they could have been more aware of when they should seek professional help.
We can hypothesize that variables such as urban/rural areas, number of hospitals, education, wealth, residential density, population size, healthcare capacity, EMS services, traffic may influence pattern of behavior of patients with ACS. This could be partially resolved by region-specific protocols. Those could include: strengthening EMS coordination and services in rural areas; social/medical campaigns; media information adjusted to areas where they are provided.
Of course centralization of some parts of medical services may also improve outcomes. Opening COVID-19 dedicated hospitals, transferring parts of the EMS services or even transferring physicians to different regions may prevent the healthcare system from collapsing.
In our study we did not observe differences in procedural characteristics pre- and during pandemic. Our results are mostly in line with other studies [6,[12], [13], [14]]. Depending on the study there are slight differences such as greater contrast use and higher radiation, less procedures from radial access or shift toward more patients with STEMI during COVID-19 pandemic. However, those results were not consistent through different studies highlighting potential discrepancies in healthcare systems depending on the region, population and “national level” treatment strategies. We have not observed major differences in patients' characteristics before and during COVID-19 pandemic neither in Krakow nor in Krosno. Those results are similar to other studies where also no significant differences were reported [12,[14], [15], [16]].
Last but not least, in our study we did not observe differences in in-hospital mortality. This is in contrary to some other studies which found increased complication rate and mortality in patients during COVID-19 as compared to period before pandemic [[17], [18], [19]]. We believe there may be few explanations of those differences. First, our study compared only two sites as opposed to multicenter study of De Luca et al. and thus smaller number of patients in our study. Second, we have assessed both STEMI and NSTEMI patients while most studies concentrated on STEMI patients only. Third, none of patients in our study underwent thrombolysis before PCI procedure. Moreover, our study covered whole year of 2020 beginning from April while part of the studies included only patients admitted at the beginning of pandemic. Importantly, mortality rates may differ across different sites which not necessarily may be outlined in multicenter studies. Lastly, hospital in Krakow were the study took place was not a dedicated COVID-19 hospital.
6. Limitations
Several limitations should be noted. First, this study was a retrospective analysis. Second, we have included only two interventional cardiology centers thus our results may only be hypothesis generating and cannot be extrapolated to all the interventional cardiology units. Third, the relatively small number of patients might have introduced a selection bias. Forth, adverse events were only recorded during the hospitalization in the interventional cardiology ward – the most complex patients could have been transferred to intensive care units where the data regarding their status was not collected. Data for time periods (symptom onset) was only available for part of the patients. Lastly, due to crucial data missing we did not include April 2019 in Krakow. However, differences in ACS patients characteristics were usually found between different seasons (mainly winter and summer) not between months within the same season so that should not introduce potential bias [20,21].
7. Conclusions
Although COVID-19 pandemic ended in May 2023, strain on the medical system was still visible afterwards due to delayed procedures and missed diagnosis during pandemic. Currently the healthcare systems around the world have mostly recovered, however after the COVID-19 pandemic the need to prepare dedicated protocols for such events is clearly seen. In our study we showed that even among the same country there may be quite large differences in health condition of patients admitted with ACS. Despite not such a long distance patients behavior may be different. In Krakow, one of the biggest cities in Poland, during COVID-19 patients did not change their “pattern of admittance” to hospital. On the other hand, during COVID-19 patients living around Krosno waited till their symptoms were more severe as compared to period before pre-pandemic. Moreover, they resigned from coming to the hospitals themselves and mostly relied on EMS services coming to their homes. Those results highlight the need on concentrating on regional protocols on how to improve patient related factors and accessibility to healthcare system.
CRediT authorship contribution statement
K. Bryniarski: Writing – review & editing, Writing – original draft, Supervision, Project administration, Methodology, Formal analysis, Data curation, Conceptualization. D. Makowicz: Writing – review & editing, Project administration, Methodology, Data curation. P. Kleczynski: Writing – review & editing, Methodology, Data curation. M. Nosal: Writing – review & editing, Data curation. P. Brzychczy: Writing – review & editing, Data curation. K. Mroz: Writing – review & editing, Formal analysis, Data curation. M. Okarski: Writing – review & editing, Data curation. J. Twardosz: Writing – review & editing, Data curation. M. Gasior: Writing – review & editing, Methodology, Conceptualization. J. Legutko: Writing – review & editing, Writing – original draft, Formal analysis, Data curation, Conceptualization.
Ethical statement
All data was gathered retrospectively, and the study was approved by institutional review committee (Ethics Committee under Krakow Medical Council).
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Fee for publication was covered from grant "Pathogenesis of Acute Coronary Syndromes in Patients with COVID-19: An OCT study" sponsored by Abbott Medcial.
Acknowledgements
Fee for publication was covered from grant "Pathogenesis of Acute Coronary Syndromes in Patients with COVID-19: An OCT study" sponsored by Abbott Medcial.
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