RU2848388C1 - Method for estimating the probability of the presence of ectasia of the infarction-responsible coronary artery in myocardial infarction with st-segment elevation - Google Patents

Abstract

FIELD: medical science.

SUBSTANCE: invention refers to medicine, namely to cardiology, and can be used for assessing a probability of infarction-related coronary artery ectasia accompanying ST elevation myocardial infarction. Patient’s medical history data, clinical, biochemical blood tests, as well as coagulogram data are studied. Wherein, the following are assessed as predictors: age, presence or absence of diabetes mellitus, erythrocyte count, average volume of erythrocytes and thrombocytes, coefficient of large thrombocytes, level of total protein, total cholesterol, low density lipoproteins, total bilirubin and activated partial thromboplastin time. Derived data are used to derive a probability (p) of the presence of ectasia of the infarction-related coronary artery by a given formula. If the value p is equal to 0.535 or higher, the probability of infarction-related coronary artery ectasia is considered to be high, and if p is less than 0.535, the probability of infarction-related coronary artery ectasia is considered to be low.

EFFECT: method enables providing more accurate and reliable assessment of a probability of the presence of ectasia of the infarction-related coronary artery accompanying ST-elevation myocardial infarction by assessing a set of the most significant parameters.

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Description

The invention relates to medicine, namely to cardiology, and is intended to assess the probability of the presence of ectasia of the infarction-related coronary artery during myocardial infarction with ST segment elevation.

ST-segment elevation myocardial infarction (STEMI) is the most severe form of coronary heart disease and remains a leading cause of death worldwide. The primary cause of STEMI is the development of occlusive atherothrombosis due to rupture or erosion of an atherosclerotic plaque. Coronary artery ectasia is a condition characterized by segmental or diffuse dilation of one or more coronary arteries with a diameter greater than 1.5 times that of the adjacent normal segment or the diameter of the largest coronary artery (Kuno T. et al. A rare case of acute myocardial infarction with multivessel coronary artery ectasia successfully treated with percutaneous coronary intervention and systemic thrombolysis, Internal Medicine, 2015, 54(9), p. 1057-62; Diaz-Zamudio M. et al. Coronary artery aneurysms and ectasia: role of coronary CT angiography, Radiographics, 2009, 29(7), p. 1939-1954). With such a change in the vascular wall, there is, first of all, a slowdown in blood flow inside the coronary artery, a decrease in perfusion of both the epicardial coronary artery and the microcirculatory bed, which is associated with an increased risk of massive coronary thrombosis, the development of the phenomenon of “non-restored coronary blood flow”, as well as an increase in mortality in the long-term follow-up period (Lee H.H. et al. Recurrent thrombosis in a case of coronary ectasia with large thrombus burden successfully treated by adjunctive warfarin therapy, Acta Cardiologica Sinica, 29.5 2013, p. 462; Schram H.C.F. et al. Coronary artery ectasia, an independent predictor of noreflow after primary PCI for ST-elevation myocardial infarction, International Journal of Cardiology, 265, 2018, pp. 12-17; Wang J.W. et al. A risk score for noreflow inpatients with ST-segment elevation myocardial infarction after percutaneous coronary intervention, Clin. Cardiol., 2015, 38(4), p. 208-215; Ndrepepa G. et al. 5-Year prognostic value of no-reflow phenomenon after percutaneous coronary intervention in patients with ac ute myocardial infarction, J Am Co 11 Cardiol, 2010, 55(21), p. 2383-2389).

Coronary artery ectasia is a known predisposing factor for the development of ACS. According to the results of a large study, 22,235 coronary angiographies were performed over 4 years, of which 1,044 (4.6%) were found to have coronary artery ectasia. Moreover, in the majority of cases (more than 80%), the ectatic coronary artery was the culprit artery in the development of ACS (AN L. et al. Coronary artery ectasia: prevalence and clinical characteristics: experience from a single cardiac center, The Professional Medical Journal. 2017 Apr 6, 24(04), p. 545-553).

According to another large study conducted among 1354 patients with STEMI, coronary artery ectasia is a significant factor in the development of STEMI specifically in the territory of the ectatic coronary artery (p=0.003) (Raja W. et al. Frequency, associated risk factors and angiographical classification of coronary artery ectasia (CAE) and coronary artery aneurysm (CAA) in st elevation myocardial infarction (STEMI) patients undergoing primary percutaneous coronary intervention (PPCI), Pakistan Armed Forces Medical Journal. 69(3), 2019, p. 359-364).

Identification of risk factors and development of predictive models for the presence of infarct-related coronary artery ectasia in STEMI may serve as a basis for personalized therapy, potentially improving clinical outcomes and reducing the likelihood of complications.

Among the data in the world literature, various anamnestic and laboratory predictors that predict the presence of coronary artery ectasia have been described.

According to existing data, among patients with coronary artery ectasia, the number of those who suffer from diabetes mellitus is less common. According to the literature, this may be due to the peculiarity of the pathogenesis of diabetes mellitus, in which there is a decrease in the level of MMP in the smooth muscle cells of the vascular wall, and a decrease in endothelial dilation mediated by NO is also observed, which leads to some decrease in the expression of factors influencing the development of coronary artery ectasia (Sorrell V. et al. Origins of coronary artery ectasia, The Lancet, 1996 Jan 20, 347 (8995), p. 136-137; Kuzuya M. et al. Glycation cross-links inhibit matrix metalloproteinase-2 activation in vascular smooth muscle cells cultured on collagen lattice, Diabetologia, 2001, 44, p. 433-436).

It is believed that one of the main causes of coronary artery ectasia development is atherosclerosis (Demopoulos V.P. et al. The natural history of aneurysmal coronary artery disease, Heart, 78, 1997, p. 136-141; Markis J.E. et al. Clinical significance of coronary artery ectasia, Am. J. Cardiol., 1976, 37, p. 217-222; Swanton R.H. et al. Coronary artery ectasia - a variant of occlusive coronary arteriosclerosis, Br. Heart. J., 1978, 40, p. 393-400). It was demonstrated that a decrease in HDL levels and an increase in LDL levels are strong and independent predictors of the presence of coronary artery ectasia. Thus, an increase in HDL levels by 1 mmol/L is associated with a 15% reduction in the risk of detecting ectasia. In addition, an independent predictor of the detection of coronary artery ectasia is an increase in the LDL to HDL ratio (Jafari J et al. Low high-density lipoprotein cholesterol predisposes to coronary artery ectasia. Biomedicines, 2019, Oct 7, 7(4), p. 79).

In addition, patients with coronary artery ectasia exhibit specific blood counts. Several studies have shown an association between an increase in red blood cell distribution width and an increase in hemoglobin levels in patients with coronary artery ectasia (Vrachatis D.A. et al. Inflammatory Biomarkers in Coronary Artery Ectasia: A Systematic Review and Meta-Analysis, Diagnostics 2022, 12, p. 1026; Jafari J et al. Low high-density lipoprotein cholesterol predisposes to coronary artery ectasia, Biomedicines, 2019 Oct 7, 7(4), p. 79).

It is quite paradoxical that in patients with coronary artery ectasia, with increased levels of hemoglobin and red blood cells, lower values of total serum bilirubin are detected (Demir M et al. The relationship between serum bilirubin concentration and coronary artery ectasia, Advances in Interventional Cardiology/Postepy w Kardiologii Interwencyjnej, 2015 Sep 28, 11(3), p. 202-225; Mimethashree, K.T., A Study of Serum Bilirubin and Total Cholesterol/(Hdl+Bilirubin) in Patients with and Without Coronary Artery Disease, Diss. Rajiv Gandhi University of Health Sciences (India), 2019).

According to the literature, total bilirubin is able to act as an antioxidant, reducing lipid oxidation, inflammation in the vascular wall and preventing the development of atherosclerosis, reducing the impact of risk factors for coronary heart disease (Mayer M., Association of serum bilirubin concentration with risk of coronary artery disease, Clin. Chem., 2000, 46, p. 1723-1727; Schwertner H.A., Association of smoking and low serum bilirubin antioxidant concentrations, Atherosclerosis, 1998, 136, p. 383-387; Stocker R. et al. Antioxidant activity of albumin-bound bilirubin, Proc. Natl. Acad. Sci USA, 1987, 84, p. 5918-5922; Madhavan M. et al. Serum bilirubin distribution and its relation to cardiovascular risk in children and young adults, Atherosclerosis, 1997, 131, p. 107-113; Hopkins P.N. et al. Higher serum bilirubin is associated with decreased risk for early familial coronary artery disease, Arterioscler. Thromb. Vase. Biol., 1996, 16, p. 250-255; Djousse L. et al. Total serum bilirubin and risk of cardiovascular disease in the Framingham offspring study, Am. J. Cardiol, 2001, 87, p. 1196-2000).

In connection with the above, it is assumed that the decrease in bilirubin levels is associated with the development of compensatory mechanisms. It has been shown that higher levels of direct serum bilirubin have a beneficial effect on the state of microcirculation in the myocardium, reducing the risk of no-reflow (Gullu H. et al. High serum bilirubin concentrations preserve coronary flow reserve and coronary microvascular functions, Arteriosclerosis, thrombosis, and vascular biology, 2005 Nov 1,25(11), p. 2289-2294; Demir M. et al. The relationship between serum bilirubin concentration and coronary slow flow, Therapeutic Advances in Cardiovascular Disease, 2013 Dec, 7(6), p. 316-321).

In addition, it has been established that an increased mean platelet volume is a predictor of the presence of coronary artery ectasia (Demir S. et al. Increased mean platelet volume is associated with coronary artery ectasia, Advances in Interventional Cardiology/Posterjy w Kardiologii Interwencyjnej, 2013 Jul 1, 9(3), p. 241-245). An increase in mean platelet volume has been shown to be an unfavorable risk factor in patients in the late period after ACS, increasing the chance of death by 1.7 times (Moghadam R.H. et al. Comparison of mean platelet volume levels in coronary artery ectasia and healthy people: systematic review and meta-analysis, Blood research, 2018 Dec, 53(4), p. 269; Chu S.G. et al. Mean platelet volume as a predictor of cardiovascular risk: a systematic review and meta-analysis, Journal of Thrombosis and Haemostasis, 2010 Jan 1, 8(1), p. 148-156).

Other studies have described the role of chronic inflammation in patients with coronary artery ectasia. It has been demonstrated that patients with coronary artery ectasia are characterized by an increase in the neutrophil-lymphocyte ratio, C-reactive protein, interleukin-6, tumor necrosis factor-alpha (Vrachatis D.A. et al. Inflammatory Biomarkers in Coronary Artery Ectasia: A Systematic Review and Meta-Analysis, Diagnostics, 2022, 12, p. 1026), and antinuclear antibody levels (Chalikias G. et al. Coronary artery ectasia as an autoimmune disease paradigm in a cross-sectional case-control study, The American Journal of Cardiology, 2023 Oct 15, 205, pp. 63-68), which suggests the influence of the immune-inflammatory component on the likelihood of developing coronary artery ectasia. However, the described risk factors for the presence of coronary artery ectasia have some drawbacks. The severity of any given risk factor was not adjusted relative to other risk factors when constructing predictive models, which may be due to insufficient predictive effectiveness.

Thus, there is a need to develop a method for assessing the probability of the presence of ectasia of the infarct-related coronary artery in ST-segment elevation myocardial infarction that is free from the above-mentioned drawback.

The technical result of the proposed method is to increase the accuracy and reliability of assessing the probability of the presence of ectasia of the infarction-related coronary artery in myocardial infarction with ST segment elevation by identifying more objective and accessible predictors of this process for analysis.

In order to achieve the specified technical result in the method for assessing the presence of ectasia of the infarction-related coronary artery in myocardial infarction with ST segment elevation, including the study of patient anamnestic data, clinical, biochemical blood tests, as well as coagulogram data, and the identification of predictors for assessing the probability of the presence of ectasia of the infarction-related coronary artery in myocardial infarction with ST segment elevation with the creation of a mathematical model that allows assessing the probability of the presence of ectasia of the infarction-related coronary artery depending on the level of predictors, it is proposed to assess age, the presence of diabetes mellitus, the level of red blood cells, the mean volume of red blood cells and platelets, the coefficient of large platelets, the level of total protein, total cholesterol, low-density lipoproteins, the level of total bilirubin and activated partial thromboplastin time as predictors, the obtained data to be entered into the prognostic mathematical model:

p=1/(1+e ^-z )

z=-9.676 + 0.049 * X _age - 0.654 * X _diabetes + 0.671 * X _{red blood cells} + 0.028 * X _MCV + 0.449 * X _MPV + 0.093 * X _P-LCR - 0.037 * X _{total protein} - 0.735 * X _{total cholesterol} + 0.852 * X _LDL - 0.117 * X _bilirubin + 0.034 * X _APTT ;

X _age – patient’s age, years;

X _DM - presence of diabetes mellitus, 0 - absence, 1 - presence;

X _erythrocytes - the number of erythrocytes, 10 ¹² /l;

X _MCV - mean corpuscular volume, fl;

X _MPV - mean platelet volume, fl;

X _P-LCR - large platelet coefficient, %;

X _{total_protein} – level of total protein in blood serum, g/l;

X _{total_cholesterol} - total cholesterol level, mmol/l;

X _LDL - low density lipoprotein level, mmol/l;

X _bilirubin - total bilirubin level, μmol/l;

Х _aPTV - activated partial thromboplastin time, sec;

and with a p value equal to 0.535 or higher, the probability of the presence of ectasia of the infarction-related coronary artery is assessed as high, with a p value less than 0.535, the probability of the presence of ectasia of the infarction-related coronary artery is assessed as low.

The method is carried out as follows.

Initial data such as age, diabetes mellitus, red blood cell count, mean corpuscular and platelet volume, large platelet ratio, total protein, total cholesterol, low-density lipoprotein, total bilirubin, and activated partial thromboplastin time are collected and analyzed. Samples were collected upon admission to the hospital.

The obtained data are entered into a predictive mathematical model:

p=1/(1+e ^-z )

where z=-9.676+0.049 * X _age - 0.654 * X _diabetes + 0.671 * X _{red blood cells} + 0.028 * X _MCV + 0.449 * X _MPV + 0.093 * X _P-LCR - 0.037 * X _{total protein} - 0.735 * X _{total cholesterol} + 0.852 * X _LDL - 0.117 * X _bilirubin + 0.034 * X _APTT ;

X _age – patient’s age, years;

X _DM - presence of diabetes mellitus, 0 - absence, 1 - presence;

X _erythrocytes - the number of erythrocytes, 10 ¹² /l;

X _MCV - mean corpuscular volume, fl;

X _MPV - mean platelet volume, fl;

X _P-LCR - large platelet coefficient, %;

X _{total_protein} – level of total protein in blood serum, g/l;

X _{total_cholesterol} - total cholesterol level, mmol/l;

X _LDL - low density lipoprotein level, mmol/l;

X _bilirubin - total bilirubin level, μmol/l;

X _APTT - activated partial thromboplastin time, sec;

and with a p value equal to 0.535 or higher, the probability of the presence of ectasia of the infarction-related coronary artery is assessed as high, with a p value less than 0.535, the probability of the presence of ectasia of the infarction-related coronary artery is assessed as low.

A retrospective multicenter study included 160 patients with STEMI (mean age 60 years). Among the study patients, 80 were in the group with infarct-related coronary artery ectasia and 80 in the group without infarct-related coronary artery ectasia. To identify predictors of infarct-related coronary artery ectasia, patient medical history data, clinical and biochemical blood tests, and coagulation profile data were analyzed. A predictive model was constructed using binary logistic regression, followed by a search for the optimal predictive function value using ROC analysis.

Between January 2014 and February 2022, a retrospective selection of 160 patients who underwent emergency primary percutaneous coronary intervention for STEMI was performed. The diagnosis of STEMI was made based on an analysis of complaints (typical chest pain lasting >30 minutes), anamnesis, 12-lead ECG data (ST segment elevation >1 mm in two or more adjacent leads or newly diagnosed left bundle branch block), and troponin I levels. Patients with cardiogenic shock on admission, with an active infectious process (including COVID-19), with a history of systemic inflammatory diseases, malignant neoplasms, liver diseases, as well as patients with baseline anemia (hemoglobin level <130 g/L for men and <120 g/L for women) were excluded from the analysis.

Initial data were collected and analyzed, including age, diabetes mellitus, red blood cell count, mean corpuscular and platelet volume, large platelet ratio, total protein, total cholesterol, low-density lipoprotein, total bilirubin, and activated partial thromboplastin time. Samples were collected upon hospital admission.

At the prehospital stage, all patients received dual antiplatelet therapy (DAT) consisting of 300 mg of acetylsalicylic acid and 600 mg of clopidogrel. Heparin at a dosage of 5000 IU was used as an anticoagulant. In addition, patients received beta-blockers, statins, and other drugs in accordance with current guidelines for the treatment of STEMI. Primary coronary angiography (CAG) was performed using a radial approach. Visualization of the coronary arteries was performed with 5F diagnostic catheters using left and right oblique projections with caudal and cranial angulation. The visualization rate was 30 frames/sec. Contrast agent (Omnipaque 350, GE Healthcare) was manually injected at each position. During CAG, the results of which were used to verify the IOCA in comparison with electrocardiographic (ECG) criteria, primary PCI was performed. After restoration of antegrade blood flow in the IOC, the severity of coronary thrombosis was assessed using the angiographic scale Thrombolysis in myocardial infarction (TIMI) thrombus grade (TTG):

Grade 0: no angiographic evidence of thrombosis

Grade 1: likely presence of a thrombus, impaired mural contrast, uneven vessel contours

Grade 2: thrombus no larger than ^1/2 _the diameter of the IOC

Grade 3: _longitudinal thrombus dimension > ^1/2 but <2 IOC diameters

Grade 4: longitudinal thrombus size >2 IOC diameters

Grade 5: total occlusion of the IOCA.

Patients were divided into two groups depending on the presence or absence of ectasia of the infarct-related coronary artery. In addition, in some patients from the infarct-related coronary artery ectasia group, primary PCI was performed in two stages: the first stage was restoration of the lumen and antegrade coronary blood flow, and the second stage was stent implantation. During the first stage of the procedure, the so-called minimally invasive mechanical strategy (MIMS) was used to restore blood flow to the TIMI 3 level, followed by intensified antiplatelet therapy. MIMS involves mechanical recanalization with a guidewire in combination with balloon dilation (balloon catheter diameter no more than 1.5-2 mm) and/or manual vacuum thromboaspiration (6 Fr Export catheter). After primary coronary angiography, all patients undergoing MIMS received IIb/IIIa glycoprotein receptor blockers for up to 48 hours. Continuous intravenous administration of unfractionated sodium heparin at a dosage of 50-60 IU/kg was used as an anticoagulant during PCI until the target heparinization level was achieved, which was assessed by determining the activated clotting time (ACT), the target indicator was 300-350 s. Subsequently, after at least 5-6 days, repeat CAG and, if necessary, stenting of residual stenosis were performed. Stent implantation into residual stenosis was carried out taking into account its significance of more than 50%. SPSS Statistics 26.0 software was used for statistical processing of the results. The normality of distribution was tested using the Kolmogorov-Smirnov method with Lilliefors correction. With a normal distribution, the quantitative indicator was presented as the arithmetic mean (M), with a standard deviation (±SD) and a 95% confidence interval (95% CI). For non-normal distribution, the quantitative indicator was presented as the median (Me) with the interquartile range (Q1-Q3). Intergroup differences were assessed using the Student's t-test or Welch's t-test (depending on the equality of variances) for normal distributions, and the Mann-Whitney U-test for non-normal distributions. Comparative analysis of categorical variables was performed using Pearson's χ2 or Fisher's exact test. The nominal indicator was represented as the absolute number of observations; the percentage of the feature in subgroups is given. Binary logistic regression was used to develop the predictive model. ROC analysis was used to adjust the optimal value of the prognostic function. In all statistical analysis procedures, the critical significance level was set at p < 0.05.

A total of 160 patients with STEMI were analyzed in the study. The average age of the subjects was 68 years, and 84% were men. Primary clinical and laboratory parameters between the compared groups are presented in Table 1.

When analyzing the baseline data, it was found that most of the analyzed data, such as male gender (p=0.52), body mass index (p=0.392), smoking (p=0.379), diabetes mellitus (p=0.34), arterial hypertension (p=1.0) were balanced between the subgroups, while patients in the infarction-related coronary artery ectasia group were older (p=0.001). In addition, in the infarction-related coronary artery ectasia group, higher values of red blood cell count (p=0.007), mean corpuscular volume (p=0.013), hemoglobin (p=0.045), mean platelet volume (<0.001), large platelet ratio (p<0.001), low-density lipoproteins (p=0.009) were found.

When analyzing the IOC data, it was found that in the group with infarction-related coronary artery ectasia, there was a tendency toward a more frequent development of infarction in the right coronary artery territory (p=0.06). In our study, 80% of patients with infarction-related coronary artery ectasia were found to have massive coronary thrombosis (TG 3-5). In turn, 99% of the control group also had massive coronary thrombosis, with no statistical difference between the subgroups.

A mathematical model was developed to predict the probability of ectasia in the infarct-related coronary artery based on various clinical and laboratory parameters. Stepwise factor selection using the elimination method yielded a logistic function including 11 predictors: The observed relationship is described by the equation:

p=1/(1+e ^-z )

where z=-9.676 + 0.049 * X _age - 0.654 * X _SD + 0.671 * X _{red blood cells} + 0.028 * X _MSM + 0.449 * X _MPV + 0.093 * X _P-LCR - 0.037 * X _{total protein} - 0.735 * X _{total cholesterol} + 0.852 * X _LDL - 0.117 * X _bilirubin + 0.034 * X _APTT ;

X _age – patient’s age, years;

X _sd - presence of diabetes mellitus, 0 - absence, 1 - presence;

X _erythrocytes - the number of erythrocytes, 10 ¹² /l;

X _MCV - mean corpuscular volume, fl;

X _MPV - mean platelet volume, fl;

X _P-LCR - large platelet coefficient, %;

X _{total_protein} – level of total protein in blood serum, g/l;

X _{total_cholesterol} - total cholesterol level, mmol/l;

X _APNP - low density lipoprotein level, mmol/l;

X _bilirubin - total bilirubin level, μmol/l;

X _APTT - activated partial thromboplastin time, sec,

and with a p value equal to 0.535 or higher, the probability of the presence of ectasia of the infarction-related coronary artery is assessed as high, with a p value less than 0.535, the probability of the presence of ectasia of the infarction-related coronary artery is assessed as low.

Based on the coefficient values, factors such as increasing age, increasing red blood cell count, increasing mean corpuscular volume, increasing mean platelet volume, increasing large platelet ratio, increasing low-density lipoprotein levels, and increasing activated partial thromboplastin time are directly related to the likelihood of infarct-related coronary artery ectasia.

While the presence of diabetes mellitus, increased cholesterol levels, serum total protein levels, and increased bilirubin levels reduce the likelihood of infarction-related coronary artery ectasia.

The resulting prognostic model is statistically significant (p<0.001). According to the Neidelgerkerk coefficient of determination, the model accounts for 50% of the factors determining the presence of ectasia in the infarct-related coronary artery.

Table 2 defines the parameters of the relationship between each of the model predictors and the odds of having ectasia of the infarction-related coronary artery.

Using ROC analysis, the most optimal value of the prognostic function P was determined. The resulting curve is shown in Fig. 1 (ROC curve characterizing the dependence of the assessment of the probability of the presence of ectasia of the infarction-related coronary artery on the value of the logistic function p).

The area under the ROC curve was 0.865±0.028 (95% CI: 0.81-0.92). The logistic function P value at the cut-off point was 0.535. Patients with P values equal to 0.535 or higher are considered to have a high probability of having ectasia of the infarct-related coronary artery; with a p value less than 0.535, the probability of having ectasia of the infarct-related coronary artery is considered to be low. The sensitivity of the model at the selected cut-off point was 77.5% (62 correct estimates out of 80 cases of the presence of ectasia of the infarct-related coronary artery), the specificity was 78.8% (63 correct estimates out of 80 cases of the absence of ectasia of the infarct-related coronary artery). The overall diagnostic efficiency was 78.1%.

According to the results of this study, a model for assessing the probability of infarction-related coronary artery ectasia based on such indicators as age, diabetes mellitus, red blood cell count, mean corpuscular and platelet volume, large platelet ratio, total protein, total cholesterol, low-density lipoprotein, total bilirubin, and activated partial thromboplastin time (APTT) provides a prediction accuracy of 78.1%. Independent predictors of the presence of infarction-related coronary artery ectasia include age, red blood cell count, mean platelet volume, large platelet ratio, and LDL level.

The results of the present study demonstrated that age is an independent predictor of the presence of ectasia in the infarction-related coronary artery, which is confirmed by literature data according to which atherosclerosis is the main cause of the development of ectasia in adulthood (Demopoulos V.P. et al. The natural history of aneurysmal coronary artery disease, Heart, 78, 1997, p. 136-141).

In addition, an increase in red blood cell count and a decrease in bilirubin levels have also been demonstrated in patients with coronary artery ectasia in other studies (Vrachatis D.A. et al. Inflammatory Biomarkers in Coronary Artery Ectasia: A Systematic Review and Meta-Analysis, Diagnostics, 2022, 12, p. 1026; Jafari J et al. Low high-density lipoprotein cholesterol predisposes to coronary artery ectasia, Biomedicines, 2019 Oct 7, 7(4), p. 79; Demir M. et al. The relationship between serum bilirubin concentration and coronary slow flow, Therapeutic Advances in Cardiovascular Disease, 2013 Dec, 7(6), p. 316-321; Mimethashree, K.T., A Study of Serum Bilirubin and Total Cholesterol/(Hdl+Bilirubin) in Patients with and Without Coronary Artery Disease, Diss. Rajiv Gandhi University of Health Sciences (India), 2019).

It should be noted that in our study, elevated hemoglobin levels also predicted the presence of infarct-related coronary artery ectasia. However, when subsequently adjusted for other factors, primarily red blood cell levels, hemoglobin levels did not improve the predictive performance of the model, and therefore were not included in the model.

An increase in mean platelet volume and large platelet ratio independently predict the presence of ectasia in the infarct-related coronary artery, suggesting the presence of certain morphological changes in blood cells. Similar changes in patients with coronary artery ectasia have been described previously (Demir S. et al., "Increased mean platelet volume is associated with coronary artery ectasia," Advances in Interventional Cardiology/Postepiy w Kardiologii Interwencyjnej, 2013 Jul 1, 9(3), p. 241-245).

It is noteworthy that in our study, an increase in the level of low-density lipoproteins is an independent predictor of the presence of ectasia of the infarction-related coronary artery, which is also confirmed by data from the world literature (Jafari J et al. Low high-density lipoprotein cholesterol predisposes to coronary artery ectasia, Biomedicines, 2019 Oct 7, 7(4), p. 79; Mahmoud K.S. et al. Clinical and laboratory predictors of isolated coronary artery ectasia in patients with chronic coronary syndromes, Inflammation, 2023 Aug 21, 12, p. 13).

Total cholesterol levels also demonstrate similar properties as an independent predictor of the presence of ectasia in the infarct-related coronary artery; however, an increase in total cholesterol levels reduces the likelihood of detecting ectasia. This is likely due to certain features of the lipid profile in patients with these coronary artery changes. It is assumed that in patients with coronary artery ectasia, total cholesterol increases due to low-density lipoproteins with a decrease in HDL levels, as demonstrated in a recent study (Jafari J et al. Low high-density lipoprotein cholesterol predisposes to coronary artery ectasia, Biomedicines, 2019 Oct 7, 7(4), p. 79).

The high prognostic value and accuracy of the method are confirmed by the clinical examples below.

Example 1. Patient X., 68 years old, was delivered by an ambulance team to the intensive care unit for cardiac patients at the Mytishchi Regional Cardiology Center on June 8, 2015, at 12:30 p.m. The patient reported severe chest pain radiating to the left arm and left shoulder blade, as well as severe general weakness and cold sweat.

The patient's medical history revealed that the onset of symptoms occurred at 10:00 AM and he self-treated unsuccessfully. As pain intensified, he called an ambulance. An ECG revealed ST-segment elevation in leads I, aVL, and V5-V6, with reciprocal ST-segment depression in leads III, aVF, and V2-V4. Subsequently, the diagnosis of lateral myocardial infarction was confirmed by troponin I testing. Prehospital, the patient received standard treatment for STEMI, including aspirin, clopidogrel, and morphine. His condition was assessed as severe. During hospitalization, a general and biochemical blood test were performed, as well as a coagulogram analysis: erythrocytes = 4.27 * 10 ¹² , MCV = 93.1 fl, MPV = 7.8 fl, P-LCR = 12.8%, total protein = 59 g / l, total cholesterol = 6.71 mmol / l, LDL = 1.9 mmol / l, bilirubin = 5.5 μmol / l, APTT = 28.2 sec. The patient did not suffer from diabetes mellitus.

Accordingly, the following values of predictors taken into account when calculating the risk of ectasia of the infarction-related coronary artery were established for this patient:

- age (X _age = 68);

- presence of diabetes mellitus (Х _СД = 0);

- the number of erythrocytes (X _erythrocytes = 4.27 * 10 ¹² );

- mean corpuscular volume (X _MCV = 93.1 fl);

- mean platelet volume (X _MPV = 7.8 fl);

- coefficient of large platelets (X _P-LCR = 12.8%);

- total serum protein (X _{total_protein} = 59 g/l);

- total cholesterol value (Total _cholesterol = 6.71 mmol/l);

- the value of low-density lipoproteins ( _LDL = mmol/l);

- total bilirubin value (X _bilirubin = 5.5 μmol/l);

- activated partial thromboplastin time (X _APTT = 28.2 sec).

By substituting the obtained variable values into the formula, we calculated the probability of having ectasia in the infarct-related coronary artery, which was 0.203. Since the obtained value did not exceed 0.535, we assumed a low risk of having ectasia in the infarct-related coronary artery. The initial coronary angiography revealed critical stenosis of the right coronary artery in the absence of diffuse or focal coronary artery ectasia. Subsequently, a Xience 3.5×18 mm stent was implanted in the patient's right coronary artery. The postoperative period was uneventful, and the patient was discharged after 7 days.

Example 2. Patient M., 52, was admitted by ambulance to the cardiac intensive care unit of the Mytishchi City Hospital on October 13, 2018, at 3:20 PM. He complained of acute chest pain radiating to his left arm. His medical history revealed that the presenting symptoms began at 1:00 PM while he was relatively calm. At 2:30 PM, he called an ambulance. His ECG revealed ST-segment elevation in leads II, III, and aVF, with reciprocal changes in leads I and aVL of up to 2 mm. The diagnosis of acute inferior STEMI was subsequently confirmed by a troponin I blood test. Prehospital, the patient received standard treatment for STEMI, including aspirin, clopidogrel, and morphine. His condition was assessed as severe. During hospitalization, a general and biochemical blood test were performed, as well as a coagulogram analysis: erythrocytes = 5.61 * 10 ¹² , MCV = 79.7 fl, MPV = 8.4 fl, P-LCR = 8.4%, total protein = 54.6 g / l, total cholesterol = 2.28 mmol / l, LDL = 0.91 mmol / l, bilirubin = 15.1 μmol / l, APTT = 53.3 sec. The patient denied a history of diabetes mellitus.

Accordingly, the following values of factors taken into account when calculating the risk of ectasia of the infarction-related coronary artery were established for this patient:

- age (X _age = 52);

- presence of diabetes mellitus (CD=0);

- the number of erythrocytes ( _{Xerythrocytes} = 5.61 * 10 ¹² );

- mean corpuscular volume (X _MCV = 79.7 fl);

- mean platelet volume (X _MPV = 8.4 fl);

- coefficient of large platelets (X _P-LCR = 8.4%);

- total serum protein (X _{total protein} = 54.6 g/l);

- total cholesterol value (X _{total_cholesterol} = 2.28 mmol/l);

- the value of low-density lipoproteins ( _LDL -C = 0.91 mmol/l);

- total bilirubin value (X _bilirubin = 15.1 μmol/l);

- activated partial thromboplastin time (X _APTT = 53.3 sec).

By substituting the obtained variable values into the formula, we calculated the risk of developing infarct-related coronary artery ectasia, which was 0.628. Since the obtained value exceeded 0.535, a high risk of infarct-related coronary artery ectasia was assumed. Initial coronary angiography revealed diffuse dilation of the RCA throughout its entire length with occlusive thrombosis (TTG 5) in the middle third of the artery. The patient successfully underwent MIMS; control angiography performed 7 days later revealed complete resorption of the TTG 0 thrombus mass. Due to the insignificant residual stenosis, it was decided not to perform RCA stenting. The patient was discharged 11 days after hospitalization.

Example 3. Patient S., 52, was delivered by an ambulance crew to the cardiac intensive care unit of the Mytishchi City Hospital on June 20, 2016, at 2:00 PM. The patient complained of acute chest pain radiating to the left arm and jaw. The anamnesis indicates that the presenting symptoms began at approximately 1:30 PM while at rest. At 2:30 PM, the patient called an ambulance crew. An ECG revealed ST-segment elevation in leads II, III, and aVF, with reciprocal changes in leads I and aVL of up to 2 mm. The diagnosis of acute inferior STEMI was subsequently confirmed by a troponin I blood test. Prehospital, the patient received standard treatment for STEMI, including aspirin, clopidogrel, and morphine. His condition was assessed as severe. During hospitalization, a general and biochemical blood test were performed, as well as a coagulogram analysis: erythrocytes = 4.31 * 10 ¹² , MCV = 88.2 fl, MPV = 7.88 fl, P-LCR = 11.9%, total protein = 70 g / l, total cholesterol = 4.46 mmol / l, LDL = 3.4 mmol / l, bilirubin = 5.7 μmol / l, APTT = 10.4 sec. The patient denied a history of diabetes mellitus.

Accordingly, the following values of factors taken into account when calculating the risk of ectasia of the infarction-related coronary artery were established for this patient:

- age (X _age = 52);

- presence of diabetes mellitus (Х _СД = 0);

- the number of erythrocytes (X _erythrocytes = 4.31 * 10 ¹² );

- mean corpuscular volume (X _MCV = 88.2 fl);

- mean platelet volume (X _MPV = 7.88 fl);

- coefficient of large platelets (X _P-LCR = 11.9%);

- total serum protein (X _{total protein} = 70 g/l);

- total cholesterol value (X _{total_cholesterol} = 4.46 mmol/l);

- the value of low-density lipoproteins ( _LDL = 3.4 mmol/l);

- total bilirubin value (X _bilirubin = 5.7 μmol/l);

- activated partial thromboplastin time (X _APTT = 26.9 sec).

By substituting the obtained variable values into the formula, we calculated the risk of ectasia in the infarct-related coronary artery, which was 0.535. Given the resulting value of 0.535, we assumed a high risk of ectasia in the infarct-related coronary artery. Initial coronary angiography revealed segmental dilation of the LAD with massive thrombosis of TTG 3 in the middle third of the artery. Balloon angioplasty was performed using a TREK 2.5×20 mm catheter, followed by implantation of a Xience 4×24 mm stent. The patient was discharged 11 days after hospitalization.

Thus, the proposed method is simple and accessible, and allows for increasing the accuracy and reliability of predicting the presence of ectasia of the infarction-related coronary artery in myocardial infarction with ST segment elevation by identifying objective and analyzable predictors of this process.

Claims (15)

A method for assessing the probability of the presence of ectasia of an infarct-related coronary artery in myocardial infarction with ST segment elevation, including a study of patient anamnestic data, clinical, biochemical blood tests, as well as coagulogram data, characterized in that age, the presence or absence of diabetes mellitus, the number of red blood cells, the mean volume of red blood cells and platelets, the large platelet ratio, the level of total protein, total cholesterol, low-density lipoproteins, the level of total bilirubin and activated partial thromboplastin time are assessed as predictors, then, based on the data obtained, the probability (p) of the presence of ectasia of an infarct-related coronary artery is determined using the formula p=1/(1+e ^-z ) z=-9.676 + 0.049 * X _age - 0.654 * X _diabetes + 0.671 * X _{red blood cells} + 0.028 * X _MCV + 0.449 * X _MPV + 0.093 * X _P-LCR - 0.037 * X _{total protein} - 0.735 * X _{total cholesterol} + 0.852 * X _LDL - 0.117 * X _bilirubin + 0.034 * X _APTT ; X _age – patient’s age, years; X _DM - diabetes mellitus, 0 - absence, 1 - presence; X _erythrocytes - the number of erythrocytes, 10 ¹² /l; X _MCV - mean corpuscular volume, fl; X _MPV - mean platelet volume, fl; X _P-LCR - large platelet coefficient, %; X _{total_protein} – level of total protein in blood serum, g/l; X _{total_cholesterol} - total cholesterol level, mmol/l; X _LDL - low density lipoprotein level, mmol/l; X _bilirubin - total bilirubin level, μmol/l; X _APTT - activated partial thromboplastin time, sec; and with a p value equal to 0.535 or higher, the probability of the presence of ectasia of the infarction-related coronary artery is assessed as high, with a p value less than 0.535, the probability of the presence of ectasia of the infarction-related coronary artery is assessed as low.