Search for Methods to Predict the Development of Heart Failure After Myocardial Infarction

Overview

Introduction Despite significant progresses in the diagnosis of myocardial infarction and the development of reperfusion treatment methods, heart failure still often complicates its course. There are three types of postinfarction heart failure: occurring in the acute period, during hospital treatment and after discharge. Factors contributing to heart failure during hospitalization for MI and after discharge include comorbidity of the patient, worsening of pre-existing CHF and comorbidities. In the last decades we can observe higher level of myocardial percutaneous coronary intervention (PCI), improvement of pre-hospital care, which decreased mortality and HF; however, the proportion of HF patients with preserved ejection fraction increased. All these factors determine the urgency of the studied problem. Purpose of the study To identify the most significant factors contributing to the development of acute and subacute heart failure after myocardial infarction Materials and methods Retrospective and prospective non-randomized parallel-group analysis of 186 suffered MI (mean age 63.5 y) during one year was performed in this work, and in the main group of patients (86 patients) at 30 days after MI, chronic heart failure over 2F by NYHA was confirmed, and in comparison group (100 patients) CHF was either absent or did not exceed 2F by NYHA. The diagnosis of MI and CHF was made according to national and European guidelines. Both groups received standard therapy for CHF: ACE inhibitors/angiotensin 2/angiotensin receptor antagonists and neprolysin inhibitor (ARNI), β-blockers, mineralocorticoid receptor antagonists (AMCR), SGLT2-receptor inhibitors; anticoagulants, antiplatelet agents, statins, diuretics if necessary were also used. One year after discharge, clinical outcomes were assessed: cardiovascular mortality, repeated hospitalizations due to decompensation of CHF, death from other causes, stroke, repeated myocardial infarction, unscheduled coronary revascularization; telephone contacts were made every month, repeat visits to the clinic - one year later. The results were based on the information collected in the course of telephone contacts and via e-mail; hospitalizations were also monitored by querying the databases of medical institutions.

The patients were recruited on the basis of regional vascular center (RVC) of the 1st cardiology department for myocardial infarction patients of State Budget Institution of Health of Novosibirsk region "City Clinical Hospital" (SBUZ NSO GKB) № 1 of Novosibirsk. According to the design, there were three points in the study: zero point - the first day of hospitalization of the patient in the hospital; the first point - day 30 of MI development; the second point - 12 months from the time of AMI development. At all stages of the study we performed the examinations stipulated by the standard of care for patients with acute myocardial infarction, clinical guidelines and dissertation research protocol: clinical status of the patient (evaluation of complaints, objective examination), laboratory tests (total blood count (TBC), total urine analysis (UPE), biochemical blood analysis (BX), instrumental examinations (ECG, chest radiography (RGCT)). Coronarography followed by percutaneous coronary intervention (PCI), EchoCG and determination of molecular genetic markers were also performed at stage 0. At any stage in the presence of cardiac rhythm and conduction abnormalities, Holter electrocardiography monitoring (HM-ECG) was performed; and a 6-minute walk test was performed at the 1st and 2nd points. Verification of the diagnosis of AMI was performed according to the criteria of the fourth universal definition of myocardial infarction, which summarizes the opinion of experts of the World Heart Federation (WHF), American Heart Association (AHA), American College of Cardiology (ACC) and European Society of Cardiology (EOC, ESC) (2018). The dissertation work included patients who met the criteria for acute type 1 MI, which included elevated cardiac troponin levels above the 99th percentile of the upper reference value, in combination with at least one additional feature: 1) a characteristic clinical picture of acute myocardial ischemia; 2) new ECG changes suggestive of ischemia; 3) a pathologic Q-wave on the ECG; 4) imaging findings confirming new areas of myocardial ischemia; and 5) presence of infarct-related artery thrombosis (ICA) on CAG. Verification of the diagnosis of acute and chronic heart failure (OSF, CHF) was performed on the basis of clinical recommendations of the European Society of Cardiology (EOC, ESC) (2016, 2021), combined recommendations of the Society of Heart Failure Specialists (SHF), Russian Society of Cardiology (RSC) and Russian Scientific Medical Society of Physicians (RSMOT) (2018). The classification of CHF according to the stages of the disease (Strazhesko-Vasilenko, 1935) and left ventricular ejection fraction (LVEF) was used, also the heart failure classification of the New York Heart Association (NYHA, 1964) was used to assess the severity of symptoms. We used Killip classification of acute heart failure. Instrumental methods of investigation ECG was recorded in 12 leads (6 standard and 6 thoracic leads) using "Megacart-400" (Siemens) in the first minutes of hospital admission, then once a day until subacute period of STEMI formed, and then once every three days. Echocardiography was performed on admission to the hospital, on the 30th day from the development of MI, and 1 year later on a Phillips ie33 device (Philips Ultrasound, USA) from the standard position, in the left side of the patient, using a 2-4 MHz ultrasound matrix transducer. The technique was performed in M- and B-modes, pulse-wave, continuous-wave Doppler, color Doppler mapping, tissue Doppler and color Doppler M-mode (Color M-mode). The following parameters were determined: PV - ejection fraction (Simpson, 1989. ), FV - end diastolic volume, CSV - end systolic volume, ESR - end systolic size, CDD - end diastolic size, FDi - end diastolic index, CSI - end systolic index, DLA - mean pulmonary artery pressure, FDD - end diastolic pressure, SW - stroke volume, MM - myocardial mass, IMM - myocardial mass index, LP - left atrium, RAP - right atrium, RV - right ventricle, VIR - isovolumic relaxation time, E - LV early diastolic filling rate, A - left ventricular late diastolic filling rate, E/A - ratio of early and late transmitral flow, DT - time of early diastolic filling slowdown, AT - time of early diastolic filling acceleration, ET - ejection period, Em - myocardial early diastolic motion rate, Am - velocity of late diastolic myocardial motion, Em/Am - ratio of velocities of early and late diastolic myocardial motion, E/e' - ratio of E-wave blood flow on mitral valve to E'-wave (ratio of early mitral valve ring motion), pulmonary vein S blood flow, pulmonary vein D blood flow, dE and dA - parameters of duration of early diastolic filling, IVCT - isovolumic time of RV contraction, Sfcmc - mitral valve fibrous ring velocity, VpvA - maximum diastolic retrograde flow velocity, SRMP - early mitral flow velocity, diastolic stiffness, Tei index - sum of isovolumetric contraction and isovolumetric relaxation times divided by ventricular ejection time, Em/SRMP - ratio of early diastolic transcuspidal flow velocity to its rate of spread. Left ventricular ejection fraction (LVEF) was calculated using the formula: LVEF = (QDO - QSO/QDO) 100% (according to Simpson's method). The presence and degree of dyskinesia of necrosis zone and scar changes, aneurysm, papillary muscle lesions and myocardial rupture zones were also determined by standard technique, in two-dimensional and one-dimensional modes and in pulse and continuous-wave Doppler Echo-CG modes. Selective CAG was performed within the first 24 hours after the patient's admission to the hospital on an INNOVA 3100 angiographic machine (USA) with access through the radial artery using standard Judkins left (Jl 4.0) and Judkins right (Jl 4.0) catheters, using X-ray contrast agents (ultravist, Gadovist). Transilluminal balloon angioplasty with stenting of the symptomatic artery was performed when hemodynamically significant stenosis exceeding 65% was diagnosed using the technique of direct stenting. Preparation of DNA preparations DNA extraction from blood was performedby phenol-chloroform extraction. Five to six volumes of buffer A (10 mMTris-HCl, pH=7.5; 10 mM NaCl; 3 mM MgCl2) were added to 1 volume of blood sample and clots were rubbed in a homogenizer. After centrifugation at 2500g for 15 min, the precipitates were washed three times with buffer A and resuspended in 1 ml of buffer B (10 mM EDTA; 100 mM NaCl; 50 mM Tris HCl, pH=8.5). After adding SDS to 0.5% and proteinase E to 200 μg/mL, the mixture was incubated for 12 hours at 56°C. Deproteinization was performed sequentially with phenol-chloroform mixture (1:1), water-saturated phenol,phenol-chloroform mixture (1:1), and chloroform. DNA was precipitated by adding NaCl solution to 1 M and 1 V isopropyl alcohol. After that, the solution was cooled for 1 h at -20 °C. The precipitate obtained by centrifugation on an Eppendorf microcentrifuge at 12000g for 15 min was washed three times with 75% ethanol followed by centrifugation for 5 min. 12000g and, after drying at 56 °C, dissolved in deinanilized water to a DNA concentration of 0.5 µg/μl.Genotyping of polymorphisms was performed using real-time PCR according to the manufacturer's protocol (TaqMan probes, Thermo Fisher Scientific, USA) on a StepOnePlus instrument. They were selected according to the results ofinternational full genome-wide association studies (GWAS), which confirmed the association of these SNPs with coronary heart disease (CHD),development of heart failure. Statistical methods of material processing The influence of clinical, demographic, functional, biochemical, markers not and treatment methods on the development of acute, hospital and distant postinfarction chronic heart failure was assessed by odds ratio. Statistical analysis of molecular genetic data was performed using SPSS 22.0 software package. the first step was to determine the frequencies of genotypes and alleles of the studied CHF in ACS patients with elevated cardiospecific markers and in the comparison group, where cardiospecific markers were within normal limits; then we assessed the compliance of genotype frequencies with Hardy-Weinberg equilibrium in control group (Chi-square criterion). Comparison of the level of quantitative indices in carriers of different genotypes was performed after checking the normality of the distribution of these traits by the Kolmogorov-Smirnov test. If the traits met the criteria of normal distribution, a single-factor analysis of variance was used. Significance of differences between the two genotypic classes was additionally checked using the t-test for two independent samples. The significance of differences between the two genotypic classes was additionally tested with the Mann-Whitney test for two independent samples if the investigated trait did not meet the criteria of normal distribution, comparison of the level of this trait among the carriers of different genotypes was performed using the Kruskal-Wallis test. The association of SNPs with risk factors related to categorical variables was tested with conjugation tables using Pearson's chi-square test. In the case of four-field tables, we compared samples by genotype and allele frequencies using Fisher's exact two-sided criterion. The risk of disease outcome/risk factor for a particular allele or genotype was calculated as odds ratio. Correlation, factor and regression analysis methods were used to develop mathematical models for predicting the risk of postinfarct CVD. The first two groups of methods were used to identify significant independent variables (attributes) that correlate well with the probability of an adverse outcome, but weakly correlate with each other (to exclude multicollinearity of the model). Regression analysis methods were used to choose the structure of the regression model and to estimate its coefficients. Two coefficients, which have a simple interpretation, were used to test the adequacy of the constructed model: * sensitivity coefficient; * specificity coefficient; * coefficient of accuracy.