Myocardial Infarction Class Research Articles

Assessment of long-term cardiovascular events in patients with acute myocardial infarction complicated by acute heart failure

Annotation. The purpose of the study is to establish the frequency of occurrence, structure and correlation of adverse cardiovascular events among patients who have experienced an acute myocardial infarction (MI) complicated by acute heart failure (AHF). The study included 308 MI patients, among them 215 men (69.8%) and 93 women (30.2%). The average age of the examined patients was (62.9±0.6) years. Among all patients, 161 (52.3%) were diagnosed with MI without signs of AHF (I class according to Killip, group I), 44 (14.3%) had MI combined with 2nd class of AHF, and 55 (17.8%) – class III MI and AHF (patients with Killip II and III AHF were combined into group II, 99 patients), and in 48 (15.6%) cases MI and AHF class IV according to Killip (group III) were detected. All patients underwent additional laboratory examination (quantitative troponin I, D-dimer, CPK-MV, C-reactive protein, NTproBNP), echocardiography and lung ultrasound during hospitalization and upon discharge from the hospital, coronary ventriculography in supplement to the standard examination. The statistical analysis of the results was carried out in the "Statistica 7.0" program package. Character frequency (%) was determined using Pearson's χ2 test, mean value (М±m), Student’s t-test and Mann-Whitney test were used for statistical analysis, and Spearman’s correlation analysis was used. It was established that in group I there were 9 (5.6%) fatal cases during the year, in group II – 7 (7%) (р1-2=0.62), in group III – 3 (6.3%) cases (p2-3=0.54). In the group of MI with AHF II-III, there were significantly more cases of repeated MI – 4 (4%), while in group I there was no case (р1-2=0.01), and in group III there was 1 case (2.1%), (p2-3=0.54). Among the reasons for hospitalization during the year in all groups, the leading one was the progression of heart failure – from 16.7% in group III to 28.3% in group II without a significant difference between groups. Unstable angina was the reason for inpatient treatment more often in group II – 12.1% of cases and only in 4.9% in group I (р1-2=0.035). The occurrence of adverse events within 1 year among patients with MI and AHF II-III correlates with the degree of hypertension (r=0.24, p=0.014), the history of hypertension (r=0.33, p=0.0004), the presence of the atrial fibrillation in anamnesis (r=0.29, p=0.0021), creatinine level (r=0.32, p=0.0022), NTproBNP (r=0.38, p=0.0001), hemoglobin (r =-0.23, p=0.032), the number of affected vessels (r=0.28, p=0.004), the end-diastolic size of the left ventricle (r=0.31, p=0.0031), the size of the left atrium (r= 0.34, p=0.0007) and left ventricular ejection fraction (r=0.27, p=0.001). Further studies should be aimed at expanding the prediction capabilities of isolated events in patients with MI and different classes of AHF.

Prediction of the Development of Acute Heart Failure of High Grades in Patients with Myocardial Infarction and Percutaneous Coronary Intervention

The aim of the study was to determine the risk factors for the occurrence of acute heart failure (AHF) of high degrees (Killip classes III and IV) among patients with myocardial infarction (MI).
 Materials and methods. We examined 308 MI patients who were treated at the specialized cardiology department. The mean age of the subjects was 62.9±0.6 years. There were 161 (52.3%) patients with MI without signs of heart failure (HF) (Killip class I), 44 (14.3%) with MI combined with class II AHF, 55 (17.8%) with MI and class III AHF, and 48 (15.6%) with MI and Killip class IV AHF. In addition to the general clinical examination, all the patients underwent additional laboratory examination (quantitative determination of troponin I, D-dimer, creatine kinase-MB, C-reactive protein, N-terminal prohormone of brain natriuretic peptide [NT-proBNP]), echocardiography and lung ultrasound during hospitalization, as well as coronary angiography.
 Results. A correlation between the occurrence of class III AHF (pulmonary edema) and class IV AHF (cardiogenic shock) and a number of anamnestic, clinical, functional and laboratory indicators was established. The following predictors of the development of class III AHF among patients with MI were calculated through regression analysis: a decrease in the level of O2 saturation during hospitalization, an increase in blood pressure during hospitalization, localization of the main heart attack-related lesion of the distal part of the right coronary artery, a decrease in the left ventricular ejection fraction. With less significance, predictors of the development of class III AHF were also defined as a decrease in the level of hemoglobin, the duration of hypertension in the history, the degree of hypertension, the history of any form of atrial fibrillation.
 Conclusions. A decrease in diastolic blood pressure irrespective of medical support and an increase in the level of NT-proBNP were established as predictors of the development of Killip class IV AHF. Further studies to predict the occurrence of HF and long-term consequences after MI with high-grade HF are promising and can provide an opportunity to optimize the treatment of patients by preventing severe complications.

Detection of Myocardial Infarction From 12-Lead ECG Trace Images Using Eigendomain Deep Representation Learning

Myocardial infarction (MI) is a life-debilitating emergency in which there is a lack of blood flow in the heart muscle, resulting in permanent damage to the myocardium and sudden cardiac death. The 12-lead electrocardiogram (ECG) is a standardized diagnostic test conducted in hospitals to detect and localize MI-based heart disease. To diagnose MI, the cardiologist visualizes the alternations in the patterns of the 12-lead-based ECG trace image. The automated detection of MI from the 12-lead-based ECG trace image using artificial intelligence (AI) based approaches is important in the clinical study for the accurate diagnosis of MI disease. This paper proposes a novel eigendomain-based deep representation learning approach to automatically detect MI using 12-lead ECG trace images. The singular value decomposition (SVD) and eigendomain grouping are employed to evaluate five modes or components from the 12-lead ECG trace image. The EfficientNetV2B2-based transfer learning model extracts feature maps from the 12-lead ECG trace image and all five modes. The global average pooling (GAP), batch normalization (BN), drop-out, and soft-max layers are used for each feature map to obtain the probability scores. The concatenated probability scores of all feature maps, followed by the dense layer and output layer, are used to detect MI. A public database containing the 12-lead ECG trace images is used to evaluate the performance of the proposed approach. The results show that for the MI class, the proposed approach has achieved the accuracy value of 100%. Similarly, for normal versus MI versus other cardiac arrhythmia-based disease classification schemes, the proposed approach has obtained the overall accuracy, F1-score, specificity, and sensitivity values of 99.03%, 99.01%, 99.49%, and 98.96%, respectively using 5-fold cross-validation (CV). The suggested approach has demonstrated higher overall accuracy than twenty-four existing transfer learning-based models to detect MI using 12-lead ECG trace images.

The prognostic significance of grade of ischemia in the ECG in patients with ST-elevation myocardial infarction: A substudy of the randomized trial of primary PCI with or without routine manual thrombectomy (TOTAL trial)

BackgroundThe importance of the grade of ischemia (GI) ECG classification in the risk assessment of patients with STEMI has been shown previously. Grade 3 ischemia (G3I) is defined as ST-elevation with distortion of the terminal portion of the QRS complex in two or more adjacent leads, while Grade 2 ischemia (G2I) is defined as ST-elevation without QRS distortion. Our aim was to evaluate the prognostic impact of the GI classification on the outcome in patients with STEMI. Methods7,211 patients from the TOTAL trial were included in our study. The primary outcome was a composite of cardiovascular death, recurrent myocardial infarction (MI), cardiogenic shock, or New York Heart Association (NYHA) class IV heart failure within one year. ResultsThe primary outcome occurred in 153 of 1,563 patients (9.8%) in the G3I group vs. 364 of 5,648 patients (6.4%) in the G2I group (adjusted HR 1.27; 95% CI, 1.04 - 1.55; p=0.022). The rate of cardiovascular death (4.8% vs. 2.5%; adjusted HR 1.48; 95% CI 1.09 - 2.00; p=0.013) was also higher in patients with G3I. ConclusionsG3I in the presenting ECG was associated with an increased rate of the composite of cardiovascular death, recurrent MI, cardiogenic shock, or NYHA class IV heart failure within one year compared to patients with G2I. Patients with G3I also had a higher cardiovascular death compared to patients with G2I.

Automated detection of myocardial infarction in ECG using modified Stockwell transform and phase distribution pattern from time-frequency analysis

Myocardial infarction (MI), usually referred as heart attack, takes place when blood circulation stops to specific portion of the heart resulting permanent damage to the heart muscles. It is an important task to identify the occurrence of MI from the ECG recordings efficiently. Most of the detection procedures include advanced signal processing methods, more ECG features and composite classifiers, making the overall procedure complex. This paper aims at automated identification of MI using modified Stockwell transform (MST) based time-frequency analysis and a phase information distribution pattern method. The morphological, pathological and temporal alterations in ECG waveforms resulting from the onset of MI are noticed in the phase distribution pattern of the ECG signal. Two discriminating features, utterly reflecting these alterations, are recognized for 12 leads of the MI affected ECG signal. Prior informations regarding the pathological characteristics of the specific disease are required for the correct detection of MI using few numbers of ECG leads. Thus, in this paper 12 lead ECG signals have been considered for identification of MI. The two-class classification problem with MI class and healthy individual class is performed using the threshold based classification regulation. Both healthy control and MI affected ECG signals are collected from the PTB diagnostic ECG database. The accuracy, sensitivity and specificity are found to be 99.93%, 99.97% and 99.30% for detection of MI. The proposed method has got the superiority in terms of simplicity of features, small feature dimension and simpler classification rule ensuring faster, accurate and easier MI detection.

Detection of Cardiac Abnormalities from Multilead ECG using Multiscale Phase Alternation Features

The cardiac activities such as the depolarization and the relaxation of atria and ventricles are observed in electrocardiogram (ECG). The changes in the morphological features of ECG are the symptoms of particular heart pathology. It is a cumbersome task for medical experts to visually identify any subtle changes in the morphological features during 24 hours of ECG recording. Therefore, the automated analysis of ECG signal is a need for accurate detection of cardiac abnormalities. In this paper, a novel method for automated detection of cardiac abnormalities from multilead ECG is proposed. The method uses multiscale phase alternation (PA) features of multilead ECG and two classifiers, k-nearest neighbor (KNN) and fuzzy KNN for classification of bundle branch block (BBB), myocardial infarction (MI), heart muscle defect (HMD) and healthy control (HC). The dual tree complex wavelet transform (DTCWT) is used to decompose the ECG signal of each lead into complex wavelet coefficients at different scales. The phase of the complex wavelet coefficients is computed and the PA values at each wavelet scale are used as features for detection and classification of cardiac abnormalities. A publicly available multilead ECG database (PTB database) is used for testing of the proposed method. The experimental results show that, the proposed multiscale PA features and the fuzzy KNN classifier have better performance for detection of cardiac abnormalities with sensitivity values of 78.12 %, 80.90 % and 94.31 % for BBB, HMD and MI classes. The sensitivity value of proposed method for MI class is compared with the state-of-art techniques from multilead ECG.

GW24-e2957 Efficacy of ivabradine in combination with metoprolol versus uptitration of metoprolol in patients after Q-wave myocardial infarction with early left ventricular systolic dysfunction

ObjectivesThe purpose of the study was to evaluate the effect of combination of ivabradine with metoprolol tartrate versus uptitration of metoprolol tartrate on left ventricular (LV) systolic function and plasma...

Association of Coexisting Diabetes and Depression With Mortality After Myocardial Infarction

OBJECTIVEDiabetes and depression are both linked to an increased mortality risk after myocardial infarction (MI). Population-based studies suggest that having both diabetes and depression results in an increased mortality risk, beyond that of having diabetes or depression alone. The purpose of this study was to examine the joint association of diabetes and depression with mortality in MI patients.RESEARCH DESIGN AND METHODSData were derived from two multicenter cohort studies in the Netherlands, comprising 2,704 patients who were hospitalized for MI. Depression, defined as a Beck Depression Inventory score ≥10, and diabetes were assessed during hospitalization. Mortality data were retrieved for 2,525 patients (93%).RESULTSDuring an average follow-up of 6.2 years, 439 patients died. The mortality rate was 14% (226 of 1,673) in patients without diabetes and depression, 23% (49 of 210) in patients with diabetes only, 22% (118 of 544) in patients with depression only, and 47% (46 of 98) in patients with both diabetes and depression. After adjustment for age, sex, smoking, hypertension, left ventricular ejection fraction, prior MI, and Killip class, hazard ratios for all-cause mortality were 1.38 (95% CI 1.00–1.90) for patients with diabetes only, 1.39 (1.10–1.76) for patients with depression only, and as much as 2.90 (2.07–4.07) for patients with both diabetes and depression.CONCLUSIONSWe observed an increased mortality risk in post-MI patients with both diabetes and depression, beyond the association with mortality of diabetes and depression alone.

ACC/AHA 2007 Guidelines on Perioperative Cardiovascular Evaluation and Care for Noncardiac Surgery: Executive Summary

TABLE OF CONTENTSPreamble 686Definition of the Problem 688Purpose of These Guidelines 688Methodology and Evidence 689General Approach to the Patient 692History 693Physical Examination and Routine Laboratory Tests 693Multivariable Indices to Predict Preoperative Cardiac Morbidity 694Clinical Assessme

Participation Bias and Its Impact on the Assembly of a Genetic Specimen Repository for a Myocardial Infarction Cohort

To assess participation bias in the assembly of a specimen repository for genetic studies and to examine the association of participation with outcome within the Olmsted County myocardial infarction (MI) cohort. From January 1, 1979, to May 31, 2006, 3081 persons had MI in Olmsted County, MN. Face-to-face contact was used to recruit patients who were hospitalized for an acute event. Persons who had had an MI before establishment of this repository were contacted by mail. At initial contact, we sought consent to use blood samples for genetic studies. Persons who refused were contacted by mail and were asked to consent to the use of stored tissue samples. For deceased subjects, stored tissue was collected when available. Of the 3081 persons in the Olmsted County MI cohort, 1994 participated in the study; 1007 (50.5%) blood and 987 (49.5%) tissue specimens were provided. Participants were more likely to be younger men with hypertension, comorbidities, and non-ST-segment elevation MI (all, P<.05). Participants who provided blood specimens were more likely to have non-ST-segment elevation MI and lower Killip class than those who provided tissue. After adjustment for age, sex, hypertension, ST-segment elevation, Killip class, and comorbidities, participation was not associated with outcome. Participants who provided blood specimens were less likely to have heart failure (hazard ratio, 0.49; 95% confidence interval, 0.40-0.59; P<.01) or to die (hazard ratio, 0.16; 95% confidence interval, 0.12-0.21; P<.01) than those who provided tissue. A variety of sources can be used to assemble community specimen repositories. Baseline characteristics differed between participants and nonparticipants and, among participants, by specimen source. Participants who provided blood specimens had better outcomes than those who provided tissue specimens. No survival advantage was observed for participants after combining blood and tissue specimens.

Acute coronary syndromes: unstable angina and non-Q-wave myocardial infarction.

Ischemic heart disease includes a wide spectrum of conditions, ranging from silent ischemia and exertion-induced angina, through unstable angina, to acute MI. Unstable angina occupies the center of this spectrum, causing disability and risk greater than that of chronic stable angina but less than that of acute MI1 (Fig 1⇓). Although non–Q-wave MI for many years was considered prognostically similar to unstable angina, recent longitudinal studies indicate that it is similar to Q-wave infarction2 3 (Fig 2⇓). Figure 1. Cumulative 6-month mortality from ischemic heart disease. Diagnosis on admission to hospital (n=21 761; 1985 to 1992). From Duke Cardiovascular Database. Reproduced with permission from Reference 1. Figure 2. Top, Cumulative 1-year combined death or MI among patients with Q-wave and non–Q-wave MI treated with fibrinolysis. Reproduced with permission from Reference 2. Bottom, Risk of subsequent cardiac events in stable convalescing patients after first non–Q-wave and Q-wave MI. Reproduced with permission from Reference 3. The concept of unstable angina has emerged from observations of frequent symptoms preceding acute MI, followed by prospective documentation that unstable symptoms frequently culminated in acute MI. The syndrome was rapidly accepted as a well-defined clinical entity as specific clinical manifestations, pathophysiological mechanisms, laboratory findings, and treatment became better characterized. Unstable angina is currently one of the leading causes of hospital admission for CAD, and non–Q-wave MI accounts for >30% of admissions for acute MI.1 4 Yet, the diagnosis of unstable angina remains clinical, based on symptom recognition. The physician caring for patients with unstable angina is in a privileged position of recognizing rapidly evolving CAD and being able to intervene to prevent irreversible left ventricular damage and progression of CAD. Unstable angina is classically described as a heterogeneous disease, referring to a wide spectrum of clinical manifestations from stable angina to MI, of disease …

Risk stratification after myocardial infarction using signal-averaged electrocardiographic criteria adjusted for sex, age, and myocardial infarction location.

The objectives were to investigate the factors influencing signal-averaged ECGs (SAECGs) recorded in patients after myocardial infarction (MI) and to develop criteria for predicting arrhythmic events (AEs) that account for these factors. SAECGs were recorded 5 to 15 days after MI in 2461 patients without bundle-branch block. The duration (QRSd), terminal potential (VRMS), and terminal duration (LAS) of the filtered QRS were measured. During follow-up (17 +/- 8 months), AEs (arrhythmic death; ventricular tachycardia, VT; ventricular fibrillation, VF) occurred in 80 patients (3.3%). Receiver operating characteristic curves showed that QRSd discriminated patients with all types of AEs, but VRMS and LAS discriminated only VT patients; QRSd minus LAS also discriminated AE patients. Sex, age, and MI location significantly affected the SAECG; survivors without VT or VF were divided into subgroups (2 sex x 4 age x 2 MI), and QRSd values exceeding the 70th percentile in each subgroup predicted AEs with a sensitivity of 65.4%. An unadjusted QRSd criterion showed the same overall sensitivity and specificity but with less uniform values for each subgroup. A Cox model was constructed by use of multiple prognostic indicators, and in rank order, QRSd, previous MI, and Killip class were predictive of AEs. SAECG adjustments for sex, age, and MI location did not improve sensitivity and specificity but produced a more uniform predictive performance. The proposed criteria are based only on QRSd, because late potentials (VRMS and LAS) did not discriminate patients with sudden death. Duration of high-level activity during QRS (QRSd-LAS) can predict AEs, suggesting that the arrhythmogenic substate involves a large mass of myocardium.

Greater Case-Fatality after Myocardial Infarction among Mexican Americans and Women than among Non-Hispanic Whites and Men: The Corpus Christi Heart Project

Age-adjusted 28-day case-fatality rates were higher among Mexican Americans than among non-Hispanic whites and higher among women than among men hospitalized for definite or possible myocardial infarction in Corpus Christi, Nueces County, Texas, from May 1, 1988, through April 30, 1990. The authors therefore examined whether these higher case-fatality rates were associated with greater prevalence of previously diagnosed coronary heart disease or diabetes; with greater age, frequency of definite myocardial infarction, or congestive heart failure; with higher values of indicators of severity of infarction, including peak creatine phosphokinase levels and scales prognostic of early mortality after myocardial infarction; and with differences in receipt of in-hospital therapy. The overall 28-day case-fatality rate among 1,228 patients hospitalized for myocardial infarction during a 24-month period was 7.3%. After adjustment for age; diabetes; myocardial infarction class (definite vs. possible); congestive heart failure; the Norris and Peel severity indices; peak total creatine phosphokinase; and receipt of thrombolytic therapy, aspirin, calcium channel blockers, beta-blockers, anticoagulants, angioplasty, and bypass surgery, the risk of 28-day case-fatality for Mexican Americans in relation to non-Hispanic whites was 1.49 (95% confidence interval 0.92-2.40). The corresponding risk for women in relation to men was 1.80 (95% confidence interval 1.12-2.89). These findings should alert clinicians to the high-risk status of these groups of patients.

Body surface potential mapping of ST segment changes in acute myocardial infarction. Implications for ECG enrollment criteria for thrombolytic therapy.

Several large, randomized clinical trials have shown that early thrombolytic therapy substantially reduces early mortality after acute myocardial infarction (MI). In most trials, eligibility criteria include typical chest pain and diagnostic ST segment elevation in two or more contiguous leads of the standard 12-lead ECG. Unfortunately, large areas of the thoracic surface are left unexplored by the standard electrode positions. As a consequence, acute MI patients with ST elevation in regions not interrogated by the conventional electrodes may not receive reperfusion therapy and its attendant benefits. The present study compares 120-lead body surface potential map (BSPM) data from 131 patients with acute MI and 159 normal control subjects (N). The MI population was stratified according to the location of ventricular wall motion abnormalities evidenced by radionuclide imaging into 76 patients with anterior MI (AMI), 32 patients with inferior MI (IMI), and 23 patients with posterior MI (PMI). BSPM were recorded within 24 hours of admission. Group mean BSPM of the ST segment were obtained for N, AMI, IMI, and PMI by sampling the time-normalized ST-T waveform at 18 equal intervals and averaging the voltages at each electrode site over the first five of these 18 ST-T time instants. Corresponding discriminant maps were also computed for each pairwise comparison (AMI versus N, IMI versus N, and PMI versus N) by subtracting the normal group mean voltages from each MI group mean voltages and by further dividing each resulting difference by the composite standard deviation calculated from the pooled groups. Discriminant analysis for each bigroup classification was also performed using as measurements the ST magnitudes in 120 electrode sites from each individual. Finally, the number of patients in each MI group with ST changes outside the 95% normal range was calculated for each electrode position. The following results were obtained: 1) In each MI group, ST depression departs more significantly from normal values than ST elevation. 2) The most significant ST changes (both ST elevation and ST depression) are observed in IMI, the least significant in AMI. 3) For each pairwise comparison, measurements from two lead sites are entered into the stepwise discriminant procedure: the first measurement is ST depression, the second ST elevation. Classification rates are 82% for AMI, 93% for PMI, and 100% for IMI at a specificity level of 95%. 4) From the six leads selected for optimal classification of the three MI groups, five are outside the area sampled by the conventional precordial electrodes. 5) The use of site-dependent thresholds for ST measurements based on 95% normal range yields the best compromise between sensitivity and specificity. A fixed threshold of 1 mm for ST elevation or ST depression produces increased sensitivity in AMI at the cost of marked loss in specificity and reduces sensitivity in both IMI and PMI with no benefit in specificity. Analysis of BSPM identifies areas on the torso where the most significant ST changes most frequently occur in acute MI. Two leads from areas with the most abnormal ST changes achieve optimal classification in each MI class. Of these six leads, five are outside the standard precordial lead positions. ST depression is the most potent discriminator for each MI group and contains information independent from ST elevation. Quantitative analysis of ST magnitude at each electrode site allows determination of best thresholds for ECG criteria. Appropriate selection of ECG leads may help remove inconsistencies in current ECG selection criteria and improve comparability of treatment results.