Screening Sportsmen and Sportswomen Over Age 35: The Relevance of an Exercise Electrocardiogram. Data From the SEEPRED Study.

INTRODUCTION: The importance of exercise electrocardiogram (ECG) is still controversial in the prevention of cardiovascular events among sportsmen and sportswomen. The aim of this study was to assess the relevance of exercise ECG as a screening tool to prevent cardiovascular events when any cardiovascular disease (CVD) risk factors are present. METHODS: The study included leisure time asymptomatic sportsmen and sportswomen over age 35 evaluated from 2011 to 2016 at the University Hospital of Saint-Etienne (France). Major adverse cardiovascular events (MACE) and atrial fibrillation were collected at 3 years. RESULTS: Of the cohort of 2457 sportsmen and sportswomen (mean age 50.2 ± 9.4 years), 50 (2%) had a high-risk SCORE2. A total of 256 exercise ECGs (10%) were defined as positive, most of them due to silent myocardial ischemia (SMI) (n = 196; 8%). These 196 SMI cases led to 33 coronary angiograms (1%), which revealed 23 significant coronary stenoses requiring revascularization. In multivariate logistic regression analysis, having at least two CVD risk factors was independently associated with (1) positive exercise ECG (OR = 1.80 [95% CI: 1.29-2.52], p = 0.0006), with (2) suspected SMI (OR = 2.57 [95% CI: 1.10-6.02], p = 0.0304), with (3) confirmed SMI (OR = 8.20 [95% CI: 3.46-19.46], p < 0.0001) and with (4) cardiovascular events (MACE or atrial fibrillation) (OR = 6.95 [95% CI: 3.49-13.81], p < 0.0001) at 3 years (median). CONCLUSIONS: The study supports the European recommendations for the use of exercise ECG in evaluation of asymptomatic leisure time sportsmen over age 35. Having at least two CVD risk factors was the best predictor for presence of coronary artery stenosis that may increase the risk for adverse events. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT06024863.

Assessment of Myocardial Viability in Ischemic Cardiomyopathy With Reduced Left Ventricular Function Undergoing Coronary Artery Bypass Grafting.

BACKGROUND: We aim to provide a comprehensive review of the current state of knowledge of myocardial viability assessment in patients undergoing coronary artery bypass grafting (CABG), with a focus on the clinical markers of viability for each imaging modality. We also compare mortality between patients with viable myocardium and those without viability who undergo CABG. METHODS: A systematic database search with meta-analysis was conducted of comparative original articles (both observations and randomized controlled studies) of patients undergoing CABG with either viable or nonviable myocardium, in EMBASE, MEDLINE, Cochrane database, and Google Scholar, from inception to 2022. Imaging modalities included were dobutamine stress echocardiography (DSE), cardiac magnetic resonance (CMR), single-photon emission computed tomography (SPECT), and positron emission tomography (PET). RESULTS: A total of 17 studies incorporating a total of 2317 patients were included. Across all imaging modalities, the relative risk of death post-CABG was reduced in patients with versus without viability (random-effects model: odds ratio: 0.42; 95% confidence interval: 0.29-0.61; p < 0.001). Imaging for myocardial viability has significant clinical implications as it can affect the accuracy of the diagnosis, guide treatment decisions, and predict patient outcomes. Generally, based on local availability and expertise, either SPECT or DSE should be considered as the first step in evaluating viability, while PET or CMR would provide further evaluation of transmurality, perfusion metabolism, and extent of scar tissue. CONCLUSION: The assessment of myocardial viability is an essential component of preoperative evaluation in patients with ischemic heart disease undergoing surgical revascularization. Careful patient selection and individualized assessment of viability remain paramount.

Comparison of embolic risk in left ventricular thrombus between nonischemic and ischemic cardiomyopathy: A nationwide database analysis.

BACKGROUND: Left ventricular (LV) thrombus is not common but poses significant risks of embolic stroke or systemic embolism. However, the distinction in embolic risk between nonischemic cardiomyopathy (NICM) and ischemic cardiomyopathy (ICM) remains unclear. METHODS AND RESULTS: In total, 2738 LV thrombus patients from the JROAD-DPC (Japanese Registry of All Cardiac and Vascular Diseases Diagnosis Procedure Combination) database were included. Among these patients, 1037 patients were analyzed, with 826 (79.7%) having ICM and 211 with NICM (20.3%). Within the NICM group, the distribution was as follows: dilated cardiomyopathy (DCM; 41.2%), takotsubo cardiomyopathy (27.0%), hypertrophic cardiomyopathy (18.0%), and other causes (13.8%). The primary outcome was a composite of embolic stroke or systemic embolism (SSE) during hospitalization. The ICM and NICM groups showed no significant difference in the primary outcome (5.8% vs. 7.6%, p = 0.34). Among NICM, SSE occurred in 12.6% of patients with DCM, 7.0% with takotsubo cardiomyopathy, and 2.6% with hypertrophic cardiomyopathy. Multivariate logistic regression analysis for SSE revealed an odds ratio of 1.4 (95% confidence interval [CI], 0.7-2.7, p = 0.37) for NICM compared to ICM. However, DCM exhibited a higher adjusted odds ratio for SSE compared to ICM (2.6, 95% CI 1.2-6.0, p = 0.022). CONCLUSIONS: This nationwide shows comparable rates of embolic events between ICM and NICM in LV thrombus patients, with DCM posing a greater risk of SSE than ICM. The findings emphasize the importance of assessing the specific cause of heart disease in NICM, within LV thrombus management strategies.

Objective Ischemia, Subjective Angina, and Psychological Distress in Angina With No Obstructive Coronary Disease.

BACKGROUND: Angina with no obstructive coronary disease (ANOCA) and ischemia with no obstructive coronary disease, prevalent yet underrecognized conditions, mostly affect women. Previous studies rarely distinguished between them. We aimed to compare the prevalence of objective ischemia through various examinations in women with ANOCA and assess the impact of objective and subjective ischemia on their mental health. METHODS AND RESULTS: A total of 84 eligible women with ANOCA and 42 controls underwent mental stress, pharmacological stress, exercise stress, and Holter testing. Objective evidence of myocardial ischemia was assessed by positron emission tomography-computed tomography and ECG, and subjective symptoms were graded using the Canadian Cardiovascular Society scale (CCS). Psychological assessments were conducted using 6 scales. Among 84 women with ANOCA, 37 (44%) received a diagnosis of ischemia with no obstructive coronary disease following mental stress testing, 20 (28.6%) through pharmacological stress testing, 14 (21.2%) via exercise stress testing, and 24 (32.9%) from Holter. Mental stress-induced myocardial ischemia was more prevalent (P<0.05). Among 54 patients with ANOCA who completed all tests, 30% showed no ischemia, and only 1 (1.9%) showed ischemia in all tests. In addition, patients with ANOCA had higher psychological scores than controls (P<0.01). No significant differences was observed in psychological scores between ANOCA with positive and negative ischemia test results (P>0.05). However, ANOCA with milder angina (CCS I) exhibited higher scores across the Hospital Anxiety and Depression Scale, State-Trait Anxiety Inventory, Perceived Stress Scale, and Posttraumatic Stress Disorder Checklist-Civilian Version and a higher prevalence of Type D personality traits (P<0.05). CONCLUSIONS: In patients with ANOCA, the positive rate of myocardial ischemia exhibits variability among several noninvasive tests. A worsened psychological state is more closely linked to milder angina symptoms than to ischemia performance, highlighting the importance of focusing on symptom management in their psychological care. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03982901.

Using machine learning to predict acute myocardial infarction and ischemic heart disease in primary care cardiovascular patients.

BACKGROUND: Early recognition, which preferably happens in primary care, is the most important tool to combat cardiovascular disease (CVD). This study aims to predict acute myocardial infarction (AMI) and ischemic heart disease (IHD) using Machine Learning (ML) in primary care cardiovascular patients. We compare the ML-models' performance with that of the common SMART algorithm and discuss clinical implications. METHODS AND RESULTS: Patient-level medical record data (n = 13,218) collected between 2011-2021 from 90 GP-practices were used to construct two random forest models (one for AMI and one for IHD) as well as a linear model based on the SMART risk prediction algorithm as a suitable comparator. The data contained patient-level predictors, including demographics, procedures, medications, biometrics, and diagnosis. Temporal cross-validation was used to assess performance. Furthermore, predictors that contributed most to the ML-models' accuracy were identified. The ML-model predicting AMI had an accuracy of 0.97, a sensitivity of 0.67, a specificity of 1.00 and a precision of 0.99. The AUC was 0.96 and the Brier score was 0.03. The IHD-model had similar performance. In both ML-models anticoagulants/antiplatelet use, systolic blood pressure, mean blood glucose, and eGFR contributed most to model accuracy. For both outcomes, the SMART algorithm was substantially outperformed by ML on all metrics. CONCLUSION: Our findings underline the potential of using ML for CVD prediction purposes in primary care, although the interpretation of predictors can be difficult. Clinicians, patients, and researchers might benefit from transitioning to using ML-models in support of individualized predictions by primary care physicians and subsequent (secondary) prevention.

Which Test Should I Order for an Inpatient Evaluation of Cardiac Ischemia?

AbstractTesting for cardiac ischemia, or for the obstructive coronary artery disease (CAD) that causes cardiac ischemia, is common among hospitalized patients. Many testing options exist. Choosing an appropriate test can be challenging and requires accurate risk stratification. Two major categories of testing are available: stress testing (also known as functional testing) and anatomical testing. Stress testing evaluates specifically for ischemia and can be conducted with or without imaging. Anatomical testing visualizes the obstructive CAD that causes ischemia. This article reviews how to choose an appropriate test for the evaluation of cardiac ischemia in the inpatient setting, using case examples to illustrate the considerations involved.

Stress-Induced Autonomic Dysfunction is Associated With Mental Stress-Induced Myocardial Ischemia in Patients With Coronary Artery Disease.

BACKGROUND: Mental stress-induced myocardial ischemia (MSIMI) is associated with adverse cardiovascular outcomes in individuals with coronary artery disease, but the mechanisms underlying this phenomenon are unknown. We examined the relationship between stress-induced autonomic dysfunction, measured by low heart rate variability (HRV) in response to stress, and MSIMI in patients with stable coronary artery disease. We hypothesized that stress-induced autonomic dysfunction is associated with higher odds of MSIMI. METHODS: In 735 participants with stable coronary artery disease, we measured high- and low-frequency HRV in 5-minute intervals before and during a standardized laboratory-based speech stressor using Holter monitoring. HRV at rest and stress were categorized into low HRV (first quartile) versus high HRV (second to fourth quartiles); the low category was used as an indicator of autonomic dysfunction. Multivariable logistic regression models were used to examine the association of autonomic dysfunction with MSIMI. RESULTS: The mean age was 58 (SD, ±10) years, 35% were women, 44% were Black participants, and 16% developed MSIMI. Compared with high HRV during stress, low HRV during stress (both high and low frequencies) was associated with higher odds of MSIMI after adjusting for demographic and clinical factors (odds ratio for high-frequency HRV, 2.1 [95% CI, 1.3-3.3]; odds ratio for low-frequency HRV, 2.1 [95% CI, 1.3-3.3]). Low-frequency HRV at rest was also associated with MSIMI but with slightly reduced effect estimates. CONCLUSIONS: In individuals with coronary artery disease, mental stress-induced autonomic dysfunction may be a mechanism implicated in the causal pathway of MSIMI.

Beyond Coronary Artery Disease: Assessing the Microcirculation.

Ischemic heart disease (IHD) affects more than 20 million adults in the United States. Although classically attributed to atherosclerosis of the epicardial coronary arteries, nearly half of patients with stable angina and IHD who undergo invasive coronary angiography do not have obstructive epicardial coronary artery disease. Ischemia with nonobstructive coronary arteries is frequently caused by microvascular angina with underlying coronary microvascular dysfunction (CMD). Greater understanding the pathophysiology, diagnosis, and treatment of CMD holds promise to improve clinical outcomes of patients with ischemic heart disease.

Triglyceride-glucose index is associated with myocardial ischemia and poor prognosis in patients with ischemia and no obstructive coronary artery disease.

BACKGROUND: Ischemia and no obstructive coronary artery disease (INOCA) is increasingly recognized and associated with poor outcomes. The triglyceride-glucose (TyG) index is a reliable alternative measure of insulin resistance significantly linked to cardiovascular disease and adverse prognosis. We investigated the association between the TyG index and myocardial ischemia and the prognosis in INOCA patients. METHODS: INOCA patients who underwent both coronary angiography and myocardial perfusion imaging (MPI) were included consecutively. All participants were divided into three groups according to TyG tertiles (T1, T2, and T3). Abnormal MPI for myocardial ischemia in individual coronary territories was defined as summed stress score (SSS) ≥ 4 and summed difference score (SDS) ≥ 2. SSS refers to the sum of all defects in the stress images, and SDS is the difference of the sum of all defects between the rest images and stress images. All patients were followed up for major adverse cardiac events (MACE). RESULTS: Among 332 INOCA patients, 113 (34.0%) had abnormal MPI. Patients with higher TyG index had a higher rate of abnormal MPI (25.5% vs. 32.4% vs. 44.1%; p = 0.012). Multivariate logistic analysis showed that a high TyG index was significantly correlated with abnormal MPI in INOCA patients (OR, 1.901; 95% CI, 1.045-3.458; P = 0.035). During the median 35 months of follow-up, 83 (25%) MACE were recorded, and a higher incidence of MACE was observed in the T3 group (T3 vs. T2 vs. T1: 36.9% vs. 21.6% vs. 16.4%, respectively; p = 0.001). In multivariate Cox regression analysis, the T3 group was significantly associated with the risk of MACE compared to the T1 group (HR, 2.338; 95% CI 1.253-4.364, P = 0.008). CONCLUSION: This study indicates for the first time that the TyG index is significantly associated with myocardial ischemia and poor prognosis among INOCA patients.

Challenges and benefits of using the HeartDiet food frequency questionnaire in cardiac rehabilitation practice.

BACKGROUND AND AIMS: A heart-healthy diet is an important component of secondary prevention in ischemic heart disease. The Danish Health Authority recommends using the validated 19-item food frequency questionnaire HeartDiet in cardiac rehabilitation practice to assess patients' need for dietary interventions, and HeartDiet has been included in national electronic patient-reported outcome instruments for cardiac rehabilitation. This study aims to evaluate challenges and benefits of its use. The objectives are to: 1) describe HeartDiet responses of patients with ischemic heart disease and discuss HeartDiet's suitability as a screening tool, 2) discuss whether an abridged version should replace HeartDiet. METHODS AND RESULTS: A cross-sectional study using data from a national feasibility test. HeartDiet was sent electronically to 223 patients with ischemic heart disease prior to cardiac rehabilitation. Data were summarised with descriptive statistics, and Spearman's rank correlations, explorative factor analysis, and Cohen's kappa coefficient were used to derive and evaluate abridged versions. The response rate was 68 % (n = 151). Evaluated with HeartDiet, no respondents had a heart-healthy diet. There was substantial agreement between HeartDiet and an abridged 9-item version (kappa = 0.6926 for Fat Score, 0.6625 for FishFruitVegetable Score), but the abridged version omits information on milk products, wholegrain, nuts, and sugary snacks. CONCLUSION: With the predefined cut-offs, HeartDiet's suitability as a screening tool to assess needs for dietary interventions was limited, since no respondents were categorised as having a heart-healthy diet. An abridged version can replace HeartDiet, but the tool's educational potential will be compromised, since important items will be omitted.

Diagnostic value of galectin-3, fractalkine, IL-6, miR-21 and cardiac troponin I in human ischemic cardiomyopathy.

OBJECTIVE: The primary objective of this study was to assess the diagnostic potential of galectin-3 (Gal-3), fractalkine (FKN), interleukin (IL)-6, microRNA(miR)-21, and cardiac troponin I (cTnI) in patients with ischemic cardiomyopathy (ICM). METHOD: A total of 78 ICM patients (Case group) and 80 healthy volunteers (Control group) admitted to our hospital for treatment or physical examination from Aug. 2018 to Feb. 2020 were included in the current study. The serum concentration of Gal-3, FKN, IL-6, miR-21, and plasma expression of cTnI of both groups were determined. The severity of ICM was classified using New York Heart Association (NYHA) scale. RESULTS: When compared with the control group, the case group had a significantly high blood concentration of Gal-3, FKN, IL-6, miR-21, and cTnI (P < 0.001). NYHA class II patients had lower blood levels of Gal-3, FKN, IL-6, miR-21, and cTnI than that in patients of NYHA class III and IV without statistical significance (P > 0.05). However, statistical significance could be achieved when comparing the above-analyzed markers in patients classified between class III and IV. Correlation analysis also revealed that serum levels of Gal-3, FKN, IL-6, miR-21, and cTnI were positively correlated with NYHA classification (R = 0.564, 0.621, 0.792, 0.981, P < 0.05). CONCLUSION: Our study revealed that up-regulated serum Gal-3, FKN, IL-6, miR-21, and cTnI levels were closely related to the progression of ICM. This association implies that these biomarkers have diagnostic potential, offering a promising avenue for early detection and monitoring of ICM progression.

Contributions of elevated CRP, hyperglycaemia, and type 2 diabetes to cardiovascular risk in the general population: observational and Mendelian randomization studies.

OBJECTIVE: To investigate the contributions of low-grade inflammation measured by C-reactive protein (CRP), hyperglycaemia, and type 2 diabetes to risk of ischemic heart disease (IHD) and cardiovascular disease (CVD) death in the general population, and whether hyperglycaemia and high CRP are causally related. RESEARCH DESIGN AND METHODS: Observational and bidirectional, one-sample Mendelian randomization (MR) analyses in 112,815 individuals from the Copenhagen General Population Study and the Copenhagen City Heart Study, and bidirectional, two-sample MR with summary level data from two publicly available consortia, CHARGE and MAGIC. RESULTS: Observationally, higher plasma CRP was associated with stepwise higher risk of IHD and CVD death, with hazard ratios and 95% confidence intervals (95%CI) of 1.50 (1.38, 1.62) and 2.44 (1.93, 3.10) in individuals with the 20% highest CRP concentrations. The corresponding hazard ratios for elevated plasma glucose were 1.10 (1.02, 1.18) and 1.22 (1.01, 1.49), respectively. Cumulative incidences of IHD and CVD death were 365% and 592% higher, respectively, in individuals with both type 2 diabetes and plasma CRP ≥ 2 mg/L compared to individuals without either. Plasma CRP and glucose were observationally associated (ß-coefficient: 0.02 (0.02, 0.03), p = 3 × 10- 20); however, one- and two-sample MR did not support a causal effect of CRP on glucose (-0.04 (-0.12, 0.32) and - 0.03 (-0.13, 0.06)), nor of glucose on CRP (-0.01 (-0.08, 0.07) and - 0.00 (-0.14, 0.13)). CONCLUSIONS: Elevated concentrations of plasma CRP and glucose are predictors of IHD and CVD death in the general population. We found no genetic association between CRP and glucose, or vice versa, suggesting that lowering glucose pharmacologically does not have a direct effect on low-grade inflammation.

Cost prediction for ischemic heart disease hospitalization: Interpretable feature extraction using network analysis.

OBJECTIVES: Ischemic heart disease (IHD) is a significant contributor to global mortality and disability, imposing a substantial social and economic burden on individuals and healthcare systems. To enhance the efficient allocation of medical resources and ultimately benefit a larger population, accurate prediction of healthcare costs is crucial. METHODS: We developed an interpretable IHD hospitalization cost prediction model that integrates network analysis with machine learning. Specifically, our network-enhanced model extracts explainable features by leveraging a diagnosis-procedure concurrence network and advanced graph kernel techniques, facilitating the capture of intricate relationships between medical codes. RESULTS: The proposed model achieved an R2 of 0.804 ± 0.008 and a root mean square error (RMSE) of 17,076 ± 420 CNY on the temporal validation dataset, demonstrating comparable performance to the model employing less interpretable code embedding features (R2: 0.800 ± 0.008; RMSE: 17,279 ± 437 CNY) and the hybrid graph isomorphism network (R2: 0.802 ± 0.007; RMSE: 17,249 ± 387 CNY). The interpretation of the network-enhanced model assisted in pinpointing specific diagnoses and procedures associated with higher hospitalization costs, including acute kidney injury, permanent atrial fibrillation, intra-aortic balloon bump, and temporary pacemaker placement, among others. CONCLUSION: Our analysis results demonstrate that the proposed model strikes a balance between predictive accuracy and interpretability. It aids in identifying specific diagnoses and procedures associated with higher hospitalization costs, underscoring its potential to support intelligent management of IHD.

Risk Stratification Using Right Ventricular Longitudinal Strain Ratio Derived from 13N-Ammonia PET in Patients with Ischemic Heart Disease.

Purpose To investigate whether right ventricular (RV) myocardial strain ratio (RVMSR) assessed using nitrogen 13 ammonia (13N-NH3) PET can predict cardiovascular events in patients with ischemic heart disease (IHD). Materials and Methods This retrospective study included 480 consecutive patients (mean age, 66 years ± 12 [SD]; 334 males and 146 females) with IHD who underwent 13N-NH3 PET. RVMSR was defined as the ratio of RV strain during stress to that at rest. The primary end point was major adverse cardiac events (MACEs), defined as cardiac death or heart failure hospitalization. The ability of RVMSR to predict MACE was assessed using receiver operating characteristic (ROC) curve and Kaplan-Meier analyses. Cox proportional hazards regression analysis was used to calculate hazard ratios (HRs) with 95% CIs. Results ROC curve analysis identified a sensitivity and specificity of 84% and 82%, respectively, for predicting MACE from RVMSR. Patients with reduced RVMSR (<110.2) displayed a significantly higher rate of MACE than those with a preserved RVMSR (34 of 240 vs four of 240; P < .001). Cox proportional hazards regression analysis of imaging parameters, including myocardial flow reserve, indicated that RVMSR was an independent predictor of MACE (HR, 0.94 [95% CI: 0.92, 0.97]; P < .001). Conclusion RVMSR was an independent predictor of MACE and has potential to aid in the risk stratification of patients with IHD. Keywords: Right Ventricular Myocardial Strain Ratio, Myocardial Flow Reserve, Ischemic Heart Disease, 13N-Ammonia Positron Emission Tomography Supplemental material is available for this article. © RSNA, 2024.

Meta-analysis of the association between interleukin-17 and ischemic cardiovascular disease.

BACKGROUND: Interleukin-17 (IL-17) has been hypothesized to be involved in ischemic cardiovascular disease (ICVD). However, the association of IL-17 with ICVD remained unclear. The aim of this study was to systematically analyze the available evidence regarding the association between IL-17 and ICVD. METHODS: We searched the PubMed, Web of Science, Cochrane Library, and Embase databases up to October 2023 to identify publications on the association between IL-17 and ICVD. The merged results were analyzed using a random effects model for meta-analysis and subgroup analysis. RESULTS: A total of 955 publications were initially identified in our search and screened; six studies were eventually included in the analysis. The average age of study participants was 60.3 ± 12.6 years and 65.5% were men. There was a high degree of heterogeneity among studies. The results showed that IL-17 level were higher in the case group than those in the control group (standardized mean difference, SMD = 1.60, 95% confidence interval (95% CI): 0.53-2.66, P = 0.003). In sensitivity analysis, the merged results showed good robustness. Additionally, subgroup analysis showed that race and ethnicity, sample size, and detection methods were significant factors influencing heterogeneity in the published studies. CONCLUSION: Our finding revealed that increased IL-17 level contributed to the development of ICVD, suggesting IL-17 as a potential risk marker. Further research is needed to establish IL-17 as a therapeutic biomarker of ICVD.

Myocardial motion in acute ischemia: revealing invisible deformation by echocardiography.

Echocardiography has been used clinically to assess regional myocardial wall motion for the diagnosis of acute myocardial ischemia or stress-induced ischemia, but it is often difficult to distinguish hypokinetic motion from normal motion. Myocardial wall motion is affected by loading conditions as well as intrinsic contractility, making it challenging to define a normal range of wall motion. Therefore, hypokinesis is usually diagnosed by comparing target areas with other areas of myocardium considered normal (relative hypokinesis). Myocardial strain analysis by tissue Doppler echocardiography and speckle-tracking echocardiography has enabled objective and quantitative evaluation of regional myocardial wall motion. Peak systolic strain decreases during acute ischemia, but subtle and invisible myocardial motion, such as early systolic lengthening (ESL) and postsystolic shortening (PSS), also occurs, and the analysis of these subtle motions can improve the diagnostic accuracy of ischemia. However, the diagnosis of ischemic myocardium by strain analysis is not widely performed in clinical practice at this time due to several limitations. This article reviews the features of myocardial motion during acute ischemia, the mechanisms of ESL and PSS, the diagnosis of ischemic myocardium using strain analysis, and current approaches and future challenges to overcome the limitations in the detection of relative hypokinesis. This article also explains the use of ESL and PSS to detect myocardial ischemic memory that remains after brief ischemia.

Forward problem of electrocardiography based on cardiac source vector orientations.

To localize the unusual cardiac activities non-invasively, one has to build a prior forward model that relates the heart, torso, and detectors. This model has to be constructed to mathematically relate the geometrical and functional activities of the heart. Several methods are available to model the prior sources in the forward problem, which results in the lead field matrix generation. In the conventional technique, the lead field assumed the fixed prior sources, and the source vector orientations were presumed to be parallel to the detector plane with the unit strength in all directions. However, the anomalies cannot always be expected to occur in the same location and orientation, leading to misinterpretation and misdiagnosis. To overcome this, the work proposes a new forward model constructed using the VCG signals of the same subject. Furthermore, three transformation methods were used to extract VCG in constructing the time-varying lead fields to steer to the orientation of the source rather than just reconstructing its activities in the inverse problem. In addition, the unit VCG loop of the acute ischemia patient was extracted to observe the changes compared to the normal subject. The abnormality condition was achieved by delaying the depolarization time by 15ms. The results involving the unit vectors of VCG demonstrated the anisotropic nature of cardiac source orientations, providing information about the heart's electrical activity.

The role of beat-by-beat cardiac features in machine learning classification of ischemic heart disease (IHD) in magnetocardiogram (MCG).

Cardiac electrical changes associated with ischemic heart disease (IHD) are subtle and could be detected even in rest condition in magnetocardiography (MCG) which measures weak cardiac magnetic fields. Cardiac features that are derived from MCG recorded from multiple locations on the chest of subjects and some conventional time domain indices are widely used in Machine learning (ML) classifiers to objectively distinguish IHD and control subjects. Most of the earlier studies have employed features that are derived from signal-averaged cardiac beats and have ignored inter-beat information. The present study demonstrates the utility of beat-by-beat features to be useful in classifying IHD subjects (n = 23) and healthy controls (n = 75) in 37-channel MCG data taken under rest condition of subjects. The study reveals the importance of three features (out of eight measured features) namely, the field map angle (FMA) computed from magnetic field map, beat-by-beat variations of alpha angle in the ST-T region and T wave magnitude variations in yielding a better classification accuracy (92.7 %) against that achieved by conventional features (81 %). Further, beat-by-beat features are also found to augment the accuracy in classifying myocardial infarction (MI) Versus control subjects in two public ECG databases (92 % from 88 % and 94 % from 77 %). These demonstrations summarily suggest the importance of beat-by-beat features in clinical diagnosis of ischemia.