Use of electrocardiographic depolarization abnormalities for detection of stress-induced ischemia as defined by myocardial perfusion imaging

Enhancing the diagnosis of functionally relevant coronary artery disease with machine learning

Functionally relevant coronary artery disease (fCAD) can result in premature death or nonfatal acute myocardial infarction. Its early detection is a fundamentally important task in medicine. Classical detection approaches suffer from limited diagnostic accuracy or expose patients to possibly harmful radiation. Here we show how machine learning (ML) can outperform cardiologists in predicting the presence of stress-induced fCAD in terms of area under the receiver operating characteristic (AUROC: 0.71 vs. 0.64, p = 4.0E-13). We present two ML approaches, the first using eight static clinical variables, whereas the second leverages electrocardiogram signals from exercise stress testing. At a target post-test probability for fCAD of <15%, ML facilitates a potential reduction of imaging procedures by 15-17% compared to the cardiologist's judgement. Predictive performance is validated on an internal temporal data split as well as externally. We also show that combining clinical judgement with conventional ML and deep learning using logistic regression results in a mean AUROC of 0.74.

Revisiting the diagnostic and prognostic significance of high-frequency QRS analysis in cardiovascular diseases: a comprehensive review

Cardiovascular diseases (CVDs) present a significant global public health threat, contributing to a substantial number of cases involving morbidity and mortality. Therefore, the early and accurate detection of CVDs plays an indispensable role in enhancing patient outcomes. Decades of extensive research on electrocardiography at high frequencies have yielded a wealth of knowledge regarding alterations in the QRS complex during myocardial ischemia, as well as the methodologies to assess and quantify these changes. In recent years, the analysis of high-frequency QRS (HF-QRS) components has emerged as a promising non-invasive approach for diagnosing various cardiovascular conditions. Alterations in HF-QRS amplitude and morphology have demonstrated remarkable sensitivity as diagnostic indicators for myocardial ischemia, often surpassing measures of ST-T segment changes. This comprehensive review aims to provide an intricate overview of the current advancements, challenges, and prospects associated with HF-QRS analysis in the field of CVDs.

The combination of high-frequency QRS and ST-segment alterations during exercise stress tests enhanced the diagnostic efficacy for coronary artery disease

BACKGROUND

High-frequency QRS (HF-QRS) manifests as a novel adjunct electrocardiographic marker with potential utility in coronary artery disease (CAD) detection.

HYPOTHESIS

We hypothesize that HF-QRS analysis may be superior to conventional ST-segment analysis in detecting CAD, and the combination of these two analyses in the exercise stress test may enhance the diagnostic efficacy for CAD.

METHODS

The study incorporated a sample of 157 patients (mean age 62 ± $\pm $  9 years) referred for nonemergent angiography. Before angiography, patients underwent exercise stress testing utilizing an upright bicycle. High-resolution electrocardiogram (ECG) data were collected during the exercise test, facilitating both HF-QRS and conventional ST-segment analyses. The diagnostic efficacy of HF-QRS and ST-segment analysis were compared, utilizing angiographic outcomes as the gold standard. The study design integrated HF-QRS analysis and ST-segment analysis via sequential and concurrent testing protocols.

RESULTS

In terms of CAD detection, HF-QRS analysis displayed superior sensitivity compared to conventional ST-segment analysis (63% vs. 37%, p = .002). The serial test significantly increased specificity from 79% to 97% (p = .002) compared to ST-deviation analysis alone. It showed a markedly low sensitivity of 26%. The parallel test significantly increased sensitivity from 37% to 77% (p < .001), while retaining a moderate level of specificity of 51%. The quantity of ECG leads exhibiting a positive HF-QRS response demonstrated a correlation with the severity of CAD (p < .001).

CONCLUSIONS

HF-QRS analysis exhibited superior sensitivity in detecting angiographically confirmed CAD relative to conventional ST-segment analysis. Moreover, the combination of HF-QRS and ST-segment alterations during exercise stress test enhanced the diagnostic efficacy for CAD.

Cardiological Functional Assessment of National Olympic Team of Kazakhstan

Athletes carry an increased risk of cardiovascular (CV) conditions. Due to the relatively high loads and intensity of the training process, athletes' CV systems undergo various adaptations, which can combine in the future and provoke unexpected outcomes. Most CV screening protocols have several successive steps. The aim of our study was to perform a cardiological functional assessment of the National Olympic Team of Kazakhstan via several noninvasive protocols to close the gaps between the approaches and collect solid data for the prevention of sudden cardiac death (SCD) incidence among Kazakhstani athletes.

METHODS

The methods used in this study were 12-lead resting electrocardiography (ECG), echocardiography, cardiointervalography, cardiopulmonary exercise testing (CPET), and HyperQ stress testing.

RESULTS

One case was detected via 12-lead resting ECG. Another case of the slowdown of the heart rate (HR) recovery was detected via cardiointervalography with no clinical signs and normal ECG. The HyperQ stress testing of the women's basketball team detected a positive result in four leads in one athlete.

CONCLUSION

Our results demonstrate that the CV systems of athletes require the implementation of several diagnostic methods in rest and stress conditions for more precise evaluation, with each of the methods fulfilling the whole picture for the prevention of such tragic events as sudden cardiac death and sudden cardiac arrest.

Comparative Analysis of the Diagnostic Effectiveness of SATRO ECG in the Diagnosis of Ischemia Diagnosed in Myocardial Perfusion Scintigraphy Performed Using the SPECT Method

There is a great need for early diagnosis of ischemic heart disease (IHD), the most common cause of which is haemodynamic disorders caused mainly by obstructive atherosclerosis of the coronary arteries. The diagnosis of IHD is usually made with the use of functional tests, which include resting ECG (R) or examination of significant perfusion disorders during exercise using the SPECT method. Despite the fact that the ECG (R) test is commonly used in cardiological diagnostics, it has a limited diagnostic value, especially in people with a low probability of coronary artery disease (CAD). In order to increase the effectiveness of the ECG (R) examination, SATRO ECG software, based on the single fibres heart activity model (SFHAM), was used to evaluate the electrocardiograms. The introduction of new classifiers from the available medical data to the analysis made it possible to evaluate the diagnostic efficacy of SATRO ECG (TOT) in predicting significant perfusion disorders in the exercise SPECT (TOT 2). These disorders are most often caused by obstructive atherosclerosis of the coronary arteries, which is the main cause of CAD. The database of 316 patients (219 men and 97 women, aged 57 ± 10 years) was analyzed using resting and stress ECG, perfusion scintigraphy performed using the SPECT method, and SATRO ECG analysis. The diagnostic efficacy parameters of SATRO ECG (TOT) in predicting significant perfusion abnormalities in the exercise-induced SPECT (TOT 2) study were: sensitivity, 99%; specificity, 91%; concordance, 96%; and positive, 96%, and negative, 97%, predictive values. The Kappa–Cohen coefficient was 0.92, and the statistical significance coefficient was p < 0.001. These results indicate a statistically significant agreement in the diagnosis of IHD in both diagnostic methods used.

Changes in High-Frequency Intracardiac Electrogram Indicate Cardiac Ischemia

High-frequency QRS (HFQRS) analysis of surface ECG is a reliable marker of cardiac ischemia (CI). This study aimed to assess the response of HFQRS signals from standard intracardiac electrodes (iHFQRS) to CI in swine and compare them with conventional ST-segment deviations. Devices with three intracardiac leads were implanted in three swine in a controlled environment. CI was induced by inflating a balloon in epicardial coronary arteries. A designated signal-processing algorithm was applied to quantify the iHFQRS content before, during, and after each occlusion. iHFQRS time responses were compared to conventional ST-segment deviations. Thirty-three over thirty-nine (85%) of the occlusions presented significant reduction in the iHFQRS signal, preceding ST-segment change, being the only indicator of CI in brief occlusions. iHFQRS was found to be an early indicator for the onset of CI and demonstrated superior sensitivity to conventional ST-segment deviations during brief ischemic episodes.

Incremental value of high-frequency QRS analysis for diagnosis and prognosis in suspected exercise-induced myocardial ischaemia

Aim:

Exercise stress testing is used to detect myocardial ischaemia, but is limited by low sensitivity and specificity. The authors investigated the value of the analysis of high-frequency QRS components as a marker of abnormal depolarization in addition to standard ST-deviations as a marker of abnormal repolarization to improve the diagnostic accuracy.

Methods and results:

Consecutive patients undergoing bicycle exercise stress nuclear myocardial perfusion imaging were prospectively enrolled. Presence of myocardial ischaemia, the primary diagnostic endpoint, was adjudicated using MPI and coronary angiography. Automated high-frequency QRS analysis was performed in a blinded fashion. The prognostic endpoint was major adverse cardiac events (MACEs) during two years of follow-up. Exercise-induced ischaemia was detected in 147/662 patients (22%). The sensitivity of high-frequency QRS was similar to ST-deviations (46% vs. 43%, p=0.59), while the specificity was lower (75% vs. 87%, p&lt;0.001). The combined use of high-frequency QRS and ST-deviations classified 59% of patients as ‘rule-out’ (both negative), 9% as ‘rule-in’ (both positive) and 32% in an intermediate zone (one test positive). The sensitivity for ‘rule-out’ and the specificity for ‘rule-in’ improved to 63% and 97% compared with ST-deviation analysis alone (both p&lt;0.001). MACE-free survival was 90%, 80% and 42% in patients in the ‘rule-out’, intermediate and ‘rule-in’ groups (p&lt;0.001). After adjustment for age, gender, ST-deviations and clinical post-test probability of ischaemia, high-frequency QRS remained an independent predictor for the occurrence of MACEs.

Conclusion:

The use of high-frequency QRS analysis in addition to ST-deviation analysis improves the diagnostic accuracy during exercise stress testing and adds independent prognostic information.

High-frequency QRS analysis to supplement ST evaluation in exercise stress electrocardiography: Incremental diagnostic accuracy and net reclassification

BACKGROUND

Exercise stress electrocardiography (ECG) alone is underutilized in part due to poor diagnostic accuracy. High-frequency QRS analysis (HF-QRS) is a novel tool to supplement ST evaluation during stress ECG. We compared the diagnostic accuracy and net reclassification of HF-QRS analysis compared with ST evaluation for substantial myocardial ischemia by exercise SPECT myocardial perfusion imaging (MPI).

METHODS AND RESULTS

Exercise SPECT MPI was performed in 257 consecutive eligible patients (mean age 59 ± 12, 67% male). An ischemic HF-QRS pattern was defined as a ≥ 1 µV absolute reduction and a ≥ 50% relative reduction of the root-mean-square of the 150-250 Hz band signal in ≥ 3 leads. Left ventricular ischemia of ≥ 10% on SPECT MPI was the diagnostic standard for substantial myocardial ischemia. HF-QRS analysis demonstrated incremental diagnostic value to ST evaluation plus clinical risk factors (AUC 0.804 vs 0.749, P < .0001). A HF-QRS + ST -analysis strategy identified 92.3% of subjects with substantial ischemia and no abnormality in 59.9% of the cohort. No cardiac events occurred in patients without substantial ischemia identified by HF-QRS analysis.

CONCLUSIONS

In this prospective analysis, exercise stress ECG with HF-QRS analysis identified any and substantial ischemia with high diagnostic accuracy and may allow more than half of referred patients to safely avoid imaging.

ECG features and methods for automatic classification of ventricular premature and ischemic heartbeats: A comprehensive experimental study

Accurate detection of cardiac pathological events is an important part of electrocardiogram (ECG) evaluation and subsequent correct treatment of the patient. The paper introduces the results of a complex study, where various aspects of automatic classification of various heartbeat types have been addressed. Particularly, non-ischemic, ischemic (of two different grades) and subsequent ventricular premature beats were classified in this combination for the first time. ECGs recorded in rabbit isolated hearts under non-ischemic and ischemic conditions were used for analysis. Various morphological and spectral features (both commonly used and newly proposed) as well as classification models were tested on the same data set. It was found that: a) morphological features are generally more suitable than spectral ones; b) successful results (accuracy up to 98.3% and 96.2% for morphological and spectral features, respectively) can be achieved using features calculated without time-consuming delineation of QRS-T segment; c) use of reduced number of features (3 to 14 features) for model training allows achieving similar or even better performance as compared to the whole feature sets (10 to 29 features); d) k-nearest neighbours and support vector machine seem to be the most appropriate models (accuracy up to 98.6% and 93.5%, respectively).

Value of Exercise ECG for Risk Stratification in Suspected or Known CAD in the Era of Advanced Imaging Technologies

Exercise stress electrocardiography (ExECG) is underutilized as the initial test modality in patients with interpretable electrocardiograms who are able to exercise. Although stress myocardial imaging techniques provide valuable diagnostic and prognostic information, variables derived from ExECG can yield substantial data for risk stratification, either supplementary to imaging variables or without concurrent imaging. In addition to exercise-induced ischemic ST-segment depression, such markers as ST-segment elevation in lead aVR, abnormal heart rate recovery post-exercise, failure to achieve target heart rate, and poor exercise capacity improve risk stratification of ExECG. For example, patients achieving ≥10 metabolic equivalents on ExECG have a very low prevalence of inducible ischemia and an excellent prognosis. In contrast, cardiac imaging techniques add diagnostic and prognostic value in higher-risk populations (e.g., poor functional capacity, diabetes, or chronic kidney disease). Optimal test selection for symptomatic patients with suspected coronary artery disease requires a patient-centered approach factoring in the risk/benefit ratio and cost-effectiveness.

High-frequency QRS analysis superior to conventional ST-segment analysis of women with chest pain

BACKGROUND

The novel analysis of high-frequency QRS components (HF/QRS) has been proposed in patients with chest pain (CP) referred for exercise tolerance test (ex-ECG). We sought to evaluate the prognostic role of exercise high-frequency QRS-analysis (ex-HF/QRS) in patients with recent-onset stable CP, in the emergency setting.

METHODS

Patients with CP underwent ex-ECG. A decrease greater than or equal to 50% of the signal of HF/QRS intensity was considered as index of ischemia as ST-segment depression greater than or equal to 2 mm or greater than or equal to 1 mm associated with CP. Exclusion criteria were QRS duration greater than or equal to 120 milliseconds and inability to exercise. Baseline characteristics were adjusted with the propensity score matching specifying nearest-neighbor matching in cardiovascular risk factors and risk scores. The primary end point was the composite of coronary stenosis greater than or equal to 70% or acute coronary syndrome, revascularization, and cardiac death on the 6-month follow-up.

RESULTS

Of 589 patients, 22 achieved the end point. On the univariate analysis, known cardiovascular disease, GRACE score, and ex-HF/QRS were predictors of the end point. On the multivariate analysis, only ex-HF/QRS was predictor of the end point (odd ratio, 28; 95% confidence interval [CI], 6-120; P < .001). Overall, the ex-HF/QRS when compared to ex-ECG showed higher sensitivity (91% vs 27%; P = .02), lower specificity (74% vs 86%; P = .09), and comparable negative predictive value (99% vs 97%; P = .78). Receiver operating characteristic curve analysis showed the larger area of ex-HF/QRS (0.83; 95% CI, 0.75-0.90) over ex-ECG (0.57; CI, 0.44-0.70) and GRACE score (0.65; CI, 0.54-0.76); P < .03 on C-statistic. Women showed the largest area (0.89; CI, 0.83-0.95; P < .03) vs the other clinical data.

CONCLUSIONS

In patients with CP, the novel ex-HF/QRS analysis has a valuable incremental prognostic role over ex-ECG, especially in women.

Identification of exercise-induced ischemia using QRS slopes

In this work we studied a computer-aided approach using QRS slopes as unconventional ECG features to identify the exercise-induced ischemia during exercise stress testing and demonstrated that the performance is comparable to the experts' manual analysis using standard criteria involving ST-segment depression. We evaluated the performance of our algorithm using a database including 927 patients undergoing exercise stress tests and simultaneously collecting the ECG recordings and SPECT results. High resolution 12-lead ECG recordings were collected continuously throughout the rest, exercise, and recovery phases. Patients in the database were classified into three categories of moderate/severe ischemia, mild ischemia, and normal according to the differences in sum of the individual segment scores for the rest and stress SPECT images. Philips DXL 16-lead diagnostic algorithm was run on all 10-s segments of 12-lead ECG recordings for each patient to acquire the representative beats, ECG fiducial points from the representative beats, and other ECG parameters. The QRS slopes were extracted for each lead from the averaged representative beats and the leads with highest classification power were selected. We employed linear discriminant analysis and measured the performance using 10-fold cross-validation. Comparable performance of this method to the conventional ST-segment analysis exhibits the classification power of QRS slopes as unconventional ECG parameters contributing to improved identification of exercise-induced ischemia.

Comparison of exercise electrocardiogram and exercise echocardiography in intermediate-risk chest pain patients

BACKGROUND

The novel exercise computer-assisted high-frequency QRS analysis (HF/QRS) has demonstrated improved sensitivity and specificity over the conventional ST/electrocardiogram-segment analysis (ST/ECG) in the detection of myocardial ischemia. The aim of the present study was to compare the diagnostic value of the validated exercise echocardiography (ex-Echo) with the novel exercise ECG (ex-ECG) including HF/QRS and ST/ECG analysis.

METHODS

A prospective cohort study was conducted in the emergency department of a tertiary care teaching Hospital. Patients with chest pain (CP), normal resting ECGs, troponins, and echocardiography, labeled as "intermediate-risk" for adverse coronary events, underwent the novel ex-ECG and ex-Echo. An ST-segment depression of at least 2 mV or at least 1 mV when associated with CP was considered as an index of ischemia, as well as a decrease of at least 50% in HF/QRS intensity, or new wall motion abnormalities on ex-Echo. Exclusion criteria were QRS duration of at least 120 milliseconds, poor echo-acoustic window, and inability to exercise. Patients were followed up to 3 months. The end point was the composite of coronary stenoses of 50% or greater at angiography or acute coronary syndrome, revascularization, and cardiovascular death on the 3-month follow-up.

RESULTS

Of 188 patients enrolled, 18 achieved the end point. The novel ex-ECG and ex-Echo showed comparable negative predictive value (97% vs 96%; P = .930); however, sensitivity was 83% vs 61%, respectively (P = .612), and specificity was 64% vs 92%, respectively,(P = .026). The areas on receiver operating characteristic analysis were comparable (ex-ECG: 0.734 [95% confidence interval, or CI, 0.62-0.85] vs ex-Echo: 0.767 [CI, 0.63-0.91]; C statistic, P = .167). On multivariate analysis, both ex-ECG (hazard ratio, 5; CI, 1-20; P = .017) and ex-Echo (HR, 12; CI, 4-40; P < .001) were predictors of the end point.

CONCLUSIONS

In intermediate-risk CP patients, the novel ex-ECG including HF/QRS added to ST/ECG analysis was a valuable diagnostic tool and might be proposed to avoid additional imaging. However, the novel test needs additional study before it can be recommended as a replacement for current techniques.

Improved detection of ischemic heart disease by combining high-frequency electrocardiogram analysis with exercise stress echocardiography

Background and Objectives

Because the exercise treadmill test (ETT) based on ST-segment analysis is limited due to low sensitivity and specificity, there has been an interest in the additional analysis of high-frequency components of QRS (HFQRS) for the detection of coronary artery disease (CAD). We sought to evaluate the feasibility and clinical usefulness of HFQRS analysis during exercise stress echocardiography (ESE).

Subjects and Methods

We evaluated 175 patients (age 57±9,118 men) who performed ESE and either coronary computed tomographic angiography or coronary angiography. ETT was performed using the HyperQ stress system for both conventional ST-segment analysis and HFQRS intensity analysis.

Results

Thirty-two patients (31%) had significant CAD. The sensitivity and specificity of HFQRS analysis were 68.8% and 74.8%, respectively. The combined model, including HFQRS analysis and ESE, provided the best diagnostic accuracy, with the area under the receiver-operating characteristics curve (AUC) of 0.948 {95% confidence interval (CI)=0.913-0.984} compared with ST-segment analysis (AUC 0.679, 95% CI=0.592-0.766).

Conclusion

HFQRS analysis during ESE is feasible and may provide additional diagnostic information for the detection of significant CAD.

High-frequency QRS analysis in patients with acute myocardial infarction: a preliminary study

BACKGROUND

The 12-lead electrocardiogram (ECG) is a primary tool in the evaluation and risk stratification of patients with suspected acute myocardial infarction (AMI), even though the initial ECG of these patients is often normal or nondiagnostic. Myocardial ischemia induces depolarization changes that can be quantified by analysis of high-frequency QRS (HFQRS) components. We aimed to demonstrate the potential usefulness of HFQRS analysis in diagnosing myocardial ischemia by characterizing the morphological patterns of the HFQRS signals in patients with AMI before and following reperfusion.

METHODS

Five-minute high-resolution ECG was acquired from 30 patients with AMI (age 55 ± 11 years, 26 men) upon their admission to the intensive coronary care unit (ICCU). Serial ECGs were acquired following coronary revascularization and after additional 24 hours (24h). High-frequency morphology index (HFMI), quantifying the extent of ischemic patterns was computed by a custom software, and its values were compared between the serial ECG measurements.

RESULTS

HFMI values were significantly higher on the admission ECG as compared to the post intervention ECG (4.6 ± 2.9% vs 3.4 ± 2.3%, P < 0.05) and to the 24h ECG (4.6 ± 2.9% vs 2.8 ± 2.1%, P < 0.01). In 79% of the patients who were successfully revascularized HFMI value decreased from admission ECG to 24h ECG.

CONCLUSIONS

Analysis of HFQRS morphology in patients with AMI provides information about the existence and severity of myocardial ischemia. HFQRS analysis may aid in risk stratification of patients with suspected myocardial ischemia, complementarily to conventional ECG.