Detection of coronary artery disease from the normal resting ECG using nonlinear mathematical transformation

Schreck, David M.; Ng, Lawrence; Schreck, Brad S; Bosco, Samuel; Zacharias, Daniel; Wortzel, Jay V

doi:10.1016/s0196-0644(88)80298-1

Annals of Emergency Medicine

1988

DOI: 10.1016/s0196-0644(88)80298-1

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Detection of coronary artery disease from the normal resting ECG using nonlinear mathematical transformation

David M. Schreck

Lawrence Ng

Brad S Schreck

et al.

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Cited by 13 publications

(1 citation statement)

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“…However, unlike a standard ECG, the Vectraplex ECG system, utilizing supplementary proprietary analysis (eigenvalue modeling of the various vectors, quantifying dipolar and multipolar forces), 3,4 yields additional information, dubbed the "cardiac electrical biomarker" (CEB), that is proposed to add to the sensitivity and specificity of findings. The Vectraplex ECG system has been previously studied in retrospective patient groups and compared to traditional ECG computer and human analysis.…”

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confidence: 99%

Sensitivity and specificity of the Vectraplex electrocardiogram system with a cardiac electric biomarker in the diagnosis of ST-elevation myocardial infarction

Mixon¹,

Hardegree²,

Shah³

et al. 2019

Baylor University Medical Center Proceedings

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ST-elevation myocardial infarction (STEMI) is a clinical diagnosis based on a compatible history and characteristic electrocardiographic changes. In the current era, STEMI is treated emergently with angiography, leading to percutaneous coronary intervention. However, false-positive electrocardiograms (ECGs) occur, resulting in unnecessary emergent catheterizations. We hypothesized that the Vectraplex cardiac electrical biomarker (CEB) would increase the specificity for the diagnosis of STEMI. We studied 50 patients who were identified by standard of care (clinical history, physical exam, and 12-lead ECG) as suspected to have STEMI and tested the sensitivity and specificity of the Vectraplex ECG system. Using the final clinical diagnosis (based on history, ECGs, troponin values, and angiographic findings) as the gold standard, we found the CEB value to be quite dynamic, with a reasonable sensitivity and a good positive predictive value but generally poor specificity and negative predictive value. It offered only a 20% improvement compared to 50-50 performance on receiver operator curves.

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mentioning

confidence: 99%

Sensitivity and specificity of the Vectraplex electrocardiogram system with a cardiac electric biomarker in the diagnosis of ST-elevation myocardial infarction

Mixon¹,

Hardegree²,

Shah³

et al. 2019

Baylor University Medical Center Proceedings

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RETRACTED ARTICLE: Cardiac arrhythmia detection using dual-tree wavelet transform and convolutional neural network

Madhavi¹,

Kora²,

Reddy³

et al. 2022

Soft Comput

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The non-stationary ECG signals are used as a key tools in screening coronary diseases. ECG recording is collected from millions of cardiac cells' and depolarization and re-polarization conducted in a synchronized manner as: The P-wave occurs first, followed by the QRScomplex and the T-wave, which will repeat in each beat. The signal is altered in a cardiac beat period for different heart conditions. This change can be observed in order to diagnose the patient's heart status. There are life-threatening (critical) and non-life -threatening (noncritical) arrhythmia (abnormal Heart). Critical arrhythmia gives little time for surgery, whereas non-critical needs additional life-saving care. Simple naked eye diagnosis can mislead the detection. At that point, Computer Assisted Diagnosis (CAD) is therefore required. In this paper Dual Tree Wavelet Transform (DTWT) used as a feature extraction technique along with Convolution Neural Network (CNN) to detect abnormal Heart. The findings of this research and associated studies are without any cumbersome artificial environments. The CAD method proposed has high generalizability; it can help doctors efficiently identify diseases and decrease misdiagnosis.

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Heart disease detection using hybrid of bacterial foraging and particle swarm optimization

Kora¹,

Abraham

Meenakshi³

2019

Evolving Systems

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Detection of coronary artery disease from the normal resting ECG using nonlinear mathematical transformation

Cited by 13 publications

References 5 publications

Sensitivity and specificity of the Vectraplex electrocardiogram system with a cardiac electric biomarker in the diagnosis of ST-elevation myocardial infarction

Sensitivity and specificity of the Vectraplex electrocardiogram system with a cardiac electric biomarker in the diagnosis of ST-elevation myocardial infarction

RETRACTED ARTICLE: Cardiac arrhythmia detection using dual-tree wavelet transform and convolutional neural network

Heart disease detection using hybrid of bacterial foraging and particle swarm optimization

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