A Digital Electrocardiographic System for Assessing Myocardial Electrical Instability: Principles and Applications

Area of Science:

• Cardiology
• Biomedical Engineering
• Medical Technology

Background:

• Myocardial electrical instability is a critical factor in adverse cardiovascular events (ACVE).
• Accurate monitoring and prediction of ACVE are essential for patient management in cardiology.
• Existing methods may lack the precision or scope to fully capture electrical instability markers.

Purpose of the Study:

• To develop and evaluate an ECG hardware and software system (Intecard 7.3) for monitoring myocardial electrical instability.
• To assess the diagnostic and prognostic capabilities of this system in a clinical setting.
• To establish a predictive model for ACVE risk stratification using ECG-derived markers.

Main Methods:

• Developed the Intecard 7.3 system for beat-to-beat ECG analysis, measuring parameters like fragmented QRS, QRS-T angle, T-wave alternans, and QT interval/dispersion.
• Evaluated the system in 734 patients with ischemic heart disease or cardiomyopathy and 112 healthy individuals.
• Utilized digital precision processing for enhanced accuracy of ECG signal analysis.

Main Results:

• Intecard 7.3 reliably identified fragmented QRS complexes and calculated spatial QRS-T angle, T-wave alternans, QT interval, and QT dispersion with high precision.
• Patients experiencing ACVE showed significantly higher frequencies of fragmented QRS, larger QRS-T angles, increased T-wave alternans, prolonged QT intervals, and greater QT dispersion compared to those without ACVE.
• A personalized ACVE risk stratification model achieved 77% predictive accuracy, with 75% sensitivity and 78% specificity.

Conclusions:

• The Intecard 7.3 system effectively uses ECG markers of myocardial electrical instability to predict life-threatening ventricular tachyarrhythmias and sudden cardiac death.
• The system demonstrates a predictive accuracy of 77% for adverse cardiovascular events.
• Its non-invasiveness, high productivity, and reasonable cost make it a valuable tool for healthcare at all levels.