MCG Literature

Diagnosing ischemia in emergency department (ED) patients with suspected acute coronary syndrome (sACS) is challenging with equivocal disposition of intermediate risk patients.

To These are the first data linking magnetocardiographical parameters and subsequent significant fatal events in people, suggesting structural and functional components to clinical life-threatening ventricular arrhythmogenesis.

In this study, MCG demonstrated a sensitivity of 91.2% and specificity of 84.6% in identifying patients with STEMI versus healthy subjects.

This study of 364 patients demonstrates the ability of MCG to detect CAD, even in patient subgroups without specific biomarker or ECG changes. In the overall patient cohort, MCG’s sensitivity and specificity were 84% and 85% respectively. In the more challenging patient sub-population that did not display ECG or biomarker changes, MCG displayed a sensitivity and specificity of 73.5% and 82.3% respectively.

In this trial, MCG showed an accuracy of 94% for grouping patients into severe CAD (stenosis over 80% or FFR < 0.8), mild CAD (50-80% stenosis and FFR > 0.8), and no CAD groups across 133 patients. This study demonstrates MCG’s potential use as a stenosis stratification tool with high accuracy and a high negative predictive value of 93%.

This 200-patient cross-sectional study demonstrated a 90% accuracy (91% sensitivity and 88% specificity) for magnetocardiography (MCG) and machine learning versus a gold standard of percutaneous angiogra- phy for detecting significant CAD with stenosis over 50%. This study demonstrates the effective use of magnetocardiography early in the chest pain triage process to accurately rule-out CAD with high negative predictive value and accuracy.