Automatic electrocardiographic algorithm for assessing severity of ischemia in ST-segment elevation myocardial...

Area of Science:

• Cardiology
• Medical Technology
• Biomedical Engineering

Background:

• Terminal QRS distortion on ECGs indicates severe ischemia in STEMI patients.
• The Sclarovsky-Birnbaum Severity of Ischemia score is complex and not widely used clinically.
• Automating ECG scoring can improve the clinical application of ischemia severity assessment.

Purpose of the Study:

• To develop an automatic algorithm for quantifying ischemia severity using ECGs in STEMI patients.
• To validate the performance of the automatic scoring algorithm against manual scoring.
• To assess the correlation between automatically determined ischemia severity and infarct size biomarkers.

Main Methods:

• A development set of 50 STEMI ECGs was scored manually and by the developed algorithm.
• Agreement between manual and automatic scores was evaluated using kappa statistics.
• A test set of 199 STEMI ECGs was analyzed by the algorithm, and results were compared with Troponin T and CKMB levels.

Main Results:

• The automatic algorithm showed strong agreement (kappa=0.83) with manual scoring, with high sensitivity and specificity.
• The algorithm classified 21% of STEMI patients as having severe ischemia.
• Patients with severe ischemia identified by the algorithm had significantly higher Troponin T and CKMB levels, indicating larger infarct size.

Conclusions:

• The developed automatic ECG algorithm is suitable for clinical use in assessing ischemia severity in STEMI.
• Automatic scoring of ECGs for ischemia severity is associated with larger infarct sizes, as estimated by biomarkers.