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Published on: May 28, 2019
Automatic electrocardiographic algorithm for assessing severity of ischemia in ST-segment elevation myocardial
Yama Fakhri1, Jacob Melgaard2, Hedvig Bille Andersson3
1Department of Cardiology, The Heart Centre, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark; Department of Medicine, Nykøbing Falster Hospital, Nykøbing F, Denmark.
Insights
An automated electrocardiogram (ECG) algorithm accurately identifies severe ischemia in ST-elevation myocardial infarction (STEMI) patients. This tool correlates ECG findings with larger infarct sizes, aiding clinical practice.
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.
Background:
Terminal QRS distortion on the electrocardiogram (ECG) is a sign of severe ischemia in patients with STEMI and can be quantified by the Sclarovsky-Birnbaum Severity of Ischemia. Due to score complexity, it has not been applied in clinical practice. Automatic scoring of digitally recorded ECGs could facilitate clinical application. We aimed to develop an automatic algorithm for the severity of ischemia.
Methods:
Development set: 50 STEMI ECGs were manually (Manual-score) and automatically (Auto-score) scored by our designed algorithm. The agreement between Manual- and Auto-score was assessed by kappa statistics. Test set: ECGs from 199 STEMI patients were assigned a severity grade (severe or non-severe ischemia) by the Auto-score. Infarct size estimated by median peak Troponin T (TnT) and Creatinine Kinase Myocardial Band (CKMB) was tested between the groups.
Results:
The agreement between Manual- and Auto-score was 0.83 ((95% CI 0.55-1.00), p < 0.0001), sensitivity 75% and specificity 100%, PPV 100% and NPV 94.6%. In the test set 152 (76%) patients were male, mean age 61 ± 12 years. The Auto-score designated severe ischemia in 42 (21%) and non-severe ischemia in 157 (79%) patients. Patients with ECG signs of severe vs. non-severe ischemia had significantly higher levels of biomarkers of infarct size. In multiple linear regression, ECG sign of severe ischemia was an independent predictor for higher TnT and CKMB levels.
Conclusion:
The automatic ECG algorithm for severity of ischemia in STEMI performs adequately for clinical use. Severe ischemia obtained by the Auto-score was associated with biomarker estimated larger infarct size.
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