Electrocardiographic abnormalities in epilepsy: analysis of cardiac conduction patterns and SUDEP Risk
Noheir Ashraf Ibrahem Fathy Hassan1, Eman A Toraih2,3, Mohab Orz4
1Aswan Faculty of Medicine, Aswan, Egypt.
Summary
Epilepsy patients show higher rates of cardiac electrical abnormalities like QRS axis deviation and T wave changes. While these findings suggest electrophysiological instability, they are not yet validated biomarkers for sudden unexpected death in epilepsy (SUDEP).
Area of Science:
- Cardiology
- Neurology
- Medical Statistics
Background:
- Electrocardiographic (ECG) abnormalities are potential contributors to sudden unexpected death in epilepsy (SUDEP).
- Understanding the prevalence and patterns of ECG abnormalities in epilepsy is crucial for risk assessment.
Purpose of the Study:
- To systematically review and meta-analyze the prevalence of ECG abnormalities in epilepsy patients.
- To investigate age-specific patterns and the association of these abnormalities with mortality risk.
Main Methods:
- A systematic literature search adhering to PRISMA guidelines was conducted through September 2024.
- Eleven studies involving 2,775 epilepsy patients and 2,751 controls were analyzed using random-effects models.
- Age-stratified and mortality analyses were performed to assess specific risk factors.
Main Results:
- QRS axis deviation (23.1% vs 3.2%) and T wave abnormalities (31.2% vs 5.0%) were significantly more prevalent in epilepsy patients.
- ST segment changes showed a 3.6-fold increased risk (RR: 3.55).
- Prolonged QTc was more common in adults (13.5%) than pediatric patients (2.4%), with no significant mortality differences observed in basic ECG parameters.
Conclusions:
- Epilepsy patients exhibit distinct cardiac electrical abnormalities, particularly in conduction axis and repolarization.
- These findings indicate potential electrophysiological instability but require prospective validation as SUDEP biomarkers.
- Clinical implementation necessitates rigorous validation due to substantial heterogeneity in retrospective data.
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