Surface Electrocardiogram Predictors of Sudden Cardiac Arrest
Samy A Abdelghani1, Todd M Rosenthal1, Daniel P Morin2
1Department of Cardiology, Ochsner Clinic Foundation, New Orleans, LA.
Insights
Identifying patients at risk for sudden cardiac arrest (SCA) is crucial. Current electrocardiogram (ECG) predictors show variable effectiveness, necessitating multifactorial risk assessment for SCA.
Area of Science:
- Cardiology
- Medical Diagnostics
Background:
- Sudden cardiac arrest (SCA) accounts for approximately 50% of heart disease deaths in industrialized nations.
- Identifying high-risk patients enables prophylactic interventions like implantable cardioverter defibrillators to improve survival.
- Surface electrocardiogram (ECG) predictors are key to noninvasive risk stratification.
Purpose of the Study:
- To review current knowledge on surface ECG predictors for sudden cardiac arrest.
- To evaluate the effectiveness of various noninvasive electrocardiographic methods in predicting SCA risk.
Main Methods:
- Literature review of noninvasive electrocardiographic testing methods for SCA prediction.
- Analysis of studies examining ECG parameters for sudden cardiac arrest risk stratification.
Main Results:
- Several ECG parameters studied include QT prolongation, QRS duration, fragmented QRS, early repolarization, Holter monitoring, heart rate variability, heart rate turbulence, signal-averaged ECG, T wave alternans, and T-peak to T-end.
- These individual ECG findings demonstrated variable effectiveness as screening tools for SCA.
Conclusions:
- No single ECG finding adequately stratifies patients for sudden cardiac arrest risk.
- Future risk stratification may involve combining multiple ECG parameters into multifactorial calculators.
Background:
Heart disease is a major cause of death in industrialized nations, with approximately 50% of these deaths attributable to sudden cardiac arrest. If patients at high risk for sudden cardiac arrest can be identified, their odds of surviving fatal arrhythmias can be significantly improved through prophylactic implantable cardioverter defibrillator placement. This review summarizes the current knowledge pertaining to surface electrocardiogram (ECG) predictors of sudden cardiac arrest.
Methods:
We conducted a literature review focused on methods of predicting sudden cardiac arrest through noninvasive electrocardiographic testing.
Results:
Several electrocardiographic-based methods of risk stratification of sudden cardiac arrest have been studied, including QT prolongation, QRS duration, fragmented QRS complexes, early repolarization, Holter monitoring, heart rate variability, heart rate turbulence, signal-averaged ECG, T wave alternans, and T-peak to T-end. These ECG findings have shown variable effectiveness as screening tools.
Conclusion:
At this time, no individual ECG finding has been found to be able to adequately stratify patients with regard to risk for sudden cardiac arrest. However, one or more of these candidate surface ECG parameters may become useful components of future multifactorial risk stratification calculators.
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