Einthoven and electrical risk: Value of the electrocardiogram to predict sudden cardiac death

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The year was 1903, and Einthoven was a man well ahead of his time, but even he may not have realized the durable and lasting impact of his invention, the electrocardiogram (ECG). Over a century later, the ECG remains the most commonly utilized and broadly available cardiac test. The diagnostic utility of the ECG spans coronary disease manifestations, structural heart disease, conduction system disorders, and cardiac arrhythmias. As a noninvasive measure of global cardiac electrical activity, this tool has special utility for prediction of lethal ventricular arrhythmias and sudden cardiac death (SCD).
In this issue of the Journal, Toukola and co‐workers evaluated the potential significance of an abnormal ECG marker, fragmented QRS complex (fQRS), in the specific context of exercise‐related SCD.1 Even though the overall benefits of exercise are undeniable and exercise‐related SCD occurs in the small minority of patients,2 the paradox of transiently increased SCD risk during exercise is well documented. However, there are no methods of risk assessment that effectively identify high‐risk patients. From the analysis of archived resting 12‐lead ECGs obtained on 276 SCD patients, they report that fQRS in at least two consecutive anterior leads was significantly more common in exercise‐related SCD compared with both SCD at rest, and the general population. These are interesting findings, but there are some significant caveats that should be considered. The overall effect size of fQRS in the anterior leads on exercise‐related SCD risk, is modest. ECGs from witnessed SCD cases were only available in a small subgroup (7%) of the overall FinGesture cohort, resulting in a large amount of missing data and creating potential for selection bias. It would be critical to validate these findings in a separate population. The manifestation of fQRS on the ECG may indicate discontinuous electrical conduction in larger areas of diseased myocardium and fibrosis.3 However, a pathophysiological correlation with re‐entrant arrhythmias would, at a minimum, require cardiac magnetic resonance imaging to be performed in the same patients. Finally, it is relevant to put these findings in the context of the larger problem that still awaits a solution. How do we identify the overall population of patients at highest risk of SCD, and can the ECG play an important role?
For the familial arrhythmia syndromes such as long QT and Brugada, the ECG is the main avenue for establishing the diagnosis but also provides prognostic information. For example, the absolute value of the corrected QT interval (QTc) and the type of spontaneous Brugada pattern are linked to risk of future arrhythmia. However, for the more common forms of SCD manifestation due to coronary disease or cardiomyopathies, assessment of risk is complex since it often represents the end result of multiple myocardial remodeling processes working together.4 Different components of the surface ECG may potentially reflect distinct aspects of the SCD risk cascade. Therefore, a large body of investigative work has been dedicated to identification of potential markers from the ECG that may help identify the individual at highest risk of SCD. The current resurgence of interest in the ECG for this purpose is based on the diminishing returns from employing the left ventricular ejection fraction (LVEF) < 35% as the main clinically utilized predictor of SCD risk. Recent attempts to deploy combinations of a variety of clinical and plasma biomarkers as “SCD risk scores” have not gained traction since these appear to predict both SCD and overall cardiovascular mortality to equivalent extents. Today, the major gap in our knowledge vis a vis SCD risk stratification is the lack of predictors that will identify increased risk of sudden arrhythmic death.
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