A Summary of the AHA/ACC/HRS Scientific Statement on Noninvasive Risk Stratification Techniques for Identifying Patients at Risk for Sudden Cardiac Death

A scientific statement on the findings for use of noninvasive risk stratification techniques for identifying patients at risk for sudden cardiac death (SCD) was recently published.¹ Sudden cardiac death has been defined as a death due to cardiovascular causes, within an hour after symptom onset, and occurring outside the hospital, in the emergency room, or as a DOA at hospital arrival. A variety of risk stratification techniques have been developed over the past 30 years with the goal of trying to predict which patients are more likely to develop SCD. The techniques generally focus on prediction of reversible ventricular arrhythmias. The risk stratification techniques reviewed for this scientific statement focused on ischemic, dilated and hypertrophic cardiomyopathies. The goal of the noninvasive approaches has been to focus on a factor known to be a trigger for ventricular tachycardia (VT) or ventricular fibrillation (VF), and attempt to determine its presence. The categories that have evolved include tests that detect: ¹ 1) Slowed conduction; this includes measurement of the QRS duration and the signal-averaged ECG (SAECG); 2) Heterogeneities in ventricular repolarization; these include QT interval, QT dispersion, and T-wave alternans; 3) Imbalance in autonomic tone; these include heart rate variability, heart rate turbulence, heart rate recovery after exercise, and baroreceptor sensitivity; 4) Extent of myocardial damage and scar formation; this would include left ventricular ejection fraction and the six-minute walk; 5) Ventricular ectopy; this includes long-term ambulatory monitoring. The following is a brief description of the techniques that were reviewed for this scientific statement.

Noninvasive Risk-Stratification Techniques

Left Ventricular Ejection Fraction (LVEF). This may be assessed by radionuclide and radiographic contrast ventriculography or by 2-D echocardiography. ¹ The testing is fairly easy to achieve. This is the most consistently reported risk factor associated with overall mortality and SCD in the heart failure population. ¹ QRS Duration. This is a measurement of the QRS width on the electrocardiogram and represents conduction delay in the ventricles. QT Interval and QT Dispersion. The QT interval is a measure of ventricular action potential durations; the QT interval shortens with an increased heart rate. The QT is shorter in men than in women.1 QT measurement may be problematic as it varies in different leads. QT dispersion is the measured difference between the longest and shortest QT on the ECG. QT dispersion is believed to reflect dispersion of myocardial recovery. ¹ Signal-Averaged ECG. Delayed or prolonged activation of portions of the ventricle may be detected through use of signal-averaging. This technique detects late potentials, or low-amplitude signals found at the end of the QRS. Late potentials may represent a substrate for reentry or the earliest activation during VT. Short-Term HRV. Heart rate variability analysis is a way to evaluate autonomic nervous system modulation of the SA node, with inference of autonomic activity to the rest of the heart. It has been proposed that the analysis of HRV, especially the parasympathetic effects on the SA node, may be used to help predict mortality. ¹ Ventricular Ectopy and NSVT. For the post-MI patient, ventricular ectopy and nonsustained VT on Holter monitoring have been associated with increased risk for SCD. Long-Term HRV. This is the assessment of HRV through Holter monitoring. HRV measurement by this method has revealed that HRV may be a better marker of nonarrhythmic mortality. Heart Rate Turbulence. This technique measures the short-term fluctuation in sinus cycle length that follows a PVC. The mechanism of this finding is not known, but is believed to be a measure of vagal responsiveness, much like baroreflex sensitivity. ¹ Exercise Capacity and NYHA Class. The presence of heart failure is known to contribute to arrhythmogenesis and increase the risk of SCD. Heart Rate Recovery and Recovery Ventricular Ectopy. A delayed return to baseline heart rates post exercise testing suggests impaired parasympathetic tone and increased risk of death. Frequent or severe ventricular ectopy for the first five minutes post exercise test was found to be related to increased risk of death. ¹ T-Wave Alternans. This reflects repolarization alternans at a cellular level and is thought to occur when the heart rate exceeds the ability of cardiac cells to cycle intracellular calcium. This phenomenon occurs at relatively lower rates in patients susceptible to ventricular arrhythmias. ¹ Baroreceptor Sensitivity (BRS). This is the adaptation of R-R intervals to changes in blood pressure. ¹ Phenylephrine bolus is used to assess BRS.

Evaluation of Hypertrophic Cardiomyopathy

HCM is a genetic disease that is considered the most common cause of SCD in both the young and in competitive athletes. The testing recommended for risk stratification in this group is the ECG, ambulatory ECG, treadmill or bicycle testing, and 2-D ECHO, in addition to obtaining a personal and family history. ¹

Issues Related to Risk Stratification

Some important issues were identified related to the whole practice of risk stratification. First, the goal for each patient should be identified. Second, the timing of the evaluation may be crucial. It is known that there is a heightened mortality risk the first several months postinfarction. ¹ The approach to testing the post-MI patient needs to be examined. Third, there are no data to determine what specifically is considered optimum testing. The study group identified a need for further development in risk stratification. They also recommended the incorporation of newer approaches, such as genetic testing, serum markers, and new imaging techniques, into the process. In addition, it is believed probable that multiple tests would ultimately need to be incorporated into a risk stratification strategy. ¹

Conclusion

The data that has emerged from the research into the prediction of events with these techniques has failed to reveal what exactly precipitates SCD events. More research into the combination of factors that lead to SCD was recommended. The opportunities for research are vast.

For more information, please visit: https://circ.ahajournals.org/cgi/content/full/118/14/1497#SEC8