br Signal averaged electrocardiography SAECG

Signal-averaged electrocardiography (SAECG) SAECG is a high-resolution electrocardiographic technique developed in the 1970s for detecting patients who are prone to SCD after MI. It is based on the theory that lethal ventricular arrhythmias leading to SCD often have a reentrant mechanism. Reentry requires a unidirectional block and conduction delay sufficient to recover excitability, and areas of delayed conduction within the infarcted ventricular myocardium can often be observed as low-amplitude, high-frequency potentials located in the late segment of the QRS complex by invasive EPSs (late potentials: LPs). However, LPs are obscured by noise in a standard body surface ECG because of their low amplitude. SAECG allows the detection of LPs by signal averaging, which improves the signal-to-noise ratio. In general, SAECG recordings are obtained from the Frank X, Y, and Z leads during sinus rhythm, and a total of 200–250 cycles are averaged to obtain a noise level of <0.2–0.4μV. The signals are amplified, digitized, averaged, and bidirectionally filtered with a band-pass filter at frequencies between 40 and 250Hz. The filtered QRS duration (f-QRS), root mean square voltage of the terminal 40ms of the filtered QRS complex (RMS40), and duration of low-amplitude signals of <40μV in the terminal filtered QRS complex (LAS40) are measured (Fig. 3). LPs are considered to be positive if two of the following criteria are met: (1) f-QRS>120ms, (2) RMS40<20μV, and (3) LAS40>38ms [36]. To date, previous studies have reported that abnormal SAECG is useful for identifying patients with VT after MI [37–39]. Gomes et al. evaluated 1925 patients with asymptomatic nonsustained VT, coronary artery disease, and left ventricular dysfunction in a multicenter trial. An f-QRS>114ms (abnormal SAECG) independently predicted arrhythmic death, cardiac arrest, and cardiac death, independent of clinical variables, cardioverter-defibrillator implantation, and antiarrhythmic drug therapy. The 5-year rates of arrhythmic death or cardiac arrest (28% versus 17%, P=0.0001), cardiac death (37% versus 25%, P=0.0001), and total mortality (43% versus 35%, P=0.0001) were significantly higher in patients with abnormal SAECG. They also assessed the prognostic utility of SAECG at different levels of LVEF. The results showed that the combination of an LVEF <30% and an abnormal SAECG identified a particularly high-risk subset. It was concluded that SAECG is a powerful predictor of poor outcomes, and the noninvasive combination of an abnormal SAECG and a reduced LVEF may help identify high-risk patients [39]. Many studies on LPs in MI patients were conducted before the reperfusion era [1–3]. Some investigators suggested that LPs are less common among patients after thrombolysis and percutaneous coronary intervention, and they limit the utility of SAECG for arrhythmia risk Dihydrodaidzein [40–43]. In addition, Ikeda et al. suggested that LPs were independent predictors of sustained VT after MI but had no significant prognostic role in predicting SCD or resuscitated cardiac arrest [44]. Furthermore, we previously investigated the prevalence of LPs in patients with VT and VF after MI. The positive rate of LPs was 92% in VT patients and 50% in VF patients [45]. LPs may reflect an arrhythmogenic substrate, which is responsible for macroreentrant VT and is not useful for prediction of VF. Besides, LPs are more common in patients with inferior infarction than in those with anterior infarction. This may be because peri-infarct tissue in an anterior infarction is activated during the early phase of ventricular activation, and delayed potential may be hidden within the QRS complex. At present, routine use of SAECG for identifying patients at high risk of SCD is not adequately recommended [35].
Heart rate variability (HRV) HRV is a physiological phenomenon of beat-to-beat variation in cardiac cycle length, which is influenced by autonomic tone. Depressed HRV reflects autonomic disturbances, which may increase the risk of lethal ventricular arrhythmias. In 1987, Kleiger et al. analyzed HRV in 808 patients with MI. They found that HRV was the strongest univariate predictor of mortality. The relative risk of mortality was 5.3 times higher in the group with HRV <50ms than in the group with HRV >100ms. HRV remained a significant predictor of mortality even after adjusting for clinical, demographic, and other Holter features and ejection fraction [8]. Since then, HRV has been widely investigated and has subsequently been well established as a risk factor for poor clinical outcome in MI patients. Autonomic Tone and Reflexes After Myocardial Infarction investigators evaluated the prognostic value of HRV in post-MI patients. They found that patients with low standard deviation of normal-to-normal relative risk (RR) intervals (SDNN) and LVEF <35% carried an RR of 6.7 (95% confidence interval [CI], 3.1–14.6) compared with patients with LVEF >35% and less compromised SDNN (≥70ms) [10]. Zuanetti et al. assessed the prognostic value of HRV for total and cardiovascular mortality in the fibrinolytic era. All indexes of low HRV could identify patients with a higher total mortality, and the independent predictive value of low HRV was confirmed by the adjusted analysis [9]. Camm et al. evaluated HRV in 3717 post-MI patients with left ventricular dysfunction. In their cohort, patients with low HRV had a significantly higher 1-year mortality than did those with high HRV (15% versus 9.5%, P<0.0005), despite nearly identical LVEF values [46]. They concluded that low HRV independently identified a subpopulation at high risk of mortality. Depressed HRV is currently considered a strong predictor of mortality and lethal ventricular arrhythmias in post-MI patients, but the evidence is lacking. Currently, HRV is recommended as a Class IIb, Level of Evidence B risk-stratification tool among post-MI patients [35]. Further studies are needed to establish its role in risk stratification.