Signal-averaged electrocardiogram. Improved identification of patients with ventricular tachycardia using a 28-lead optimal array

Performance comparison of 6 in-hospital patient monitoring systems in the detection and alarm of ventricular cardiac arrhythmias

Background

Patient monitoring devices are critical for alerting of potential cardiac arrhythmias during hospitalization; however, there are concerns of alarm fatigue due to high false alarm rates.

Objective

The purpose of this study was to evaluate the sensitivity and false alarm rate of hospital-based continuous electrocardiographic (ECG) monitoring technologies.

Methods

Six commonly used multiparameter bedside monitoring systems available in the United States were evaluated: B125M (GE HealthCare), ePM10 and iPM12 (Mindray), Efficia and IntelliVue (Philips), and Life Scope (Nihon Kohden). Sensitivity was tested using ECG recordings containing 57 true ventricular tachycardia (VT) events. False-positive rate testing used 205 patient-hours of ECG recordings containing no cardiac arrhythmias. Signals from ECG recordings were fed to devices simultaneously; high-severity arrhythmia alarms were tracked. Sensitivity to true VT events and false-positive rates were determined. Differences were assessed using Fisher exact tests (sensitivity) and Z-tests (false-positive rates).

Results

B125M raised 56 total alarms for 57 annotated VT events and had the highest sensitivity (98%; P <.05), followed by iPM12 (84%), Life Scope (81%), Efficia (79%), ePM10 (77%), and IntelliVue (75%). B125M raised 20 false alarms, which was significantly lower (P <.0001) than iPM12 (284), Life Scope (292), IntelliVue (304), ePM10 (324), and Efficia (493). The most common false alarm was VT, followed by nonsustained VT.

Conclusion

We found significant performance differences among multiparameter bedside ECG monitoring systems using previously collected recordings. B125M had the highest sensitivity in detecting true VT events and lowest false alarm rate. These results can assist in minimizing alarm fatigue and optimizing patient safety by careful selection of in-hospital continuous monitoring technology.

Mechanisms, prediction and treatment of ventricular tachyarrhythmias occurring late after myocardial infarction

Studies from the 1980s, refined in the intervening years, have examined the milieu for ventricular tachycardia (VT) and ventricular fibrillation (VF) occurring late after acute myocardial infarction (AMI). The arrhythmogenic substrate appears to be patchy areas of fibrous tissue interdigitating with viable bundles of myocardium which have distorted orientation and tortuous interconnections. These promote conduction delay in sinus rhythm. Factors found to promote induction of VT rather than VF are longer conduction delay in sinus rhythm, larger infarct size, a more ragged infarct edge and longer ventricular extrastimulus coupling intervals. Predictors of spontaneous VT and VF late after AMI include inducible VT at electrophysiological studies (EPS), delayed conduction in sinus rhythm detected as late potentials on signal-averaged surface electrocardiogram (ECG), and low left ventricular ejection fraction (LVEF). Treatments of propensity for VT or VF after AMI include insertion of a defibrillator (ICD), which has the best track record, antiarrhythmic medication (less reliable), and ablation or excision of arrhythmogenic substrate (for refractory VT and VF).

Late QRS activity in signal-averaged magnetocardiography, body surface potential mapping, and orthogonal ECG in postinfarction ventricular tachycardia patients

BACKGROUND

Delayed electrical activity necessary for re-entrant ventricular tachycardia (VT) is detectable noninvasively with high resolution techniques. We compared high resolution signal-averaged analysis of magnetocardiography (MCG), body surface potential mapping (BSPM), and orthogonal three-lead ECG (SA-ECG) in the identification of patients prone to VT after myocardial infarction (MI).

METHODS

Patients with remote myocardial infarction and cardiac dysfunction were studied, 22 with (VT group) and 22 without VT (control group). MCG with seven channels and BSPM with 63 and SA-ECG with three orthogonal leads were registered. After signal-averaging and highpass filtering, three time domain analysis (TDA) parameters describing late electrical activity were computed: QRS duration (QRSd), root mean square amplitude (RMS) of the last 40 ms of QRS, and the duration of the low-amplitude QRS end (LAS).

RESULTS

All parameters by each method were significantly different between the patients' groups. For example, LAS parameter in MCG was 59 (SD 22) ms in the VT group vs. 37 (SD 13) ms in controls (P < 0.001), 77 (SD 22) ms vs. 56 (SD 19) ms in BSPM (P = 0.002), and 60 (SD 24) ms vs. 39 (SD 22) ms in SA-ECG (P = 0.005). The combination of LAS parameter in MCG and SA-ECG resulted in improved performance in comparison to any single parameter with 95% sensitivity and 68% specificity.

CONCLUSIONS

All three high resolution methods identified VT propensity among post-MI patients with cardiac dysfunction and between-method differences were small. Information in MCG and SA-ECG may be complementary and their combination could be of value in postinfarction arrhythmia risk assessment.

Signal-averaged isoharmonic body surface maps of patients with ischemic cardiomyopathy

INTRODUCTION

Prevention of sudden arrhythmic cardiac death depends on accurate identification of individuals at high risk. Previous studies of signals recorded directly from arrhythmogenic tissue suggested that the predictive value of the signal-averaged ECG could be enhanced by expanded temporal, spectral, and spatial analysis. Accordingly, we performed a prospective study of 192-lead signal-averaged body surface maps from 43 patients with ischemic cardiomyopathy referred for electrophysiologic study. Three groups were included: 15 patients with clinical ventricular tachycardia (VT), 12 patients with inducible VT, and 16 patients with non-VT.

METHODS AND RESULTS

The patients were well matched with regard to age, gender, infarct location, ejection fraction (28% +/- 9%), QRS duration, and incidence of nonsustained VT (96%). Isoharmonic maps of the entire cardiac cycle were constructed for each patient. The peaks of the 1-7 Hz isoharmonic maps distinguished patients with clinical VT from non-VT and inducible VT patients (1,152 +/- 273, 852 +/- 283, and 808 +/- 272, respectively; P = 0.003). After prospective observation for 22 +/- 16 months, the combined endpoint of spontaneous sustained VT, ventricular fibrillation, appropriate defibrillator therapy, and death was predicted by inducibility of VT (relative risk 3.8, P = 0.008) and by the signal-averaged isoharmonic body surface map (relative risk 3.1, P = 0.02).

CONCLUSION

These results confirm the diagnostic utility of signal-averaged isoharmonic body surface maps in a rigorously defined patient population.

An approach to the detection of autonomic neuropathy by use of signal-averaged electrocardiography

The beat-to-beat variation of PR interval, which is thought to be a reflection of autonomic nervous system, is difficult to measure with accuracy because the variation is too subtle. However, R wave amplitude in the P wave triggered SAECG is easily attenuated in comparison to that in the R wave triggered SAECG, which might be due to PR interval fluctuation. To determine whether autonomic neuropathy could be detected by use of SAECG, two types of SAECGs triggered by P and R waves were recorded in 23 diabetics with autonomic neuropathy and 41 age matched controls. The peak voltage of filtered QRS complex was measured in the R wave and P wave triggered SAECGs. Percent attenuation of the filtered QRS voltage was calculated by dividing the difference between the voltages in the R wave and P wave triggered SAECGs by the voltage in R wave triggered SAECG. The percent attenuation of filtered QRS voltage was significantly smaller in diabetics with autonomic neuropathy than controls (4.6% +/- 4.9% vs 16.3% +/- 15.0%; P < 0.001). These results suggest that the degree of attenuation of filtered QRS voltage in the P wave triggered SAECG would be useful for the detection of autonomic neuropathy.

Behavior of late potentials on the body surface during programmed ventricular stimulation

OBJECTIVES

This study sought to evaluate the behavior of late potentials on the body surface by signal averaging during programmed stimulation and to correlate the findings with the cycle length of induced ventricular tachycardia.

BACKGROUND

Clinically relevant late potentials may be concealed within the QRS complex and may be missed by the conventional signal-averaged electrocardiogram (SAECG). In contrast, some late potentials may arise from dead-end pathways or pathways not capable of supporting sustained ventricular tachycardia (VT). It has been shown that durations of late potentials in sinus rhythm correlate poorly with VT cycle length.

METHODS

Signal-averaged electrocardiography during sinus rhythm, right ventricular pacing (S1) and introduction of a right ventricular extrastimulus (S2) was performed in 95 patients: 11 patients with a structurally normal heart and no inducible VT (Group I); 44 with a previous myocardial infarction (MI) and no inducible monomorphic VT (Group II); and 40 with a previous MI and inducible monomorphic VT (Group III).

RESULTS

The best subset of SAECG variables and the best cut points for each variable to differentiate between patients with and without VT were first established for each rhythm studied. Total duration of the filtered QRS complex (QRSD) was found to be the only independent predictor of inducibility of VT. When late potentials were defined for these criteria (QRSD > OR = 113, > or = 178 and > or = 168 ms for the SAECG during sinus rhythm, S1 and S2, respectively), there was no difference in the incidence of false positive (16% vs. 18%) or false negative (30% vs. 26%) late potentials between sinus rhythm and S1. During S2, there were significantly fewer false positive late potentials (11% vs. 16%) and fewer false negative late potentials (17% vs. 30%) than with sinus rhythm. Compared with sinus rhythm, 31% of the false positive late potentials detected during sinus rhythm were lost, whereas 43% of the false negative late potentials became detectable after S2, resulting in improved sensitivity (83% vs. 70%), specificity (89% vs. 84%) and predictive accuracy (86% vs. 77%, p < 0.05). Among the patients with VT, QRSD during S2 achieved the best correlation with VT cycle length (r = 0.74) and was the only independent predictor of VT cycle length when all SAECG variables were considered.

CONCLUSIONS

Late potentials revealed by ventricular extrastimuli but concealed during sinus rhythm may be clinically relevant and may explain some of the false negative late potentials and reduced sensitivity of the conventional SAECG in predicting VT. In contrast, those late potentials that are detected during sinus rhythm but lost after ventricular extrastimuli are often clinically irrelevant and may account for the false positive late potentials and reduced specificity of the conventional SAECG.

Clinical applications of body surface potential mapping

Accumulated evidence suggests that the electrocardiographic information provided by the standard 12-lead electrocardiogram can be improved by use of multilead electrocardiograms. The clinical utility of body surface potential mapping is related to the selective regional information provided by the increased number of leads. That clinical utility includes such things as improved localization of accessory pathways in preexcitation syndromes, improved localization of pacing sites within the ventricles, localization of late potentials, and improved recognition of acute myocardial ischemia. Recording equipment and interpretation schemes are available to make possible more widespread application of potential mapping.