Does the abnormal signal-averaged electrocardiogram predict future appropriate therapy in patients with implantable cardioverter-defibrillators?
BACKGROUND
Several studies have documented the prognostic significance of the signal-averaged electrocardiogram (SAECG) both after myocardial infarction and nonischemic cardiomyopathy. However, whether the SAECG can identify patients with implantable cardioverter-defibrillator (ICD) who receive appropriate therapy has not been hitherto completely investigated.


METHODS
Between August 2002 and August 2004, 83 consecutive ICD patients who had had SAECGs recorded were enrolled in this study. All patients were followed up in the outpatient ICD clinic, and interrogated electrograms were collected.


RESULTS
Over 9.0 +/- 2.8 months of follow-up, 27 (32%) patients had appropriate ICD therapy for ventricular tachycardia or fibrillation; 15 (55.6%) patients had abnormal; and the remaining 12 (44.4%) had normal SAECGs. Of the 56 patients with no appropriate therapy, 27 (48.2%) and 29 (51.8%) patients had abnormal and normal SAECGs, respectively. There were no statistically significant differences between the 2 groups in SAECG findings (P = .41). A Cox regression analysis showed that the left ventricular ejection fraction was the only predictor of appropriate therapy (P = .02). Subgroup analysis of the patients with coronary artery disease and spontaneous monomorphic ventricular tachycardia indicated that left ventricular ejection fraction (P = .03) and abnormal SAECG (P = .02) were predictors of appropriate therapy.


CONCLUSIONS
Our data demonstrate that except for the subgroup of patients with coronary artery disease presenting with monomorphic ventricular tachycardia, the SAECG did not predict ventricular tachyarrhythmia recurrence and, hence, appropriate ICD therapy. Thus, SAECG findings should generally not be a factor in decision for ICD implantation.
Haghjoo
Majid
M
Department of Pacemaker and Electrophysiology, Rajaie Cardiovascular Medical and Research Center, School of Medicine, Iran University of Medical Sciences, P.O. Box 15745-1341, Tehran 1996911151, Iran. majid.haghjoo@gmail.com
Arya
Arash
A
Parsaie
Mozhgan
M
Dehghani
Mohammad Reza
MR
Sadr-Ameli
Mohammad Ali
MA
D000328:Adult; D000368:Aged; D016009:Chi-Square Distribution; D003327:Coronary Disease / Q000503:physiopathology* / Q000628:therapy*; D017147:Defibrillators, Implantable; D004562:Electrocardiography; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011379:Prognosis; D016016:Proportional Hazards Models; D012815:Signal Processing, Computer-Assisted