Automated Quantification of Low-Amplitude Abnormal QRS Peaks From High-Resolution ECG Recordings Predicts Arrhythmic Events in Patients With Cardiomyopathy

Background— Cardiomyopathy patients are at risk of sudden death, typically from scar-related abnormalities of electrical activation that promote ventricular tachyarrhythmias. Abnormal intra-QRS peaks may provide a measure of altered activation. We hypothesized that quantification of such QRS peaks (QRSp) in high-resolution ECGs would predict arrhythmic events in implantable cardioverter–defibrillator (ICD)–eligible cardiomyopathy patients. Methods and Results— Ninety-nine patients with ischemic or non-ischemic dilated cardiomyopathy undergoing prophylactic ICD implantation were prospectively enrolled (age 62±11 years, left ventricular ejection fraction 27±7%). High-resolution (1024 Hz) digital 12-lead ECGs were recorded during intrinsic rhythm. QRSp was quantified for each precordial lead as the total number of low-amplitude deflections that deviated from their respective naive QRS template. The primary end point of arrhythmic events was defined as appropriate ICD therapy or sustained ventricular tachyarrhythmias. After a median follow-up of 24 (15–43) months, 20 (20%) patients had arrhythmic events. Both QRSp and QRS duration were greater in those with arrhythmic events (both P <0.001) and this was consistent for QRSp for both cardiomyopathy types. In a multivariable Cox regression model that included age, left ventricular ejection fraction, QRS duration, and QRSp, only QRSp was an independent predictor of arrhythmic events (hazard ratio, 2.1; P <0.001). Receiver operating characteristic analysis revealed that a QRSp ≥2.25 identified arrhythmic events with greater sensitivity (100% versus 70%, P <0.05) and negative predictive value (100% versus 89%, P <0.05) than QRS duration ≥120 ms. Conclusions— QRSp measured from high-resolution digital 12-lead ECGs independently predicts ventricular tachyarrhythmias in ICD-eligible cardiomyopathy patients. This novel QRS morphology index has the potential to improve sudden death risk stratification and patient selection for prophylactic ICD therapy.