Can QRS scoring predict left ventricular scar and clinical outcomes?

Rosengarten, James, Scott, Paul A., Chiu, OK, Shambrook, JS, Curzen, N. and Morgan, John M. (2013) Can QRS scoring predict left ventricular scar and clinical outcomes? Europace, 15 (7), 1034-1041. (doi:10.1093/europace/eut014). (PMID:23493411)

Abstract

AIMS: Identifying patients with potential to benefit from implantable cardioverter defibrillator (ICD) therapy is challenging. Myocardial scar detected using cardiovascular myocardial resonance imaging with late gadolinium enhancement (CMR-LGE) is associated with ventricular arrhythmia. Its use is constrained due to limited availability, unlike electrocardiogram (ECG) which is widely available. Selvester QRS scoring detects scar, although the reported performance varies. The study aims were to determine whether QRS score (a) detects scar (b) varies with scar characteristics, and (c) can meaningfully predict sudden cardiac death.

METHODS AND RESULTS:
We investigated 64 consecutive ICD recipients (age 66 ± 11 years, 80% male, median left ventricular ejection fraction 30%) with coronary artery disease who had undergone CMR-LGE prior to device implantation, over 4 years in a single centre (2006-2009). A modified QRS score was measured on the ECG performed prior to ICD implantation. Clinical end points were (i) appropriate ICD therapy and (ii) all cause mortality. QRS score was associated with CMR scar (r = 0.42, P = 0.001) and scar surface area (r = 0.41, P = 0.001), but not subendocardial scar. Strongest correlation was seen in those patients with transmural scar only (r = 0.62, P = 0.01). During 42 ± 13 months follow-up, QRS score was not predictive of appropriate ICD therapy, but was significantly related to all cause mortality (hazard ratio = 1.16; confidence interval = 1.03-1.30; P = 0.01).

CONCLUSION:
QRS scoring performed best in quantifying transmural scar, and shows association with medium-term mortality risk, but not with risk of ventricular arrhythmia. It may be that the score is best suited as a risk stratifier of those with least potential to benefit from ICD

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Contributors

Author: N. Curzen

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