An ECG index of myocardial scar enhances prediction of defibrillator shocks: an analysis of the Sudden Cardiac Death in Heart Failure Trial.

Journal Article (Journal Article)

BACKGROUND: Only a minority of patients receiving implantable cardioverter-defibrillators (ICDs) for the primary prevention of sudden death receive appropriate shocks, yet almost as many are subjected to inappropriate shocks and device complications. Identifying and quantifying myocardial scar, which forms the substrate for ventricular tachyarrhythmias, may improve risk stratification. OBJECTIVE: This study sought to determine whether the absence of myocardial scar detected by novel 12-lead electrocardiographic (ECG) Selvester QRS scoring criteria identifies patients with low risk for appropriate ICD shocks. METHODS: We applied QRS scoring to 797 patients from the ICD arm of the Sudden Cardiac Death in Heart Failure Trial. Patients were followed up for a median of 45.5 months for ventricular tachycardia/fibrillation treated by the ICD or sudden tachyarrhythmic death (combined group referred to as VT/VF). RESULTS: Increasing QRS score scar size predicted higher rates of VT/VF. Patients with no scar (QRS score = 0) represented a particularly low-risk cohort with 48% fewer VT/VF events than the rest of the population (absolute difference 11%; hazard ratio 0.52, 95% confidence interval 0.31 to 0.88). QRS score scar absence versus presence remained a significant prognostic factor after controlling for 10 clinically relevant variables. Combining QRS score (scar absence versus presence) with ejection fraction (≥ 25% versus < 25%) distinguished low-, middle-, and high-risk subgroups with 73% fewer VT/VF events in the low-risk versus high-risk group (absolute difference 22%; hazard ratio = 0.27, 95% confidence interval 0.12 to 0.62). CONCLUSION: Patients with no scar by QRS scoring have significantly fewer VT/VF events. This inexpensive 12-lead ECG tool provides unique, incremental prognostic information and should be considered in risk-stratifying algorithms for selecting patients for ICDs.

Full Text

Duke Authors

Cited Authors

  • Strauss, DG; Poole, JE; Wagner, GS; Selvester, RH; Miller, JM; Anderson, J; Johnson, G; McNulty, SE; Mark, DB; Lee, KL; Bardy, GH; Wu, KC

Published Date

  • January 2011

Published In

Volume / Issue

  • 8 / 1

Start / End Page

  • 38 - 45

PubMed ID

  • 20884379

Pubmed Central ID

  • PMC3010478

Electronic International Standard Serial Number (EISSN)

  • 1556-3871

Digital Object Identifier (DOI)

  • 10.1016/j.hrthm.2010.09.071


  • eng

Conference Location

  • United States