Predicting appropriate shocks in patients with heart failure: Patient level meta-analysis from SCD-HeFT and MADIT II.
BACKGROUND: No precise tools exist to predict appropriate shocks in patients with a primary prevention ICD. We sought to identify characteristics predictive of appropriate shocks in patients with a primary prevention implantable cardioverter defibrillator (ICD). METHODS: Using patient-level data from the Multicenter Automatic Defibrillator Implantation Trial II (MADIT II) and the Sudden Cardiac Death in Heart Failure Trial (SCD-HeFT), we identified patients with any appropriate shock. Clinical and demographic variables were included in a logistic regression model to predict appropriate shocks. RESULTS: There were 1,463 patients randomized to an ICD, and 285 (19%) had ≥1 appropriate shock over a median follow-up of 2.59 years. Compared with patients without appropriate ICD shocks, patients who received any appropriate shock tended to have more severe heart failure. In a multiple logistic regression model, predictors of appropriate shocks included NYHA class (NYHA II vs. I: OR 1.65, 95% CI 1.07-2.55; NYHA III vs. I: OR 1.74, 95% CI 1.10-2.76), lower LVEF (per 1% change) (OR 1.04, 95% CI 1.02-1.06), absence of beta-blocker therapy (OR 1.61, 95% CI 1.23-2.12), and single chamber ICD (OR 1.67, 95% CI 1.13-2.45). CONCLUSION: In this meta-analysis of patient level data from MADIT-II and SCD-HeFT, higher NYHA class, lower LVEF, no beta-blocker therapy, and single chamber ICD (vs. dual chamber) were significant predictors of appropriate shocks.
- Al-Khatib, Sana Mustapha
- Friedman, Daniel
- Lee, Kerry L.
- Mark, Daniel Benjamin
- Schmidler, Gillian Denise Sanders
- Zeitler, EP; Al-Khatib, SM; Friedman, DJ; Han, JY; Poole, JE; Bardy, GH; Bigger, JT; Buxton, AE; Moss, AJ; Lee, KL; Dorian, P; Cappato, R; Kadish, AH; Kudenchuk, PJ; Mark, DB; Inoue, LYT; Sanders, GD
- November 2017
Volume / Issue
- 28 / 11
Start / End Page
- 1345 - 1351
Pubmed Central ID
Electronic International Standard Serial Number (EISSN)
Digital Object Identifier (DOI)
- United States