Developing a risk model for in-hospital adverse events following implantable cardioverter-defibrillator implantation: a report from the NCDR (National Cardiovascular Data Registry).

Journal Article (Journal Article)

OBJECTIVES: To better inform patients and physicians of the expected risk of adverse events and to assist hospitals' efforts to improve the outcomes of patients undergoing implantable cardioverter-defibrillator (ICD) implantation, we developed and validated a risk model using data from the NCDR (National Cardiovascular Data Registry) ICD Registry. BACKGROUND: ICD prolong life in selected patients, but ICD implantation carries the risk of periprocedural complications. METHODS: We analyzed data from 240,632 ICD implantation procedures between April 1, 2010, and December 31, 2011 in the registry. The study group was divided into a derivation (70%) and a validation (30%) cohort. Multivariable logistic regression was used to identify factors associated with in-hospital adverse events (complications or mortality). A parsimonious risk score was developed on the basis of beta estimates derived from the logistic model. Hierarchical models were then used to calculate risk-standardized complication rates to account for differences in case mix and procedural volume. RESULTS: Overall, 4,388 patients (1.8%) experienced at least 1 in-hospital complication or death. Thirteen factors were independently associated with an increased risk of adverse outcomes. Model performance was similar in the derivation and validation cohorts (C-statistics = 0.724 and 0.719, respectively). The risk score characterized patients into low- and-high risk subgroups for adverse events (≤10 points, 0.3%; ≥30 points, 4.2%). The risk-standardized complication rates varied significantly across hospitals (median: 1.77, interquartile range 1.54, 2.14, 5th/95th percentiles: 1.16/3.15). CONCLUSIONS: We developed a simple model that predicts risk for in-hospital adverse events among patients undergoing ICD placement. This can be used for shared decision making and to benchmark hospital performance.

Full Text

Duke Authors

Cited Authors

  • Dodson, JA; Reynolds, MR; Bao, H; Al-Khatib, SM; Peterson, ED; Kremers, MS; Mirro, MJ; Curtis, JP; NCDR,

Published Date

  • March 4, 2014

Published In

Volume / Issue

  • 63 / 8

Start / End Page

  • 788 - 796

PubMed ID

  • 24333491

Pubmed Central ID

  • PMC3954985

Electronic International Standard Serial Number (EISSN)

  • 1558-3597

Digital Object Identifier (DOI)

  • 10.1016/j.jacc.2013.09.079


  • eng

Conference Location

  • United States