Title

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

Document Type

Article

Publication Date

3-2014

Abstract

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.