Developing a Risk Model for In-Hospital Adverse Events Following Implantable Cardioverter-Defibrillator Implantation: A Report From the NCDR (National Cardiovascular Data Registry)

Objectives ter inform patients and physicians of the expected risk of adverse events and to assist hospitalsʹ 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. ound olong life in selected patients, but ICD implantation carries the risk of periprocedural complications. s lyzed 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. s l, 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). sions eloped 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.