Developing a Risk Model for In-Hospital Adverse Events Following Implantable Cardioverter-Defibrillator Implantation

作者：Dodson John A; Reynolds Matthew R; Bao Haikun; Al Khatib Sana M; Peterson Eric D; Kremers Mark S; Mirro Michael J; Curtis Jeptha P^*

来源：Journal of the American College of Cardiology, 2014, 63(8): 788-796.

DOI：10.1016/j.jacc.2013.09.079

• complication
• implantable cardioverter-defibrillator
• quality of care
• registry

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.

• 出版日期2014-3-4