Risk Factors for Infections Involving Cardiac Implanted Electronic Devices

BACKGROUND Cardiac implantable electronic device infection is a major complication that usually requires device removal. PADIT (Prevention of Arrhythmia Device Infection Trial) was a large cluster crossover trial of conventional versus incremental antibiotics. OBJECTIVES This study sought to investigate independent predictors of device infection in PADIT and develop a novel infection risk score. METHODS In brief, over 4 6-month periods, 28 centers used either conventional or incremental prophylactic antibiotic treatment in all patients. The primary outcome was hospitalization for device infection within 1 year (blinded endpoint adjudication). Multivariable logistic prediction modeling was used to identify the independent predictors and develop a risk score for device infection. The prediction models were internally validated with bootstrap methods. RESULTS Device procedures were performed in 19,603 patients, and hospitalization for infection occurred in 177 (0.90%) within 1 year of follow-up. The final prediction model identified 5 independent predictors of device infection (prior procedures [P], age [A], depressed renal function [D], immunocompromised [I], and procedure type [T]) with an optimism-corrected C-statistic of 0.704 (95% confidence interval: 0.660 to 0.744). A PADIT risk score ranging from 0 to 15 points classified patients into low (0 to 4), intermediate (5 to 6) and high (>= 7) risk groups with rates of hospitalization for infection of 0.51%, 1.42%, and 3.41%, respectively. CONCLUSIONS This study identified 5 independent predictors of device infection and developed a novel infection risk score in the largest cardiac implantable electronic device trial to date, warranting validation in an independent cohort. The 5 independent predictors in the PADIT score are readily adopted into clinical practice. (C) 2019 Published by Elsevier on behalf of the American College of Cardiology Foundation.