Proposal for a Novel Score to Determine the Risk of Cardiac Implantable Electronic Device Infection.

INTRODUCTION AND

OBJECTIVES

The use of cardiac implantable electronic devices (CIEDs) has expanded in recent years. Infection related to these devices constitutes one of the main complications and is associated with high morbidity, mortality, and financial cost. The aim of this study was to construct a predictive risk score of acquiring CIED infection.

METHODS

We designed a retrospective, nested case-control study. Both cases and controls belonged to a cohort that included all patients who underwent a CIED-related procedure between January 2009 and December 2015. Cases were defined as patients with infection, and 3 infection-free controls were randomly selected from the cohort for each case included.

RESULTS

During the study period, 2323 procedures were performed. A total of 33 CIED-related infections were identified. Ninety-nine patients were selected as controls. Independent risk factors were the Charlson index (OR, 1.33; 95%CI, 1.07-1.67), oral anticoagulation (OR, 3.51; 95%CI, 1.44-8.54), revision or replacement of a previous device (OR, 2.75; 95%CI, 1.12-6.71) and the presence of more than 2 leads (OR, 3.42; 95%CI, 1.25-9.37). A predictive risk score was generated and denominated CIED-AI (Charlson Index, more than 2 leads/Electrodes, Device revision/replacement, oral Anticoagulation, previous Infection). This score had an area under the receiver operating characteristic curve of 0.79 (95%CI, 0.71-0.88).

CONCLUSIONS

The CIED-AI score may help to identify patients at higher risk of infection, who could be candidates for intensive preventive measures.