Luis Martin Moltrasio
Instituto Cordis, Argentina
Title: CIED (Cardiac implantable Electronic Device)-related endocarditis. Diagnostic/treatment algorithm proposal in a limited resources setting
Biography
Biography: Luis Martin Moltrasio
Abstract
CIED-related endocarditis refers to infection involving the transvenous portion of the lead (with involvement of the contiguous endocardium or tricuspid valve). CIED systemic infection can occur with or without involvement of the generator pocket. Patients with systemic infection generally have positive blood cultures and/or vegetation on TEE. This infection primarily involve the intracardiac portion of the lead and essentially represent a right-sided endocarditis. The approach to evaluation of suspected CIED-related endocarditis is summarized in various algorithms and includes, clinical presentations, blood cultures and echocardiography.
The limitations of TEE for discriminating between infectious lead vegetations and thrombus were demonstrated, infectious and noninfectious echodensities did not differ in their echocardiographic characteristics.
In general, successful management of CIED-related endocarditis requires an antibiotic therapy and explantation of the entire CIED (leads, including residual leads that are non-functional, and pulse generator). For patients with echocardiography demonstrating a valve or lead vegetation, without definitive diagnostic of endocarditis, in general physicians favor presumptive treatment for endocarditis, but antimicrobial treatment up to four weeks without device removal has a very low chance of success and raise antimicrobial resistance. Otherwise device removal without a define endocarditis, in a low resources setting is associated, due our experience, with increased morbimortality.
In many cases with suspected infection, fluorine-18 fluorodeoxyglucose positron emission tomography computed tomography (18F-FDG-PET/CT) scanning may be helpful to define, however such diagnostic test, involves transfers of more than one thousand kilometers in our region. Our team have developed an evidence and experience based algorithm to try to resolve these problems in a low resource setting.