Early Diagnosis of Defibrillation Lead Dislodgement

Abstract

Objectives: This study sought to develop and evaluate an algorithm for early diagnosis of dislodged implantable cardioverter-defibrillator (ICD) leads.

Background: Dislodged defibrillation leads may sense atrial and ventricular electrograms (EGMs), triggering shocks in the vulnerable period that induce ventricular fibrillation (VF).

Methods: We developed a 2-step algorithm by using experimental lead dislodgements (LDs) at ICD implantation and a control dataset of newly implanted, in situ leads. Step 1 consisted of an alert triggered by abrupt decrease in R-wave amplitude and increase in pacing threshold. Step 2 withheld therapy based on ventricular EGM evidence of LD identified from experimental LD behavior. We estimated the algorithm's performance using a registry dataset of 3,624 new implantations and an atrial dislodgement dataset of 14 LDs at the atrium.

Results: In the registry dataset, the algorithm identified 20 of 21 radiographic LDs (95%) at a median of 11 days before clinical diagnosis. Step 1 had positive predictive values of 57% for radiographic LD and 77% for surgical revision. The false positive rate was 0.4% after step 1 and ≤0.2% after step 2. In the atrial dislodgement dataset, step 1 identified all 14 LDs; step 2 would have prevented inappropriate therapy in all 7 patients with stored EGMs at LD, including 2 patients with fatal, shock-induced VF.

Conclusions: An ICD algorithm can facilitate early diagnosis of defibrillation LD. Additional data are needed to determine the safety of withholding shocks based on EGM evidence of LD.

Keywords: implantable cardioverter-defibrillator; lead dislodgement; lead displacement; lead migration.