Related Experiment Video
Updated: Feb 6, 2026

FISH for Pre-implantation Genetic Diagnosis
Published on: February 23, 2011
Early Diagnosis of Defibrillation Lead Dislodgement
Junaid A B Zaman1, Kelvin Chua1, Ali A Sovari1
1Cardiac Electrophysiology, Cedars-Sinai Heart Center, Cedars-Sinai Medical Center, Los Angeles California.
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.
Related Concept Videos
Nursing Diagnosis
The nursing diagnosis focuses on evidence-based...
Phase-lead and Phase-lag Controllers
Formulating and Validating Nursing Diagnosis I
There are thirteen domains...
Documentation of Nursing Diagnosis
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters...
Formulating and Validating Nursing Diagnosis II
Risk nursing diagnoses represent clinical judgments of an individual, family, or community more vulnerable to developing the health problem than others...
Diabetes: Symptoms, Diagnosis, and Complications

