Performance of an ICD algorithm to detect lead noise and reduce inappropriate shocks

Area of Science:

• Cardiology
• Biomedical Engineering

Background:

• Implantable cardioverter-defibrillators (ICDs) treat ventricular tachyarrhythmias.
• Lead noise can cause inappropriate ICD therapy by mimicking ventricular activity.
• A novel algorithm aims to differentiate lead noise from true arrhythmias.

Purpose of the Study:

• Evaluate an algorithm's efficacy in distinguishing ICD lead noise from ventricular tachycardia/fibrillation (VT/VF).
• Assess the algorithm's ability to prevent inappropriate shocks.
• Determine if the algorithm delays appropriate VT/VF therapy.

Main Methods:

• Prospective testing of the algorithm using near- and far-field electrogram (EGM) recordings.
• Recordings included induced lead noise (sustained/non-sustained) and VT/VF.
• Algorithm performance was evaluated on a bench-top device, documenting diagnosis and therapy timing.

Main Results:

• The algorithm correctly identified 97.1% of sustained lead noise and 90.4% of non-sustained lead noise.
• It accurately detected 100% of VT/VF recordings.
• No significant increase in detection time for VT/VF was observed.

Conclusions:

• The SecureSense™ algorithm effectively distinguishes lead noise from VT/VF.
• It reduces inappropriate shocks caused by lead noise.
• The algorithm alerts clinicians to potential lead failures without compromising VT/VF detection.