P-wave evidence as a method for improving algorithm to detect atrial fibrillation in insertable cardiac monitors

Area of Science:

• Cardiology
• Biomedical Engineering
• Medical Device Technology

Background:

• Premature atrial contractions and sick sinus syndrome frequently cause false atrial fibrillation (AF) detection in insertable cardiac monitors (ICMs).
• Inappropriate AF detection can lead to unnecessary patient anxiety and medical interventions.

Purpose of the Study:

• To validate a novel algorithm designed to decrease inappropriate AF detection in ICMs.
• The algorithm leverages P-wave identification within the cardiac cycle to improve AF detection accuracy.

Main Methods:

• An improved ICM algorithm was developed, incorporating P-wave detection to reduce AF evidence.
• Algorithm performance was validated against Holter monitor data over a 46-hour period.
• ICM detections were compared with Holter annotations for episode and duration accuracy.

Main Results:

• The improved algorithm reduced inappropriate AF episodes by 46% and duration by 55%.
• Sensitivity for detecting true AF episodes (≥2 minutes) was 85% (90% per-patient average).
• Inappropriate detections were significantly reduced with only a minimal decrease (2%) in appropriate AF episode detection.

Conclusions:

• Incorporating P-wave information into ICM algorithms substantially improves AF detection accuracy.
• The enhanced algorithm effectively minimizes false positives, leading to more reliable AF monitoring.
• This technological advancement offers a more precise tool for diagnosing and managing atrial fibrillation.