TruAF Detection Algorithm Cardiac Device Features

Traditionally, single chamber ICDs have been unable to determine whether a patient is experiencing AF episodes due to the lack of an atrial lead — until now.

With the TruAF™ Detection Algorithm, you can detect AF without an atrial lead.

How It Works

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Atrial Fibrillation can conduct into the ventricle resulting in a variable heart rate, which can lead to variability in the timing of the R waves. The TruAF Detection Algorithm monitors R-R variability and looks for patterns, then determines if the variability and pattern are sufficient to meet the classification of AF.

This provides you the opportunity to determine if your patient has AF, quantify the time in AF, and determine if the ventricular rate is controlled. This information — combined with other patient factors — allows you to help manage your patients who have AF.

Clinical Evidence

Multiple independent, real-world analyses demonstrate that atrial fibrillation is commonly found with Visia AF ICD patients.1-2 Continuous monitoring in single chamber ICD patients may allow for early AF identification and intervention.

 

Graph showing incidence of AF in single chamber ICD patients in two different studies.

Boriani, et al.1 Brown, et al.2

TIME PERIOD

6 months

6 months

MINIMUM
AF DETECTED

≥ 6 minutes

≥ 6 minutes

PATIENT HISTORY

Unknown AF history before implant

No prior AF history before implant

DATA FORM

CareLink™ device database

Medtronic surveillance registry

TYPE OF DATA

Real-world observational analysis

Real-world observational analysis

N=

4,920 Visia AF ICD patients

159 Visia AF ICD patients

Detection Algorithm Summary

TruAF Detection Summary
1

Boriani G, et al. Understanding the incidence of AF in single-chamber ICD patients: a real-world analysis. Presented at Europace 2017.

2

Brown ML, et al. New AF Occurrence in Single-Chamber ICD Patients: Insights from a Real-World Investigation. Presented at HRS 2018.