TruAF Detection Algorithm Cardiac Device Features

Overview

A study from 2015 showed 20% of single chamber ICD patients may develop atrial fibrillation (AF) within the first 2 years of implant.1 This can lead to an increased risk of stroke and/or heart failure.2,3 Unfortunately, a significant number of AF episodes are asymptomatic and therefore missed when using standard intermittent monitoring techniques.4-9

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

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.


Multiple independent, real-world analyses demonstrate that atrial fibrillation is commonly found with Visia AF ICD patients.10-11 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. Brown, et al.

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 database10

Medtronic surveillance registry11

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

Schloss EJ, et al. How Common is New Onset Atrial Fibrillation in Single Chamber ICD Patients? Sub-analysis from the PainFree SST Study. Presented at AHA 2015 (Abstract 17946).

2

Wolf PA, et al. Stroke. 1991;22:983-988.

3

Stewart S, et al. Am J Med. 2002;113:359-364.

4

Strickberger SA, Ip J, Saksena S, Curry K, Bahnson TD, Ziegler PD. Relationship between atrial tachyarrhythmias and symptoms. Heart Rhythm. February 2005;2(2):125-131.

5

Verma A, Champagne J, Sapp J, et al. Discerning the incidence of symptomatic and asymptomatic episodes of atrial fibrillation before and after catheter ablation (DISCERN AF): a prospective, multicenter study. JAMA Intern Med. January 28, 2013;173(2):149-156.

6

Orlov MV, Ghali JK, Araghi-Niknam M, et al. Asymptomatic atrial fibrillation in pacemaker recipients: incidence, progression, and determinants based on the atrial high rate trial. Pacing Clin Electrophysiol. March 2007;30(3):404-411.

7

Quirino G, Giammaria M, Corbucci G, et al. Diagnosis of paroxysmal atrial fibrillation in patients with implanted pacemakers: relationship to symptoms and other variables. Pacing Clin Electrophysiol. January 2009;32(1):91-98.

8

Page RL, Wilkinson WE, Clair WK, McCarthy EA, Pritchett EL. Asymptomatic arrhythmias in patients with symptomatic paroxysmal atrial fibrillation and paroxysmal supraventricular tachycardia. Circulation. January 1994;89(1):224-227.

9

Ziegler PD, Koehler JL, Mehra R. Comparison of continuous versus intermittent monitoring of atrial arrhythmias. Heart Rhythm. December 2006;3(12):1445-1452.

10

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

11

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