Overview

Traditionally, single chamber implantable cardioverter defibrillators (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.




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.

Detection algorithm summary

1 Does the patient have AF?
Check AF episodes on interval plot and EGM
 

Clinical
decision

Decorative element

2 If yes, how much?
Check AF burden information on Quick Look™ II and Cardiac Compass™ trends
3 If yes, is it rate controlled?
Check vs. rate during AF on Cardiac Compass™ trends
4

What are the patient factors?

  • Congestive heart failure
  • Hypertension
  • Diabetes mellitus
  • Stroke/TIA/thromboembolism
  • Vascular disease (prior MI/PAD/aortic plaque)
  • Age
  • Gender

Incidence of AF in single chamber ICD population


  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



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