Stroke doctors

Holter monitoring for cryptogenic stroke patients to enhance atrial fibrillation detection while reducing costs

Illustration medecin cardiologue

Challenges in detecting atrial fibrillation in post-stroke patients

Identifying AF in post-stroke patients is a significant challenge, made even more difficult by a healthcare system whose clinical protocols often lack clarity regarding:

• Which patients should be investigated

• How investigations should be organized and followed up

This results in variability in AF detection rates after cryptogenic stroke across neurology centers, as well as unjustified workloads for cardiology departments.

 

The Gervasy service is based on a diagnostic pathway

The Gervasy diagnostic pathway for patients with cryptogenic stroke is designed to robustly and cost-effectively identify atrial fibrillation as quickly as possible, aiming to prevent subsequent strokes.

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1. Robust diagnostic

A 28 days, 3-lead Holter monitor applied promptly after the stroke for optimal monitoring

  • Provision of Holter devices for application in the stroke ward close to the stroke index or in a TIA clinic.
  • Upload of raw ECG for Gervasy processing.
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2. Precise assessment of AF risk

5 different calculations of AF risk

The Gervasy platform calculates AF risk using five different methods to identify patients eligible for an implantable loop recorder.

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3. Long diagnostic

Implantable loop recorder monitored remotely for 12 months

  • A Gervasy physiologist recommends an implantable loop recorder for high risks patients following several unsuccessful long Holter.
  • Gervasy or the stroke center arranges for the insertion of an implantable loop recorder.
  • A Gervasy physiologist provides ongoing remote patient monitoring.

Strict quality controls to ensure optimal quality and best medical practice

Gervasy has developped a quality control database generated by its electronic platform to ensure a consistent service for its stroke doctors customers and their patients. 

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  1. Documentation of patients' medical characteristics 

by stroke nurse in the  Gervasy platform to calculate atrial fibrillation risks.

2. Documentation of diagnostic results

by Gervasy physiologist in the Gervasy platform for the Holter or the implacable loop recorder  to create a shared database.

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3. Gervasy quality controls

which compares with database based on patients' risks.

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4. Machine learning to improve knowledge

The Gervasy expert committee analyses the database to enhance medical practice through publications and partnership with medical devices suppliers.