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EHRA 2024: Late-Breaking Science Video Collection

Published: 22 April 2024

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Now Playing
Part 1 | Session 7 of 7
AI-Enabled Single-Lead ECG Can Unmask Conduction Tissue Disease
Laurent Fiorina

Up Next

2m 52s

Part 2 3 Trials that Will Change My Practice With Dr Luigi Di Biase
Luigi Di Biase

4m 54s

Part 1 | Session 1 Venous Vascular Closure Vs Manual Compression: Style-AF Roland R Tilz

4m 3s

Part 1 | Session 2 FIH Clinical Series of Conformable "Single Shot" PFA Catheter for PVI Vivek Reddy

8m 5s

Part 1 | Session 3 Risk of Stroke or Embolism and AF: ARTESiA Substudy William McIntyre

2m 53s

Part 1 | Session 4 Ablation Strategies for Repeat Procedures in Recurrent AF: ASTRO Boris Schmidt

5m 26s

Part 1 | Session 5 Non-Vitamin K Antagonist Oral Anticoagulant in AHRE Patients: NOAH Julius Nikorowitsch

6m 51s

Part 1 | Session 6 Personalised PVI: The QDOT-by-LAWT Trial Giulio Falasconi

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Overview

For short, concise coverage of the key data revealed, our accessible Expert Interviews were conducted with select faculty, focussing on the results, applicability and impact on future research and clinical practice.

More from this programme

Part 1

Expert Interviews

7 sessions
Venous Vascular Closure Vs Manual Compression: Style-AF	Watch now
FIH Clinical Series of Conformable "Single Shot" PFA Catheter for PVI	Watch now
Risk of Stroke or Embolism and AF: ARTESiA Substudy	Watch now
Ablation Strategies for Repeat Procedures in Recurrent AF: ASTRO	Watch now
Non-Vitamin K Antagonist Oral Anticoagulant in AHRE Patients: NOAH	Watch now
Personalised PVI: The QDOT-by-LAWT Trial	Watch now
AI-Enabled Single-Lead ECG Can Unmask Conduction Tissue Disease	Watch now

Part 2

Highlights

1 session
3 Trials that Will Change My Practice With Dr Luigi Di Biase	Watch now

About the episode

EHRA 24 - In this short interview, we are joined by Dr Laurent Fiorina (Cardiovascular Institute Paris-Sud (ICPS), FR) joins us to discuss the findings from a clinical investigation into diagnosing conduction tissue disease using an AI-enabled single-lead coronary ECG device.

This observational, prospective clinical trial aims to investigate the performance of an artificial intelligence algorithm interpreting The aim of this study is to evaluate the ability of an artificial intelligence (AI)-enabled single-lead ambulatory electrocardiogram (ECG) to identify patients who experienced asystole due to sinus pause or complete heart block in the past 2 weeks.

The study included 319,396 unselected 14-day ambulatory ECG recordings (mean age 60.5 ± 17.8; 60% female) collected from five Independent Diagnostic Testing Facilities. Researchers developed a deep learning-based model using the last 24 hours of each recording to identify patients with daytime sinus pause of ≥3 seconds, prolonged sinus pause at any time of ≥6 seconds, or complete heart block documented during the previous 13 days of monitoring.

Interview Questions:

What is the importance of this study?
What was the study design and patient population?
What are the key findings?
What are some of the key challenges and opportunities in AI AF detection in 2024?
What are your take-home messages?

Recorded on-site at EHRA in Berlin, 2024.

Faculty Biographies

Laurent Fiorina

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