PO-06-205 Deep learning based assessment of T:R ratios during prolonged screening in S-ICD patients experienced inappropriate shocks secondary to T-wave over-sensing
PO-06-205 Deep learning based assessment of T:R ratios during prolonged screening in S-ICD patients experienced inappropriate shocks secondary to T-wave over-sensing
Background: the conventional S-ICD screening involves a static 10-second ECG screening at various body positions with an eligibility cut-off T:R ratio of 1:3. Despite this screening, S-ICD patients experience higher rates of inappropriate shocks (IAS) compared to transvenous ICD patients, with the primary cause of IAS being T-wave over-sensing (TWO). In this study, we explored cases of patients who experienced IAS due to TWO using a 24-hour Holter recording and a deep-learning AI tool.
Objective: to explore the changes of T:R ratios over 24-hour period in atients who experienced IAS due to TWO using a 24-hour Holter recording and a deep-learning AI tool.
Methods: patients who had IAS secondary to TWO were identified and fitted with a 24-hour Holter monitor to record their S-ICD vectors. The AI tool was then applied to assess the T:R ratio across the entire duration of the recordings.
Results: ten patients (mean age 59 ± 20 years, 60% male) were recruited. Of these, three patients had ischemic cardiomyopathy, three had non-ischemic cardiomyopathy, and the remaining patients had hypertrophic cardiomyopathy, arrhythmogenic right ventricular cardiomyopathy (ARVC), congenital heart disease, or valvular heart disease. Although each of these patients had passed conventional screening before implant, none maintained a T:R ratio threshold of 1:3 across all vectors over 24 hours.
Conclusion: T:R ratios appear to fluctuate based on factors such as physical activity and body position. We believe these patients experienced IAS due to these fluctuations in T:R ratios, despite initially passing the standard screening. We propose the adoption of prolonged screening to optimise selection, implant position and vector selection for S-ICD candidates, with the goal of reducing inappropriate shocks and minimising related psychosocial impacts.
S723-S724
Toon, Lin-Thiri
f03b2a78-b35c-4893-bd00-bfecc5d22c3d
ElRefai, Mohamed
28916fea-4687-4d4b-99aa-961e73b710ab
Abouelasaad, Mohamed
62c5bd28-9c5f-4287-8b63-b25b2a2b7966
Wiles, Benedict
a42ba978-24c3-4533-8eca-498102004477
Ward, Samuel
15ee7a4d-9af0-4b76-a47d-836e731fa039
Dunn, Anthony
37d0fe10-1dbb-4985-b764-defd49f17277
Zemkoho, Alain
30c79e30-9879-48bd-8d0b-e2fbbc01269e
Roberts, Paul
32fe1d97-dc53-49a1-9b4a-f866d0b7d13d
Paisey, John
b1f1229b-a681-4117-bcd7-bc80210bd85b
24 April 2025
Toon, Lin-Thiri
f03b2a78-b35c-4893-bd00-bfecc5d22c3d
ElRefai, Mohamed
28916fea-4687-4d4b-99aa-961e73b710ab
Abouelasaad, Mohamed
62c5bd28-9c5f-4287-8b63-b25b2a2b7966
Wiles, Benedict
a42ba978-24c3-4533-8eca-498102004477
Ward, Samuel
15ee7a4d-9af0-4b76-a47d-836e731fa039
Dunn, Anthony
37d0fe10-1dbb-4985-b764-defd49f17277
Zemkoho, Alain
30c79e30-9879-48bd-8d0b-e2fbbc01269e
Roberts, Paul
32fe1d97-dc53-49a1-9b4a-f866d0b7d13d
Paisey, John
b1f1229b-a681-4117-bcd7-bc80210bd85b
Toon, Lin-Thiri, ElRefai, Mohamed, Abouelasaad, Mohamed, Wiles, Benedict, Ward, Samuel, Dunn, Anthony, Zemkoho, Alain, Roberts, Paul and Paisey, John
(2025)
PO-06-205 Deep learning based assessment of T:R ratios during prolonged screening in S-ICD patients experienced inappropriate shocks secondary to T-wave over-sensing.
Heart Rhythm, 22 (4), .
(doi:10.1016/j.hrthm.2025.03.1745).
Record type:
Meeting abstract
Abstract
Background: the conventional S-ICD screening involves a static 10-second ECG screening at various body positions with an eligibility cut-off T:R ratio of 1:3. Despite this screening, S-ICD patients experience higher rates of inappropriate shocks (IAS) compared to transvenous ICD patients, with the primary cause of IAS being T-wave over-sensing (TWO). In this study, we explored cases of patients who experienced IAS due to TWO using a 24-hour Holter recording and a deep-learning AI tool.
Objective: to explore the changes of T:R ratios over 24-hour period in atients who experienced IAS due to TWO using a 24-hour Holter recording and a deep-learning AI tool.
Methods: patients who had IAS secondary to TWO were identified and fitted with a 24-hour Holter monitor to record their S-ICD vectors. The AI tool was then applied to assess the T:R ratio across the entire duration of the recordings.
Results: ten patients (mean age 59 ± 20 years, 60% male) were recruited. Of these, three patients had ischemic cardiomyopathy, three had non-ischemic cardiomyopathy, and the remaining patients had hypertrophic cardiomyopathy, arrhythmogenic right ventricular cardiomyopathy (ARVC), congenital heart disease, or valvular heart disease. Although each of these patients had passed conventional screening before implant, none maintained a T:R ratio threshold of 1:3 across all vectors over 24 hours.
Conclusion: T:R ratios appear to fluctuate based on factors such as physical activity and body position. We believe these patients experienced IAS due to these fluctuations in T:R ratios, despite initially passing the standard screening. We propose the adoption of prolonged screening to optimise selection, implant position and vector selection for S-ICD candidates, with the goal of reducing inappropriate shocks and minimising related psychosocial impacts.
This record has no associated files available for download.
More information
e-pub ahead of print date: 24 April 2025
Published date: 24 April 2025
Identifiers
Local EPrints ID: 509776
URI: http://eprints.soton.ac.uk/id/eprint/509776
ISSN: 1547-5271
PURE UUID: 4f0b60bb-67bb-49cf-b2d0-358b7a6b0f57
Catalogue record
Date deposited: 04 Mar 2026 17:55
Last modified: 05 Mar 2026 02:47
Export record
Altmetrics
Contributors
Author:
Lin-Thiri Toon
Author:
Mohamed ElRefai
Author:
Mohamed Abouelasaad
Author:
Benedict Wiles
Author:
Samuel Ward
Author:
Anthony Dunn
Author:
Paul Roberts
Author:
John Paisey
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics