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Record W4410621838 · doi:10.1093/europace/euaf085.453

Spatiotemporal dispersion characterization in persistent and long-standing persistent atrial fibrillation patients, insights from the TAILORED-AF trial

2025· article· en· W4410621838 on OpenAlexaff
Isabel Deisenhofer, J.-P. Albenque, Sonia Busch, Edouard Gitenay, Sabine Lotteau, Marie‐Sophie Nguyen‐Tu, Amélie Dayot, Anthony Appetiti, P Milpied, Jérôme Kalifa, Tom De Potter, Seth Goldbarg, Atul Verma, John D. Hummel

Bibliographic record

VenueEP Europace · 2025
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsAtrial fibrillationCardiologyMedicineInternal medicineDispersion (optics)OpticsPhysics

Abstract

fetched live from OpenAlex

Abstract Background/Introduction The TAILORED-AF trial (NCT04702451) was the first randomized, superiority trial demonstrating that artificial intelligence (AI)-guided ablation of persistent atrial fibrillation (AF) patients targeting spatiotemporal dispersion in addition to pulmonary vein isolation (PVI) is superior to PVI alone after one year of follow-up. Purpose This TAILORED-AF sub-analysis aims to characterize spatiotemporal dispersion regions in relation to atrial regions where AF terminated during an AI-guided tailored ablation procedure. Methods Spatiotemporal dispersion maps were built during index ablation procedures with an artificial intelligence-guided spatiotemporal dispersion software. Dispersion atrial extent was defined as the ratio of dispersion surface area in a chamber over its total chamber surface area quantified with an in-house algorithm. The algorithm estimates pixel surface area values from 2D snapshots collected from 3D navigation maps. After (i) conversion of antero-posterior and postero-anterior 2D view snapshots into grayscale-transformed images, (ii) the background was removed and the atria were segmented. Then, (iii) tags were detected, segmented and (iv) connected to remnant regions. Finally, spatiotemporal dispersion region locations and extent were superimposed with tags corresponding to AF termination locations in patients in whom AF was terminated. This corresponded to a location where AF terminated by ablation into sinus rhythm/atrial tachycardia or where the AF cycle length increased by a minimum of 20ms. Results The Tailored arm population included 187 persistent and long-standing persistent AF patients. The dispersion extent was higher in the left atrium (LA) compared to the right atrium (RA) (14.7% [8.1%-24.5%] vs 0.6% [0.0%-2.5%], p<0.0001). All patients (100%) had dispersion in the LA, whereas dispersion was only detected in the RA in 79% of the patients. The most frequent regions in LA exhibiting dispersion were the LA posterior wall with 20% [8%-31%] extent, LA anterior wall with 15% [8%-25%] extent and the LA roof with 10% [4%-19%] extent. The acute AF termination rate was 66%. All AF termination locations (100%) were found within dispersion regions: 25% in the lower quartile dispersion extent, 26% in the medium quartile and 49% in the higher quartile. In 81% of the patients, AF termination occurred in the LA, from which 20% located in the PV region and 80% outside the PV region. AF terminated in the RA in 19% of the patients (Figure). Conclusion(s) While pursuing an AI-guided ablation of persistent atrial fibrillation, spatiotemporal dispersion and AF termination predominantly occurs in the left atrium. Still, 19% of termination is observed after ablation in minimally extended regions of the RA. These findings highlight the importance of mapping and ablating in the RA when conducting a spatiotemporal dispersion-based ablation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.276
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
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