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Record W4410621348 · doi:10.1093/europace/euaf085.434

Early recurrence of atrial arrhythmia and healthcare utilization during the 8-week blanking period following catheter ablation of atrial fibrillation

2025· article· en· W4410621348 on OpenAlexafffund
Alexander P. Benz, Jeffrey M. Singh, Guy Amit, Juan G. Acosta‐Vélez, David Conen, Bishoy Deif, Syamkumar Divakaramenon, William F. McIntyre, Viwe Mtwesi, Jason D. Roberts, Jorge Wong, Jeff S. Healey

Bibliographic record

VenueEP Europace · 2025
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsRoyal Victoria Regional Health CentreMcMaster UniversityUniversity of TorontoPopulation Health Research Institute
FundersHamilton Health Sciences
KeywordsAtrial fibrillationCatheter ablationMedicineCardiologyInternal medicineAblationBlankingCatheterSurgery

Abstract

fetched live from OpenAlex

Abstract Background The 2024 EHRA/HRS/APHRS/LAHRS expert consensus statement proposed an 8-week "blanking period" for clinical trials involving catheter ablation of atrial fibrillation (AF), in which recurrences are not seen as a failure of treatment. However, the relationship between early recurrence of atrial arrhythmia and clinical events during the first 8 weeks following catheter ablation is not well defined. Purpose To study the association between recurrence of atrial arrhythmia in the first 14 days following catheter ablation of AF and healthcare utilization in the first 8 weeks following ablation. Methods We analyzed prospectively collected data from participants enrolled in the IMPROVE-PVI randomized trial testing colchicine 0.6 mg twice daily vs. placebo for 10 days following catheter ablation of AF. All participants received a 14-day Holter immediately following ablation. Recurrence of atrial arrhythmia was defined as Holter-documented AF, atrial flutter, or atrial tachycardia >30 seconds, and healthcare utilization was defined as any of emergency department visit, cardiovascular hospitalization, cardioversion, or repeat ablation. Blinded adjudicators assessed arrhythmias and outcomes. We built regression models to estimate the association between early recurrence of atrial arrhythmia and healthcare utilization. Results We analyzed data from 194 patients who wore a Holter immediately following catheter ablation of AF (median age 61 years, 22% female, 70% first procedure). The median HATCH score (hypertension: 1, age≥75 years: 1, transient ischemic attack or stroke: 2, chronic obstructive pulmonary disease [COPD]: 1, heart failure: 2) was 1 (interquartile [IQR] range, 0-1; range, 0-5), and 144 patients (74%) were discharged on an antiarrhythmic drug. During a median monitoring duration of 13 days, 61 patients (31%) had recurrent atrial arrhythmia. A total of 25 patients (13%) had a healthcare utilization event in the first 8 weeks following catheter ablation. Adjusted for the HATCH score, early recurrence of atrial arrhythmia was significantly associated with healthcare utilization (adjusted odds ratio 6.21, 95% confidence interval 2.49-15.51), as was higher burden of AF (per 1%-increase in AF burden, adjusted odds ratio 1.03, 95% confidence interval 1.01-1.05). Colchicine did not reduce early recurrence of atrial arrhythmia (hazard ratio 0.98, 95% confidence interval 0.59-1.61), nor did it reduce healthcare utilization within 8 weeks of ablation (hazard ratio 0.92, 95% confidence interval 0.42-2.02). Conclusions Nearly 1 in 3 patients had early recurrence of atrial arrhythmia in the first 14 days following catheter ablation of AF. More than 1 in 8 patients experienced a clinical meaningful event during the 8-week "blanking period" following catheter ablation, which was largely driven by early recurrence of atrial arrhythmia. Colchicine reduced neither early recurrence of atrial arrhythmia nor healthcare utilization.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.048
GPT teacher head0.328
Teacher spread0.280 · 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 source (direct Gemma or distilled Codex), 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 routes2
Has abstractyes

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