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Record W7127924511 · doi:10.1093/eurheartj/ehaf784.457

Balancing stroke and bleeding risks: the impact of stopping anticoagulation after aAF ablation - a systematic review and meta-analysis

2025· article· en· W7127924511 on OpenAlexaboutno aff
Sogol Koolaji, D A Gorog, Vias Markides

Bibliographic record

VenueEuropean Heart Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsDiscontinuationObservational studyStroke (engine)Atrial fibrillationRandomized controlled trialOdds ratioConfidence intervalMeta-analysisCatheter ablationMEDLINE

Abstract

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Abstract Background Catheter ablation has become an effective treatment for atrial fibrillation (AF), potentially reducing the need for continued oral anticoagulant (OAC). However, the optimal anticoagulation strategy post-ablation remains uncertain, particularly in low-risk patients due to inconsistent evidence regarding the balance of thromboembolic and bleeding risks. Purpose We aimed to evaluate the safety and clinical outcomes of OAC discontinuation compared to continuation after AF ablation, with a focus on low-risk patients. Methods A systematic review and meta-analysis was performed, involving a comprehensive search of PubMed, Embase, and Medline (1990-2024) to identify studies assessing OAC discontinuation after AF ablation (successful ablation at the time of discontinuation). Eligible studies included randomized controlled trials, cohort studies, and observational studies comparing continued versus discontinued OAC. Risk of bias was assessed using the Newcastle-Ottawa Scale for observational studies. Meta-analysis was performed using the Meta package in R with Mantel-Haenszel models, heterogeneity was assessing with I² statistic, and continuity correction where zero events in both groups. Pooled odds ratios (OR) and 95% confidence intervals (95% CI) were calculated for ischemic stroke (IS) and Intracranial haemorrhage (ICH) outcomes reported in studies. Moreover, to compare IS reduction with ICH rise, a weight of 1.5 was given to ICH. Results A total of 32 studies were included (1 clinical trial, 17 retrospective, and 14 prospective cohorts), with sample sizes ranging from 106 to 231,374 patients. Most studies did not apply CHA2DS2VASc specific inclusion criteria, except for four studies including only patients with CHA2DS2VASc ≥2. Follow-up durations varied from 1-6 years. The decision to discontinue OAC was guided by physician discretion, thromboembolic risk assessment and adherence to clinical guidelines. Meta-analysis of 16 studies reporting IS found no significant difference in IS between On-OAC and Off-OAC patients (pooled OR: 1.11 [0.72-1.72], I² = 14.2%, p = 0.29). Similarly, in CHA2DS2VASc <2 patients, no significant difference was observed (OR: 1.16 [0.20-6.72]). However, in CHA2DS2VASc ≥2 patients, On-OAC significantly reduced IS risk compared to Off-OAC (OR: 0.25 [0.09-0.64]). Overall, ICH risk was significantly higher in On-OAC patients, with a pooled OR of 5.17 (2.37-11.27). The ratio of total IS to weighted-ICH ORs was <1 in overall and CHA2DS2VASc<2 groups, indicating greater ICH increase than IS reduction in the On-OAC group. This ratio was >1 in CHA2DS2VASc ≥2, but not statistically significant. Conclusion Our findings suggest that OAC discontinuation may be considered in selected low-risk patients post-AF ablation, while high-risk patients (CHA2DS2VASc ≥2) may benefit from continued OAC. Further well-designed randomized trials are needed to refine post-ablation anticoagulation strategies.Forest plot Table of included studies. IS to ICH

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)0.020
metaresearch head score (Gemma)0.040
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.040
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0220.047
Bibliometrics0.0090.009
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.148
GPT teacher head0.410
Teacher spread0.262 · 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 designMeta-analysis
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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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