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Record W4412099148 · doi:10.1136/bmjopen-2024-086485

Association between left atrial appendage volume and atrial fibrillation recurrence after catheter ablation: a systematic review and meta-analysis

2025· review· en· W4412099148 on OpenAlexaboutno aff
Pengfei Chen, Ming Guo, Chen Chen, Deng Pan, Jianpeng Du, Dazhuo Shi

Bibliographic record

VenueBMJ Open · 2025
Typereview
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePublication biasMeta-analysisAtrial fibrillationFunnel plotCochrane LibraryInternal medicineCatheter ablationObservational studyCardiologySurgery

Abstract

fetched live from OpenAlex

Objectives To evaluate the association between left atrial appendage volume (LAAV) and atrial fibrillation (AF) recurrence after catheter ablation (CA) and explore the potential mechanism. Design Systematic review and meta-analysis. Data sources PubMed, EMBASE, Web of Science and Cochrane Library databases were searched systematically from inception through 28 September 2024 to identify relevant studies. Eligibility criteria Observational studies that estimated the association between LAAV and AF recurrence. Data extraction and synthesis Two independent investigators screened studies for inclusion and extracted data. Statistical heterogeneity was assessed using the Cochrane Q-test and I², with p<0.1 or I² > 50% indicating significant heterogeneity. This study used a random-effects model to account for potential heterogeneity. The quality of the included studies was assessed using the Newcastle–Ottawa Scale (NOS), Risk of Bias in Non-randomized Studies of Interventions (ROBINS-I tool) and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Publication bias was examined through funnel plots and Egger’s test. Result Seventeen studies (3078 patients) were included. Meta-analysis of 11 studies suggested that LAAV was significantly associated with the risk of AF recurrence in both univariate (HR 1.06, 95%CI 1.04 to 1.08, p<0.01; I 2 =49.7%) and multivariate analyses (HR 1.10, 95%CI 1.05 to 1.16, p<0.01; I 2 =77.4%). The relationship between LAAV and recurrence of persistent AF (HR 1.11, 95% CI 1.03 to 1.20, p<0.05; I² = 73.0%) was significant. However, no significant association was found for paroxysmal AF (HR 1.01, 95% CI 0.94 to 1.07, p>0.05; I² = 0%). Meta-analysis of 13 studies suggested that patients with recurrence had larger LAAV values than those without recurrence (standardised mean difference (SMD) 0.54, 95% CI 0.36 to 0.71, p<0.01; I 2 =67.9%), and persistent AF patients had larger LAAV values than paroxysmal AF (SMD 0.29, 95% CI 0.02 to 0.57, p=0.05; I 2 =60.6%). Sensitivity analyses did not change these results. Subgroup analyses largely aligned with the overall findings, though study design and sample size contributed to heterogeneity. The mean NOS scores indicated moderate to high study quality; ROBINS-I assessments showed that most studies had a low to moderate overall risk of bias; and the GRADE approach rated the certainty of outcome evidence as low. Conclusions Our study suggests that LAAV may be a significant predictor of AF recurrence after CA. Incorporating LAAV into pre-ablation screening may enhance risk stratification, guiding tailored follow-up and treatment strategies. PROSPERO registration number CRD42022339910.

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)0.016
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: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.040
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0240.042
Bibliometrics0.0100.010
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 head0.194
GPT teacher head0.458
Teacher spread0.264 · 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
GenreReview

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

Citations1
Published2025
Admission routes1
Has abstractyes

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