O Volume do Apêndice Atrial Esquerdo Prediz a Recorrência de Fibrilação Atrial após Ablação por Cateter de Radiofrequência: Uma Metanálise
Bibliographic record
Abstract
BACKGROUND: The influence of left atrial appendage volume (LAAV) on the recurrence of atrial fibrillation (AF) following radiofrequency catheter ablation remains unclear. OBJECTIVES: We performed a meta-analysis to assess whether LAAV is an independent predictor of AF recurrence following radiofrequency catheter ablation. METHODS: The PubMed and the Cochrane Library databases were searched until March 2022 to identify publications evaluating LAAV in association with AF recurrence after radiofrequency catheter ablation. Seven studies that fulfilled the specified criteria of our analysis were found. We used the Newcastle-Ottawa Scale to evaluate the quality of the studies. The pooled effects were evaluated depending on standardized mean differences (SMDs) or hazard ratios (HRs) with 95% confidence intervals (CIs). P values < 0.05 were considered statistically significant. RESULTS: A total of 1017 patients from 7 cohort studies with a mean follow-up 16.3 months were included in the meta-analysis. Data from 6 studies (943 subjects) comparing LAAV showed that the baseline LAAV was significantly higher in patients with AF recurrence compared to those without AF (SMD: -0.63; 95% CI: -0.89 to -0,37; all p values < 0.05; I2= 62.6%). Moreover, higher LAAV was independently associated with a significantly higher risk of AF recurrence after radiofrequency catheter ablation (HR: 1.10; 95% CI: 1.02 to 1.18). CONCLUSIONS: The meta-analysis showed that there is a significant correlation between LAAV and AF recurrence after radiofrequency catheter ablation, and the role of LAAV in AF patients should not be ignored in clinical practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.043 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".