P2838The impact of anesthesia depth on catheter ablation for atrial fibrillation: a systematic review and meta-analysis of observational studies
Bibliographic record
Abstract
Abstract Objectives This meta-analysis and systematic review seeks to compare both characteristic parameters and procedural outcomes of catheter ablation in patients under GA/deep sedation and mild/moderate sedation. Background Catheter ablation has become a widely applied intervention for treating symptomatic AF and arrhythmias that are refractory to medical therapy. It can be conducted through from mild sedation to general anesthesia. Methods PubMed and Embase were searched up to July 2018 for randomized controlled trials, cohort and observational studies that assessed the outcomes of catheter ablation under GA/deep sedation or mild/moderate sedation. 12 studies were included in this meta-analysis after screening with the inclusion and exclusion criteria. Heterogeneity between studies and publication bias was evaluated by I2 index and Egger's regression, respectively. Results Our meta-analysis found catheter AF ablation with GA/deep sedation to be associated with reduced risk of recurrence (RR: 0.79, 95% CI: 0.56 to 1.13, P=0.20) and complications (RR: 0.95, 95% CI: 0.64 to 1.42, P=0.82), though statistically insignificant. In terms of procedural parameters, there was non-significant difference between the two groups when both procedural time (SMD: −0.13, 95% CI: −0.90 to 0.63, P=0.74) and fluoroscopy time (SMD: −0.41, 95% CI: −1.40 to 0.58, P=0.41) were considered. Multivariate meta-regression demonstrated hypertension as an independent moderating factor for complication risk. Complications Comparison Conclusion Apart from an increased likelihood of procedural success, ablation by GA/deep sedation was found to be non-significantly different from the mild/moderate sedation approach in both procedural parameters and outcome measures.
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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 | 0.013 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.050 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 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) | 0.006 | 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".