Sedation Versus General Anesthesia for Ablation of Ventricular Arrhythmias: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
ABSTRACT: Ventricular arrhythmias (VA), including ventricular tachycardia and fibrillation, are critical cardiac conditions that are often managed by catheter ablation among those unresponsive to pharmacologic therapy. The choice of anesthesia and sedation regimens for VA ablations may impact arrhythmia inducibility and hemodynamic stability, which can affect procedural success and complication rates. This systematic review and meta-analysis aimed to compare the efficacy and safety of sedation versus general anesthesia (GA) among patients undergoing VA ablation. The review was prospectively registered on PROSPERO (CRD42023441553). Database searches were conducted across five major databases from inception to March 9, 2024 to identify randomized trials or observational studies including adult patients undergoing ablations for VA. Screening and data extraction were completed in duplicate. Risk-of-bias assessments were conducted using ROBINS-I as all included studies were observational, and the quality of evidence was evaluated using the GRADE framework. Six observational studies (N = 16,435) were included. No significant differences were found between sedation and GA for total procedure time (MD: -14.16 minutes; 95%CI: -38.61 to 10.29 minutes), arrhythmia non-inducibility (RR: 0.73; 95% CI: 0.33-1.58), acute ablation success (RR: 1.06; 95% CI: 0.65-1.71), or procedural complications (RR: 0.72; 95% CI: 0.28-1.85). However, sedation was associated with significantly lower intraprocedural hemodynamic instability (RR: 0.28; 95% CI: 0.12-0.70). These findings indicate that while sedation and GA have comparable outcomes, sedation may be associated with less hemodynamic instability during VA ablation. However, more high-quality studies are needed to confirm these results.
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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 | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.035 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 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".