Techniques improving electrical cardioversion success for patients with atrial fibrillation: a systematic review and meta-analysis
Bibliographic record
Abstract
AIMS: Electrical cardioversion is commonly used to restore sinus rhythm in patients with atrial fibrillation (AF), but procedural technique and clinical success vary. We sought to identify techniques associated with electrical cardioversion success for AF patients. METHODS AND RESULTS: We searched MEDLINE, EMBASE, CENTRAL, and the grey literature from inception to October 2022. We abstracted data on initial and cumulative cardioversion success. We pooled data using random-effects models. From 15 207 citations, we identified 45 randomized trials and 16 observational studies. In randomized trials, biphasic when compared with monophasic waveforms resulted in higher rates of initial [16 trials, risk ratio (RR) 1.71, 95% CI 1.29-2.28] and cumulative success (18 trials, RR 1.10, 95% CI 1.04-1.16). Fixed, high-energy (≥200 J) shocks when compared with escalating energy resulted in a higher rate of initial success (four trials, RR 1.62, 95% CI 1.33-1.98). Manual pressure when compared with no pressure resulted in higher rates of initial (two trials, RR 2.19, 95% CI 1.21-3.95) and cumulative success (two trials, RR 1.19, 95% CI 1.06-1.34). Cardioversion success did not differ significantly for other interventions, including: antero-apical/lateral vs. antero-posterior positioned pads (initial: 11 trials, RR 1.16, 95% CI 0.97-1.39; cumulative: 14 trials, RR 1.01, 95% CI 0.96-1.06); rectilinear/pulsed biphasic vs. biphasic truncated exponential waveform (initial: four trials, RR 1.11, 95% CI 0.91-1.34; cumulative: four trials, RR 0.98, 95% CI 0.89-1.08) and cathodal vs. anodal configuration (cumulative: two trials, RR 0.99, 95% CI 0.92-1.07). CONCLUSIONS: Biphasic waveforms, high-energy shocks, and manual pressure increase the success of electrical cardioversion for AF. Other interventions, especially pad positioning, require further study.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.028 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| 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".