Efficacy and safety of cryoballoon ablation in the elderly: A systematic review and meta‑analysis of clinical trials
Bibliographic record
Abstract
Cryoballoon ablation has comparable efficacy with catheter ablation in atrial fibrillation (AF) treatment. However, there has been no systematic review or meta-analysis on this subject despite some studies on cryoballoon ablation in elderly patients with AF. The PubMed, Embase, Cochrane Library and Web of Science databases were comprehensively searched up to February 2023. The present study selected trials that compared the efficacy and safety of cryoballoon ablation in the elderly with the young that lasted for ≥12 months. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were used to conduct the present review. For quality assessment of included studies, the Newcastle-Ottawa scale was used. Two reviewers screened all articles independently according to the inclusion criteria. The main outcomes were procedural time, fluoroscopy time, success rate and transient phrenic nerve palsy (tPNP). A total of six articles were ultimately included. Data regarding procedural time, fluoroscopy time and success rate were available for five trials. The tPNP complication rate was reported in all trials. The differences in procedural time (mean difference, 0.29; 95% CI, -4.93 to 5.50; P=0.91), fluoroscopy time (mean difference, -0.59; 95% CI, -2.07 to 0.89; P=0.43), success rate (odds ratio, 0.981; 95% CI, 0.72 to 1.34; P=0.903) and tPNP rate (mean difference, 0.955; 95% CI, 0.452 to 2.020; P=0.904) between the elderly and young groups were all not significant. It was concluded that cryoballoon ablation was as safe and effective in elderly patients with AF as in young patients.
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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 | 0.018 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.035 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".