Cryoablation Versus RF Ablation for AVNRT: A Meta‐Analysis and Systematic Review
Bibliographic record
Abstract
INTRODUCTION: Atrioventricular nodal reentrant tachycardia (AVNRT) is the most common supraventricular tachycardia referred for ablation. High success rates have been accompanied with a small risk of atrioventricular (AV) block. Cryoablation has been used as an alternative to radiofrequency (RF) ablation, but studies have been underpowered in comparing the 2 techniques. METHODS AND RESULTS: An electronic search and hand-search of reference lists for published and unpublished data was carried out. Comparative studies (cohort and randomized controlled trials) of RF versus cryoablation for AVNRT were identified independently by 2 reviewers. Searches were limited to English language human studies. The primary metameter was long-term AVNRT recurrence (>2 months postprocedure and ECG/electrophysiology study [EPS]-documented) and secondary metameters included acute procedural failure and AV block requiring pacing. A total of 5,617 patients in 14 trials were included in this systematic review. Acute procedural failure with cryoablation was slightly higher than with RF ablation, but the difference was not statistically significant (risk ratio [RR] 1.44 [95% confidence interval; CI 0.91-2.28], P = 0.12). Long-term recurrence was higher with cryoablation (RR 3.66 [95% CI 1.84-7.28], P = 0.0002) even after adjusting for larger (6 mm) cryocatheter tips, "insurance lesions" and longer (>6 months) follow-up duration. RF ablation for AVNRT was associated with permanent AV block in 0.75% of patients, but was not reported in any patients treated with cryoablation (n = 1066, P = 0.01). CONCLUSIONS: Cryoablation is a safe and effective treatment for AVNRT. Although late-recurrence is more common with cryoablation than with RF ablation, avoidance of permanent AVN block makes it an attractive option in patients where the avoidance of AV block assumes higher priority (such as children and young adults).
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.025 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".