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Record W4280492135 · doi:10.1093/europace/euac053.197

Hot balloon versus cryoballoon ablation in patients with atrial fibrillation: a systematic review and meta-analysis

2022· review· en· W4280492135 on OpenAlexaboutno aff
Konstantinos A. Papathanasiou, Sotiria G. Giotaki, Charalambos Kossyvakis, Dimitrios Kazantzis, Dimitrios A. Vrachatis, Gerasimos Deftereos, Konstantinos Raisakis, Andreas Kaoukis, Dimitrios Avramides, Gerasimos Siasos, G Giannopoulos, Spyridon Deftereos

Bibliographic record

VenueEP Europace · 2022
Typereview
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAtrial fibrillationMeta-analysisConfidence intervalInternal medicineStudy heterogeneityFunnel plotCochrane LibraryCatheter ablationRandom effects modelOdds ratioPublication biasCardiologySurgery

Abstract

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Abstract Funding Acknowledgements Type of funding sources: None. Background Atrial fibrillation (AF) incidence is expected to increase more than 60% in the following 30 years. Catheter ablation is the treatment of choice for medically intractable AF with arrhythmia recurrence remaining an unsolved issue. Purpose We systematically reviewed existing literature to compare the efficacy of hot balloon (HBA) versus cryoballoon ablation (CBA). Methods PubMed, Scopus, ClinicalTrials.gov, medRxiv and Cochrane Library (according to PRISMA guidelines) were scrutinized for relevant articles up to 2 December 2021. Eligible studies had to compare clinical outcomes (arrhythmia recurrence rates or/and procedural data or/and safety outcomes) between patients undergoing HBA and CBA for AF. Quality assessment of studies was conducted via the Newcastle-Ottawa Scale (high quality≥ 7, moderate 4-6, poor <4). Statistical pooling was performed according to a random-effect model with generic inverse-variance weighting of odds ratios and mean differences computing risk estimates with 95% confidence intervals. The presence of heterogeneity among studies was evaluated under the Cochran Q chi-square test. I² values of 25%, 50% and 75% have been assigned adjectives of low, moderate, and high heterogeneity. Publication biases were assessed by visual inspection of funnel plots. Results PRISMA study search and individual study characteristics are presented in Figure 1. Literature search identified 131 studies, 5 of which (evaluating 513 patients) met inclusion criteria. Patients undergoing HBA demonstrated similar long term recurrence rate as compared to CBA treated controls (OR: 0.68; 95% CI: 0.38-1.22; p-value: 0.19; I2: 0%). Procedural aspects, such as touch-up radiofrequency ablation (per pulmonary vein), procedure time (min) and fluoroscopic time (min) did not differ among treatment arms (OR: 1.79; 95% CI: 0.84-3.83; p-value: 0.13, I2: 80%, MD: 9.69; 95% CI: -2.78-22.16; p-value: 0.13, I2: 63%, and OR: 1.03; 95% CI: -9.50-7.44; p-value: 0.81, I2: 87%, respectively). Regarding safety outcomes (Figure 1), the small number of the reported events precluded us from analyzing these data. Yet, tamponade and phrenic nerve injury were infrequent in both modalities; pulmonary vein stenosis of at least moderate severity (>50% luminal narrowing) was reported in 18 instances in the HBA arm as compared to zero events in the CBA arm. Of note, all events were asymptomatic. Quality assessment scores are shown in Figure 1. Four studies were of high quality and one study was of moderate quality. Funnel-plot distributions of the pre-specified outcomes indicated absence of publication bias for all outcomes. High statistical heterogeneity and the small number of patients included are the main limitations of this study. Conclusion Hotballoon ablation is a promising therapeutic option for patients suffering from AF, featuring comparable efficacy and procedural outcomes with cryoablation. Safety outcomes, especially PV stenosis, mandate further evaluation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.028
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0200.033
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.135
GPT teacher head0.360
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

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Citations1
Published2022
Admission routes1
Has abstractyes

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