Comparison of safety and effectiveness of different sheaths in ablation of focal atrial tachycardia: a retrospective study
Bibliographic record
Abstract
Background: A novel visualized steerable sheath, referred to as the Vizigo sheath, has been utilized in clinical interventions. The objective of this study was to evaluate and contrast the efficacy and safety of the Vizigo sheath with other sheaths in the catheter ablation (CA) for focal atrial tachycardia (FAT). Methods: A retrospective cohort study was conducted on consecutive patients with CA for FAT from March 2019 to February 2022. Objectives were to assess the impact of the Vizigo sheath on acute and long-term ablation success rates, procedural and fluoroscopy times, and contact force (CF). Results: A total of 164 patients, mean age 50±15 years, 97 (59.1%) women, underwent CA of FAT using the Vizigo sheath (N=42), non-visualized steerable sheath (N=36), or other conventional sheath (N=86). Age, sex, body mass index (BMI), presence of hypertension, heart failure, and diabetes mellitus were not significantly different among the three groups. The acute success rate of 94.0% was similar among the three groups. Over a follow-up of 14±2 months, the Vizigo sheath was associated with superior arrhythmia-free survival (88.1%) when compared to non-visualized steerable (69.4%; P=0.04) and other conventional (72.1%, P=0.046) sheaths. Procedural duration, number of ablation lesions, and ablation times were similar among the three groups. However, the Vizigo sheath was associated with lower fluoroscopy times (e.g., 145 vs. 250 s with Vizigo versus non-visualized steerable sheaths, P=0.03) and higher CF (e.g., average CF 12.0 versus 8.0 g with Vizigo versus non-visualized steerable sheaths, P=0.003). Conclusions: The application of Vizigo sheath can improve the long-term success rate of FAT and reduce the radiation exposure of patients and medical staff in our single-center limited sample study. More research may be needed in the future to confirm our findings.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".