Clinical effectiveness and efficiency of a new steerable sheath technology for radiofrequency ablation in Chinese patients with atrial fibrillation: a retrospective comparative cohort study
Bibliographic record
Abstract
Background: The clinical effectiveness and efficiency of a steerable sheath for radiofrequency catheter ablation (RFCA) in Chinese patients with atrial fibrillation (AF) needs to be compared with a fixed curve sheath to optimize RFCA procedure. Methods: This retrospective study included adult AF patients with their first RFCA that was conducted by the same electrophysiologist using a steerable sheath (VIZIGO, Biosense Webster, Inc.) or a fixed curve sheath (NaviEase, Synaptic Medical) in a Chinese tertiary care hospital from January to November 2021. The medical records kept at the hospital were the source of study data that included patient baseline characteristics and outcome measures for the clinical effectiveness and efficiency of RFCA procedure. Multivariate generalized linear regression analyses were performed to explore the impact of sheath type on clinical effectiveness and efficiency after adjustment. Results: Fourteen patients using steerable sheath and 34 patients using fixed curve sheath for RFCA were included in the data analysis. Most of patient baseline characteristics associated with the two study groups were comparable except that the steerable sheath group had significantly higher left atrium diameter (41.9±6.5 vs. 38.1±3.9 mm, P=0.017) and larger left atrium volume (150.4±29.5 vs. 126.8±27.5 mL, P=0.017) than the fixed curve sheath group. Using steerable sheath was associated with significantly shorter total pulmonary vein isolation (PVI) fluoroscopy time and post-surgery hospital length of stay (LOS) than using fixed curve sheath in both unadjusted comparisons (PVI fluoroscopy time: 1.3±1.5 vs. 4.0±3.9 min, P=0.004; post-surgery LOS: 2.1±0.7 vs. 2.9±1.5 days, P=0.034) and multivariate generalized regression analyses (PVI fluoroscopy time: coefficient =−0.859, P=0.014; post-surgery LOS: coefficient =−0.303, P=0.018). Conclusions: Compared to fixed curve sheath, steerable sheath used for RFAC could have the potential to shorten the PVI fluoroscopy time and reduce post-surgery LOS in a Chinese real-world hospital setting. Future real-world studies with large sample size are needed to confirm our study findings.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".