Distance between the descending aorta and the left inferior pulmonary vein as a determinant of biophysical parameters during paroxysmal atrial fibrillation cryoablation
Bibliographic record
Abstract
INTRODUCTION: The distance from the descending aorta (DA) to the posterior wall of the left atrium (LA) is variable. We aimed to determine whether the proximity between the DA and the left inferior pulmonary vein (LIPV) ostium has an impact on biophysical parameters and cryoballoon (CB) ablation efficacy during LIPV freezing. METHODS: Patients referred for CB-ablation of atrial fibrillation (AF) in two high-volume centers were included. Cryoablation data were collected prospectively for each patient. The anatomical relationships between the LIPV and the DA (distance LIPV ostium-DA, presence of an aortic imprint on the posterior aspect of the LIPV) were then retrospectively analysed on the LA computed tomography scans realized before AF ablation. RESULTS: A total of 350 patients were included (70% men, 59.7 ± 11.5 years). The decrease in the Ostium-DA distance was significantly correlated to the increase in the time-to-isolation (TTI) (r = -.31; p = .036), with less negative temperature (r = -.11; p = .045). Similarly, the presence of an aortic imprint on the LIPV was associated with a longer TTI (p < .001). The analysis of redo procedures data shows a trend toward the presence of shorter ostium-DA distances (15.3 ± 3.29 vs. 18.1 ± 4.99, p = .15) and more frequent aortic imprints (63.6% vs. 47.5%, p = .34) in patients with LIPV reconnection as opposed to patients without reconnection in the LIPV. CONCLUSION: Our findings indicated that the DA seems to have a "radiator" effect influencing LIPV cryoablation parameters during CB-ablation. Additional studies will be needed to elucidate whether this biophysical influence has a clinical impact in LIPVs reconnections.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".