Cardiac Computed Tomography for Atrial Fibrillation Patients Undergoing Ablation
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to correlate early recurrence of atrial fibrillation (AF) after ablation with noninvasive imaging using cardiac computed tomography (CT). METHODS: CT image data of 260 patients who had undergone wide area circumferential ablation (WACA) between October 2005 and August 2010 as well as from 30 subjects in sinus rhythm without a history of AF (control group) were retrospectively analyzed. To evaluate early outcome of AF ablation, all AF patients underwent follow-up with a 30-day event monitor 3 to 4 months after ablation. In addition, a cardiac CT was also performed 3 to 4 months after ablation to exclude pulmonary vein (PV) stenosis. The presence of early AF was correlated with anatomic and functional PV and left atrial parameters, as assessed by cardiac CT. RESULTS: A total of 70 patients (26.9%) were found to have early recurrence of AF. However, we found no association between PV or left atrial anatomic or functional parameters derived from cardiac imaging with early AF recurrence. Furthermore, no correlation (P>0.05) between AF recurrence and coronary artery stenosis, anatomic origin of the sinoatrial, or atrioventricular nodal arteries was observed. Finally, PV contraction did not predict AF recurrence. However, when comparing PV contraction in WACA patients with the control group, a significant (P<0.05) reduction in left superior PV and right superior PV contractility was found in patients after radiofreqency ablation. CONCLUSIONS: In our relatively large cohort, cardiac CT did not yield any anatomic or functional markers for the prediction of early AF recurrence after undergoing WACA. However, our data may provide insights into functional changes that occur following ablation procedures.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.000 | 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".