Atrial anatomical variations on computed tomography angiography associated with atrial fibrillation and those predicting recurrence following pulmonary vein isolation
Bibliographic record
Abstract
Abstract Background We aim to investigate the atrial anatomical variations in patients with and without atrial fibrillation (AF) using cardiac-computed tomography angiography (CCTA) and identify features associated with AF recurrence following pulmonary vein isolation. Materials and Methods We retrospectively reviewed 502 CCTAs of patients with AF performed prior to a pulmonary vein isolation procedure with 1058 CCTAs of patients without AF performed to rule out coronary artery disease between 2014 and 2017. Anatomical variations of both atria including left atrial diverticula (LAD), right atrial diverticula (RAD), Bachmann bundle shunt (BBS), and pulmonary vein anatomy were assessed. Results We found that patients with AF were older (67 ± 14 vs 63 ± 13 years, P = .039), had a higher prevalence of diabetes (24.4%) versus (14.7%), P = .006, and cerebrovascular accidents (3.8%) versus (0.9%), P = .044 when compared with patients without AF. Furthermore, on CCTAs patients with AF demonstrated a significantly higher prevalence of BBS (11% vs 4.1%, P < .001), LAD (19% vs 7.7%, P < .001), and RAD (9.8% vs 2.1%, P < .001) when compared to patients without AF. Logistic multivariable regression analyses of CCTA findings demonstrated increased odd ratios (OR) in those with AF of BBS (OR = 3.51, 95% CI, 2.32-5.35, P < .001), LAD (OR = 2.94, 95% CI, 2.12-4.07, P < .001), RAD (OR = 1.54, 95% CI, 1.19-2.11, P = .03), LA diameter (OR = 2.42, 95% CI, 1.65-3.39, P < .001). Importantly, multivariate Cox regression showed that the LA dimension is a predictor of AF recurrence (HR = 1.019, 95% CI, 1.001-1.051, P = .02). Conclusion AF patients have a higher prevalence of BBS, LAD, and RAD in comparison to patients without AF. Mean LA diameter predicts AF recurrence after the pulmonary vein isolation procedure.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".