Increased epicardial adipose tissue volume is associated with PR interval prolongation
Bibliographic record
Abstract
PURPOSE: Epicardial fat is visceral adipose tissue that possesses inflammatory properties. Inflammation and obesity are associated with cardiovascular disease and arrhythmogenesis, but little is known about the relationship between epicardial fat and PR-Interval prolongation. The purpose of this study was to investigate the association between epicardial adipose tissue (EAT) volume and PR-interval prolongation as assessed by computed tomography (CT) and Twelve-lead ECGs. METHODS: Patients (n=287) were referred for 64-slice CT for exclusion of coronary artery disease and EAT volumes were determined. Twelve-lead ECGs were obtained from each subject and were evaluated by two independent readers. RESULTS: Patients with significant PR interval prolongation had higher median EAT volume than patients with normal PR interval. Statistically significant correlations were observed between the EAT volume and the PR interval (p = 0.183, p = 0.003), and QRS duration (p = 0.144, p = 0.018). Multivariate and trend analyses confirmed that EAT volume was independently associated with the presence of PR interval prolongation. The receiver operator characteristics curve of EAT volume showed that an EAT volume >144.4 cm³ was associated with PR interval prolongation. CONCLUSION: This study indicates that EAT volume is highly associated with PR interval prolongation. Whether epicardial fat plays a role in the pathogenesis of PR interval prolongation requires future investigation.
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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) | 0.002 | 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".