Abstract 4366692: Left Atrial Lipomatous Metaplasia in Patients with Atrial Fibrillation
Bibliographic record
Abstract
Background: Epicardial adipose tissue is associated with prevalent and incident atrial fibrillation (AF). The mechanism for this association has been at least partially attributed to fatty atrial infiltration, or lipomatous metaplasia (LM), of the left atrium (LA). Objective: The purpose of this study was to quantitate the extent of LA LM using contrast enhanced computed tomography (CECT) and to examine its association with intracardiac electrogram characteristics using high density electroanatomic mapping in patients referred for AF ablation. Methods: The retrospective cohort included consecutive patients who underwent CECT and LA high-density mapping (Pentaray, Biosense Webster) prior to AF ablation between January 2021- 2023. Univariable associations were examined using nonparametric tests. The association of bipolar voltage amplitude and mid-LA myocardial CECT image intensity (< 0 Hounsfield units indicative of LM, ADAS 3D software), at each electroanatomic map point, was examined using a mixed effects linear regression model clustered by patient. Results: The cohort consisted of 34 patients with mean age 66.4 ± 9.5 years, BMI of 31.7 ± 9.5 kg/m2, left atrial volume index (LAVI) 38.0 ± 8.1 mL, and EF 51 ±13%. Of all patients, 41% were female, 65% had persistent AF, 74% had hypertension, 41% had coronary disease, 12% had diabetes, 33% had sleep apnea, and 15% had prior stroke or TIA. LM was detected among 53% of patients (95% CI 36-69%), and was unassociated with age, BMI, LAVI, AF type, sex, diabetes, sleep apnea, or hypertension. Bipolar voltage was associated with CECT attenuation (-0.2 mV/ Hounsfield unit, P<0.001), but was unassociated with LM. Conclusions: LA LM was prevalent in a small cohort of patients undergoing AF ablation and was unassociated with traditional risk factors and voltage mapping. Additional studies are warranted to refine the understanding of LM as an atrial myopathy.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".