Comparing Left Atrial Low Voltage Areas in Sinus Rhythm and Atrial Fibrillation Using Novel Automated Voltage Analysis: A Pilot Study
Bibliographic record
Abstract
Background: Low voltage areas (LVAs) have been proposed as surrogate markers for left atrial (LA) scar. Correlation between voltages in sinus rhythm (SR) and atrial fibrillation (AF) have previously been measured via point-by-point analysis. We sought to compare LA voltage composition measured in SR to AF, utilizing a high-density automated voltage histogram analysis (VHA) tool in those undergoing pulmonary vein isolation (PVI) for persistent AF (PeAF). Methods: PVI. Maps required ≥ 1,000 voltage points in each rhythm and had a standardized procedure (mapped in AF then remapped in SR post-PVI). We created six anatomical segments (AS) from each map: anterior, posterior, roof, floor, septal and lateral AS. These were analyzed by VHA, categorizing atrial LVAs into 10 voltage aliquots 0 - 0.5 mV. Data were analyzed using SPSS v.26. Results: We acquired 58,342 voltage points (n = 10 patients, mean age: 67 ± 13 years, three females). LVA burdens of ≤ 0.2 mV, designated as "severe LVAs", were comparable between most AS (except on the posterior wall) with good correlation. Mapped voltages between the ranges of 0.21 and 0.5 mV were labeled as "diseased LA tissue", and these were found significantly more in AF than SR. Significant differences were seen on the roof, anterior, posterior, and lateral AS. Conclusions: Diseased LA tissue (0.21 - 0.5 mV) burden is significantly higher in AF than SR, mainly in the anterior, roof, lateral, and posterior wall. LA "severe LVA" (≤ 0.2 mV) burden is comparable in both rhythms, except with respect to the posterior wall. Our findings suggest that mapping rhythm has less effect on the LA with voltages < 0.2 mV than 0.2 - 0.5 mV across all anatomical regions, excluding the posterior wall.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| 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".