Mechanisms of Wave Fractionation at Boundaries of High-Frequency Excitation in the Posterior Left Atrium of the Isolated Sheep Heart During Atrial Fibrillation
Bibliographic record
Abstract
BACKGROUND: High-frequency fractionated electrograms recorded during atrial fibrillation (AF) in the posterior left atrium (PLA) and elsewhere are being used as target sites for catheter ablation. We tested the hypothesis that highly periodic electric waves emerging from AF sources at or near the PLA give rise to the most fractionated activity in adjacent locations. METHODS AND RESULTS: Sustained AF was induced in 8 isolated sheep hearts (0.5 micromol/L acetylcholine). Endocardial videoimaging (DI-4-ANEPPS) and electric mapping of the PLA enabled spatial characterization of dominant frequencies (DFs) and a regularity index (ratio of DF to total power). Regularity index showed that fractionation was lowest within the area with the maximal DF (DFmax domain; 0.19+/-0.02) and highest within a band of &3 mm (0.16+/-0.02; P=0.047) at boundaries with lower-frequency domains. The numbers of spatiotemporal periodic episodes (25.9+/-2.3) and rotors per experiment (1.9+/-0.7) were also highest within the DFmax domain. Most commonly, breakthrough waves at the PLA traveled toward the rest of the atria (76.8+/-8.1% outward versus 23.2+/-8.1% inward; P<0.01). In both experiments and simulations with an atrial ionic model, fractionation at DFmax boundaries was associated with increased beat-to-beat variability of conduction velocity and directionality with wavebreak formation. CONCLUSIONS: During stable AF, the PLA harbors regular, fast, and highly organized activity; the outer limit of the DFmax domain is the area where the most propagation pattern variability and fractionated activity occur. These new concepts introduce a new perspective in the clinical use of high-frequency fractionated electrograms to localize sources of AF precisely at the PLA and elsewhere.
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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 | 0.000 |
| 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) | 0.000 | 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 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".