Abstract 1364: Not All Refractory Period Abbreviation Promotes Atrial Fibrillation Equally: A Comparison Between Vagal and Atrial Tachycardia Remodeled Substrates
Bibliographic record
Abstract
Background: Vagal (VG) and atrial tachycardia remodeled (ATR) AF substrates share many features: reduced effective refractory period (ERP), increased ERP heterogeneity and some common molecular mechanisms (I KACh enhancement by acetylcholine release in VG, constitutive I KACh enhancement in ATR). This study compared VG and ATR substrates at comparable ERP abbreviation. Methods: In each of 5 VG dogs, bilateral cervical VG stimulation parameters were adjusted (mean±SD: 3.6±1.7 V and 12.2±1.5 Hz; 0.2 ms) to produce the same mean ERP (at 4 RA and 4 LA sites) as a sex and weight matched ATR dog (RA paced 400 bpm × 7 days). Mean duration of burst pacing induced AF (DAF) and local dominant frequencies (DFs, analyzed by FFT at 240 bipolar electrodes, Fig A ) were determined. Results: Mean ERP was 79±13 ms in VG and 78±13 ms in ATR dogs. DAF was greater in VG than ATR dogs (1056±323 vs 289±510 s *P<0.01; both significantly > control, 43±61 s). Despite matched ERPs, there were significant differences in DF distribution (Fig B ): DF was faster (mean DF: 11.8±1.1 Hz VG vs 9.7±1.3 Hz ATR*) and DF variability greater (indicated by SD: 1.8±0.6 Hz VG vs 0.8±0.5 Hz ATR*) in VG dogs. AF drivers reflected by maximum DF zones were adjacent to autonomic ganglia (over RA in 4/5) for VG dogs; in ATR dogs driver zones were less clear and showed variable location. Conclusions: For a comparable atrial ERP, VG AF is faster and more persistent than AF with an ATR substrate. These results are consist with modeling work suggesting that VG-induced hyperpolarization is an important contributor to AF-maintaining rotor stabilization and acceleration, and indicate important differences between these superficially similar AF substrates.
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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) | 0.004 | 0.001 |
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".