Influence of Propafenone on Resetting and Termination of Canine Atrial Flutter
Bibliographic record
Abstract
Previous studies on atrial flutter (AF) presumed that resetting was due to the prematurity effect (PE) in which the stimulated antegrade wavefront travels in the tail of the AF preexisting wavefront. We studied the collision effect (CE) between the AF and the stimulated retrograde wavefronts, its contribution to resetting, and its relationship to AF termination and how they are affected by the Class IC agent propafenone (PPF). A canine model of AF was created using a Y-shaped lesion in the right atrium in 14 dogs (33 +/- 3 kg). Five atrial bipolar electrodes were positioned around the tricuspid valve. In a subsequent set of 11 dogs, we used 16 bipolar electrodes for recording. AF was induced by burst pacing. Single and multiple stimuli were applied to measure conduction time and reset-response curves (RRCs). This was repeated after the administration of PPF (1 mg/kg loading dose for 10 minutes, followed by 1.8 mg/kg/per hour infusion). Three distinct mechanisms were found to contribute to the RRC: the PE, the CE, and heterogeneity. PPF stabilized the RRC, increased significantly the cycle length (CL), the duration of the effective refractory period, as well as the duration of the excitable gap. However, PPF did not alter the duration of the fully excitable portion. We studied 36 annihilations without and 48 with PPF. Transient fibrillation was found in 75% of the episodes without, compared to 22% with PPF. Other types of termination such as conduction block, CL oscillations, and reversal of activation were found for 25% of the episodes without and 78% with PPF. In many cases, conduction block and CL oscillations were associated with a failure of propagation of the stimulated antegrade wavefront in the region of collision. Termination by reversal of activation suggests that propagation was two dimensional and could not be represented by a one dimensional movement. The average coupling interval (in percent of CL), that induced fibrillation was not significantly different from that at which conduction block occurred. This suggests that transient fibrillation is associated with a weak CE rather than with rapid pacing. The CE is amplified by multiple stimuli and PPF. The incidence of transient fibrillation in AF annihilation diminishes with PPF as the CE becomes more important. This suggests that the evaluation of PE and CE in AF may be an indication of the risk of atrial fibrillation.
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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 | 0.000 | 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".