Mechanisms of atrial fibrillation termination by rapidly unbinding Na<sup>+</sup> channel blockers: insights from mathematical models and experimental correlates
Bibliographic record
Abstract
Atrial fibrillation (AF) is the most common sustained clinical arrhythmia and is a problem of growing proportions. Recent studies have increased interest in fast-unbinding Na(+) channel blockers like vernakalant (RSD1235) and ranolazine for AF therapy, but the mechanism of efficacy is poorly understood. To study how fast-unbinding I(Na) blockers affect AF, we developed realistic mathematical models of state-dependent Na(+) channel block, using a lidocaine model as a prototype, and studied the effects on simulated cholinergic AF in two- and three-dimensional atrial substrates. We then compared the results with in vivo effects of lidocaine on vagotonic AF in dogs. Lidocaine action was modeled with the Hondeghem-Katzung modulated-receptor theory and maximum affinity for activated Na(+) channels. Lidocaine produced frequency-dependent Na(+) channel blocking and conduction slowing effects and terminated AF in both two- and three-dimensional models with concentration-dependent efficacy (maximum approximately 89% at 60 microM). AF termination was not related to increases in wavelength, which tended to decrease with the drug, but rather to decreased source Na(+) current in the face of large ACh-sensitive K(+) current-related sinks, leading to the destabilization of primary generator rotors and a great reduction in wavebreak, which caused primary rotor annihilations in the absence of secondary rotors to resume generator activity. Lidocaine also reduced the variability and maximum values of the dominant frequency distribution during AF. Qualitatively similar results were obtained in vivo for lidocaine effects on vagal AF in dogs, with an efficacy of 86% at 2 mg/kg iv, as well as with simulations using the guarded-receptor model of lidocaine action. These results provide new insights into the mechanisms by which rapidly unbinding class I antiarrhythmic agents, a class including several novel compounds of considerable promise, terminate AF.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".