Experimental studies of atrial fibrillation: a comparison of two pacing models
Bibliographic record
Abstract
Rapid ventricular pacing (RVP) is a well-established animal model of atrial fibrillation (AF). However, this model is limited by a high mortality rate and severe heart failure. The purpose of our study was to assess a new canine model of inducible AF. We performed acute, short-term, simultaneous atrioventricular pacing (SAVP) and RVP (in random order) in 14 dogs for 30 s. SAVP produced more echocardiographic pulmonary venous flow reversal, a greater increase in mean pulmonary capillary wedge pressure, and a significantly greater decrease in left atrial emptying function (-84.4 +/- 38.6% vs. -23.7 +/- 27.1%, P < 0.05) than RVP. Thirty dogs were randomized to three, longer-term, study groups: eight dogs in the control group (no pacing), eight dogs in the RVP group (2 wk at 240 beats/min followed by 3 wk at 220 beats/min), and fourteen dogs in the SAVP group (2 wk at 220 beats/min). SAVP induced less left ventricular dysfunction but more left atrial dysfunction than RVP. SAVP dogs had similar atrial effective refractory periods as RVP dogs but more heterogeneity in conduction and more AF inducibility (83% vs. 40%, P < 0.05) and maintenance (median 1,660 vs. 710 s, P < 0.05) than RVP dogs. SAVP induced more collagen turnover and was associated with a significantly greater increase in type III collagen in the atria compared with RVP dogs (6.9 +/- 1.5 vs. 4.8 +/- 1.6, respectively, P < 0.05 vs. 1.1 +/- 0.7 in unpaced control dogs). In conclusion, the SAVP model induced profound mechanical and substrate atrial remodeling and reproducible sustained AF. This new model is clinically relevant and may be useful for testing AF interventions.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".