Intra-Atrial Pressure Increases Rate and Organization of Waves Emanating From the Superior Pulmonary Veins During Atrial Fibrillation
Bibliographic record
Abstract
BACKGROUND: Atrial fibrillation (AF) commonly associates with atrial dilatation by poorly understood mechanisms. We hypothesized that elevation of intra-atrial pressure elicits high-frequency and spatio-temporally organized left atrial (LA) sources emanating from the superior pulmonary veins. METHODS AND RESULTS: We used a stretch-related AF model in the sheep heart to induce stable episodes of AF (>40 minutes) in 9 animals. Video movies of the LA free wall (LAFW) and LA superior pulmonary vein junction (JPV) were obtained by using di-4-ANEPPS. Electrograms from the right atrium were recorded. At intra-atrial pressures >10 cm H2O, the maximum dominant frequency (DFMax) was significantly higher in the JPV than in the LAFW (12.0+/-0.2 and 10.5+/-0.2 Hz, respectively [mean+/-SEM]; P<0.001). Below 10 cm H2O, DFMax was similar in the JPV and LAFW (10.8+/-0.3 versus 10.2+/-0.3 Hz; P=0.6); DFMax in both JPV and LAFW was significantly higher than in the right atrium (7.8+/-0.3 Hz; P<0.001). Analysis of excitation direction in JPV showed positive correlation between intra-atrial pressure and the number of waves emanating from the left superior pulmonary vein (r=0.79, P=0.02) but not from the LAFW (r=0.54, P=0.09). The number of spatio-temporally periodic waves in the JPV correlated with pressure (r=0.92, P=0.002). In 3 cases, JPV rotors were identified with a cycle length equal to 1/DFMax. CONCLUSIONS: We demonstrate for the first time that an increase in intra-atrial pressure increases the rate and organization of waves emanating from the superior pulmonary veins underlying stretch-related 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 | 0.000 |
| 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) | 0.001 | 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".