Consequences of Atrial Tachycardia-Induced Remodeling Depend on the Preexisting Atrial Substrate
Bibliographic record
Abstract
BACKGROUND: All animal studies of atrial tachycardia (AT) remodeling to date have been performed in normal hearts, but clinical atrial fibrillation (AF) often occurs in the setting of heart disease. This study evaluated the effects of a pathological AF substrate on AT-induced remodeling. METHODS AND RESULTS: Fourteen control dogs, 12 AT-only dogs (400 bpm for 1 week), 14 congestive heart failure (CHF) dogs (CHF only, ventricular tachypacing, 220 to 240 bpm for 5 weeks), and 13 CHF+AT dogs (ventricular tachypacing-induced CHF, 1 week of AT superimposed on the last week of ventricular tachypacing) were studied for evaluation of AT effects in normal hearts (AT-only versus control dogs) and CHF hearts (CHF+AT versus CHF-only dogs). In normal hearts, AT strongly decreased the effective refractory period (ERP) and abolished ERP rate adaptation, whereas conduction velocity was unaltered. In CHF dogs, AT reduced ERP to a significantly lesser extent, did not alter ERP rate adaptation, and reduced conduction velocity. AT alone increased atrial vulnerability to extrastimuli and prolonged AF. In the presence of CHF, AT had no clear effect on atrial vulnerability but increased the prevalence of prolonged AF. CONCLUSIONS: The electrophysiological effects of AT are different in hearts with a CHF-induced pathological substrate for AF than in normal hearts. These findings have potentially important implications for understanding how AF occurring in diseased hearts begets 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) | 0.000 | 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".