Mechanisms of atrial remodeling and clinical relevance.
Bibliographic record
Abstract
PURPOSE OF REVIEW: Atrial fibrillation usually occurs in the context of an atrial substrate produced by alterations in atrial tissue properties referred to as remodeling. Remodeling can result from cardiac disease, cardiac arrhythmias, or biologic processes such as senescence. Recent advances in understanding remodeling have allowed for insights into mechanisms underlying atrial fibrillation that have been transferred from experimental models to humans. This paper reviews recent progress in understanding atrial remodeling, as well as the consequent clinical insights into atrial fibrillation pathophysiology and treatment. RECENT FINDINGS: Two principal forms of remodeling have been described in animal models of atrial fibrillation: ionic remodeling, which affects cellular electrical properties, and structural remodeling, which alters atrial tissue architecture. Atrial tachycardias (particularly rapid tachyarrhythmias such as atrial flutter and atrial fibrillation) cause ionic remodeling, which decreases the atrial refractory period and promotes atrial reentry. Congestive heart failure produces atrial interstitial fibrosis, which promotes arrhythmogenesis by interfering with atrial conduction properties. Recent animal studies have provided insights into the pathways involved in remodeling, and have indicated the pathophysiological role of remodeling in specific contexts. In addition, work in animal models has provided information about pharmacological interventions that can prevent the development of remodeling. Clinical studies have shown that novel approaches to remodeling prevention identified in animal work have potential therapeutic value in man. SUMMARY: Understanding atrial remodeling has the potential to improve our appreciation of the pathophysiology of clinical atrial fibrillation and to allow for the development of useful new therapeutic approaches.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".