Atrial remodeling and atrial fibrillation in acquired forms of cardiovascular disease
Bibliographic record
Abstract
Atrial fibrillation (AF) is prevalent in common conditions and acquired forms of heart disease, including diabetes mellitus (DM), hypertension, cardiac hypertrophy, and heart failure. AF is also prevalent in aging. Although acquired heart disease is common in aging individuals, age is also an independent risk factor for AF. Importantly, not all individuals age at the same rate. Rather, individuals of the same chronological age can vary in health status from fit to frail. Frailty can be quantified using a frailty index, which can be used to assess heterogeneity in individuals of the same chronological age. AF is thought to occur in association with electrical remodeling due to changes in ion channel expression or function as well as structural remodeling due to fibrosis, myocyte hypertrophy, or adiposity. These forms of remodeling can lead to triggered activity and electrical re-entry, which are fundamental mechanisms of AF initiation and maintenance. Nevertheless, the underlying determinants of electrical and structural remodeling are distinct in different conditions and disease states. In this focused review, we consider the factors leading to atrial electrical and structural remodeling in human patients and animal models of acquired cardiovascular disease or associated risk factors. Our goal is to identify similarities and differences in the cellular and molecular bases for atrial electrical and structural remodeling in conditions including DM, hypertension, hypertrophy, heart failure, aging, and frailty.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".