Role of Inflammation in Atrial Fibrillation Pathophysiology and Management
Bibliographic record
Abstract
Atrial fibrillation (AF) is the most common clinically relevant arrhythmia, but the methods available for treating AF and its complications (of which the most important is thrombogenesis), as well as for assessing AF risk and underlying pathophysiology, are largely limited. Emerging evidence suggests a significant role of inflammation in the pathogenesis of AF. That evidence includes elevated serum levels of inflammatory biomarkers in AF subjects, the expression of inflammatory markers in cardiac tissues of AF patients and animal models of AF, and beneficial effects of anti-inflammatory drugs in experimental AF paradigms. Inflammation is suggested to be linked to various pathological processes, such as oxidative stress, apoptosis, and fibrosis, that promote AF substrate formation. Inflammation has also been associated with endothelial dysfunction, platelet activation, and coagulation cascade activation, leading to thrombogenesis. Thus, inflammation may contribute to both the occurrence/maintenance of AF and its thromboembolic complications. Here, we review the evidence for a role of inflammation and inflammatory biomarkers in the risk management and treatment of AF. We also summarize the current knowledge of inflammation-dependent cellular and molecular mechanisms in AF pathophysiology and their potential as therapeutic targets.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".